Made in America


April 17, 2022

Made in America isthe autobiography of Sam Walton, founder of Wal-Mart. It’s a terrific book. H. Ross Perot commented:

Every person who dreams of building a great businessmust read this book. Sam Walton set the standard for listening to his customers and listening to the people who do the work. In addition to being a great entrepreneur and business leader, Sam Walton was, above all, a fine, decent, kind, generous man.

Outline:

  • Learning to Value a Dollar
  • Starting on a Dime
  • Bouncing Back
  • Swimming Upstream
  • Raising a Family
  • Recruiting the Team
  • Taking the Company Public
  • Rolling Out the Formula
  • Building the Partnership
  • Stepping Back
  • Creating a Culture
  • Making the Customer Number One
  • Meeting the Competition
  • Expanding the Circles
  • Thinking Small
  • Giving Something Back
  • Running a Successful Company: Ten Rules That Worked For Me

Sam Walton:

…ours is a story about the kinds of traditional principles that made America great in the first place. It is a story about entrepreneurship, and risk, and hard work, and knowing where you want to go and being willing to do what it takes to get there. It’s a story about believing in your idea even when maybe some other folks don’t, and about sticking to your guns. But I think more than anything it proves there’s absolutely no limit to what plain, ordinary working people can accomplish if they’re given the opportunity and the encouragement and the incentive to do their best. Because that’s how Wal-Mart became Wal-Mart: ordinary people joined together to accomplish extraordinary things.

A wal-mart store with people walking around.

(Photo by Sven, via Wikimedia Commons)

 

LEARNING TO VALUE A DOLLAR

Walton says growing up during the Great Depression impacted his views on money. Walton’s dad – who was a very hard worker – had a number of jobs, including banker, farmer, farm-loan appraiser, insurance agent, and real estate agent. When he was out of work in the Great Depression, Walton’s dad eventually went to work for his brother’s Walton Mortgage Company.

In twenty-nine, thirty, and thirty-one, he had to repossess hundreds of farms from wonderful people whose families had owned the land forever… All of this must have made an impression on me as a kid…

Walton’s mother started a little milk business. Young Walton helped his mom. Walton also started selling magazine subscriptions. And he had a paper route from the seventh grade through college.

I learned from a very early age that it was important for us kids to help provide for the home, to be contributors rather than just takers. In the process, of course, we learned how much hard work it took to get your hands on a dollar, and that when you did it was worth something. One thing my mother and dad shared completely was their approach to money: they just didn’t spend it.

A close up of the front side of a one dollar bill

(Image by Hohum, via Wikimedia Commons)

Walton remarks that he didn’t know much about business, even after earning a college degree in the subject. When he got to know his wife Helen’s family, he learned a great deal from Helen’s father L. S. Robson. Walton writes:

He influenced me a great deal. He was a great salesman, one of the most persuasive individuals I have ever met. And I am sure his success as a trader and a businessman, his knowledge of finance and the law, and his philosophy had a big effect on me. My competitive nature was such that I saw his success and admired it. I didn’t envy it. I admired it. I said to myself: maybe I will be as successful as he is someday.

Helen’s father organized the family businesses as a partnership. Walton later adopted this approach, creating what would later be called Walton Enterprises.

How does Walton view money?

Here’s the thing: Money has never meant that much to me, not even in the sense of keeping score. If we had enough groceries, and a nice place to live, plenty of room to keep and feed my bird dogs, a place to hunt, a place to play tennis, and the means to get the kids good educations – that’s rich. No question about it. And we have it. We’re not crazy. We don’t live like paupers the way some people depict us. We all love to fly, and we have nice airplanes, but I’ve owned about eighteen airplanes over the years, and I never bought one of them new.

When it comes to Wal-Mart, Walton has always been very cheap. Wal-Mart didn’t buy a jet until the company approached $40 billion in sales “and even then they had to practically tie me up and hold me down to do it.” In the early days of Wal-Mart, when they went on buying trips, they’d pack as many as eight people into one room.

Why did Wal-Mart continue to be cheap even after it had become a behemoth? Walton:

We exist to provide value to our customers, which means that in addition to quality and service, we have to save them money. Every time Wal-Mart spends one dollar foolishly, it comes right out of our customers’ pockets. Every time we save them a dollar, that puts us one more step ahead of the competition – which is where we always plan to be.

 

STARTING ON A DIME

Walton was always ambitious:

Mother must have been a pretty special motivator, because I took her seriously when she told me I should always try to be the best I could at whatever I took on. So, I have always pursued everything I was interested in with a true passion – some would say obsession – to win. I’ve always held the bar pretty high for myself: I’ve set extremely high personal goals.

A stack of words that are written on top of each other.

(Photo by Travelling-light)

As a kid, Walton was a class officer several years. He was also a Boy Scout. And he played football, baseball, and basketball. In both high school and college (at the intramural level), he continued to play sports.

In high school, Walton was student body president and he was active in many clubs. He enjoyed basketball and was a “gym rat,” always at the gym playing hoops. When Walton was a senior, his basketball team went undefeated and won the state championship. This was one of his “biggest thrills.”

Walton continues:

My high school athletic experience was really unbelievable, because I was also the quarterback on the football team, which went undefeated too – and won the state championship as well… I guess I was just totally competitive as an athlete, and my main talent was probably the same as my best talent as a retailer – I was a good motivator.

Walton comments that his ambition and competitive spirit led him to consider as a distant goal running for President of the United States. In the meantime, he became president of the student body while at the University of Missouri. Walton:

I learned early that one of the secrets to campus leadership was the simplest thing of all: speak to people coming down the sidewalk before they speak to you. I did that in college. I did it when I carried my papers. I would always look ahead and speak to the person coming toward me. If I knew them, I would call them by name, but even if I didn’t I would still speak to them… I ran for every office that came along.

A bunch of different words that are written in english.

(Illustration by Madmirror)

While in college, Walton continued delivering papers. He had hired a few helpers by this point, and was making $4,000 to $5,000 a year. [That’s the equivalent of at least $60,000 to $75,000 in 2018 dollars.] Walton also waited tables and was a lifeguard. He graduated from the University of Missouri in June 1940.

Walton thought he was going to be an insurance salesman because his high school girlfriend’s father sold insurance for General American Life Insurance Company. It seemed like a lucrative career and Walton knew he could sell.

Walton wanted to attend Wharton business school, but he realized that even with his paper route and other jobs, he wouldn’t have enough money to pay for it. Walton met with two company recruiters who came to the Missouri campus. One was from J. C. Penney and the other from Sears Roebuck.

Walton says he got into retail – starting at J. C. Penney – simply because he was tired and wanted “a real job.” Although he was only making $75 a month, Walton loved retail. That’s where he stayed for the next fifty-two years.

Walton almost lost his job because he had never learned handwriting very well. Fortunately, the store manager, Duncan Majors, was a great motivator and believed in Walton. Duncan Majors was proud of having trained more Penney managers than anyone else in the country at that time. He spent time training and developing all his boys.

By early 1942, as an ROTC graduate, Walton prepared to join the war effort. But he flunked the physical due to a minor heart irregularity. Walton wandered south, toward Tulsa, thinking he might like to work in the oil business. Instead, he got a job at a big Du Pont gunpowder plant in the town of Pryor, outside Tulsa. That’s where he met his wife Helen Robson at a bowling alley. She was smart, educated, ambitious, opinionated, strong-willed, and energetic, and she was an athlete who enjoyed the outdoors.

Walton served in the military:

I wish I could recount a valiant military career – like my brother Bud, who was a Navy bomber pilot on a carrier in the Pacific – but my service stint was really fairly ordinary time spent as a lieutenant and then as a captain doing things like supervising security at aircraft plants and POW camps in California and around the country.

By 1945, Walton knew he wanted to go into a retailing and to own his own store. He read every book he could on retailing.

People today, looking back, know that Wal-Mart initially had a small-town strategy. This was just luck. Helen, Sam Walton’s wife, said she wouldn’t live in any town with more than 10,000 people.

Walton discovered that there was a Ben Franklin variety store that he could run in Newport, Arkansas – a cotton and railroad town of 7,000 people. The current owner was losing money and wanted to sell the store. Walton bought it for $25,000 – $5,000 of his own money and $20,000 from Helen’s father. Walton made a mistake, however, by not examining the lease agreement carefully.

A store front of a store called franklin.

(Photo by PenelopeIsMe, via Wikimedia Commons)

Walton set an ambitious goal:

I wanted my little Newport store to be the best, most profitable variety store in Arkansas within five years… Set that as a goal and see if you can’t achieve it. If it doesn’t work, you’ve had fun trying.

One important lesson Walton grasped early on was that you can learn from everybody. Walton would spend the rest of his career implementing this principle. He would visit as many stores as possible and speak with as many people as possible.

At the beginning, Walton’s main competition was across the street: Sterling Store, managed by John Dunham. Walton spent huge amounts of time visiting Sterling Store in order to absorb as much as he could.

Walton also learned a great deal from the Ben Franklin franchise program. It was a complete course in how to run a store. The only trouble was that franchisees weren’t given much discretion. Walton was told what merchandise to sell and how much to sell it for. Walton also had to buy the merchandise at set prices. Soon Walton started buying merchandise directly from manufacturers. He was always looking for “offbeat suppliers” from whom he could get a good deal. Walton did a lot of driving.

Walton says he learned a simple lesson that would later change the way retailers sell and customers buy:

…say I bought an item for 80 cents. I found that by pricing it at $1.00 I could sell three times more of it than by pricing it at $1.20. I might make only half the profit per item, but because I was selling three times as many, the overall profit was much greater. Simple enough. But this is really the essence of discounting… In retailer language, you can lower your markup but earn more because of the increased volume.

Walton tried many different promotional things. For instance, they put a popcorn machine and then an ice cream machine out in front of the store. Both turned out to be profitable.

No matter how well things were going, Walton was a tinkerer:

…I never could leave well enough alone, and, in fact, I think my constant fiddling and meddling with the status quo may have been one of my biggest contributions to the later success of Wal-Mart.

A blue background with several different types of lab equipment.

(Illustration by lkonstudio)

When Walton took over the Ben Franklin store, it had done $72,000 in annual sales. The first year Walton managed the store, it did $105,000 in sales. The second year was $142,000 and the third year was $175,000.

After five years, Walton ended up reaching his goal:

That Little Ben Franklin store was doing $250,000 in sales a year, and turning $30,000 to $40,000 a year in profit. It was the number-one Ben Franklin store – for sales and profit – not only in Arkansas, but in the whole six-state region.

Unfortunately, Walton was unable to keep the store because he forgot to include a clause in the lease that gave him an option to renew after the first five years. Walton notes that it was the low point of his business career. But he remained determined:

I’ve never been one to dwell on reverses, and I didn’t do so then. It’s not just a corny saying that you can make a positive out of most any negative if you work at it hard enough. I’ve always thought of problems as challenges, and this one wasn’t any different… I didn’t dwell on my disappointment. The challenge at hand was simple enough to figure out: I had to pick myself up and get on with it, do it all over again, only even better this time.

 

BOUNCING BACK

Helen’s father and Walton drove to Bentonville, Arkansas. They found an old variety store whose owners were looking to sell. But the two parties couldn’t reach an agreement. Later, on his own, Helen’s father was able to reach an agreement with the sellers.

Although the store had done only $32,000 in sales before Walton bought it, he had big plans. Walton had heard about two Ben Franklin stores that were using a new concept: self-service. All the merchandise was sitting on shelves for the customers to pick out. The check-out registers were at the front of the store.

A blue banner with the word server written in it.

(Illustration by Alexmillos)

Walton adopted the self-service concept for his Bentonville store. He called it Walton’s Five and Dime. The store did well right away. Part of the reason was Walton’s friendliness and his habit of yelling at people from a block away.

Walton then started looking for other stores that he could manage in other towns. He found one in Fayetteville and used the same name: Walton’s Five and Dime. It, too, was set up using self-service. Walton comments:

This was the beginning of our way of operating for a long while to come. We were innovating, experimenting, and expanding. Somehow over the years, folks have gotten the impression that Wal-Mart was something I dreamed up out of the blue as a middle-aged man, and that it was just this great idea that turned into an overnight success. It’s true that I was forty-four when we opened our first Wal-Mart in 1962, but the store was totally an outgrowth of everything we’d been doing since Newport – another case of me being unable to leave well enough alone, another experiment. And like most other overnight successes, it was twenty years in the making.

Walton made his first real hire at the manager level: Willard Walker. Walton found Willard by looking in competitors’ stores. He would continue using this approach to finding talent going forward. Also, Walton offered Willard equity in the business.

Meanwhile, Walton’s brother Bud had bought his own Ben Franklin store in Versailles, Missouri. So Walton asked his brother if he wanted to go fifty-fifty on a new Ben Franklin store that was going to be part of a shopping center in Kansas City. Bud agreed.

Based on what he saw in Kansas City, Walton got the notion of going into shopping center development. He persisted with the idea for two years. But it didn’t work.

I probably lost $25,000, and that was at a time when Helen and I were counting every dollar. It was probably the biggest mistake of my business career. I did learn a heck of a lot about the real estate business from the experience, and maybe it paid off somewhere down the line – though I would rather have learned it some cheaper way.

Wal-Mart executive David Glass:

Two things about Sam Walton distinguish him from almost everyone else I know. First, he gets up every day bound and determined to improve something. Second, he is less afraid of being wrong than anyone I’ve ever known. And once he sees he’s wrong, he just shakes it off and heads in another direction.

Walton developed a love of flying. His first plane, a two-seater, only went 100 miles an hour, but it allowed him to get places in a straight line. One time, the motor cut off for about a minute. Walton thought he was done. But he was able to circle around and land with a dead engine.

A small airplane sitting on top of an airport runway.

(Photo by TSRL, via Wikimedia Commons)

As Walton proceeded to open up new stores, he created business partnerships that included – along with other partners – himself, Bud, Sam’s dad, Helen’s two brothers, and even Sam and Helen’s kids, who invested their paper route money.

John Walton (one of Sam and Helen’s four kids):

This is hard to believe, but between my paper route money and the money I made in the Army – both of which I invested in those stores – that investment is worth about $40 million today.

In less than fifteen years, they had become the largest independent variety store operator. But in 1960, they were still only doing $1.4 million a year. Walton continued to look for ways to improve.

Soon he learned that if they built a huge store, they could sell as much as $2 million a year from one location. Walton traveled the country to look at the “early discounters.” For example, in California, Sol Price had started Fed-Mart. Closer to Arkansas, there was Herb Gibson, who sold cheaper than anyone else, but also sold higher volume than anyone else.

Soon Walton built his first discount store – what would become the first Wal-Mart. Because they couldn’t use Ben Franklin at all, Walton had to make arrangements with a distributor in Springfield, Missouri. Since nobody wanted to take a chance on the first Wal-Mart, Sam and Helen had to borrow even more than they already had:

We pledged houses and property, everything we had. But in those days, we were always borrowed to the hilt.

By the time they had three Wal-Marts up and running, Walton knew that it would work.

 

SWIMMING UPSTREAM

Wal-Mart’s challenges strengthened it:

Many of our best opportunities were created out of necessity. The things that we were forced to learn and do, because we started out underfinanced and undercapitalized in these remote, small communities, contributed mightily to the way we’ve grown as a company. Had we been capitalized, or had we been the offshoot of a large corporation the way I wanted to be, we might not ever have tried the Harrisons or the Rogers or the Springdales and all those other little towns we went into in the early days.

A light bulb with the words necessity is the mother of invention.

(Illustration by Miaoumiaou)

Early on, Wal-Mart didn’t have systems or computers. Walton recalls that much of what they did was poorly done. But they stayed focused on low prices:

The idea was simple: when customers thought of Wal-Mart, they should think of low prices and satisfaction guaranteed. They could be pretty sure they wouldn’t find it cheaper anywhere else, and if they didn’t like it, they could bring it back.

Wal-Mart lacked established distributors. Salesmen would randomly show up. It was difficult to get the bigger companies like Proctor & Gamble to show any interest.

The basic discounter’s strategy was to sell health products – toothpaste, mouthwash, headache remedies, soap, shampoo – at cost. This brought people into the store. The discounter would price everything else also at low prices, but with a 30 percent markup.

Gradually, Walton phased out his variety stores until all the stores were Wal-Marts.

Headquarters would give a profit and loss statement to each individual Wal-Mart store. Problems could be handled immediately. Most store managers owned a piece of their stores, so they were incentivized to maximize profit over time. Walton:

For several years the company was just me and the managers in the stores. Most of them came to us from variety stores, and they turned into the greatest bunch of discount merchants anybody ever saw. We all worked together, but each of them had lots of freedom to try all kinds of crazy things themselves.

Walton mentions Don Whitaker as being like an operations manager. Claude Harris was the first buyer.

Walton talks about the importance of merchandising:

…there hasn’t been a day in my adult life when I haven’t spent time thinking about merchandising. I suspect I have emphasized item merchandising and the importance of promoting items to a greater degree than most any other retail management person in this country. It has been an absolute passion of mine. It is what I enjoy doing as much as anything in the business. I really love to pick an item – maybe the most basic merchandise – and then call attention to it. We used to say you could sell anything if you hung it from the ceiling. So we would buy huge quantities of some thing and dramatize it. We would blow it out of there when everybody knew we would have only sold a few had we just left it in the normal store position. It is one of the things that has set our company apart from the very beginning and really made us difficult to compete with. And, man, in the early days of Wal-Mart it really got crazy sometimes.

A purple background with yellow dots and white text that says " 6 0 % off ".

(Illustration by Beststock Images)

For instance, one of Wal-mart’s managers, Phil Green, created the world’s largest display of Tide. It was eighteen cases high, 75 or 100 feet long, and 12 feet wide. Everyone thought Phil was crazy, but he sold all of it at deeply discounted prices.

Wal-Mart executive David Glass comments:

The philosophy it teaches, which rubs off on all the associates and the store managers and the department heads, is that your stores are full of items that can explode into big volume and big profits if you are just smart enough to identify them and take the trouble to promote them.

Glass explains that in retail, you’re either operations driven or merchandise driven. If a retailer is merchandise driven, they can always improve operations. But retailers that are operations driven often don’t learn merchandising. Early every Saturday morning, Wal-Mart managers would meet and critique their own and others’ merchandising. Walton:

We wanted everybody to know what was going on and everybody to be aware of the mistakes we made. When somebody made a bad mistake – whether it was myself or anybody else – we talked about it, admitted it, tried to figure out how to correct it, and then moved on to the next day’s work.

Wal-Mart associates also continued Walton’s practice of constantly checking out the competition in order to find ways to improve.

 

RAISING A FAMILY

On family vacations, it was a given that Walton would visit as many stores as possible.

Walton never pressured his kids at all to go into retailing. But they got involved anyway. Rob became the first company lawyer for Wal-Mart. Jim got involved with locating and buying store sites. John became the second company pilot. (John was a Green Beret medic who later created a business that builds boats.) Alice was a buyer for Wal-Mart and then developed her own investment company.

Walton worries that his grandchildren might join the “idle rich.”

Maybe it’s time for a Walton to start thinking about going into medical research and working on cures for cancer, or figuring out new ways to bring culture and education to the underprivileged…

 

RECRUITING THE TEAM

Walton notes that he has the personality of a promoter but the soul of an operator. He never stops trying to improve things. When the idea of discounting began to catch on, Walton visited every store and every headquarters he could. He gleaned something from each visit. He may have gotten the most from his study of Sol Price, an excellent operator who had started Fed-Mart in southern California in 1955. Walton:

I guess I’ve stolen – I actually prefer the word “borrowed” – as many ideas from Sol Price as from anybody else in the business.

Most discounters failed. Walton explains:

It all boils down to not taking care of their customers, not minding their stores, not having folks in their stores with good attitudes, and that was because they never even really tried to take care of their own people. If you want the people in the stores to take care of the customers, you have to make sure you’re taking care of the people in the stores. That’s the most important single ingredient of Wal-Mart’s success.

As Wal-Mart continued to expand, it had to hire more executives. Ferold Arend was the company’s first vice president of operations (and later president).

Logistics also became increasingly important. Walton got the idea of using computers long before they were very useful. But computers kept improving. Abe Marks comments on Walton:

He was really ten years away from the computer world coming. But he was preparing himself. And this is a very important point: without the computer, Sam Walton could not have done what he’s done. He could not have built a retailing empire the size of what he’s built, the way he built it. He’s done a lot of other things right, too, but he could not have done it without the computer. It would have been impossible.

A warehouse was long overdue. But Walton had already borrowed heavily and the company also had borrowed heavily. Walton:

…We were generating as much financing for growth as we could from the profits of the stores, but we were also borrowing everything we could. I was taking on a lot of personal debt to grow the company – it approached $2 million [over $14 million in 2018 dollars]… The debt was beginning to weigh on me.

A group of orange cubes with the letters e, b and b written on them.

(Photo by Adonis1969)

Wal-Mart needed someone to run operations. Walton hired a fellow named Ron Mayer. Walton says 1968 to 1976 – the time Ron was in charge of operations – was the most important period in Wal-Mart’s history. Walton:

We were forced to be ahead of our time in distribution and in communication because our stores were sitting out there in tiny little towns and we had to stay in touch and keep them supplied. Ron started the programs that eventually improved our in-store communications system. Building on the groundwork already laid by Ferold Arend, Ron also took over distribution and began to design and build a system that would enable us to grow as fast as we could come up with the money. He was the main force that moved us away from the old drop shipment method, in which a store ordered directly from the manufacturer and had the merchandise delivered directly to the store by common carrier. He pushed us in some new directions, such as merchandise assembly, in which we would order centrally for every store and then assemble their orders at the distribution center, and also cross-docking, in which preassembled orders for individual stores would be received on one side of our warehouse and leave out the other.

 

TAKING THE COMPANY PUBLIC

The company’s cash shortage forced it to give up five sites where they were going to build new stores. Going public could solve the cash problem. Thus far, there were a number of different partnership agreements for the various stores.

So Rob started to work on the plan, which was to consolidate all these partnerships into one company and then sell about 20 percent of it to the public. At the time, our family owned probably 75 percent of the company, Bud owned 15 percent or so, some other relatives owned a percentage…

A note that is sitting on top of some papers.

(Photo by Designer491)

Anybody who bought stock in Wal-Mart’s first public offering in late 1970 – at a price of $16.50 per share – and who held it, did extraordinarily well. Walton:

…let’s say you bought 100 shares back in that original public offering, for $1,650. Since then, we’ve had nine two-for-one stock splits, so you would have 51,200 shares today. Within the last year, it’s traded at right under $60 a share. So your investment would have been worth right around $3 million…

An investment of $1,650 in late 1970 would have turned into $3 million over the ensuing two decades. An investment of $16,500 would have become $30 million. Since then, Wal-Mart has continued to grow, albeit more slowly.

Going public allowed Walton to pay off all his debts.

Walton never worried about market expectations, especially over the short term:

If we fail to live up to somebody’s hypothetical projection for what we should be doing, I don’t care. It may knock our stock back a little, but we’re in it for the long run. We couldn’t care less about what is forecast or what the market says we ought to do. If we listened very seriously to that sort of stuff, we never would have gone into small-town discounting in the first place.

 

ROLLING OUT THE FORMULA

Jack Shewmaker, later president and COO, made this remark about working at Wal-Mart in 1970:

It would be safe to say that in those days we all worked a minimum of sixteen hours day.

There is only one way to success, it's called hard work.

(Illustration by Roman Doroshenko)

Kmart was expanding rapidly, but wouldn’t go into towns with below 50,000 population. Gibson’s, another prominent discounter, wouldn’t go into towns much below 10,000. But Wal-Mart knew it could be profitable even in towns with under 5,000. As for big cities:

We never planned on actually going into the cities. What we did instead was build our stores in a ring around a city – pretty far out – and wait for the growth to come to us. That strategy worked practically everywhere.

The airplane became a useful tool for looking at real estate. When Walton was flying, he would get low and turn the plane on its side when he passed over real estate of interest.

Walton would visit individual stores as often as possible, and he expected his executives to do the same. But much of the day-to-day operations Walton left to folks like Ferold Arend and Ron Mayer, then later Jack Shewmaker, and after that David Glass and Don Soderquist. Walton sees his role as picking good people and then giving them maximum authority and responsibility. Many have pointed out that Walton is extremely good at picking the right people.

Every Saturday morning, Walton would go to work at 2 or 3 a.m. He would spend several hours examining data for many of the stores. This allowed him to be prepared for the Saturday morning meeting at 7:30 a.m. Walton:

But if you asked me am I an organized person, I would have to say flat no, not at all. Being organized would really slow me down. In fact, it would probably render me helpless. I try to keep track of what I’m supposed to do, and where I’m supposed to be, but it’s true I don’t keep much of a schedule.

Walton fondly recalls this initial period:

Managing that whole period of growth was the most exciting time of all for me personally. Really, there has never been anything quite like it in the history of retailing. It was the retail equivalent of a real gusher: the whole thing, as they say in Oklahoma and Texas, just sort of blowed. We were bringing great folks on board to help make it happen, but at that time, I was involved in every phase of the business: merchandising, real estate, construction, studying the competition, arranging the financing, keeping the books – everything. We were all working untold hours, and we were tremendously excited about what was going on.

A group of coins stacked on top of each other.

(Photo byBj¸rn Hovdal)

Wal-Mart’s phenomenal growth:

Year Stores Sales
1970 32 $31 million
1972 51 $78 million
1974 78 $168 million
1976 125 $340 million
1978 195 $678 million
1980 276 $1.2 billion

Walton observes:

On paper, we really had no right to do what we did. We were all pounding sand, and stretching our people and our talents to the absolute maximum.

Walton would hire people who lacked experience but showed potential. He believed that a lack of knowledge and experience could be overcome with passion and a willingness to work extremely hard.

Distribution continued to be challenging:

…I don’t think our distribution system ever really got under complete control until David Glass finally relented and came on board in 1976. More than anybody else, he’s responsible for building the sophisticated and efficient system we use today.

 

BUILDING THE PARTNERSHIP

Giving associates a stake in the business, and giving them the chance to participate in decisions that would impact profitability, was an essential part of Wal-Mart’s growth and success.

A white block that says equity spelled out in black letters.

(Photo by Adonis1969)

Walton realized that the more you share profits with associates, the more profitable the company can become. Walton explains:

…the way management treats the associates is exactly how the associates will then treat the customers. And if the associates treat the customers well, the customers will return again and again, andthat is where the real profit in this business lies, not in trying to drag strangers into your stores for one-time purchases based on splashy sales or expensive advertising. Satisfied, loyal, repeat customers are at the heart of Wal-Mart’s spectacular profit margins, and those customers are loyal to us because our associates treat them better than salespeople in other stores do.

Walton says this biggest regret is not including associates in the initial profit-sharing plan when the company went public in 1970. But in 1971, Walton started giving associates part ownership of the business. Many associates realized they were better off working at Wal-Mart – which is non-unionized – than they would be working somewhere that is unionized. Why? Both because associates can become part owners and because Wal-Mart executives have a policy of always listening to any associate with an issue or idea.

 

STEPPING BACK

One of Walton’s hobbies was tennis, which he preferred to golf since golf takes too long. Walton’s tennis partner George Billingsley says about Walton:

He loved the game. He never gave you a point, and he never quit. But he is a fair man. To him, the rules of tennis, the rules of business, and the rules of life are all the same, and he follows them. As competitive as he is, he was a wonderful tennis opponent – always gracious in losing and in winning. If he lost, he would say, ‘I just didn’t have it today, but you played marvelously.’

Walton also enjoyed training his dogs:

I pride myself on being able to train my own dogs, and I’ve never had a dog handler, like some of these country gentlemen friends of mine. I enjoy picking out ordinary setter or pointer pups and working with them…

Walton nearly always had his dogs with him when he drove around. He loved the outdoors and was a believer in conservation. Also, he liked to hunt birds. Some of his best friends were bird hunters.

A group of birds standing next to each other.

(Photo by Cynoclub)

Walton stepped back somewhat from Wal-Mart in 1976. Unfortunately, two factions in the company developed and they began to compete fiercely. The old guard, including many store managers, were loyal to Ferol. The new guard lined up behind Ron. (Many in the new guard had been hired by Ron.) Soon everybody began taking sides. It was very unhealthy.

Walton made the problem much worse by appointing Ron CEO. Walton thought things might run OK this way. But Walton couldn’t stay out of things. He continued doing everything he was doing before.

The truth is, I failed at retirement worse than just about anything else I’ve ever tried.

Walton didn’t think the company was going in the right direction, so he decided to step back in as CEO. He asked Ron to stay as vice chairman and CFO. But Ron had wanted to run the company, so he decided to leave.

Before he left, Ron told Walton that Wal-Mart had such a strong organization that it would continue to do well. But Ron’s faith in Wal-Mart didn’t prevent roughly one third of senior managers from leaving after Ron left.

Walton believes most setbacks can be turned into opportunities. He promoted Jack Shewmaker to executive vice president of operations, personnel, and merchandise. And Walton hired David Glass as executive vice president in charge of finance and distribution.

These two guys are completely different in personality, but they are both whip smart. And with us up against it like we were, everybody had to head in the same direction. Once again, Wal-Mart proved everybody wrong, and we just blew the doors off our previous performances. David made us a stronger company almost immediately. Ron Mayer may have been the architect of our original distribution systems, but David Glass, frankly, was much better than Ron at distribution, and that was one of the big areas of expertise I had been afraid of losing. David also was much better at fine-tuning and honing our accounting systems. He, along with Jack, was a powerful advocate for much of the high technology that keeps us operating and growing today. And not only did he turn out to be a great chief financial officer, he also proved to be a fine talent with people. This new team was even more talented, more suited for the job at hand than the previous one.

 

CREATING A CULTURE

A group of wooden blocks with letters on them.

(Photo by Maurizio Distefano)

Saturday morning meetings often began with a cheer. Walton:

It’s sort of a “whistle while you work” philosophy, and we not only have a heck of a good time with it, we were better because of it. We build spirit and excitement. We capture the attention of our folks and keep them interested, simply because they never know what’s coming next. We break down barriers, which helps us communicate better with one another. And we make our people feel part of a family in which no one is too important or too puffed up to lead a cheer or be the butt of a joke…

In 1984, Walton lost a bet to David Glass and “had to pay up by wearing a grass skirt and doing the hula on Wall Street.” (Glass bet that the company would achieve a pretax profit of more than 8 percent; Walton bet against it.) While outsiders might have viewed it as a publicity stunt, Walton observes that it’s a part of Wal-Mart’s culture to make things interesting, unpredictable, and fun.

…we thrive on a lot of the traditions of small-town America, especially parades with marching bands, cheerleaders, drill teams, and floats. Most of us grew up with it, and we’ve found that it can be even more fun when you’re an adult who usually spends all your time working. We love all kinds of contests, and we hold them all the time for everything from poetry to singing to beautiful babies. We like theme days, where everyone in the store dresses up in costume.

Wal-Mart turned its annual meeting for shareholders into a fun, two-day event.

One potential problem for nearly all large companies is resistance to change. Walton writes:

So I’ve made it my own personal mission to ensure that constant change is a vital part of the Wal-Mart culture itself… In fact, I think one of the greatest strengths of Wal-Mart’s ingrained culture is its ability to drop everything and turn on a dime.

Ongoing education is also important. Associates can go to the Wal-Mart Institute at the University of Arkansas. Or they can, with the company’s help, earn college degrees.

 

MAKING THE CUSTOMER NUMBER ONE

A heart that is cut out of paper.

(Photo by Feelfree777)

For my whole career in retailing, I have stuck with one guiding principle… the secret of successful retailing is to give your customers what they want. And really, if you think about it from your point of view as a customer, you want everything: a wide assortment of good quality merchandise; the lowest possible prices; guaranteed satisfaction with what you buy; friendly, knowledgeable service; convenient hours; free parking; a pleasant shopping experience.

Walton defends Wal-Mart:

Of all the notions I’ve heard about Wal-Mart, none has ever baffled me more than this idea that we are somehow the enemy of small-town America. Nothing could be further from the truth: Wal-Mart has actually kept quite a number of small towns from becoming practically extinct by offering low prices and saving literally billions of dollars for the people who live there, as well as by creating hundreds of thousands of jobs in our stores.

Beyond its direct economic impact – customers vote with their feet and have saved huge amounts of money – Wal-Mart is committed to creating a sense of community in its managers and associates. Community involvement is important.

In the early days of Wal-Mart, department stores put pressure on Wal-Mart. The department stores didn’t like the fact that many of their customers were switching to Wal-Mart simply because Wal-Mart’s prices were much lower. The department stores even tried to use “fair trade” laws to block discounters from doing business.

Furthermore, Wal-Mart’s vendors weren’t all happy about Wal-Mart’s determination to get the lowest possible prices from them. Walton spells out his company’s reasoning:

…we are the agents for our customers. And to do the best job possible, we’ve got to become the most efficient deliverer of merchandise that we can. Sometimes that can best be accomplished by purchasing goods directly form the manufacturer. And other times, direct purchase simply doesn’t work. In those cases, we need to use middlemen to deal with smaller manufacturers and make the process more efficient. What we believe in strongly is our right to make that decision – whether to buy directly or from a rep – based on what it takes to best serve our customers.

 

MEETING THE COMPETITION

Walton:

…We decided that instead of avoiding our competitors, or waiting for them to come to us, we would meet them head-on. It was one of the smartest strategic decisions we ever made… Our competitors have honed and sharpened us to an edge we wouldn’t have without them.

Two chess pieces are facing each other on a chessboard.

(Photo by Nataliia Shcherbyna)

Bud Walton:

Competition is very definitely what made Wal-Mart – from the very beginning. There’s not an individual in these whole United States who has been in more retail stores – all types of retail stores, too, not just discount stores – than Sam Walton. Make that all over the world. He’s been in stores in Australia and South America, Europe and Asia and South Africa. His mind is just so inquisitive when it comes to this business. And there may not be anything he enjoys more than going into a competitor’s store trying to learn something from it.

At a regional meeting of discounters, competitors went through Wal-Mart’s stores and offered their critiques. Wal-Mart executives were surprised at how many things they weren’t doing well. But they listened carefully and made adjustments accordingly. Those adjustments were crucial in preparing Wal-Mart to begin competing more broadly with Kmart. (Kmart had 1,000 stores while Wal-Mart only had 150 at that time.)

Many discounters were driven out of business in the mid-1970s when the economy weakened. Wal-Mart began to buy struggling retailers. In 1981, Wal-Mart had almost no stores east of the Mississippi. But Kuhn’s Big K stores – with 112 locations – was faltering. Wal-Mart had a difficult time deciding what to do, but they finally acquired Kuhn’s. After working through some problems related to the acquisition, Wal-Mart was now in a position to keep growing amazingly fast. Walton:

We exploded from that point on, almost always opening 100 new stores a year, and more than 150 in some years…

I don’t know how the folks around executive offices see me, and I know they get frustrated with the way I make everybody go back and forth on so many issues that come up. But I see myself as being a little more inclined than most of them are to take chances. On something like the Kuhn’s decision, I try to play a “what-if” game with the numbers – but it’s generally my gut that makes the final decision.

 

EXPANDING THE CIRCLES

…one of the main reasons we’ve been able to roll this company out nationally was all the pressure put on me by guys like David Glass and, earlier, Jack Shewmaker and Ron Mayer, to invest so heavily in technology. Yes, I argued and resisted, but I eventually signed the checks. And we have been able to move way out front of the industry in both communications and distribution… I would go so far as to say, in fact, that the efficiencies and economies of scale we realize from our distribution system give us one of our greatest competitive advantages.

Many people have contributed over the years, but David Glass has to get the lion’s share of the credit for where we are today in distribution. David had a vision for automated distribution centers – linked by computer both to our stores and to our suppliers – and he set about building such a system, beginning in 1978 at Searcy, Arkansas.

Wal-Mart’s warehouses reached a point where they could directly replenish nearly 85 percent of inventory compared to 50 to 65 percent for competitors. When in-store merchants place computer orders, the orders arrive at the store in about two days. Most competitors had to wait five or more days for their orders to arrive.

Wal-Mart has a private fleet of trucks. Walton would regularly meet in the drivers’ break room at 4 a.m. with a bunch of doughnuts. He would ask them all sorts of questions about the stores. Most truck drivers were very candid, which gave Walton another way to gain store-level intelligence.

A large building with a lot of windows on the side.

(Wal-Mart distribution center, Photo by Redwood8)

Walton describes a distribution center:

Start with a building of around 1.1 million square feet, which is about as much floor space as twenty-three football fields, sitting out somewhere on some 150 acres. Fill it high to the roof with every kind of merchandise you can imagine, from toothpaste to TV’s, toilet paper to toys, bicycles to barbecue grills. Everything in it is bar-coded, and a computer tracks the location and movement of every case of merchandise, while it’s stored and when it’s shipped out. Some six hundred to eight hundred associates staff the place, which runs around the clock, twenty-four hours a day. On one side of the building is a shipping dock with loading doors for around thirty trucks at a time – usually full. On the other side is the receiving dock, which may have as many as 135 doors for unloading merchandise.

These goods move in and out of the warehouse on some 8 1/2 miles of laser-guided conveyor belts, which means that the lasers read the bar codes on the cases and then direct them to whatever truck is filling the order placed by one of the stores it’s servicing that night… When the thing is running full speed, it’s just a blur of boxes and crates flying down those belts, red lasers flashing everywhere, directing this box to that truck, or that box to this truck. Out in the parking lot, whole packs of Wal-Mart trucks rumble in and out all day.

 

THINKING SMALL

Walton on thinking small:

…the bigger Wal-Mart gets, the more essential it is that we think small. Because that’s exactly how we have become a huge corporation – by not acting like one… If we ever forget that looking a customer in the eye, and greeting him or her, and asking politely if we can be of help is just as important in every Wal-Mart today as it was in that little Ben Franklin in Newport, then we just ought to go into a different business because we’ll never survive in this one.

In a giant, centrally driven company, there’s no place for creativity, no room for the maverick merchant, no need for the entrepreneur or the promoter.

Walton shares six principles for how to think small:

  • Think One Store at a Time
  • Communicate, Communicate, Communicate
  • Keep Your Ear to the Ground
  • Push Responsibility – and Authority – Down
  • Force Ideas to Bubble Up
  • Stay Lean, Fight Bureaucracy

Think One Store at a Time

The focus always has to be on lowering prices, improving service, and making things better for customers who shop in the stores. Similarly, getting the right merchandising mix requires merchandisers at the store level, who deal with customers face to face, day in and day out.

When managers meet at the end of the week, the discussion of sales is at the individual store level. No other large retailer does that.

Communicate, Communicate, Communicate

Walton says:

If you had to boil down the Wal-Mart system to one single idea, it would probably be communication, because it is one of the real keys to our success.

[…]

That’s why we’ve spent hundreds of millions of dollars on computers and satellites – to spread all the little details around the company as fast as possible.

Sometimes Walton would get a message to everyone by doing a TV recording. One time, he had all the associates pledge to follow “the ten-foot rule.” If you come within 10 feet of a customer, look her in the eye, greet her, and ask her if you can help her. Walton told all the associates that, if they did this, not only would it be better for customers, but the associates themselves would become better leaders in the process.

Keep Your Ear to the Ground

Both district managers and regional managers are expected to travel around to individual stores, just as Walton himself used to do all the time. Valuable intelligence is always available using this approach.

As with any retailer, there’s always a head-to-head confrontation between operations and merchandising. At Wal-Mart, there are some enormous arguments. But they have a rule never to leave an item hanging in the weekly meeting. They always make a decision. Sometimes it’s wrong and gets corrected ASAP. But once the decision is made, everyone is on board as long as the decision stands.

Push Responsibility – and Authority – Down

As much as possible, every level of manager is given responsibility and authority – and is rewarded with equity. Many Wal-Mart managers who never went to college end up performing very well.

Force Ideas to Bubble Up

This goes with pushing responsibility down. Any associate can have a good idea about how to improve something. It’s happened countless times at Wal-Mart.

Stay Lean, Fight Bureaucracy

Bureaucracy builds up naturally unless the culture is to eliminate or limit bureaucracy as much as possible. Walton is committed to not letting egos get out of control because, in his view, much bureaucracy is the result of some empire builder’s ego.

 

RUNNING A SUCCESSFUL COMPANY: TEN RULES THAT WORKED FOR ME

  • RULE 1: COMMIT to your business. Believe in it more than anybody else. I think I overcame every single one of my personal shortcomings by the sheer passion I brought to my work.
  • RULE 2: SHARE your profits with all your associates, and treat them as partners. In turn, they will treat you as a partner, and together you will all perform beyond your wildest expectations.
  • RULE 3: MOTIVATE your partners. Money and ownership alone aren’t enough. Constantly, day by day, think of new and more interesting ways to motivate and challenge your partners. Set high goals, encourage competition, and then keep score. If things get stale, cross-polinate; have managers switch jobs with one another to stay challenged… Don’t become too predictable.
  • RULE 4: COMMUNICATE everything you possibly can to your partners. The more they know, the more they’ll understand. The more they understand, the more they’ll care.
  • RULE 5: APPRECIATE everything your associates do for the business… all of us like to be told how much somebody appreciates what we do for them.
  • RULE 6: CELEBRATE your successes. Find some humor in your failures. Don’t take yourself so seriously. Loosen up, and everybody around you will loosen up. Have fun. Show enthusiasm – always.
  • RULE 7: LISTEN to everyone in your company. And figure out ways to get them talking. The folks on the front lines – the ones who actually talk to the customer – are the only ones who really know what’s going on out there.
  • RULE 8: EXCEED your customers’ expectations. If you do, they’ll come back over and over. Give them what they want – and a little more. Let them know you appreciate them. Make good on all your mistakes, and don’t make excuses – apologize. Stand behind everything you do.
  • RULE 9: CONTROL your expenses better than your competition. This is where you can always find the competitive advantage.
  • RULE 10: SWIM upstream. Go the other way. Ignore the conventional wisdom. If everybody else is doing it one way, there’s a good chance you can find your niche by going in exactly the opposite direction. But be prepared for a lot of folks to wave you down and tell you you’re headed the wrong way.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Grinding It Out


April 10, 2022

I was an overnight success all right, but thirty years is a long, long night.

In Grinding It Out,Ray Kroc tells the story of how he created McDonald’s. Kroc launched the company in 1954 when he was 52 years old. Twenty-two years later McDonald’s topped one billion in total revenue.

A close up of a hamburger and fries

(Photo by Ruslan Gilmanshin)

 

CHAPTER 1

Kroc spent seventeen years selling paper cups before he discovered a five-spindled milk-shake machine called the Multimixer. Kroc:

It wasn’t easy to give up security and a well-paying job to strike out on my own… I plunged gleefully into my campaign to sell a Multimixer to every drug store soda fountain and dairy bar in the nation. It was a rewarding struggle. I loved it. Yet I was alert to other opportunities.

A black and white photo of a kitchen with many dishes.

(Multimixer, Photo by Visitor7, via Wikimedia Commons)

Kroc began to hear about the McDonald brothers. They had not just one Multimixer. Nor just two or three. They had eight Multimixers. This peaked Kroc’s curiosity, so he went to look at the McDonald brothers’ operation in San Bernardino, California.

At first, Kroc wasn’t impressed. But then he saw all the helpers arriving and setting up. Soon they were moving really fast. And flocks of people were in line getting hamburgers. Each hamburger was only 15 cents, and there was almost no wait between the customer placing an order and the order being filled.

Kroc spoke with several customers and learned that they just loved the food. Kroc was captivated by the system. He asked the McDonald brothers to join him for dinner, which they did:

I was fascinated by the simplicity and effectiveness of the system they described that night. Each step in producing the limited menu was stripped down to its essence and accomplished with a minimum of effort. They sold hamburgers and cheeseburgers only. The burgers were a tenth of a pound of meat, all fried the same way, for fifteen cents. You got a slice of cheese on it for four cents more. Soft drinks were ten cents, sixteen-ounce milk shakes were twenty cents, and coffee was a nickel.

The McDonald brothers showed Kroc the design of a new drive-in building. It was red and white with touches of yellow. There was a set of arches that went through the roof. There was also a tall sign out front with arches illuminated by neon tubes.

Kroc’s excitement grew:

That night in my motel room I did a lot of heavy thinking about what I’d seen during the day. Visions of McDonald’s restaurants dotting crossroads all over the country paraded through my brain. In each store, of course, were eight Multimixers whirring away and paddling a steady flow of cash into my pockets.

The next day, Kroc returned to see the operation in action again. He paid particular attention to how the french fries were made. McDonald’s french fries were outstanding and a key to the store’s success. Kroc observed carefully and thought that he had memorized the process for making terrific french fries. Kroc admits this was a mistake because he missed a few things.

Kroc met with Mac and Dick McDonald again. This time, Kroc asked them why they didn’t expand into a chain. The brothers demurred. When pressed, they pointed to their house on a hill. They said they were leading a peaceful existence and didn’t want any more problems. Eventually, Kroc said that he himself could open up the new locations.

 

CHAPTER 2

Kroc:

When I flew back to Chicago that fateful day in 1954, I had a freshly signed contract with the McDonald brothers in my briefcase. I was a battle-scared veteran of the business wars, but I was still eager to go into action. I was 52 years old. I had diabetes and incipient arthritis. I had lost my gall bladder and most of my thyroid gland in earlier campaigns. But I was convinced the best was ahead of me. I was still green and growing, and I was flying along at an altitude slightly higher than a plane.

Kroc recounts that he was born in Oak Park, just west of Chicago, in 1902. Kroc’s parents were of Czech origin Bohemians, as Ray says. His father, Louis Kroc, had gone to work for Western Union at age twelve and had worked his way up. Ray Kroc’s mother, Rose, was “a loving soul.” She gave piano lessons to make extra money.

A map of czech republic with the flag on it.

(Czech Republic on map with flag pin, Photo by Sjankauskas)

Ray Kroc’s brother, Bob, became a professor and medical researcher, but Ray wasn’t much interested in school. Ray wasn’t even interested in reading books:

I was never much of a reader when I was a boy. Books bored me. I liked action. But I spent a lot of time thinking about things. I’d imagine all kinds of situations and how I would handle them.

They called me Danny Dreamer a lot, even later when I was in high school and would come home all excited about some scheme I’d thought up. I never considered my dreams wasted energy; they were invariably linked to some form of action. When I dreamed about having a lemonade stand, for example, it wasn’t long before I set up a lemonade stand. I worked hard at it, and I sold a lot of lemonade. I worked at a grocery store one summer when I was still in grammar school. I worked at my uncle’s drug store. I worked in a tiny music store I’d started with two friends. I worked at something whenever possible. Work is the meat in the hamburger of life. There is an old saying thatall work and no play makes Jack a dull boy. I never believed it because, for me, work was play. I got as much pleasure out of it as I did from playing baseball.

Kroc went with his father to see many Chicago Cubs games. The Cubs were contenders then.

Kroc enjoyed working for his uncle Earl Edmund Sweet’s drug store soda fountain in Oak Park.

That was where I learned that you could influence people with a smile and enthusiasm and sell them a sundae when what they’d come for was a cup of coffee.

Kroc learned to play the piano well. He thought he could make money as a piano man. He ended up going into the music store business with two friends. But it didn’t really work.

Though Kroc didn’t like schoolone reason being that the progress felt much too slowthere was one school activity he did like: debating.

When World War I came, Kroc got a job selling coffee beans and novelties door-to-door. He thought he wouldn’t need to go back to school. Soon Kroc felt he should be a part of the war effort. Kroc:

My parents objected strenuously, but I finally talked them into letting me join up as a Red Cross ambulance driver. I had to lie about my age, of course, but even my grandmother could accept that. In my company, which assembled in Connecticut for training, was another fellow who had lied about his age to get in. He was regarded as a strange duck, because whenever we had time off and went out on the town to chase girls, he stayed in camp drawing pictures. His name was Walt Disney.

Kroc writes that he wanted to be a salesman, and also to play the piano. For a time, he sold novelty ribbons. Kroc was doing well:

In 1919 anyone making twenty-five or thirty dollars a week was doing well, and it wasn’t long beforeon good weeks with a lot of musical jobsI was making more money than my father.

Kroc had several jobs as a piano man, including playing in a band at Paw-Paw Lake, Michigan. That’s where he met his first wife, Ethel Flemming, of Scottish background.

Kroc continues:

My next job was in Chicago’s financial district as a board marker on the New York Curb, as the market that became the American Stock Exchange used to be called. My employer was a firm named Wooster-Thomas. A substantial sound to that, I thought. My job was to read the ticker tape and translate the symbols from it into prices that I posted on the blackboard for the scrutiny of the gentlemen who frequented our office. I later learned that the impressive-sounding name fronted a bucket-shop operation that was selling watered stock all over the place.

A bit later, Kroc got a job selling Lily brand paper cups.

 

CHAPTER 3

Kroc was selling Lily paper cups from early in the morning until 5:00 or 5:30pm. He says he would have worked longer, but he had a job playing piano at radio station WGES in Oak Park. Kroc worked at WGES 6pm to 8pm, and then 10pm to 2am. Kroc:

I was driven by ambition. I hated to be idle for a minute.

A close up of several cups on the table

(Photo of paper cups by Fedoseeva Galina)

Kroc again:

My cup sales kept growing as I learned how to plan my work and work my plan. My confidence grew at the same rate. I found that my customers appreciated a straightforward approach. They would buy if I made my pitch and asked for their order without a lot of beating around the bush. Too many salesmen, I found, would make a good presentation and convince the client, but they couldn’t recognize that critical moment when they should have stopped talking. If I ever notice my prospect starting to fidget, glancing at his watch or looking out the window or shuffling the papers on his desk, I would stop talking right then and ask for his order.

Winter of 1924 was tough for the paper cup business. Kroc notes that one reason he didn’t do well was because he put the customer first:

My philosophy was one of helping my customer, and if I couldn’t sell him by helping him improve his own sales, I felt I wasn’t doing my job.

Kroc started doing well in the paper cup business. But knowing how things slowed down in the winter, Kroc took a 5-month leave of absence. He got a job in Fort Lauderdale, Florida, selling real estate for W. F. Morang & Son. Kroc quickly became a top salesman.

The property was underwater, but there was a solid bed of coral rock beneath, and the dredging for the intercoastal raised all the lots high and dry, with permanent abutments. People who purchased those lots really got a bargain, even though the prices were astronomical for those times, because the area is now one of the most beautiful in all of Florida, and lots there are worth many times what they sold for then.

Of course, there were many lots sold at that time that didn’t turn out to be good investments at all. There was a great deal of chicanery. After a crackdown, Kroc got a job playing piano before returning to Chicago.

 

CHAPTER 4

From 1927 to 1937, Kroc focused entirely on selling paper cups. The paper container industry was undergoing several changes. But then the stock market crashed in 1929, which ushered in the Great Depression. Kroc’s father, who had been successfully speculating in real estate, was hit hard.

In 1930, Kroc saw an opportunity at the soda fountains in Walgreen’s Drug Company.

A close up of an ice machine with many different drinks

(Soda fountain, Photo by Bigapplestock)

At Walgreen’s, customers could buy sodas “to go.” Kroc tried to convince the food service man for Walgreen’s, a man named McNamarra. No go. But then Kroc got McNamarra to try it for one month using free cups.

Finally he agreed. I brought him the cups, and we set the thing up at one end of the soda fountain. It was a big success from the first day. It wasn’t long before McNamarra was more excited about the idea of takeouts than I was. We went in to see Fred Stoll, the Walgreen purchasing agent, and set up what was to be a highly satisfactory arrangement for both of us. The best part of it for me personally was that every time I saw a new Walgreen’s store going up it meant new business. This sort of multiplication was clearly the way to go. I spent less and less time chasing pushcart vendors around the West Side and more time cultivating large accounts where big turnover would automatically winch in sales in the thousands and hundreds of thousands. I went after Beatrice Creamery, Swift, Armour, and big plants with in-factory food service systems such as U.S. Steel.

Soon Kroc had roughly fifteen salesmen working for him.

I loved to see one of these young fellows catch hold and grow in his job. It was the most rewarding thing I’d ever experienced.

Kroc counselled his salesmen to sell themselves first, which would make it easier to sell paper cups.

Kroc mentions one of his customers, Ralph Sullivan in Battle Creek, Michican, who invented a new way to make milk shakes:

Ralph had come up with the idea of reducing butterfat content in a milk shake by making it with frozen milk. The traditional method of making a shake was to put eight ounces of milk into a metal container, drop in two small scoops of ice cream, add flavoring, and put the concoction onto a spindle mixer. Ralph’s formula was to take regular milk, add a stabilizer, sugar, corn starch, and a bit of vanilla flavoring and freeze it. The result was ice milk. He would put four ounces of milk into a metal container, drop in four scoops of this ice milk, and finish it off in the traditional way. The result was a much colder, much more viscous drink, and people loved it. The lines around his store in the summertime were nothing less than amazing. This ice milk shake had a lot of advantages over regular milk shakes. Instead of being a thin, semicool drink, it was thick and very cold.

The Multimixer was a piece of equipment that could make five milk shakes at once. It was a game changer. Kroc ended up leaving the paper cup business in order to sell Multimixers. Kroc formed a partnership with the inventor of the Multimixer, Earl Prince.

 

CHAPTER 5

Kroc encountered a great deal of adversity in his life, especially when he was trying to sell Multimixers.

For me, this was the first phase of grinding it out building my personal monument to capitalism. I paid tribute… for many years before I was able to rise with McDonald’s on the foundation I had laid. Perhaps without that adversity I might not have been able to persevere later on when my financial burdens were redoubled.

A red stamp that says share work.

(Illustration by Chris Dorney)

Kroc successfully marketed Multimixers at restaurant and dairy association conventions. Soon Kroc was so busy that he had to hire a bookkeeper. Partly by luck, he found Mrs. June Martino. She was warm and compassionate, but also focused and able. June studied electronics at Northwestern University. Because higher mathematics was difficult for her, she had a tutor. She was determined and “no challenge was too big for her,” notes Kroc.

 

CHAPTER 6

In Southern California in the early 1930s, the drive-in restaurant came into existence. Mac and Dick McDonald were New Englanders who moved to Southern California to work on movies. At one point, they ran their own movie theatre. Sometimes they only ate on meal a day in order to save money. They would have a hot dog from a nearby stand.

Dick McDonald later recalled that he and his brother noticed that the hot dog stand was the only business doing well then. That probably gave the brothers the idea of launching a drive-in restaurant.

The McDonald brothers’ first restaurant in San Bernardino was doing a great deal of business, but it still wasn’t very profitable. Kroc:

So they did a courageous thing. They closed that successful restaurant in 1948 and reopened it a short time later with a radically different kind of operation. It was a restaurant stripped down to the minimum in service and menu, the prototype for legions of fast-food units that later would spread across the land. Hamburgers, fries, and beverages were prepared on an assembly line basis, and, to the amazement of everyone, Mac and Dick included, the thing worked! Of course, the simplicity of the procedure allowed the McDonalds to concentrate on quality in every step, and that was the trick.

A hamburger restaurant with many items on the ground.

(Original McDonald’s fast food restaurant, Photo by Cogart Strangehill, via Wikimedia Commons)

Kroc reached an agreement with the McDonald brothers. Kroc would be able to franchise copies of McDonald’s everywhere in the United States. He admits he made a mistake in the contract with the McDonalds: any changes to Kroc’s units would have to be put in writing, signed by both brothers, and sent by registered mail. The McDonalds had an affable openness and Kroc trusted them. But there would be problems later.

The agreement stipulated that Kroc would receive 1.9 percent of gross sales from franchisees. Of that, 0.5 percent would go to the McDonald brothers. Kroc also could charge an initial franchise fee of $950 for each license.

Making great french fries was essential:

…I had explained to Ed MacLuckie with great pride the McDonald’s secret for making french fries. I showed him how to peel the potatoes, leaving just a bit of the skin to add flavor. Then I cut them into shoestring strips and dumped them into a sink of cold water. The ritual captivated me. I rolled my sleeves to the elbows and, after scrubbing down in proper hospital fashion, I immersed my arms and gently stirred the potatoes until the water went white with starch. Then I rinsed them thoroughly and put them into a basket for deep frying in fresh oil.

The only trouble was that, after following this process, the french fries tasted like mush. Something had gone wrong or there was a missing step. Eventually Kroc learned that potatoes taste better if they’re allowed to dry out. (Without knowing it, the McDonald brothers had been letting their potatoes dry in the desert breeze.) It took Kroc and associates three months before they perfected the process of making french fries.

Kroc’s first store was in a mediocre location, but it did well. Many of Kroc’s golfing friends from Rolling Green became successful McDonald’s operators.

Kroc frequently helped prepare a McDonald’s for opening. He didn’t mind mopping or cleaning the restrooms, even if he was in his suit.

 

CHAPTER 7

Harry Sonneborn resigned as vice-president of Tastee-Freeze and sold all his stock because he wanted to work in Ray Kroc’s organization. Sonneborn had noticed how exceptionally well a McDonald’s restaurant nearby was doing. Kroc told him that McDonald’s couldn’t afford to hire him. However, the company needed the help and Harry was persistent. McDonald’s ended up hiring him.

Kroc envisioned Sonneborn dealing with finance, June Martino running the office, and he himself managing operations and new development. Kroc, Sonneborn, and Martino worked extremely hard, but it was also fun:

We were breaking new ground, and we had to make a lot of fundamental decisions that we live with for years to come. This is the most joyous kind of executive experience. It’s thrilling to see your creation grow.

A large yellow banana shaped building with two red and white flags.

(Old style McDonald’s, Photo by Wahkeenah, via Wikimedia Commons)

Kroc writes that one fundamental decision he made was that the corporation would not be a supplier for its operators. Kroc explains:

My belief was that I had to help the individual operator succeed in every way I could. His success would ensure my success. But I couldn’t do that and, at the same time, treat him as a customer. There is a basic conflict in trying to treat a man as a partner on the one hand while selling him something at a profit on the other. Once you get into the supply business, you become more concerned about what you are making on sales to your franchisee than with how his sales are doing… Our method enabled us to build a sophisticated system of purchasing that allows the operator to get his supplies at rock-bottom prices.

Opening new locations was slow and painful work. Kroc describes what they were trying to build:

We wanted to build a restaurant system that would be known for food of consistently high quality and uniform methods of preparation.

A man standing in front of an open window.

(Photo by Ben Garney, via Wikimedia Commons)

Kroc and associates also realized that McDonald’s should go into the restaurant development business. The idea came from Harry Sonneborn. They started Franchise Realty Corporation with $1,000 paid-in capital. Harry turned that into $170 million worth of real estate. The idea was to get a property owner to lease his land on a subordinated basis. Kroc observes:

This was the beginning of real income for McDonald’s. Harry devised a formula for the monthly payments being made by our operators that paid our own mortgage and other expenses plus a profit. We received this monthly minimum or a percentage of the volume the operator did, whichever was greater.

Harry succeeded in getting life insurance companies to invest, which gave McDonald’s the capital they needed to keep growing rapidly.

Kroc notes the gratitude he felt toward Harry Sonneborn and June Martino:

…June later told me that all the while her two boys were growing up, she never made it to one of their birthday parties or graduation ceremonies, and there were several times that she had to be in the office on Christmas. I knew what she and Harry were doing, because I was in the same boat… I couldn’t give them raises to compensate them for their past efforts, but I could make sure that they would be rewarded when McDonald’s became one of the country’s major companies, which I never doubted it would. I gave them stock ten percent to June and twenty percent to Harry and ultimately it would make them rich.

 

CHAPTER 8

Fred Turner was a terrific worker and natural leader, says Kroc. At first, Turner was going to be a franchisee. To get experience, he started out as a worker in an already established McDonald’s. But Kroc realized that Turner should be in charge of corporate operations. Turner started at headquarters in January 1957. The company opened twenty-five new locations that year, and Turner was involved in every one.

Also involved in each opening in 1957 was Jim Schindler, a stainless-steel supplier from Leitner Equipment Company. At June’s suggestion, Kroc hired Schindler. Kroc had to pay him $12,000 a year, more than Harry, June, or Ray himself was getting. Kroc remarks that Schindler might not have come on board for that salary had he not had a Bohemian background like Kroc.

Kroc comments on a difference between Sonneborn and himself:

Harry was the scholarly type. He analyzed situations on the basis of management theory and economic principles. I proceeded on the strength of my salesman’s instinct and my subjective assessment of people.

A green wall with the word " stink " spelled out in colorful blocks.

(Illustration by Airdone)

Although he wasn’t perfect, Kroc excelled at picking the right people, which was central to McDonald’s success. But Kroc couldn’t explain exactly how he did it.

Sonneborn and Kroc complemented each other in many ways. And Fred Turner added another dimension. For instance, the hamburger bun was an object of close attention for McDonald’s. Fred Turner had some ideas:

We were buying our buns in the midwest from Louis Kuchuris’ Mary Ann Bakery. At first they were cluster buns, meaning that the buns were attached to each other in clusters of four to six, and they were only partially sliced. Fred pointed out that it would be much easier and faster for a griddle man if we had individual buns instead of clusters and if they were sliced all the way through. The baker could afford to do it our way because of the large quantities of buns we were ordering. Fred also worked with a cardboard box manufacturer on the design of a sturdy, reusable box for our buns. Handling these boxes instead of the customary packages of twelve reduced the baker’s packaging cost, so he was able to give us a better price on the buns. It also reduced our shipping costs and streamlined our operations. With the old packages, it didn’t take long for a busy griddle man to find himself buried in paper. Then there was the time spent opening packages, pulling buns from the cluster, and halving them. These fractions of seconds added up to wasted minutes. A well-run restaurant is like a winning baseball team, it makes the most of every crew member’s talents and takes advantage of every split-second opportunity to speed up service.

Many suppliers were getting the chance of a lifetime to grow with McDonald’s. For example, Mary Ann Bakery went from being a small company to having a plant with a quarter-mile long conveyor belt.

Keep in mind that headquarters set the standards for quality, and also made recommendations for packaging. But each franchisee did the purchasing for itself. Headquarters also helped suppliers figure out ways to lower their costs. These cost savings were passed to the franchisees.

Kroc describes the close attention paid to the hamburger patty:

We decided that our patties would be ten to the pound, and that soon became the standard for the industry. Fred did a lot of experimenting in the packaging of patties, too. There was a kind of paper that was exactly right, he felt, and he tested and tested until he found out what it was. It had to have enough wax on it so that the patty would pop off without sticking when you slapped it onto the griddle. But it couldn’t be too stiff or the patties would slide and refuse to stack up. There also was a science in stacking patties. If you made the stack too high, the ones on the bottom would be misshapen and dried out. So we arrived at the optimum stack, and that determined the height of our meat suppliers’ packages. The purpose of all these refinements, and we never lost sight of it, was to make our griddle man’s job easier to do quickly and well. All the other considerations of cost cutting, inventory control, and so forth were important to be sure, but they were secondary to the critical detail of what happened there at that smoking griddle. This was the vital passage in our assembly line, and the product had to flow through it smoothly or the whole plant would falter.

 

CHAPTER 9

In 1960, three life insurance companies agreed to lend the company $1.5 million in exchange for 22.5 percent of the stock. The insurance companies did well when they sold their stock a few years later for $7 to $10 million. Had they held their stock until 1973, however, they would have gotten over $500 million dollars. In any case, the loan was vital to the company’s rapid expansion in the 1960s.

McDonald’s hired people and paid them as little as possible, but also gave them stock. Those who stayed did very well. Bob Papp became vice-president in charge of construction. John Haran helped Harry with real estate. Dick Boylan helped Harry with finances.

One study showed that Ray Kroc had made more millionaires than any other person in history. Kroc comments:

I don’t know about that… I’d rather say I gave a lot of men the opportunity to become millionaires. They did it themselves. I merely provided the means. But I certainly do know a powerful number of success stories.

A group of coins stacked on top of each other.

(Photo byBj¸rn Hovdal)

McDonald’s doesn’t confer success on anyone. It takes guts and staying power to make it with one of our restaurants. At the same time, it doesn’t require any unusual aptitude or intellect. Any man with common sense, dedication to principles, and a love of hard work can do it. And I have stood flatfooted before big crowds of our operators and asserted that any man who gets a McDonald’s store today and works at it relentlessly will become a success, and many will become millionaires no question.

Some people go out of their way to give the competition a bad name. Some even suggest planting spies. Kroc has a different view, although he readily admits going through the garbage cans of competitors.

My way of fighting the competition is the positive approach. Stress your own strengths, emphasize quality, service, cleanliness, and value

QSC and V are core values for McDonald’s:

  • Quality
  • Service
  • Cleaniness
  • Value

 

CHAPTER 10

The McDonald brothers offered to sell McDonald’s all the rights, the name, and the San Bernardino storeto Kroc and associates for $2.7 million, which would give each brother a million dollars after taxes. Harry designed a brilliant way to finance the purchase.

Kroc on the formation of Hamburger University:

The idea of holding classes for new operators and managers had occurred to me when I first brought Fred Turner into headquarters. He was enthusiastic about it, too, and it was one of those goals that keep coming up in meetings but are put aside to make room for more pressing things. Fred refused to let the idea get buried, though. He collaborated with Art Bender and one of our field consultants named Nick Karos to compile a training manual for operators…

A sign that says hamburger university and some flowers.

(Public domain photo)

Kroc notes the growing public attention on McDonald’s:

Ours was the kind of story the American public was longing to hear. They’d had enough of doom and gloom and cold war politics.

Dick Boylan hired a young accountant named Gerry Newman, who was brilliant. At the time, the company had huge revenue but no cash flow. Newman helped the situation by changing the pay period from weekly to bimonthly.

Kroc on integrity:

…I’ve worked out many a satisfactory deal on the strength of a handshake. On the other hand, I’ve been taken to the cleaners often enough to make me a certified cynic. But I’m just too naturally cheerful to play that role for long…

 

CHAPTER 11

Kroc had a hard time getting Harold Freund to come out of retirement and build a bakery to serve McDonald’s operators. But finally Freund agreed.

Kroc was also looking for a meat supplier. He wanted Bill Moore of Golden State Foods to do it. But Moore’s plant and equipment were outdated, and needed an infusion of capital. When Moore told Kroc about the problem, Kroc told him to hang in there because McDonald’s was going to keep growing rapidly. Moore hung in there. A few years later, Moore had enough money to build a large manufacturing and warehouse complex in City of Industry, California. Kroc:

His meat plant there now processes 300 million hamburger patties a year for McDonald’s restaurants, and in addition, he makes syrup for soft drinks and manufactures milk-shake mix. He also has gone into distribution for McDonald’s units. He perfected the one-stop service idea, in which a truck pulls up to one of our stores and fills all its needs, like an old-fashioned grocery store delivery truck, with a single call. This results in great savings for both parties….

I could tell the same story about most of the suppliers who started with us in the early days and grew right along with us.

 

CHAPTER 12

In 1963, the company built 110 stores. Revenue was $129.6 million [over $1 billion in 2018 dollars] and net income was $2.1 million [over $17 million in 2018 dollars]. Kroc believed in decentralized management:

We had 637 stores now, and it was unwieldy to supervise them all from Chicago. It has always been my belief that authority should be placed at the lowest possible level. I wanted the man closest to the stores to be able to make decisions without seeking directives from headquarters.

A hand is holding a marker and writing on the wall.

(Illustration by ibreakstock)

Kroc writes:

…for its size [1977], McDonald’s today is the most unstructured corporation I know, and I don’t think you could find a happier, more secure, harder working group of executives anywhere.

Back to 1966:

This was in July 1966, a year in which we broke through the top of our charts again with $200 million in sales, and the scoreboards on the golden arches in front of all our stores flipped to “OVER 2 BILLION SOLD.” Cooper and Golin sent out a blitz of press releases interpreting the magnitude of this event for a space-conscious public. “If laid end-to-end,” they enthused, “two billion hamburgers would circle the earth 5.4 times!” Great fun. Even Harry Sonneborn got caught up in the spirit of promoting McDonald’s, and he pulled off a stunt that made me proud of him. He wanted to have us represented in the big Macy’s Thanksgiving Day parade in New York, and he approved the concept of McDonald’s All-American High School Band, made up of the two best musicians from each state and the District of Columbia. Then he hired the world’s biggest drum and had it shipped by flatcar from a university in Texas… It was a huge success. So was the introduction of our clown, Ronald McDonald, who made his national television debut in the parade.

 

CHAPTER 13

Harry Sonneborn listened to forecasters telling him in 1967 that the country was headed into recession. If true, it perhaps made sense to conserve cash and not expand much (or at all). But such forecasts are notoriously unreliable, especially as a guide to business. No one knows when bears markets or recessions will come.

Warren Buffett puts it best:

  • We will continue to ignore political and economic forecasts, which are an expensive distraction for many investors and businessmen.
  • Market forecasters will fill your ear but never fill your wallet.
  • Stop trying to predict the direction of the stock market, the economy, interest rates, or elections.
  • [On economic forecasts:]Why spend time talking about something you don’t know anything about? People do it all the time, but why do it?

A man in a suit and tie holding a telescope.

(Illustration by Maxim Popov)

To quote Peter Lynch:

Nobody can predict interest rates, the future direction of the economy, or the stock market. Dismiss all such forecasts and concentrate on what’s actually happening to the companies in which you’ve invested.

Also, different individual businesses have different reactions to bear markets and recessions. Perhaps McDonald’s could do well enough during a recession, given its cheap prices.

In any case, Harry put a moratorium on all new store development because he thought business activity was going to slow down. But there were many dozens of new locations in the works. Why not proceed? Kroc thought McDonald’s should continue opening new locations. Kroc argued with Harry and forced the issue, with the result that Harry resigned.

McDonald’s Canada did even better than McDonald’s in the United States. There was less competition in Canada. McDonald’s Canada achieved an average of a million dollars in sales for all their locations. This put them ahead of the U.S. locations.

 

CHAPTER 14

Additions to McDonald’s menu over the years usually came from ideas that operators had. Filet-O-Fish, Big Mac, Hot Apple Pie, and Egg McMuffin, for example. Kroc:

I keep a number of experimental menu additions in the works all the time. Some of them now being tested in selected stores may find their way into general use. Others, for a variety of reasons, will never make it. We have a complete test kitchen and experimental lab on my ranch, where all of our products are tested; this is in addition to the creative facility in Oak Brook.

A blue background with several different types of lab equipment.

(Illustration by lkonstudio)

Kroc loves looking for new locations for McDonald’s stores:

Finding locations for McDonald’s is the most creatively fulfilling thing I can imagine. I go out and check out a piece of property. It’s nothing but bare ground, not producing a damned thing for anybody. I put a building on it, and the operator gets into business there employing fifty or a hundred people, and there is new business for the garbage man, the landscape man, and the people who sell the meat and buns and potatoes and other things. So out of that bare piece of ground comes a store that does, say, a million dollars a year in business. Let me tell you, it’s great satisfaction to see that happen.

 

CHAPTER 15

Kroc bought the San Diego Padres baseball team:

I was greeted like a hero in San Diego. Old men and little boys stopped me in the street to thank me for saving baseball for the city. The mayor presented me with an award in the opening ceremonies of our first home game. The sportswriters also gave me an award…

During the first home game, Kroc grabbed the microphone in the public address booth. He apologized to the crowd for the poor performance of the team. He said he was “disgusted.” This led to a new rule that no one but the official announcer can use the public address system during a game. Kroc explains that it’s no crime to lose unless you fail to do your best.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The Innovator’s Solution


April 3, 2022

The Innovator’s Dilemma is a business classic by Clayten M. Christensen. Good companies frequently fail precisely because they are good. Good companies invest insustaining technologies,which are generally high-functioning, high-margin, and demanded by customers, instead ofdisrupting technologies,which start out relatively low-functioning, low-margin, and not demanded by customers.

The Innovator’s Solution, by Clayton Christensen and Michael Raynor, aims at presenting solutions to the innovator’s dilemma.

A blue background with glowing lights and lines.

(Illustration by Rapeepon Boonsongsuwan)

Outline:

  • The Growth Imperative
  • How Can We Beat Our Most Powerful Competitors?
  • What Products Will Customers Want to Buy?
  • Who Are the Best Customers For Our Products?
  • Getting the Scope of the Business Right
  • How to Avoid Commoditization
  • Is Your Organization Capable of Disruptive Growth?
  • Managing the Strategy Development Process
  • There is Good Money and There is Bad Money
  • The Role of Senior Executives in Leading New Growth

 

THE GROWTH IMPERATIVE

As companies grow larger, it becomes more difficult to grow. But shareholders demand growth. Many companies invest aggressively to try to create growth, but most fail to do so. Why is creating growth so hard for larger companies?

A snail with a leaf in it's mouth.

(Image by Bearsky23)

Christensen and Raynor note three explanations that seem plausible but are wrong:

  • Smarter managers could have succeeded. But when it comes to sustaining growth that creates shareholder value, 90 percent of all publicly traded companies have failed to create it for more than a few years. Are 90 percent of all managers are below average?
  • Managers become risk-averse. But here again, the facts don’t support the explanation. Managers frequently bet billion-dollar companies on one innovation.
  • Creating new-growth businesses is inherently unpredictable. The odds of success are low, as reflected by how venture capitalists invest. But there’s far more to the process of creating growth than just luck.

The innovator’s dilemma causes good companies to invest in high-functioning, high-margin products that their current customers want. This can be seen in the process companies follow to fund ideas:

The process of sorting through and packaging ideas into plans that can win funding… shapes those ideas to resemble the ideas that were approved and became successful in the past. The processes have in fact evolved to weed out business proposals that target markets where demand might be small. The problem for growth-seeking managers, of course, is that the exciting growth markets of tomorrow are small today.

A dearth of good ideas is rarely the core problem in a company that struggles to launch exciting new-growth businesses. The problem is in the shaping process. Potentially innovative new ideas seem inexorably to be recast into attempts to make existing customers still happier.

It’s possible to gain greater understanding of how companies create profitable growth. If we can develop a better theory, then we can make better predictions. There are three stages in theory-building, say Christensen and Raynor:

  • Describe the phenomena in question.
  • Classify the phenomena into categories.
  • Explain what causes the phenomena, and under what circumstances.

Building a theory is iterative. Scientists keep improving their descriptions, classifications, and causal explanations.

Frequently there is not enough understanding of the circumstances under which businesses succeed.

To know for certain what circumstances they are in, managers also must know what circumstances they arenot in. When collectively exhaustive and mutually exclusive categories of circumstances are defined, things get predictable: We can state what will cause what and why, and can predict how that statement of causality might vary by circumstance.

 

HOW CAN WE BEAT OUR MOST POWERFUL COMPETITORS?

A word cloud with words related to disruptive technology.

(Illustration by T. L. Furrer)

Compared to existing products, disruptive innovations start out simpler, more convenient, and less expensive.

Once the disruptive product gains a foothold in new or low-end markets, the improvement cycle begins. And because the pace of technological progress outstrips customers’ ability to use it, the previously not-good-enough technology eventually improves enough to intersect with the needs of more demanding customers. When that happens, the disruptors are on a path that will ultimately crush the incumbents.

Most disruptive innovations are launched by entrants. A good example is minimills disrupting integrated steel companies.

Minimills discovered that by melting scrap metal, they could make steel at 20 percent lower cost than the integrated steel mills. But the quality of steel the minimills initially produced was low due to the use of scrap metal. Their steel could only be used for concrete reinforcing bar (rebar).

The rebar market was naturally more profitable for the minimills, due to their lower cost structure. The integrated steel mills were happy to give up what for them was a lower-margin business. The minimills were profitable as long as they were competing against integrated steel mills that were still supplying the rebar market. Once there were no integrated steel mills left, the price of the rebar dropped 20 percent to reflect the lower cost structure of minimills.

This pattern kept repeating. The minimills looked up-market again. The minimills expanded their capacity to make angle iron, and thicker bars and rods. The minimills reaped significant profits as long as they were competing against integrated steel mills still left in the market for bar and rod. Meanwhile, integrated steel mills gradually abandoned this market because it was lower-margin for them. After the last integrated steel mill dropped out, the price of bar and rod dropped 20 percent to reflect the costs of minimills.

So the mimimills looked up-market again to structural beams. Most experts thought minimills wouldn’t be able to roll structural beams. But the minimills were highly motivated and came up with very clever innovations. Once again, the minimills experienced nice profits as long as they were competing against integrated steels mills. But when the last integrated steel mill dropped out of the structural beam market, the price dropped 20 percent.

A line graph with different types of technology.

(Image by Megapixie, via Wikimedia Commons)

Christensen and Raynor add:

The sequence repeated itself when the leading minimill, Nucor, attacked the steel sheet business. Its market capitalization now dwarfs that of the largest integrated steel company, U.S. Steel. Bethlehem Steel is bankrupt as of the time of this writing.

This is not a history of bungled steel company management. It is a story of rational managers facing the innovator’s dilemma: Should we invest to protect the least profitable end of our business, so that we can retain our least loyal, most price-sensitive customers? Or should we invest to strengthen our position in the most profitable tiers of our business, with customers who reward us with premium prices for better products?

The authors note that these patterns hold for all companies, not just technology companies. Also, they define “technology” as “the process that any company uses to convert inputs of labor, materials, capital, energy, and information into outputs of greater value.” Christensen and Raynor:

Disruption does not guarantee success, but it sure helps: The Innovator’s Dilemma showed that following a strategy of disruption increased the odds of creating a successful growth business from 6 percent to 37 percent.

New-market disruptions relate to consumers who previously lacked the money or skills to buy and use the product, or they relate to different situations in which the product can be used. New-market disruptions compete with”nonconsumption.”

Low-end disruptions attack the least profitable and most overserved customers in the original market.

Examples of new-market disruptions:

The personal computer and Sony’s first battery-powered transistor pocket radio were new-market disruptions, in that their initial customers were new consumers – they had not owned or used the prior generation of products and services. Canon’s desktop photocopiers were also a new-market disruption, in that they enabled people to begin conveniently making their own photocopies around the corner from their offices, rather than taking their originals to the corporate high-speed photocopy center where a technician had to run the job for them.

The authors then explain low-end disruptions:

…Disruptions such as steel minimills, discount retailing, and the Korean automakers’ entry into the North American market have been pure low-end disruptions in that they did not create new markets– they were simply low-cost business models that grew by picking off the least attractive of the established firms’ customers.

Many disruptions are a hybrid of new-market and low-end.

Christensen and Raynor suggest three sets of questions to determine if an idea has disruptive potential. The first set of questions relates to new-market potential:

  • Is there a large population of people who historically have not had the money, equipment, or skill to do this thing for themselves, and as a result have gone without it altogether or have needed to pay someone with more expertise to do it for them?
  • To use the product or service, do customers need to go to an inconvenient, centralized location?

The second set of questions concerns low-end disruptions:

  • Are there customers at the low-end of the market who would be happy to purchase a product with less (but good enough) performance if they could get it at a lower price?
  • Can we create a business model that enables us to earn attractive profits at the discount prices required to win the business of these overserved customers at the low end?

A final question is a litmus test:

  • Is the innovation disruptive to all of the significant incumbent firms in the industry? If it appears to be sustaining to one or more significant players in the industry, then the odds will be stacked in that firm’s favor, and the entrant is unlikely to win.

 

WHAT PRODUCTS WILL CUSTOMERS WANT TO BUY?

Christensen and Raynor:

All companies face the continual challenge of defining and developing products that customers will scramble to buy. But despite the best efforts of remarkably talented people, most attempts to create successful new products fail. Over 60 percent of all new-product development efforts are scuttled before they ever reach the market. Of the 40 percent that do see the light of day, 40 percent fail to become profitable and are withdrawn from the market.

A person writing on the screen of an interactive whiteboard.

(Photo by Kirill Ivanov)

The authors stress that customers “hire” products to do “jobs.” We need to think about what customers are trying to do and the circumstances involved.

…This is how customers experience life. Their thought processes originate with an awareness of needing to get something done, and then they set out to hire something or someone to do the job as effectively, conveniently, and inexpensively possible… In other words, the jobs that customers are trying to get done or the outcomes that they are trying to achieve constitute a circumstance-based categorization of markets.

The authors give the example of milkshakes. What are the jobs that people “hire” milkshakes for? Nearly half of all milkshakes are bought early the morning. Often these customers want to have a less boring commute. Also, a morning milkshake helps to avoid feeling hungry at 10:00. At other times of day, parents were observed buying milkshakes for their children as a way to calm them down. Armed with this knowledge, milkshake sellers can improve the milkshakes they sell at specific times of day.

The key here is observing what people are trying to accomplish. Develop and test hypotheses accordingly. Then develop products rapidly and get fast feedback.

It’s often much easier to figure out how to develop a low-end disruption. That’s because the market already exists. The goal is to move gradually up-market.

Why do many executives, instead of following jobs-to-be-done segmentation, focus on market segments not aligned with how customers live their lives? Christensen and Raynor say there are at least four reasons:

  • Fear of focus.
  • Senior executives’ demand for quantification of opportunities.
  • The structure of channels.
  • Advertising economics and brand strategies.

The first two reasons relate to resource allocation. The second two reasons concern the targeting of customers rather than circumstances.

Focus is scary – until you realize that it only means turning your back on markets you could never have anyway. Sharp focus on jobs that customers are trying to get done holds the promise ofgreatly improving the odds of success in new-product development.

Focus spelled out in wooden blocks with a magnifying glass.

(Photo by Creativefire)

Rather than understand how customers and markets work, most market research is focused on defining the size of the opportunity. This is the mistake of basing research on the available data instead of finding out about the jobs customers are trying to do.

When they frame the customer’s world in terms of products, innovators start racing against competitors by proliferating features, functions, and flavors of products that mean little to customers. Framing markets in terms of customer demographics, they average across several different jobs that arise in customers’ lives and develop one-size-fits-all products that rarely leave most customers fully satisfied. And framing markets in terms of an organization’s boundaries further restricts innovators’ abilities to develop products that will truly help their customers get the job done perfectly.

Regarding the structure of channels:

Many retail and distribution channels are organized by product categories rather than according to the jobs that customers need to get done. This channel structure limits innovators’ flexibility in focusing their products on jobs that need to be done, because products need to be slotted into the product categories to which shelf space has been allocated.

Christensen and Raynor give the example of a manufacturer of power tools. It learned that when workers were hanging a door, they used seven different tools, none of which was specific to the task. The manufacturer invented a new tool that noticeably simplified the job. But retail chains refused to sell the new tool because they didn’t have pre-existing shelf space for it.

Brands should be based on jobs to be done.

If a brand’s meaning is positioned on a job to be done, then when the job arises in a customer’s life, he or she will remember the brand and hire the product. Customers pay significant premiums for brands that do a job well.

Some executives worry that a low-end disruption might harm their established brand. But they can avoid this issue by properly naming each product.

 

WHO ARE THE BEST CUSTOMERS FOR OUR PRODUCTS?

As long as a business can profit using discount prices, the business can do well selling a low-end innovation. It’s much harder to find new-market customers. How do you determine if nonconsumers will become consumers of a given product? Once again, the job-to-be-done perspective is crucial.

A green arrow with the words new customers next to it.

(Illustration by Alexmillos)

The authors continue:

A new-market disruption is an innovation that enables a larger population of people who previously lacked the money or skill now to begin buying and using a product and doing the job for themselves. From this point forward, we will use the termsnonconsumers andnonconsumption to refer to this type of situation, where the job needs to get done but a good solution historically has been beyond reach.

Christensen and Raynor identify four elements in new-market disruption:

  • The target customers are trying to get a job done, but because they lack the money or skill, a simple, inexpensive solution has been beyond reach.
  • These customers will compare the disruptive product to having nothing at all. As a result, they are delighted to buy it even though it may not be as good as other products available at high prices to current users with deeper expertise in the original value network. The performance hurdle required to delight such new-market customers is quite modest.
  • The technology that enables the disruption might be quite sophisticated, but disruptors deploy it to make the purchase and use of the product simple, convenient, and foolproof. It is the “foolproofedness” that creates new growth by enabling people with less money and training to begin consuming.
  • The disruptive innovation creates a whole new value network. The new consumers typically purchase the product through new channels and use the product in new venues.

When disruptions come, established firms must take two key steps: First, when it comes to resource allocation, identify the disruption as a threat. Second, those charged with building a new technology as a response should view their task as an opportunity. This group should be an independent entity within the overall company.

Disruptive channels are often required to reach new-market customers:

…A company’s channel includes not just wholesale distributors and retail stores, but any entity that adds value to or creates value around the company’s product as it wends its way toward the hands of the end user…

We use this broader definition of channel because there needs to be symmetry of motivation across the entire chain of entities that add value to the product on its way to the end user. If your product does not help all of these entities do their fundamental job better – which is to move up-market along their own sustaining trajectory toward higher-margin business – then you will struggle to succeed. If your product provides the fuel that entities in the channel need to move toward improved margins, however, then the energy of the channel will help your new venture succeed.

 

GETTING THE SCOPE OF THE BUSINESS RIGHT

It’s often advised to stick to your core competence. The trouble is that something that doesn’t seem core today may turn out to be critical tomorrow.

Consider, for example, IBM’s decision to outsource the microprocessor for its PC business to Intel, and its operating system to Microsoft. IBM made these decisions in the early 1980s in order to focus on what it did best – designing, assembling, and marketing computer systems… And yet in the process of outsourcing what it did not perceive to be core to the new business, IBM put into business the two companies that subsequently captured most of the profit in the industry.

The solution starts again with the jobs-to-be-done approach. If the current products are not good enough, integration is best. If the current products are more than good enough, outsourcing makes sense.

A wooden block with the words product design written in it.

(Photo by Marek Uliasz)

Christensen and Raynor explain product architecture and interfaces:

An architecture is interdependent at an interface if one part cannot be created independently of the other part– if the way one is designed and made depends on the way the other is being designed and made. When there is an interface across which there are unpredictable interdependencies, then the same organization must simultaneously develop both of the components if it hopes to develop either component.

Interdependent architectures optimize performance, in terms of functionality and reliability. By definition, these architectures are proprietary because each company will develop its own interdependent design to optimize performance in a different way…

In contrast, a modular interface is a clean one, in which there are no unpredictable interdependencies across components or stages of the value chain. Modular components fit and work together in well-understood and highly defined ways. A modular architecture specifies the fit and function of all elements so completely that it doesn’t matter who makes the components or subsystems, as long as they meet the specifications…

Modular architectures optimize flexibility, but because they require tight specification, they give engineers fewer degrees of freedom in design. As a result, modular flexibility comes at the sacrifice of performance.

The authors point out that most products fall between the two extremes of interdependence and pure modularity.

When product functionality and reliability are not yet good enough, firms that build their products around proprietary, interdependent architectures have a competitive advantage. That’s because competitors with product architectures that are modular have less freedom and so cannot optimize performance.

The authors mention RCA, Xerox, AT&T, Standard Oil, and U.S. Steel:

These firms enjoyed near-monopoly power. Their market dominance was the result of the not-good-enough circumstance, which mandated interdependent product or value chain architectures and vertical integration. But their hegemony proved only temporary, because ultimately, companies that have excelled in the race to make the best possible products find themselves making products that are too good.

Eventually customers evolve in what they want. They become willing to pay for speed, convenience, and customization. Product architecture evolves towards more modular design. This deeply impacts industry structure. Independent, nonintegrated organizations become able to sell components and subsystems. Industry standards develop that specify modular interfaces.

 

HOW TO AVOID COMMODITIZATION

Many think commoditization is inevitable, no matter how good the innovation. Christensen and Raynor reached a different conclusion:

One of the most exciting insights from our research about commoditization is that whenever it is at work somewhere in a value chain, a reciprocal process of de-commoditization is at work somewhere else in the value chain. And whereas commoditization destroys a company’s ability to capture profits by undermining differentiability, de-commoditization affords opportunities to create and capture potentially enormous wealth.

Companies that position themselves at a place in the value chain where performance is not yet good enough will earn the profits when a disruption is occurring. Just as Wayne Gretsky sought to skate to where the puck would be (not where it is), companies should position themselves where the money will be (not where it is).

A man in blue jacket holding hockey stick.

(Photo of Wayne Gretzky by Rick Dikeman, via Wikimedia Commons)

When products are not yet good enough, companies with interdependent, proprietary architecture have strong advantages in differentiation and in cost structures.

This is why, for example, IBM, as the most integrated competitor in the mainframe computer industry, held a 70 percent market share but made 95 percent of the industry’s profits: It had proprietary products, strong cost advantages, and high entry barriers… Making highly differentiable products with strong cost advantages is a license to print money, and lots of it.

Of course, as a company seeks to outdo competitors, eventually it overshoots on the reliability and functionality that customers can use. This leads to a change in the basis of competition. There’s evolution towards modular architectures. This process starts at the bottom of the market, where functionality overshoots first, and then moves gradually up-market.

Christensen and Raynor comment that “industry” itself is usually a faulty categorization. Value chains evolve as the processes of commoditization and de-commoditization gradually repeat over time.

What’s fascinating– it’s the innovator’s dilemma– is that as innovators are moving up the value chain, established firms gradually abandon their lower-margin products and focus on their higher-margin products. Established firms repeatedly focus on areas that increase their ROIC (return on invested capital) in the short term. But these same decisions move established firms away from where the profits will be in the future.

Brands are most valuable when products aren’t yet good enough. A brand can signal to potential customers that the products they seek will meet their standards. When the performance of the products becomes more than good enough, the power of brands diminishes. Christensen and Raynor:

The migration of branding power in a market that is composed of multiple tiers is a process, not an event. Accordingly, the brands of companies with proprietary products typically create value mapping upward from their position on the improvement trajectory– toward those customers who still are not satisfied with the functionality and reliability of the best that is available. But mapping downward from the same point– toward the world of modular products where speed, convenience, and responsiveness drive competitive success– the power to create powerful brands migrates away from the end-use product, toward the subsystems and the channel.

This has happened in heavy trucks. There was a time when the valuable brand, Mack, was on the truck itself. Truckers paid a significant premium for Mack the bulldog on the hood. Mack achieved its preeminent reliability through its interdependent architecture and extensive vertical integration. As the architectures of large trucks have become more modular, however, purchasers have come to care far more whether there is a Cummins or Caterpillar engine inside than whether the truck is assembled by Paccar, Navistar, or Freightliner.

 

IS YOUR ORGANIZATION CAPABLE OF DISRUPTIVE GROWTH?

Many innovations fail because the managers or corporations lack the capabilities to create a successful disruption. Often the very skills that cause a leading company to succeed – through sustaining innovations – cause the same company to fail when it comes to disruptive growth.

The authors define capability by what they call the RPV framework– resources, processes, and values.

Resources are usually people, or things such as technology and cash. What most often causes failure in disruptive growth is the wrong choice of managers. It’s often thought that right-stuff attributes, plus a string of uninterrupted successes, is the best way to choose leaders of a disruptive venture.

But the skills needed to run an established firm are quite different from the skills needed to manage a disruptive venture.

In order to be confident that managers have developed the skills required to succeed at a new assignment, one should examine the sorts of problems they have wrestled with in the past. It is not as important that managers have succeeded with the problem as it is for them to have wrestled with it and developed the skills and intuition for how to meet the challenge successfully the next time around. One problem with predicting future success from past success is that managers can succeed for reasons not of their own making– and we often learn far more from our failures than our successes. Failure and bouncing back from failure can be critical courses in the school of experience. As long as they are willing and able to learn, doing things wrong and recovering from mistakes can give managers an instinct for better navigating through the minefield the next time around.

A quote from seneca on a piece of paper.

(Photo by Yuryz)

Successful companies have good processes in place: “Processes include the ways that products are developed and made and the methods by which procurement, market research, budgeting, employee development and compensation, and resource allocation are accomplished.”

Processes evolve as ways to complete specific tasks. Effective organizations tend to have processes that are aligned with tasks. But processes are not flexible and they’re not meant to be. You can’t take processes that work for an established firm and expect them to work in a new-growth venture.

The most important processes usually relate to market research, financial projections, and budgeting and reporting. Some processes are hard to observe. But it makes sense to look at whether the organization has faced similar issues in the past.

Values:

An organization’s values are the standards by which employees make prioritization decisions – those by which they judge whether an order is attractive or unattractive, whether a particular customer is more important or less important than another, whether an idea for a new product is attractive or marginal, and so on.

Employees at every level make prioritization decisions. At the executive tiers, these decisions often take the form of whether or not to invest in new products, services, and processes. Among salespeople, they consist of on-the-spot, day-to-day decisions about which customers they will call on, what products to push with those customers, and which products not to emphasize. When an engineer makes a design choice or a production scheduler puts one order ahead of another, it is a prioritization decision.

This brings up a crucial point:

Whereas resources and processes are often enablers that define what an organization can do, values often represent constraints– they define what the organization cannot do. If, for example, the structure of a company’s overhead costs requires it to achieve gross profit margins of 40 percent, a powerful value or decision rule will have evolved that encourages employees not to propose, and senior managers to kill, ideas that promise gross margins below 40 percent. Such an organization would be incapable of succeeding in low-margin businesses– because you can’t succeed with an endeavor that cannot be prioritized. At the same time, a different organization’s values, shaped around a very different cost structure, might enable it to accord high priority to the very same project. These differences create the asymmetries of motivation that exist between disruptors and disruptees.

Acceptable gross margins and cost structures co-evolve. Another issue is how big a business opportunity has to be. A huge company may not consider interesting opportunities if they’re too small to move the needle. However, a wisely run large company will set up small business units for which smaller opportunities are still meaningful.

In the start-up stage, resources are important, especially people. A few key people can make all the difference.

A group of people are connected to each other.

(Photo by Golloween)

But over time, processes and values become more important. Many hot, young companies fail because the founders don’t create the processes and values needed to continue to create successful innovations.

As processes and values become almost subconscious, they come to represent theculture of the organization. When a few people are still important, it’s far easier for the company to change in response to new problems. But it becomes much more difficult when processes and values are established, and more difficult still when the culture is widespread.

Executives who are building new-growth businesses therefore need to do more than assign managers who have been to the right schools of experience to the problem. They must ensure that responsibility for making the venture successful is given to an organization whose processes will facilitate what needs to be done and whose values can prioritize those activities.

 

MANAGING THE STRATEGY DEVELOPMENT PROCESS

In every company, there are two strategy-making processes– deliberate and emergent. Deliberate strategies are conscious and analytical.

Emergent strategy… is the cumulative effect of day-to-day prioritization and investment decisions made by middle managers, engineers, salespeople, and financial staff. These tend to be tactical, day-to-day operating decisions that are made by people who are not in a visionary, futuristic, or strategic state of mind. For example, Sam Walton’s decision to build his second store in another small town near his first one in Arkansas for purposes of logistical and managerial efficiency, rather than building it in a large city, led to what became Wal-Mart’s brilliant strategy of building in small towns discount stores that were large enough to preempt competitors’ ability to enter. Emergent strategies result from managers’ responses to problems or opportunities that were unforeseen in the analysis and planning stages of the deliberate strategy-making process.

A small figure of a man standing on top of a chess board.

(Photo by Alain Lacroix)

If an emergent strategy proves effective, it can be transformed into a deliberate strategy.

Emergent processes should dominate in circumstances in which the future is hard to read and in which it is not clear what the right strategy should be. This is almost always the case during the early phases of a company’s life. However, the need for emergent strategy arises whenever a change in circumstances portends that the formula that worked in the past may not be as effective in the future. On the other hand, the deliberate strategy process should be dominant once a winning strategy has become clear, because in those circumstances effective execution often spells the difference between success and failure.

Initiatives that receive resources are strategic actions, and strategies evolve based on the results of strategic actions.Resource allocation decisions are especially influenced by a company’s cost structure – which determines gross profit margins – and by the size of a given opportunity. A great opportunity for a small company – or a small unit – might not move the needle for a large company.

Additional influences on resource allocation include the sales force’s incentive compensation system. Salespeople decide which customers to focus on and what products to emphasize. Customers, by their preferences, have significant influence on the resource allocation process. Competitors’ actions are also important.

The resource allocation process, in other words, is a diffused, unruly, and often invisible process. Executives who hope to manage the strategy process effectively need to cultivate a subtle understanding of its workings, because strategy is determined by what comes out of the resource allocation process, not by the intentions and proposals that go into it.

A word cloud of words related to resource management.

(Illustration by Amir Zukanovic)

In 1971, by chance Intel invented the microprocessor during a funded development project for a Japanese calculator company, Busicom. But DRAMs, not microprocessors, continued to represent the bulk of the company’s sales through the 1970s. By the early 1980s, DRAMs had the lowest profit margins of Intel’s products.

Microprocessors, by contrast, because they didn’t have much competition, earned among the highest gross profit margins. The resource allocation process systematically diverted manufacturing resources away from DRAMs and into microprocessors. This happened automatically, without any explicit management decisions. Senior management continued putting two-thirds of the R&D budget into DRAM research. By 1984, senior management realized that Intel had become a microprocessor company.

Intel needed both emergent and deliberate strategies:

A viable strategic direction had to coalesce from the emergent side of the process, because nobody could foresee clearly enough the future of microprocessor-based desktop computers. But once the winning strategy became apparent, it was just as critical to Intel’s ultimate success that the senior management then seized control of the resource allocation process and deliberately drove the strategy from the top.

It’s essential for start-ups to be flexible and adaptive:

Research suggests that in over 90 percent of all successful new businesses, historically, the strategy that the founders had deliberately decided to pursue was not the strategy that ultimately led to the business’s success. Entrepreneurs rarely get their strategies exactly right the first time… One of the most important roles of senior management during a venture’s early years is to learn from emergent sources what is working and what is not, and then to cycle that learning back into the process through the deliberate channel.

Once managers hit upon a strategy that works, then they must focus on executing that strategy aggressively.

The authors highlight three points of executive leverage on the strategy process. Managers must:

  • Carefully control the initial cost structure of a new-growth business, because this quickly will determine the values that will drive the critical resource allocation decisions in that business.
  • Actively accelerate the process by which a viable strategy emerges by insuring that business plans are designed to test and confirm critical assumptions using tools such as discovery-driven planning.
  • Personally and repeatedly intervene, business by business, excercising judgment about whether the circumstance is such that the business needs to follow an emergent or deliberate strategy-making process. CEOs must not leave the choice about strategy process to policy, habit, or culture.

Managers have to pay particular attention to the initial cost structure of the business:

The only way that a new venture’s managers can compete against nonconsumption with a simple product is to put in place a cost structure that makes such customers and products financially attractive. Minimizing major cost commitments enables a venture to enthusiastically pursue the small orders that are the initial lifeblood of disruptive businesses in their emergent years.

 

THERE IS GOOD MONEY AND THERE IS BAD MONEY

The type and amount of money determines investor expectations, which in turn heavily influence the markets and channels the venture can and cannot target. Many potentially disruptive ideas get turned into sustaining innovations, which generally leads to failure.

Christensen and Raynor hold that the best money in early years ispatient for growth butimpatient for profit. Disruptive markets start out small, which is why patience for growth is important. Once a viable strategy has been identified, then impatience for growth makes sense.

Impatience for profit is important so that managers will test ideas as quickly as possible.

A row of colorful glass flasks and bottles.

(Image by Vpublic)

It’s crucial to keep costs low for both low-end and new-market disruptive strategies. This determines the type of customers that are attractive.

Financial results do not signal potential stall points well. Financial results are the fruit of investments made years ago. Financial results tell you how healthy the business was, not how healthy the business is. Reliable data generally are about the past. They only help with planning if the future resembles the past, which is often only true to a limited extent.

Christensen and Raynor suggest three policies for keeping the growth engine running:

  • Launch new growth businesses regularly when the core is still healthy – when it can still be patient for growth – not when financial results signal the need.
  • Keep dividing business units so that as the corporation becomes increasingly large, decisions to launch growth ventures continue to be made within organizational units that can be patient for growth because they are small enough to benefit from investing in small opportunities.
  • Minimize the use of profit from established businesses to subsidize losses in new-growth businesses. Be impatient for profit: There is nothing like profitability to ensure that a high potential business can continue to garner the funding it needs, even when the corporation’s core business turns sour.

 

THE ROLE OF SENIOR EXECUTIVES IN LEADING NEW GROWTH

Christensen and Raynor:

The senior executives of a company that seeks repeatedly to create new waves of disruptive growth have three jobs. The first is a near-term assignment: personally to stand astride the interface between disruptive growth businesses and the mainstream businesses to determine through judgment which of the corporation’s resources and processes should be imposed on the new business, and which should not. The second is a longer-term responsibility: to shephard the creation of a process that we call a “disruptive growth engine,” which capably and repeatedly launches successful growth businesses. The third responsibility is perpetual: to sense when the circumstances are changing, and to keep teaching others to recognize these signals. Because the effectiveness of any strategy is contingent on the circumstance, senior executives need to look to the horizon (which often is at the low end of the market or in nonconsumption) for evidence that the basis of competition is changing, and then initiate projects and acquisitions to ensure that the corporation responds to the changing circumstance as an opportunity for growth and not as a threat to be defended against.

The personal involvement of a senior executive is one of the most crucial things for a disruptive business. Often the most important improvements for the entire corporation begin as disruptions.

The vast majority of companies that successfully caught a disruptive innovation are companies still run by founders.

We suspect that founders have an advantage in tackling disruption because they not only wield the requisite political clout but also have the self-confidence to override established processes in the interests of pursuing disruptive opportunities. Professional managers, on the other hand, often seem to find it difficult to push in disruptive directions that seem counterintuitive to most other people in the organization.

 

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The Innovator’s Dilemma


March 27, 2022

The Innovator’s Dilemma is a business classic by Clayten M. Christensen. Why do so many good companies consistently fail to deal with certain kinds of technological change? Precisely because good companies are good, explains Christensen. Good companies invest insustaining technologies,which are generally high-functioning, high-margin, and demanded by customers, instead ofdisrupting technologies,which start out relatively low-functioning, low-margin, and not demanded by customers.

Christensen:

…Companies stumble for many reasons, of course, among them bureaucracy, arrogance, tired executive blood, poor planning, short-term investment horizons, inadequate skills and resources, and just plain bad luck. But this book is not about companies with such weaknesses: It is about well-managed companies that have their competitive antennae up, listen astutely to their customers, invest aggressively in new technologies, and yet still lose market dominance.

Such seemingly unaccountable failures happen in industries that move fast and in those that move slow; in those built on electronics technology and those built on chemical and mechanical technology; in manufacturing and in service industries.

Christensen gives the example of Sears Roebuck. At one point, more than 2 percent of all retail sales went to Sears. Sears pioneered important innovations in retailing, such as supply chain management, store brands, catalogue retailing, and credit card sales.

At the very time Sears was being praised as one of the best-managed companies in the world – in the mid 1960’s– the company was ignoring the rise of discount retailing and home centers. Sears also let Visa and MasterCard chip away at the huge lead Sears had in the use of credit cards in retailing.

Christensen offers more examples:

In some industries this pattern of leadership failure has been repeated more than once. Consider the computer industry. IBM dominated the mainframe market but missed by years the emergence of minicomputers, which were technologically much simpler than mainframes. In fact, no other major manufacturer of mainframe computers became a significant player in the minicomputer business. Digital Equipment Corporation created the minicomputer market and was joined by a set of other aggressively managed companies: Data General, Prime, Wang, Hewlett-Packard, and Nixdorf. But each of these companies in turn missed the desktop personal computer market. It was left to Apple Computer, together with Commodore, Tandy, and IBM’s stand-alone PC division, to create the personal-computing market. Apple, in particular, was uniquely innovative in establishing the standard for user-friendly computing. But Apple and IBM lagged five years behind the leaders in bringing portable computers to market. Similarly, the firms that built the engineering workstation market– Apollo, Sun, and Silicon Graphics– were all newcomers to the industry.

Christensen observes that many of these top computer manufacturers were at one point regarded as among the best-managed companies in the world. Yet they failed to invest in disruptive technologies precisely because these leaders focused on the high-performing, high-margin products their customers wanted. Why wouldn’t you focus on the most popular and profitable products?

Christensen says Xerox missed huge growth and profit opportunities in the market for small tabletop photocopiers. And not asingle integrated steel company had by 1995 built a plant using minimill technology, even though steel minimalls just two years later captured 40 percent of the North American steel market. Finally, of the thirty manufacturers of cable-actuated power shovels, only four survived the multi-decade transition to hydraulic excavation technology. Christensen comments:

As we shall see, the list of leading companies that failed when confronted with disruptive changes in technology and market structure is a long one. At first glance, there seems to be no pattern in the changes that overtook them. In some cases the new technologies swept through quickly; in others, the transition took decades. In some, the new technologies were complex and expensive to develop. In others, the deadly technologies were simple extensions of what the leading companies already did better than anyone else. One theme common to all of these failures, however, is that the decisions that led to failure were made when the leaders in question were widely regarded as among the best companies in the world.

Christensen asks: Were these firms never well-managed? Quite the opposite:

…in the cases of well-managed firms such as those cited above,good management was the most powerful reason they failed to stay atop their industries. Preciselybecausethese firms listened to their customers, invested aggressively in new technologies that would provide their customers more and better products of the sort they wanted, and because they carefully studied market trends and systematically allocated investment capital to innovations that promised the best returns, they lost their positions of leadership.

Here’s the lesson:

There are times at which it is rightnot to listen to customers, right to invest in developing lower-performance products that promiselower margins, and right to aggressively pursue small, rather than substantial, markets.

Christensen defines “technology” broadly as “the processes by which an organization transforms labor, capital, materials, and information into products and services of greater value.”

Part One, chapters 1 through 4, explains why seemingly good decisions lead to failure when it comes to disrupting technologies. Part Two, chapters 5 through 10, offers potential solutions to the innovator’s dilemma– how managers can do the best thing for their company’s near-term health while also investing sufficient resources in potentially disruptive technologies.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The One Device


March 20, 2022

Innovation is the primary driver of GDP growth. If we want to understand how most new wealth is created – and (perhaps) if we want to find inspiration for our own tinkering– we should study history. Especially economic history, the history of science, and the history of technology.

A new book,The One Device: The Secret History of the iPhone (New York: 2017, Little, Brown and Company), is a fascinating tale by Brian Merchant.

I’ve summarized each chapter (except for one):

  • Introduction
  • Exploring New Rich Interactions (ENRI)
  • A Smarter Phone
  • Minephones
  • Scratchproof
  • Multitouched
  • Prototyping
  • Lion Batteries
  • Image Stabilization
  • Sensing Motion
  • Strong-ARMed
  • Enter the iPhone
  • Hey, Siri
  • Designed in California, Made in China
  • Sellphone
  • The Black Market
  • The One Device

A close up of an iphone on top of a table.

(Photo byPavel Å evela, Wikimedia Commons)

 

INTRODUCTION

The iPhone is the bestselling product of all time:

In 2016, Horace Dediu, a technology-industry analyst and Apple expert, listed some of the bestselling products in various categories. The top car brand, the Toyota Corolla: 43 million units. The bestselling game console, the Sony PlayStation: 382 million. The number-one book series, Harry Potter: 450 million books. The iPhone: 1 billion. That’s nine zeroes. “The iPhone is not only the bestselling mobile phone but also the bestselling music player, the best selling camera, the bestselling video screen and the bestselling computer of all time,” he concluded. “It is, quite simply, the bestselling product of all time.”

Merchant cites a study by Nielsen that found that Americans spend an average of 11 hours a day in front of a screen. About 4.7 of those hours are in front of a phone. A study by British psychologists discovered that people probably use their phones twice as often as they think they do.

A person is eating chocolate pudding with a fork.

(Photo by Olena Golubova)

Two-thirds of Apple’s revenues come from the iPhone. People read news, engage in social media, use Google maps, send and receive messages, check email, employ calendars and workflows, and take pictures. Merchant:

The iPhone isn’t just a tool; it’s the foundational instrument of modern life.

But the invention of the iPhone – like many inventions – was a culmination of a long series of inventions.

The iPhone intertwines a phenomenal number of prior inventions and insights, some that stretch back into antiquity. It may, in fact, be our most potent symbol of just how deeply interconnected the engines that drive modern technological advancement have become.

Merchant again:

The iPhone is a deeply, almost incomprehensively, collective achievement… It’s a container ship of inventions, many of which are incompletely understood. Multitouch, for instance, granted the iPhone its interactive magic, enabling swiping, pinching, and zooming. And while Jobs publicly claimed the invention as Apple’s own, multitouch was developed decades earlier by a trail of pioneers by places as varied as CERN’s particle-accelerator labs to the University of Toronto to a start-up bent on empowering the disabled. Institutions like Bell Labs and CERN incubated research and experimentation; governments poured in hundreds of millions of dollars to support them.

Moreover, the mining of the raw materials used in the iPhone, and the factory labor that goes into mass-producing iPhones, are also central to the story. The result, writes Merchant, is what J.C.R. Licklider calledman-computer symbiosis:

A coexistence with an omnipresent digital reference tool and entertainment source, an augmenter of our thoughts and enabler of our impulses.

Although Apple’s policy of secrecy made it difficult for Merchant to interview insiders, he still managed to speak with dozens of people, including iPhone designers, engineers, and executives.

 

EXPLORING NEW RICH INTERACTIONS (ENRI)

A person holding an illuminated light bulb in front of a background with hexagons.

(Photo by Peshkova)

A small group– a few young software designers, an industrial engineer, and some input engineers– started meeting to invent new ways of interfacing with machines. Their mission: “Explore new rich interactions.” Merchant refers to this group as ENRI.

The team was experimenting with every stripe of bleeding-edge hardware– motion sensors, new kinds of mice, a burgeoning technology known as multitouch– in a quest to uncover a more direct way to manipulate information. The meetings were so discreet that not even Jobs knew they were taking place. The gestures, user controls, and design tendencies stitched together here would become the cybernetic vernacular of the new century– because the kernel of this clandestine collaboration would become the iPhone.

Two key engineers in the Human Interface group – also called the UI (User Interface) group – were Bas Ording, a Dutch software designer, and Imran Chaudhri, a British designer. Greg Christie, who’d come to Apply earlier to work on Newton, ended up in charge of the Human Interface group after the Newton failed to sell well.

Civil engineer Brian Huppi had gone back to school to study mechanical engineering after reading a book about Apple, Steven Levy’sInsanely Great. The book tells the story of how Jobs separated key Apple players, put a pirate flag above their department, and pushed them to create the pioneering Macintosh.

Huppi got a job at Apple as in input engineer in 1998. He got to know the Industrial Design (ID) group, headed by Jonathan Ive. When he grew bored interating laptop hardware, Huppi spoke with Duncan Kerr, who’d worked at the well-known design firm IDEO before coming to Apple. After Huppi and Kerr talked about innovations to the user experience, Kerr asked Jony Ive if they could form a small group to work on the topic. Ive liked the idea.

Huppi and Kerr started working with Christie, Ording, and Chaudhri. And they were joined by Josh Strickon, who came from MIT’s Media Lab. Strickon’s master’s thesis involved the development of a laser range finder for hand-tracking that could sense multiple fingers. The ENRI group met weekly in a conference room with their laptops. They took extensive notes, put drawings on whiteboards, and gave presentations to one another.

There were a lot of ideas. Some feasible, some boring, some outlandish and boreline sci-fi– some of those, Huppi says, he “probably can’t talk about,” because fifteen years later, they had yet to be developed, and “Apple still might want to do them someday.”

“We were looking at all sorts of stuff,” Strickon says, “from camera-tracking and multitouch and new kinds of mice.” They studied depth-sensing time-of-flight cameras like the sort that would come to be used in the Xbox Kinect. They explored force-feedback controls that would allow users to interact directly with virtual objects with the touch of their hands.

In many ways, the group was testing the limits of the old mouse-and-keyboard interface with the computer. Could there be an easier way to zoom, or to scroll and pan? Why couldn’t the user just tap, tap, tap on the screen for certain repetitive acts?

Tina Huang, an Apple engineer, had been experiencing wrist problems. One day, she showed up to work with trackpad made by FingerWorks, a small company in Delaware. It allowed her to use fluid hand movements to communicate complex commands to her Mac. The technology was calledmultitouch finger tracking.

A person playing with an interactive tablet

(Image by Willtron, Wikimedia Commons)

FingerWorks was founded by a bright PhD student, Wayne Westerman, and his dissertation advisor.

Resistive touch works by having two layers. When you push the outer layer, the inner layer registers the touch. But the resistive touchscreen is frequently inexact and glitchy. Capacitive touch, by contrast, works when the electricity in a human finger distorts the electrostatic field on the screen. Merchant:

A new, hands-on approach to computing, free of rodent intermediaries and ancient keyboards, started to seem like the right path to follow, and the ENRI team warmed to the idea of building a new user interface around the finger-based language of multitouch pioneered by Westerman– even if they had to rewrite or simplify the vocabulary. “It kept coming up– we want to be able to move things on the screen like a piece of paper on the table,” Chaudhri says.

The ENRI group worked very hard. But they barely noticed the long hours because they were exhilarated. They could sense the potential importance of new technologies like multitouch.

 

A SMARTER PHONE

In 1994, Frank Canova helped IBM invent a smartphone – the Simon Personal Communicator – that had most of the core functions of an iPhone. But the Simon was a box that size of a brick. The iPhone, coming over a decade later, was far more powerful. And it was thin and easy to use. The Simon was too far ahead of its time.

A black phone with a keyboard on the screen.

(Photo by Bcos47, Wikimedia Commons)

Merchant quotes history of technology scholar Carolyn Marvin:

In a historical sense, a computer is no more than an instantaneous telegraph with a prodigious memory, and all the communications inventions in between have simply been eleborations on the telegraph’s original work.

In the long transformation that begins with the first application of electricity to communication, the last quarter of the nineteenth century has a special importance. Five proto-mass media were invented during this period: the telephone, phonograph, electric light, wireless, and cinema.

Merchant sums it up:

The smartphone, like every other breakthrough technology, is built on the sweat, ideas, and inspiration of countless people. Technological progress is incremental, collective, and deeply rhizomatic, not spontaneous…

The technologies that shape our lives rarely emerge suddenly and out of nowhere; they are part of an incomprehensibly lengthy, tangled, and fluid process brought about by contributors who are mostly invisible to us. It’s a very long road back from the bleeding edge.

 

MINEPHONES

In the old colonial city of Potos­, Bolivia, there is a “rich hill” called Cerro Rico, nicknamed “The Mountain That Eats Men.”

The Mountain That Eats Men bankrolled the Spanish Empire for hundreds of years. In the sixteenth century, some 60 percent of the world’s silver was pulled out of its depths. By the seventeenth century, the mining boom had turned Potos­ into one of the biggest cities in the world; 160,000 people– local natives, African slaves, and Spanish settlers– lived here, making the industrial hub larger than London at the time. More would come, and the mountain would swallow many of them. Between four and eight million people are believed to have perished there from cave-ins, silicosis, freezing, or starvation.

A mountain with a house on top of it

(Photo of Cerro Rico by Mhwater, Wikimedia Commons)

Today fifteen thousand miners– many of them children as young as six years old– continue to work the mines for tin, lead, zinc, and a bit of silver. Merchant comments:

…metal mined by men and children wielding the most primitive of tools in one of the world’s largest and oldest continuously running mines– the same mine that bankrolled the sixteenth century’s richest empire– winds up inside one of today’s most cutting-edge devices. Which bankrolls one of the world’s richest companies.

Merchant asked a mining consultant to analyze the chemical composition of the iPhone. Results:

Element Percent of iPhone by weight Grams used in iPhone Average cost per gram Value of element in iPhone
Aluminum 24.14 31.14 $0.0018 $0.055
Arsenic 0.00 0.01 $0.0022
Gold 0.01 0.014 $40 $0.56
Bismuth 0.02 0.02 $0.0110 $0.0002
Carbon 15.39 19.85 $0.0022
Calcium 0.34 0.44 $0.0044 $0.002
Chlorine 0.01 0.01 $0.0011
Cobalt 5.11 6.59 $0.0396 $0.261
Chrome 3.83 4.94 $0.0020 $0.010
Copper 6.08 7.84 $0.0059 $0.047
Iron 14.44 18.63 $0.0001 $0.002
Gallium 0.01 0.01 $0.3304 $0.003
Hydrogen 4.28 5.52
Potassium 0.25 0.33 $0.0003
Lithium 0.67 0.87 $0.0198 $0.017
Magnesium 0.51 0.65 $0.0099 $0.006
Manganese 0.23 0.29 $0.0077 $0.002
Molybdenum 0.02 0.02 $0.0176 $0.000
Nickel 2.10 2.72 $0.0099 $0.027
Oxygen 14.50 18.71
Phosphorus 0.03 0.03 $0.0001
Lead 0.03 0.04 $0.0020
Sulfur 0.34 0.44 $0.0001
Silicon 6.31 8.14 $0.0001 $0.001
Tin 0.51 0.66 $0.0198 $0.013
Tantalum 0.02 0.02 $0.1322 $0.003
Titanium 0.23 0.30 $0.0198 $0.006
Tungsten 0.02 0.02 $0.2203 $0.004
Vanadium 0.03 0.04 $0.0991 $0.004
Zinc 0.54 0.69 $0.0028 $0.002

The iPhone is 24 percent aluminum, the most abundant metal on earth. Aluminum is very light and cheap. It comes from bauxite, which is often strip-mined. It takes four tons of bauxite to make one ton of aluminum.

The iPhone is 3 percent cobalt. Most of the cobalt is in the lithium-ion battery and is mined in the Democratic Republic of Congo. The mines there are almost completely unregulated. Workers, including children, toil around the clock. Deaths and injuries are common.

Oxygen, hydrogen, and carbon in the iPhone are associated with different alloys. Indium tin oxide functions as a conductor for the touchscreen. Aluminum oxides are in the casing. Silicon oxides are found in the microchip. (Small amounts of arsenic and gallium are also in the microchip.)

Silicon makes up 6 percent of the phone.

Merchant discovered that 34 kilograms (75 pounds) of ore would have to be mined to have the materials for one 129-gram iPhone.

A billion iPhones had been sold by 2016, which translates into 34 billion kilos (37 million tons) of mined rock. That’s a lot of moved earth– and it leaves a mark. Each ton of ore processed for metal extraction requires around three tons of water. This means that each iPhone “polluted” around 100 liters (or 26 gallons) of water… Producing 1 billion iPhones has fouled 100 billion liters (or 26 billion gallons) of water.

 

SCRATCHPROOF

In the early 1950s, Don Stookey, an inventor for Corning, discovered a form of glass that didn’t break. He was experimenting and accidentally heated lithium silicate to 900 degrees Celcius instead of 600. The silicate changed into an off-white substance which didn’t break when it fell on the floor.

A white bowl and a blue dish on top of a table.

(Photo of Corningware casserole dishes by Splarka, Wikimedia Commons)

In the early 1960s, Corning kept experimenting with the goal of creating even stronger glass. Eventually they created Chemcor, which is fifteen times stronger than regular glass.

By 1969, 42 million dollars had been invested in Chemcor. Unfortunately, nobody wanted it. Chemcor was too strong for car windshields, for instance. To survive some crashes, the windshield must break. But with Chemcor, the human skull would break against the windshield.

In 2005, Corning started looking as Chemcor again to see if it could be used as strong, affordable, and scratchproof glass in cellphones. So-called Gorilla Glass was invented and is now used in iPhones and other smartphones.

A phone with two screens and one is on.

(Illustration by Artsiom Kusmartseu)

 

MULTITOUCHED

Brent Stumpe, a Danish engineer working at CERN, invented capacitive multitouch in 1970s. Steve Jobs later claimed that Apple invented multitouch, but that’s not very accurate. As with much else in the iPhone, Apple improved the technology and used it in a new way. But Apple didn’t invent it.

Several people, in addition to Stumpe, invented multitouch or a precursor to multitouch. Bill Buxton and his team were working on multitouch at the University of Toronto in 1985. Buxton says that Bob Boie, at Bell Labs, probably came up with the first working multitouch system.

Engineer Eric Arthur Johnson invented a multitouch system for air traffic controllers in 1965.

…We do know what Johnson cited as prior art in his patent, at least: two Otis Elevator patents, one for capacitance-based proximity sensing (the technology that keeps the doors from closing when passengers are in the way) and one for touch-responsive elevator controls. He also named patents from General Electric, IBM, the U.S. military, and American Mach and Foundry. All six were filed in the early to mid-1960s; the idea for touch control was “in the air” even if it wasn’t being used to control computer systems.

Finally, he cites a 1918 patent for a “type-writing telegraph system.” Invented by Frederick Ghio, a young Italian immigrant who lived in Connecticut, it’s basically a typewriter that’s been flattened into a tablet-size grid so each key can be wired into a touch system. It’s like the analog version of your smartphone’s keyboard. It would have allowed for the automatic transmission of messages based on letters, numbers, and inputs– the touch-typing telegraph was basically a pre-proto-Instant Messenger.

William Norris, CEO of the supercomputer firm Control Data Corporation (CDC), fervently believed in touchscreens as the key to digital education. Norris commercialized PLATO– Programmed Logic for Automatic Teaching Operations. By 1964, PLATO had a touchscreen. Light sensors on the four sides of the screen registered wherever a finger touched the screen.

Wayne Westerman, an electrical engineering graduate student at the University of Delaware, invented a form of multitouch in his 1999 PhD dissertation. At last multitouch was poised to go mainstream.

Westerman’s mother had chronic back pain, while Westerman himself developed tendonitis in his wrists. When Westerman finished undergraduate studies at Purdue, he followed Neal Gallagher, a favorite professor, to the University of Delaware.

Westerman’s wrist pain grew worse, which pushed him to seek a solution. He invented a set of gestures to supplant the mouse and keyboard.

Westerman founded FingerWorks in 2001 with his dissertation advisor, Dr. John Elias.

At the beginning of 2005, FingerWorks’ iGesture pad won the Best of Innovation award at CES, the tech industry’s major annual trade show.

Still, at the time, Apple execs weren’t convinced that FingerWorks was worth pursuing– until the ENRI group decided to embrace multitouch.

Merchant comments:

Apple made multitouch flow, but they didn’t create it. And here’s why that matters: Collectives, teams, multiple inventors, build on a shared history. That’s how a core, universally adopted technology emerges…

A set of hands holding and touching different types of electronic devices.

(Illustration by Onyxprj)

 

PROTOTYPING

In the summer of 2003, Jony Ive decided the multitouch project was ready to be showed to Steve Jobs. At first, Jobs dismissed it. But then he embraced it. Later, Jobs even claimed that he invented it.

There was still a great deal of work to be done. The project went on lockdown in order to keep it completely secret. At this point, the researchers weren’t thinking about a phone at all.

A red seal that says top secret and confidential.

(Image by BP22Heber, Wikimedia Commons)

The project languished until late 2004, when Steve Jobs announced to the group that Apple was going to make a phone. It would take two years to get Apple’s operating system on to a phone.

Executives would clash; some would quit. Programmers would spend years of their lives coding around the clock to get the iPhone ready to launch, scrambling their social lives, their marriages, and sometimes their health in the process.

 

LION BATTERIES

Merchant tells of his visit to SQM, or Sociedad Qu­mica y Minera de Chile – the Chemical and Mining Society of Chile. SQM is the leading producer of potassium nitrate, iodine, and lithium. It’s located in Salar de Atacama in the Atacama Desert, the most arid place on earth. The desert gets half an inch of rainfall per year, and some areas much less.

Chilean miners work this alien environment every day, harvesting lithium from vast evaporating pools of marine brine. That brine is a naturally occurring saltwater solution that’s found here in huge underground reserves. Over the millenia, runoff from the nearby Andes Mountains has carried mineral deposits down to the salt flats, resulting in brines with unusually high lithium concentrations. Lithium is the lightest metal and least dense solid element, and while it’s widely distributed around the world, it never occurs naturally in pure elemental form; it’s too reactive. It has to be separated and refined from compounds, so it’s usually expensive to get. But here, the high concentration of lithium in the salar brines combined with the ultradry climate allows miners to harness good old evaporation to obtain the increasingly precious metal.

A person holding an empty glass with white substance inside.

(Lithium hydroxide with carbonate growths, Photo by Chemicalinterest, Wikimedia Commons)

Because lithium-ion batteries are essential for smartphones, tablets, laptops, and electric cars, lithium is increasingly referred to as “white petroleum.” Lithium doubled in value in the past couple years based on a jump in projected demand.

While doing postdoc work at Stanford in the early 1970s, chemist Stan Whittingham discovered a way to store lithium ions in sheets of titanium sulfide. This formed the basis for a rechargeable battery.

Whittingham developed the lithium-ion battery while working for Exxon. Hot on the heels of an oil crisis, Exxon had decided that it wanted to be the leading energy company and the leading producer of electric vehicles. But the lithium-ion battery was expensive to produce. And it had flammability issues. Once the oil crisis had passed, Exxon returned to its focus on producing oil.

The recent jumps in projected demand are mostly due to the opening of Tesla’s Gigafactory, which will be the world’s largest lithium-ion-battery factory. The global lithium-ion-battery market is expected to double to $77 billion by 2024, says Transparency Market Research.

A satellite image of an industrial area in the desert.

(Photo of Tesla’s Gigafactory by Planet Labs, Wikimedia Commons)

 

IMAGE STABILIZATION

There are obvious similarities for two different mass-market cameras:

  • Exhibit A: You Press the Button, We Do the Rest.
  • Exhibit B: We’ve taken care of the technology. All you have to do is find something beautiful and tap the shutter button.

Merchant explains:

Exhibit A comes to us from 1888, when George Eastman, the founder of Kodak, thrust his camera into the mainstream with that simple eight-word slogan. Eastman had initially hired an ad agency to market his Kodak box camera but fired them after they returned copy he viewed as needlessly complicated. Extolling the key virtue of his product– that all a consumer had to do was snap the photos and then take the camera into a Kodak shop to get them developed– he launched one of the most famous ad campaigns of the young industry.

Exhibit B is for the iPhone camera. The two ads are similar in their focus on ease of use and in their targeting of the average consumer.

At first, the 2-megapixel camera included on the iPhone wasn’t remarkable. But it wasn’t a priority at that point. By 2016, there were 800 employees dedicated to the camera, an 8-megapixel unit with a Sony sensor, optimal image-stabilization module, and a proprietary image-signal processor.

 

SENSING MOTION

A mass in a rotating system experiences a force perpendicular to the direction of motion and to the axis of rotation. This is theCoriolis effect. The Foucault pendulum in the Paris Observatory slowly changes direction over the course of a day due to this effect.

A globe with lines and points on it

(Coriolis effect, Wikimedia Commons)

Merchant:

The gyroscope in your phone is a vibrating structure gyroscope (VSG). It is… a gyroscope that uses a vibrating structure to determine the rate at which something is rotating. Here’s how it works: A vibrating object tends to continue vibrating in the same plane if, when, and as its support rotates. So the Coriolis effect– the result of the same force that causes Foucault’s pendulum to rotate to the right in Paris– makes the object exert a force on its own support. By measuring that force, the sensor can determine the rate of rotation.

Another sensor, the accelerometer, measures the acceleration of an object. If an iPhone is sideways, then it accelerates sideways– towards the ground– due to gravity. So the iPhone knows to flip the display from portrait to landscape.

Proximity sensors knows to turn off the display when you lift the iPhone to your ear. They work by emitting tiny bursts of infrared radiation, which hit an object and are reflected back. If the object is close, then the reflected radiation is more intense.

A person is holding an iphone on the table

(Photos of proximity sensor by Hyderabaduser, Wikimedia Commons)

For the iPhone to determine its place relative to everything else, it relies on GPS (Global Positioning System) – a globe-spanning system of satellites. GPS was developed by the U.S. Naval Research Laboratory in the 1960s and 1970s.

Today, every iPhone has a dedicated GPS chip that trilaterates with Wi-Fi signals and cell towers. Google Maps uses this technology.

 

STRONG-ARMed

In 1977, Alan Kay and his colleague Adele Goldberg developed the concept of a Dynabook, which was powerful, dynamic, and very easy to use.

The Dynabook, which looks like an iPad with a hard keyboard, was one of the first mobile-computer concepts ever put forward, and perhaps the most influential. It has since earned the dubious distinction of being the most famous computer that never got built.

A man holding a laptop and a book in front of a microphone.

(Alan Kay and the prototype of Dynabook, Photo by Marcin Wichary, Wikimedia Commons)

Kay is one of the fathers of personal computing. He once said that the Mac was the “first computer worth criticizing.” Kay holds that the Dynabook still has not been built. The smartphone, shaped in part by marketing departments, simply gives people more of what they already wanted, such as news and social media.

Because Moore’s law has been in effect for fifty years now, computer chips (which include transistors) have gotten dramatically smaller, more powerful, and less energy intensive. Moore’ law may be slowing down. But depending upon progress in areas such as quantum computing, there could still be much room for improvement before any limit is reached.

The first iPhone processor had 137,500,000 transistors. But the iPhone 7, released 9 years after the first iPhone, has 3.3 billion transistors, about 240 times more. Whatever app you just downloaded has more computing power than the first mission to the moon.

The other part of the story is a breakthrough low-power processor, without which the iPhone battery would drain far too quickly. The ARM processor is the most popular ever. 95 billion have been sold, with 15 billion shipped in 2015 alone. ARM chips are in everything: smartphones, computers, wristwatches, cars, coffeemakers, etc.

ARM stands for Acorn RISC Machine. RISC isreduced instruction set computing. Berkeley researchers developed RISC after they observed that most computer programs weren’t using the majority of a given processor’s instruction set.

A computer board with many different electronic components.

(Acorn RISC PC ARM-710 CPU, Photo by Flibble, Wikimedia Commons)

Sophie Wilson and Steve Furber were star engineers for Acorn, a company founded by Herman Hauser after he met Wilson and saw some of her designs for various machines. Wilson visited a group in Phoenix that designed the processor for Acorn’s computer. Wilson was surprised to find “two senior engineers and a bunch of school kids.” Wilson and Furber realized that they could develop their own RISC CPU for Acorn. Merchant quotes Wilson:

“It required some luck and happenstance, the papers being published close in time to when we were visiting Phoenix. It also required Herman. Herman gave us two things that Intel and Motorola didn’t give their staff: He gave us no resources and no people. So we had to build a microprocessor the simplest possible way, and that was probably the reason that we were successful.”

Also, Acorn wanted to simplify their designs. So they developed SoC, or System on a Chip, which integrates all the components of a computer on to one chip. Acorn didn’t realize how important SoC would become.

Merchant describes the evolution of apps for the iPhone:

The first iPhone shipped with sixteen apps, two of which were made in collaboration with Google. The four anchor apps were laid out on the bottom: Phone, Mail, Safari, and iPod. On the home screen, you had Text, Calendar, Photos, Camera, YouTube, Stocks, Google Maps, Weather, Clock, Calculator, Notes, and Settings. There weren’t any more apps available for download and users couldn’t delete or even rearrange the apps. The first iPhone was a closed, static device.

Then Jobs, continuously pressured by software developers, decided that they would allow web apps. Brett Bilbrey, who was senior manager of Apple’s Advanced Technology Group until 2013, observed:

“The thing with Steve was that nine times out of ten, he was brilliant, but one of those times he had a brain fart, and it was like, ‘Who’s going to tell him he’s wrong?'”

If mounting pressure from developers and Apple’s own executives wasn’t enough, there was the fact that the iPhone sold poorly for the first 3 to 6 months. Scott Forstall finally convinced Jobs to allow apps. Merchant:

…This was arguably the most important decision Apple made in the iPhone’s post-launch era. And it was made because developers, hackers, engineers, and insiders pushed and pushed. It was an anti-executive decision. And there’s a recent precedent – Apple succeeds when it opens up, even a little.

The iPod took off when Apple made iTunes for Windows. Before that, the iPod hardly sold.

If an app was approved for the iPhone and if it was monetized, then Apple would take a 30 percent cut.

…And that was when the smartphone era entered the mainstream. That’s when the iPhone discovered that its killer app wasn’t the phone, but a store for more apps.

A close up of an iphone with the app store on it

(iPhone apps and app store, Photo by Michael Damkier)

There are over 2 million apps in the App Store today. As of 2014, six years after the launch of the App Store, over 627,000 jobs have been created based on iOS and U.S.-based developers have earned more than $8 billion.

On the other hand, the majority of the app money is going to games and streaming media– services designed to be as addictive as possible. This is part of Kay’s point. We have the technology for a Dynabook. We have the technology to help us engage in productive and creative pursuits. But consumerism– channeled by marketing departments– has turned mobile computers into consumption devices.

 

ENTER THE iPHONE

In the mid-2000s, top engineers at Apple were regularly disappearing mysteriously. They ended up doing top secret work on what would become the iPhone. And they had time for little else. Everyone on the team was brilliant. The mission was impossible. The deadlines were impossible. Quite a few marriages were ruined.

The iPod didn’t sell its first two years. Finally Apple introduced iTunes software so that people could manage their iPods from computers running Windows, rather than just from Apple computers. After Apple’s success with iPod hardware and iTunes software, people both inside and outside Apple were wondering what else the company could do. Many ideas were mentioned, including a camera, a phone, and an electric car.

One thing everyone at Apple agreed on was that, before the iPhone, cell phones were “terrible.” Merchant:

“Apple is best when it’s fixing things that people hate,” Greg Christie tells me. Before the iPod, nobody could figure out how to use a digital music player; as Napster boomed, people took to carting around skip-happy portable CD players loaded with burned albums. And before the Apple II, computers were considered too complex and unwieldy for the lay person.

It took time to convince Steve Jobs that Apple should do a phone. Mike Bell, who’d worked at Apple for fifteen years and at Motorola’s wireless division before that, was one of those who helped convince Jobs. Bell was sure that computers, music players, and cell phones would converge. Eventually Jobs agreed.

Jobs contacted Bas Ording and Imran Chaudhri of the touchscreen-tablet project. Jobs said, “We’re gonna do a phone.” The engineers got to work. Many features of the iPhone that we now take for granted were the result of persistent tinkering.

A computer screen with electrical drawings on it.

(Photo by Sergey Gavrilichev)

But despite compelling multitouch demos, the team still lacked a coherent concept. Jobs gave the team a 2-week ultimatum in February, 2005. The team came through. Jobs was pleased. This meant a great deal more work, of course. Then Jobs did a presentation to the Top 100 at Apple. Another huge success.

Soon there were two separate approaches, code-named P1 and P2. P1 was the iPod phone. P2 was an evolving hybrid of multitouch technology and Mac software. Tony Fadell ran P1, while Scott Forstall managed P2. It’s not clear whether it was a good idea to have these two teams compete, given how much political conflict later erupted on the iPhone project.

The iPhone’s code name was Purple. Forstall’s group was viewed as the underdog by many, since Fadell had been responsible for many millions of iPod sales. But soon the touchscreen approach won out.

The next battle was over the operating system. Fadell’s group wanted to do it like the iPod, which used a rudimentary operating system. But Forstall’s team wanted to take Apple’s main operating system, OS X, and shrink it down. One top engineer, Richard Williamson, said:

“There were some epic battles, philosophical battles about trying to decide what to do.”

Once basic scrolling operations were demonstrated on the stripped-down OS X, the decision was essentially made: OS X.

A picture of the mac os logo with an apple face drawn on it.

(Photo by Mohamed Soliman)

 

HEY, SIRI

Merchant:

Siri is really a constellation of features – speech-recognition software, a natural-language user interface,and an artificially intelligent personal assistant. When you ask Siri a question, here’s what happens: Your voice is digitized and trasmitted to an Apple server in the Cloud while a local voice recognizer scans it right on your iPhone. Speech-recognition software translates your speech into text. Natural-language processing parses it. Siri consults what tech writer Stephen Levy calls the iBrain – around 200 megabytes of data about your preferences, the way you speak, and other details. If your question can be answered by the phone itself (“Would you set my alarm for eight a.m.?”), the Cloud request is canceled. If Siri needs to pull data from the web (“Is it going to rain tomorrow?”), to the Cloud it goes, and the request is analyzed by another array of models and tools.

The history of artificial intelligence is quite fascinating. I wrote about that and related topics here:https://boolefund.com/future-of-the-mind/

A computer generated image of two brains in the middle.

(Photo by Christian Lagereek)

One recent divide in AI is whether the computer should learn through symbolic reasoning or through repeated exposure to extensive data sets. When it comes to perception – computer vision, computer speech, pattern recognition – the data-driven approach works best. Machine learning is another term for this type of approach.

One problem with machine-learned models, however, is that a human can have a hard time understanding what the computer actually “knows.”

Consider chess. At some point, computing power will be great enough that a computer will be able to “solve” the game of chess by figuring out every single possible chain of moves. Perhaps white can always win. Would we say that such a supercomputer is “intelligent”? A program like this is similar to an extremely high-powered calculator. We don’t say that calculators are “intelligent” just because they can quickly and accurately compute using astronomical numbers.

Part of the problem is that we still have much to learn about how the human brain works.

 

DESIGNED IN CALIFORNIA, MADE IN CHINA

Merchant writes about his visit to China:

The vast majority of plants that produce the iPhone’s component parts and carry out the devices’s final assembly are based here, in the People’s Republic, where low labor costs and a massive, highly skilled workforce have made the nation an ideal place to manufacture iPhones (and just about every other gadget). The country’s vast, unprecedented production capabilities – the U.S. Bureau of Labor Statistics estimated that as of 2009 there were ninety-nine million factory workers in China – has helped the nation become the world’s largest economy. And since the first iPhone shipped, the company doing the lion’s share of the manufacturing is the Taiwanese Hon Hai Precision Industry Company, Ltd., better known by its trade name, Foxconn.

Foxconn is the single largest employer on mainland China; there are 1.3 million people on its payroll. Worldwide, among corporations, only Walmart and McDonald’s employ more. As of 2016, that was more than twice as many people working for the five most valuable tech companies in the United States– Apple (66,000), Alphabet (70,000), Amazon (270,000), Microsoft (64,000), and Facebook (16,000)– combined.

A blue and black logo for the computer company

(Wikimedia Commons)

Foxconn was in the news when it was learned that many of its workers were committing suicide.

The epidemic caused a media sensation– suicides and sweatshop conditions in the House of iPhone. Suicide notes and survivors told of immense stress, long workdays, and harsh managers who were prone to humiliate workers for mistakes; of unfair fines and unkept promises of benefits.

Foxconn CEO Terry Gou installed large nets outside many of the buildings to catch falling bodies. The company also hired counselors, and made workers sign no-suicide pledges. Steve Jobs remarked that the suicide rates at Foxconn were within the national averages and were lower than at many U.S. universities. Perhaps not the best thing to say, although technically accurate.

Merchant continues:

Shenzhen was the first SEZ, or special economic zone, that China opened to foreign companies, beginning in 1980. At that time, it was a fishing village that was home to some twenty-five thousand people. In one of the most remarkable urban transformations in history, today, Shenzhen is China’s third-largest city, home to towering skyscrapers, millions of residents, and, of course, sprawling factories. And it pulled off the feat in part by becoming the world’s gadget factory. An estimated 90 percent of the world’s consumer electronics pass through Shenzhen.

Many, if not most, Chinese people believe strongly in hard work and constant improvement. They are driven in part by the memory or knowledge of how poor most Chinese were in the recent past. They fear that if they don’t work hard and keep improving, they’ll become very poor again.

Merchant spoke with as many people as he could. But he’s careful to note that he didn’t get a truly representative sample, which would have required a massive canvassing effort and interviewing thousands of employees.

Merchant learned that most workers viewed the pace of work as relentless. They agreed that most workers only last a year.

Also, many thought that the management culture was cruel. Managers often used public condemnation if a mistake was made or if quota wasn’t met. Workers were frequently expected to stay silent. Even asking to use the restroom was often met with a rebuke.

A large sign in an asian mall with people walking around.

(Protest in 2011 outside new Apple Store in Hong Kong, Photo by SACOM, Wikimedia Commons)

Many Chinese workers would like to work for Huawei, a Chinese smartphone competitor. When one worker went to the recruiting office, they told him Huawei was full. But it wasn’t. He feels he was tricked into working for Foxconn. He suspects Foxconn has a deal with the recruiter.

Furthermore, Foxconn often didn’t keep promises. They offered free housing, but then charged exorbitant prices for electricity and water. Also, bonuses were often delayed. Moreover, many workers were told they would get overtime pay, but then received regular pay. Many workers were promised a raise but never got one.

 

SELLPHONE

Merchant writes:

…Simply put, the iPhone would not be what it is today were it not for Apple’s extraordinary marketing and retail strategies. It is in a league of its own in creating want, fostering demand, and broadcasting technological cool. By the time the iPhone was actually announced in 2007, speculation and rumor over the device had reached a fever pitch, generating a hype that few to no marketing departments are capable of ginning up.

Of course, the product itself is impressive, and has to be for these marketing tactics to work so well.

A man holding an iphone in his hand.

(2010 Photo by Matthew Yohe)

In the late 1990s or early 2000s, Jobs began to use secrecy much more than before. The “magical” aspect of a new Apple product is heightened by the use of secrecy.

At the same time, Apple uses scarcity. After launching a new iPhone, Apple deliberately keeps the supplies artificially low for at least a few weeks. In general, if something humans want is scarce, they tend to want it significantly more. A well-known psychological fact that Apple carefully exploits.

 

THE BLACK MARKET

Merchant:

Huaqiangbei is a bustling downtown bazaar: crowded streets, neon lights, sidewalk vendors, and chain smokers. My fixer Wang and I wander into SEG Electronics Plaza, a series of gadget markets surrounding a towering ten-story Best-Buy-on-acid on Huaqiangbei Road. Drones whir, high-end gaming consoles flash, and customers inspect cases of chips. Someone bumbles by on a Hoverboard. A couple shops over, a clustor of kiosks hock knockoff smartphones at deep discount. One saleswoman tries to sell me an iPhone 6 that’s running Google’s Android operating system. Another pitches a shiny Huawei phone for about twenty dollars.

A group of people sitting around tables in an indoor market.

(Huaqiangbei electronics market, Photo by Lzf)

Merchant, a bit later:

In downtown Shenzhen, a couple blocks from the famed electronics market, this smoky four-story building the size of a suburban minimall is an emporium for refurbished, reused, and black-market iPhones. You have to see it to believe it. I’ve never seen so many iPhones in one place – not at an Apple store, not raised by the crowd at a rock concert, not at CES. This is just piles and piles of iPhones of every color, model, and stripe.

Some booths are tricked-out repair stalls where young men and women examine iPhones with magnifying glasses and disassemble them with an array of tiny tools. There are entire stalls filled with what must be thousands of tiny little camera lenses. Others advertise custom casings… Another table has a huge pile of silver bitten-Apple logos that a man is separating and meting out. And it’s packed full of shoppers, buyers, repair people, all talking and smoking and poring over iPhone paraphernalia.

Some of the tables don’t sell iPhones to individuals but to wholesale buyers. Counterfeits are one thing. But these iPhones are virtually indistinguishable from the real thing.

Obvious counterfeits don’t last long:

In 2015, China shut down a counterfeit iPhone factory in Shenzhen, believed to have made some forty-one thousand phones out of secondhand parts. And you may have read headlines about counterfeit iPhone rings being busted up in the United States too, from time to time. In 2016, eleven thousand counterfeit iPhones and Samsung phones worth an estimated eight million dollars were seized in an NYPD raid. In 2013, border security agents seized two hundred and fifty thousand dollars’ worth of counterfeit iPhones from a Miami shop owner who says he sourced his parts legitimately.

But counterfeits are generally easy to spot because they won’t be compatible with specific software or they’ll have obvious glitches. So any iPhone that works like an iPhone is an iPhone, notes Merchant. Those iPhones available on the black market that have been made with iPhone parts are, for all practical purposes, iPhones, right?

Apple discourages customers from getting inside their phones. It uses proprietary screws. It issues takedown requests on grounds of copyright to blogs that post repair manuals. It voids warranties if anyone tries to repair their own phone or hires a thiry-party to do so. Apple does not sell any replacement parts for iPhones; customers have to pay Apple to do it, often at high prices.

 

THE ONE DEVICE

Merchant:

There’s a reason that all those software engineers had migrated to the interface designers’ home base – the iPhone was built on intense collaboration between the two camps. Designers could pop over to an engineer to see if a new idea was workable. The engineer could tell them which elements needed to be adjusted. It was unusual, even for Apple, for teams to be so tightly integrated.

“One of the important things to note about the iPhone team was there was a spirit of ‘We’re all in this together,'” Richard Williamson says. “There was a ton of collaboration across the whole stack, all the way from Bas Ording doing innovative UI mock-ups down to the OS team with John Wright doing modifications to the kernel. And we could do this because we were all actually in this lockdown area. It was maybe just forty people at the max, but we had this hub right above Jony Ive’s design studio. In Infinite Loop Two, you had to have a second access key to get in there. We pretty much lived there for a couple of years.”

A word cloud of collaboration related words.

(Photo by Rafal Olechowski)

The team was composed of brilliant engineers across the board. They worked long hours, and constantly collaborated. They would sit down together and figure it out as they went. Many ideas that would have been delayed, or even dismissed, under most circumstances became workable in short order.

Williamson credits Steve Jobs with creating essentially a start-up inside a large company. Put the best engineers together on the most promising project, insulate them from everyone else, push them to meet very high expectations, and give them unlimited resources.

The team was very focused on making the iPhone easy and intuitive to use. They thought carefully about how people manipulate physical things in their daily life. They wanted these movements to give users clues about how to use the iPhone. It goes without saying there would never be a user’s manual – that would be a failure by the team.

Then there was hardware. Merchant spoke with Tony Fadell:

“We had to get all kinds of experts involved,” he says. “third-party suppliers to help. We had to basically make a touchscreen company.” Apple hired dozens of people to execute the multitouch hardware alone. “The team itself was forty, fifty people just to do touch,” Fadell says. The touch sensors they needed to manufacture were not widely available yet. TPK, the small Taiwanese firm they found to mass-manufacture them, would boom into a multibillion-dollar company, largely on the strength of that one contract. And that was just touch– they were going to need Wi-Fi modules, multiple sensors, a tailor-made CPU, a suitable screen, and more.

Tony Fadell called the project “a moon shot… like the Apollo project.”

A picture of the apollo logo.

(Apollo program insignia, by NASA, Wikimedia Commons)

There was never enough people and never enough time. People worked seriously hard. Vacations and holidays were out of the question. There were quite a few divorces.

Merchant spoke with Evan Doll, who was on the iPhone team:

The ENRI team created a batch of interaction demos on an experimental touchscreen rig– right before Apple needed a successor to the iPod. FingerWorks came to market with consumer-friendly multitouch– just in time for the ENRI crew to use it as a foundation. Computer chips had to shrink. “So much of it is timing and getting lucky,” Doll says. “Maybe the ARM chips that powered the iPhone had been in development for a very long time, and maybe fortuitously had reached a happy place in terms of their capabilities. The stars aligned.” They also aligned with lithium-ion battery technology, and with the compacting of cameras. With the accretion of China’s skilled labor force, and the surfeit of cheaper metals around the world. The list goes on. “It’s not just a question of waking up one morning in 2006 and deciding that you’re doing to build the iPhone; it’s a matter of making these nonintuitive investments and failed products and crazy experimentation– and being able to operate on this huge timescale,” Doll says. “Most companies aren’t able to do that.Apple almost wasn’t able to do that.”

While Steve Jobs will always be associated with the iPhone, it’s clear that a great many people contributed to its creation.

Proving the lone-inventor myth inadequate does not diminish Jobs’s role as curator, editor, bar-setter– it elevates the role of everyone else to show he was not alone in making it possible. I hope my jaunt into the heart of the iPhone has helped demonstrate that the one device is the work of countless inventors and factory workers, miners and recyclers, brilliant thinkers and child laborers, and revolutionary designers and cunning engineers. Of long-evolving technologies, of collaborative, incremental work, of fledgling startups and massive public-research institutions.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The Essays of Warren Buffett


March 13, 2022

This week’s blog post coversThe Essays of Warren Buffett: Lessons for Corporate America (4th edition, 2015), selected and arranged byLawrence A. Cunningham. The book is based on 50 years of Buffett’s letters to shareholders, organized according to topic.

Not only is Warren Buffett arguably the greatest investor of all time; butBuffett wants to be remembered as a “Teacher.” Buffett and Munger have been outstanding “professors” for decades now, carrying on the value investing community’s tradition of generosity. Munger:

The best thing a human being can do is to help another human being know more.

Every section (but taxation) from The Essays of Warren Buffett is included here:

    • Prologue: Owner-Related Business Principles
    • Corporate Governance
    • Finance and Investing
    • Investment Alternatives
    • Common Stock
    • Mergers and Acquisitions
    • Valuation and Accounting
    • Accounting Shenanigans
    • Berkshire at Fifty and Beyond

 

PROLOGUE: OWNER-RELATED BUSINESS PRINCIPLES

Buffett writes that Berkshire Hathaway shareholders are unusual because nearly all of them focus on long-term compounding of business value. At the end of a typical year, 98% of those who own shares in Berkshire owned the shares at the beginning of the year.

Buffett remarks that, to a large extent, companies end up with the shareholders they seek and deserve. Buffett sets forth Berkshire’s fifteen owner-related business principles:

    1. Although our form is corporate, our attitude is partnership. Charlie Munger and I think of our shareholders as owner-partners, and of ourselves as managing partners… We do not view the company itself as the ultimate owner of our business assets but instead view the company as a conduit through which our shareholders own the assets.
    2. In line with Berkshire’s owner-orientation, most of our directors have a major portion of their net worth invested in the company. We eat our own cooking.
    3. Our long-term economic goal (subject to some qualifications mentioned later) is to maximize Berkshire’s average annual rate of gain in intrinsic business value on a per-share basis. We do not measure the economic significance or performance of Berkshire by its size; we measure by per-share progress…
    4. Our preference would be to reach our goal by directly owning a diversified group of businesses that generate cash and consistently earn above-average returns on capital. Our second choice is to own parts of similar businesses, attained primarily through purchases of marketable common stocks by our insurance subsidiaries…
    5. Because of our two-pronged approach to business ownership and because of the limitations of conventional accounting, consolidated reported earnings may reveal relatively little about our true economic performance. Charlie and I, both as owners and managers, virtually ignore such consolidated numbers. However, we will also report to you the earnings of each major business we control, numbers we consider of great importance. These figures, along with other information we will supply about the individual businesses, should generally aid you in making judgments about them.
    6. Accounting consequences do not influence our operating or capital-allocation decisions. When acquisition costs are similar, we much prefer to purchase $2 of earnings that is not reportable by us under standard accounting principles than to purchase $1 of earnings that is reportable. This is precisely the choice that often faces us since entire businesses (whose earnings will be fully reportable) frequently sell for double the pro-rate price of small portions (whose earnings will be largely unreportable). In aggregate and over time, we expect the unreported earnings to be fully reflected in our intrinsic business value through capital gains.
    7. We use debt sparingly and, when we do borrow, we attempt to structure our loans on a long-term fixed-rate basis. We will reject interesting opportunities rather than over-leverage our balance sheet. This conservatism has penalized our results but it is the only behavior that leaves us comfortable, considering our fiduciary obligations to policyholders, lenders and the many equity holders who have committed unusually large portions of their net worth to our care. (As one of the Indianapolis ‘500’ winners said: ‘To finish first, you must first finish.’)
    8. A managerial ‘wish list’ will not be filled at shareholder expense. We will not diversify by purchasing entire businesses at control prices that ignore long-term economic consequences to our shareholders. We will only do with your money what we would do with our own, weighing fully the values you can obtain by diversifying your own portfolios through direct purchases in the stock market.
    9. We feel noble intentions should be checked periodically against results. We test the wisdom of retained earnings by assessing whether retention, over time, delivers shareholders at least $1 of market value for each $1 retained. To date, this test has been met. We will continue to apply it on a five-year rolling basis…
    10. We will issue common stock only when we receive as much in business value as we give…
    11. You should be fully aware of one attitude Charlie and I share that hurts our financial performance: Regardless of price, we have no interest at all in selling any good businesses that Berkshire owns. We are also very reluctant to sell sub-par businesses as long as we expect them to generate at least some cash and as long as we feel good about their managers and labor relations…
    12. We will be candid in our reporting to you, emphasizing the pluses and minuses important in appraising business value. Our guideline is to tell you the business facts that we would want to know if our positions were reversed. We owe you no less… We also believe candor benefits us as managers: The CEO who misleads others in public may eventually mislead himself in private.
    13. Despite our policy of candor we will discuss our activities in marketable securities only to the extent legally required. Good investment ideas are rare, valuable and subject to competitive appropriation…
    14. To the extent possible, we would like each Berkshire shareholder to record a gain or loss in market value during his period of ownership that is proportional to the gain or loss in per-share intrinsic value recorded by the company during that holding period…
    15. We regularly compare the gain in Berkshire’s per-share book value to the performance of the S&P 500…

 

CORPORATE GOVERNANCE

Buffett explains:

At Berkshire, full reporting means giving you the information that we would wish you to give to us if our positions were reversed. What Charlie and I would want under the circumstance would be all the important facts about current operations as well as the CEO’s frank view of the long-term economic characteristics of the business. We would expect both a lot of financial details and a discussion of any significant data we would need to interpret what was presented.

Buffett comments that it is deceptive and dangerous – as he and Charlie see it – for CEOs to predict publicly growth rates for their companies. Though they are pushed to do so by analysts and their own investor relations departments, such predictions too often lead to trouble. Having internal targets is fine, of course. Buffett:

The problem arising from lofty predictions is not just that they spread unwarranted optimism. Even more troublesome is the fact that they corrode CEO behavior. Over the years, Charlie and I have observed many instances in which CEOs engaged in uneconomic operating maneuvers so that they could meet earnings targets they had announced. Worse still, after exhausting all that operating acrobatics would do, they sometimes played a wide variety of accounting games to ‘make the numbers.’

Buffett offers three suggestions for investors. He says:

  • First, beware of companies displaying weak accounting… When managements take the low road in aspects that are visible, it is likely they are following a similar path behind the scenes.
  • Second, unintelligible footnotes usually indicate untrustworthy management. If you can’t understand a footnote or other managerial explanation, it’s usually because the CEO doesn’t want you to…
  • Finally, be suspicious of companies that trumpet earnings projections and growth expectations. Businesses seldom operate in a tranquil, no-surprise environment, and earnings simply don’t advance smoothly (except, of course, in the offering books of investment bankers).

Buffett writes that when CEOs fall short, it’s quite difficult to remove them. Part of the problem is that there are no objective standards.

At too many companies, the boss shoots the arrow of managerial performance and then hastily paints the bullseye around the spot where it lands.

A further problem is that the CEO has no immediate superior whose performance is itself being measured. Buffett describes this and related issues:

But the CEO’s boss is a board of directors that seldom measures itself and is infrequently held to account for substandard corporate performance. If the Board makes a mistake in hiring, and perpetuates that mistake, so what? Even if the company is taken over because of the mistake, the deal will probably bestow substantial benefits on the outgoing board members…

Finally, relations between the Board and the CEO are expected to be congenial. At board meetings, criticisms of the CEO’s performance is often viewed as the social equivalent of belching…

These points should not be interpreted as a blanket condemnation of CEOs or Boards of Directors: Most are able and hardworking, and a number are truly outstanding. But the management failings Charlie and I have seen make us thankful that we are linked with the managers of our permanent holdings. They love their businesses, they think like owners, and they exude integrity and ability.

Buffett wrote more about corporate governance on a different occasion. He points out that there are three basic manager/owner situations.

The first situation – by far the most common – is that there is no controlling shareholder. Buffett argues that directors in this case should act as if there is a single absentee owner, whose long-term interest they should try to further. If a board member sees management going wrong, he should try to convince other board members. Failing that, he should make his views known to absentee owners, says Buffett. Also, the board should set standards for CEO performance and regularly meet – without the CEO present – to measure that performance. Finally, board members should be chosen based on business savvy, interest in the job, and owner-orientation, holds Buffett.

The second situation is that the controlling owner is also the manager. In this case, if the owner/manager is failing, it’s difficult for board members to improve things. If the board members agree, they could as a unit convey their concerns. But this probably won’t achieve much. On an individual level, a board member who has serious concerns could resign.

The third governance situation is when there is a controlling owner who is not involved in management. In this case, unhappy directors can go directly to the owner, observes Buffett.

Buffett then remarks:

Logically, the third case should be the most effective in insuring first-class management. In the second case the owner is not going to fire himself, and in the first case, directors often find it very difficult to deal with mediocrity or mild over-reaching. Unless the unhappy directors can win over a majority of the board – an awkward social and logistical task, particularly if management’s behavior is merely odious, not egregious – their hands are effectively tied…

Buffett also writes that most directors are decent folks who do a first-class job. But, nonetheless, being human, some directors will fail to be objective if their director fees are a large part of their annual income.

Buffett says that Berkshire’s policy is only to work with people they like and admire. Berkshire generally only buys a business when they like and admire the manager and when that manager is willing to stay in place.

…Berkshire’s ownership may make even the best of managers more effective. First, we eliminate all of the ritualistic and nonproductive activities that normally go with the job of CEO. Our managers are totally in charge of their personal schedules. Second, we give each a simple mission: Just run your business as if:

    • you own 100% of it;
    • it is the only asset in the world that you and your family have or will ever have; and
    • you can’t sell or merge it for at least a century.

As a corollary, we tell them they should not let any of their decisions be affected even slightly by accounting considerations. We want our managers to think about what counts, not how it will be counted.

Buffett comments that very few CEOs of public companies can follow such mandates, chiefly because they have owners (shareholders) who focus on short-term prospects and reported earnings. It’s not that Berkshire ignores current results, says Buffett, but that they should never be achieved at the expense of building ever-greater long-term competitive strengths.

I believe the GEICO story demonstrates the benefits of Berkshire’s approach. Charlie and I haven’t taught Tony a thing – and never will – but we have created an environment that allows him to apply all of his talents to what’s important. He does not have to devote his time or energy to board meetings, press interviews, presentations by investment bankers or talks with financial analysts. Furthermore, he need never spend a minute thinking about financing, credit ratings or ‘Street’ expectations for earnings per share. Because of our ownership structure, he also knows that this operational framework will endure for decades to come. In this environment of freedom, both Tony and his company can convert their almost limitless potential into matching achievements.

Buffett discusses the importance of building long-term competitive strengths:

Every day, in countless ways, the competitive position of each of our businesses grows either weaker or stronger. If we are delighting customers, eliminating unnecessary costs and improving our products and services, we gain strength. But if we treat customers with indifference or tolerate bloat, our businesses will wither. On a daily basis, the effects of our actions are imperceptible; cumulatively, though, their consequences are enormous.

When our long-term competitive position improves as a result of these almost unnoticeable actions, we describe the phenomenon as ‘widening the moat.’ And doing that is essential if we are to have the kind of business we want a decade or two from now. We always, of course, hope to earn more money in the short-term. But when short-term and long-term conflict, widening the moat must take precedence.

It’s interesting that Berkshire Hathaway itself, a textile operation, is one of Buffett’s biggest investment mistakes. Furthermore, Buffett owned the textile business from 1965 to 1985, despite generally bad results. Buffett explains that he held on to this business because management was straightforward and energetic, labor was cooperative and understanding, the company was a large employer, and the business was still earning modest cash returns.

Buffett was able to build today’s Berkshire Hathaway, one of the largest and most successful companies in the world, because he took cash out of the textile operation and reinvested in a series of highly successful businesses. Buffett did have to close the textile business in 1985 – twenty years after acquiring it – because, by then, the company was losing money each year, with no prospect for improvement.

Buffett tells the story of Burlington, the largest U.S. textile enterprise. From 1964 to 1985, Burlington spent about $3 billion on improvement and expansion. This amounted to more than $200-a-share on a $60 stock. However, after 20 years, the stock had gone nowhere, while the CPI had more than tripled. Buffett:

This devastating outcome for the shareholders demonstrates what can happen when much brain power and energy are applied to a faulty premise…

My conclusion from my own experiences and from much observation of other businesses is that a good managerial record (measured by economic returns) is far more a function of what business boat you get into than it is of how effectively you row (though intelligence and effort help considerably, of course, in any business, good or bad). Should you find yourself in a chronically-leaking boat, energy devoted to changing vessels is likely to be more productive than energy devoted to patching leaks.

Buffett also covers the topic of executive pay:

When returns on capital are ordinary, an earn-more-by-putting-up-more record is no great managerial achievement. You can get the same result personally by operating from your rocking chair. Just quadruple the capital you commit to a savings account and you will quadruple your earnings. You would hardly expect hosannas for that particular accomplishment. Yet, retirement announcements regularly sing the praises of CEOs who have, say, quadrupled earnings of their widget company during their reign – with no one examining whether this gain was attributable simply to many years of retained earnings and the workings of compound interest.

If the widget company consistently earned a superior return on capital throughout the period, or if capital employed only doubled during the CEO’s reign, the praise for him may be well deserved. But if return on capital was lackluster and capital employed increased in pace with earnings, applause should be withheld. A savings account in which interest was reinvested would achieve the same year-by-year increase in earnings – and, at only 8% interest, would quadruple its annual earnings in 18 years.

The power of this simple math is often ignored by companies to the detriment of their shareholders. Many corporate compensation plans reward managers handsomely for earnings increases produced solely, or in large part, by retained earnings – i.e., earnings withheld from owners…

Buffett points out that ten-year, fixed-price options ignore the fact that earnings automatically build value, and that carrying capital has a cost. Managers in this situation profit just as they would if they had an option on the savings account that automatically was building value.

Buffett repeatedly emphasizes that excellent management performance should be rewarded. Indeed, says Buffett, exceptional managers nearly always get less than they should. But that means you have to measure return on capital versus cost of capital. Buffett does admit, however, that some managers he admires enormously disagree with him regarding fixed-price options.

Buffett designs Berkshire’s employment contracts with managers based on returns on capital employed versus the cost of that capital. If the return on capital is high, the manager is rewarded. If return on capital is sub-standard, then the manager is penalized. Fixed-price options, by contrast, besides not usually being adjustable for the cost of capital, also fall short in that they reward managers on the upside without penalizing them on the downside. (Buffett does adjust manager contracts based on the economic characteristics of the business, however. A regulated business will have lower but still acceptable returns, for instance.)

Regarding reputation, Buffett has written for over 30 years:

We can’t be perfect but we can try to be…

We can afford to lose money – even a lot of money. But we can’t afford to lose reputation – even a shred of reputation.

Most auditors, observes Buffett, see that the CEO and CFO pay their fees. So the auditors are more worried about offending the CEO than they are about accurate reporting. Buffett suggests that audit committees ask the following four questions of auditors:

  1. If the auditor were solely responsible for the preparation of the company’s financial statements, would they in any way have been prepared differently from the manner selected by management? This question should cover both material and nonmaterial differences. If the auditor would have done something differently, both management’s argument and the auditor’s response should be disclosed. The audit committee should then evaluate the facts.
  2. If the auditor were an investor, would he have received – in plain English – the information essential to his understanding the company’s financial performance during the reporting period?
  3. Is the company following the same internal audit procedure that would be followed if the auditor himself were CEO? If not, what are the differences and why?
  4. Is the auditor aware of any actions – either accounting or operational – that have had the purpose and effect of moving revenues or expenses from one reporting period to another?

Buffett remarks that this procedure would save time and expense, in addition to focusing auditors on their duty.

 

FINANCE AND INVESTING

Buffett discusses his purchase of a farm in Nebraska in 1986, a few years after a bubble in Midwest farm prices had popped. First, he learned from his son how many bushels of corn and of soybeans would be produced, and what the operating expenses would be. Buffett determined that the normalized return from the farm would be 10%, and that productivity and prices were both likely to increase over time. Three decades later, the farm had tripled its earnings and Buffett’s investment had grown five times in value.

Buffett also mentions buying some real estate next to NYU shortly after a bubble in commercial real estate had popped. The unlevered current yield was 10%. Earnings subsequently tripled and annual distributions soon exceeded 35% of the original equity investment.

Buffett says these two investments illustrate certain fundamentals of investing, which he spells out as follows:

  • You don’t need to be an expert in order to achieve satisfactory investment returns. But if you aren’t, you must recognize your limitations and follow a course certain to work reasonably well. Keep things simple and don’t swing for the fences. When promised quick profits, respond with a quick ‘no.’
  • Focus on the future productivity of the asset you are considering. If you don’t feel comfortable making a rough estimate of the asset’s future earnings, just forget it and move on. No one has the ability to evaluate every investment possibility. But omniscience isn’t necessary; you only need to understand the actions you undertake.
  • If you instead focus on the prospective price change of a contemplated purchase, you are speculating. There is nothing improper about that. I know, however, that I am unable to speculate successfully, and I am skeptical of those who claim sustained success at doing so… And the fact that a given asset has appreciated in the recent past is never a reason to buy it.
  • With my two small investments, I thought only of what the property would produce and cared not at all about their daily valuations. Games are won by players who focus on the playing field – not by those whose eyes are glued to the scoreboard. If you can enjoy Saturdays and Sundays without looking at stock prices, give it a try on weekdays.
  • Forming macro opinions or listening to the macro or market opinions of others is a waste of time. Indeed, it is dangerous because it may blur your vision of the facts that are truly important…
  • My two purchases were made in 1986 and 1993. What the economy, interest rates, or the stock market might do in the years immediately following – 1987 and 1994 – was of no importance to me in making those investments. I can’t remember what the headlines or pundits were saying at the time. Whatever the chatter, corn would keep growing in Nebraska and students would flock to NYU.

Many long-term investors make the mistake of feeling good when stock prices rise. Buffett says that if you’re going to be a long-term investor and regularly add to your investments, you should prefer stock prices to fall rather than rise. Eventually, stock prices follow business results. And it’s safe to assume the U.S. economy will continue to grow over the long term. But between now and then, if you’re a net buyer of stocks, you’re better off if stock prices fall before they rise. Buffett:

So smile when you read a headline that says ‘Investors lose as market falls.’ Edit it in your mind to ‘Disinvestors lose as market falls – but investors gain.’

Buffett advises most investors to invest in index funds: https://boolefund.com/warren-buffett-jack-bogle/

But for a handful of investors who can understand some businesses, it’s better to patiently wait for the fattest pitches. Buffett gives an analogy:

If my universe of business opportunities was limited, say, to private companies in Omaha, I would, first, try to assess the long-term economic characteristics of each business; second, assess the quality of the people in charge of running it; and, third, try to buy into a few of the best operations at a sensible price. I certainly would not wish to own an equal part of every business in town. Why, then, should Berkshire take a different tack when dealing with the larger universe of public companies? And since finding great businesses and outstanding managers is so difficult, why should we discard proven products?

Buffett then quotes the economist and investor John Maynard Keynes:

‘As time goes on, I get more and more convinced that the right method in investment is to put fairly large sums into enterprises which one thinks one knows something about and in the management of which one thoroughly believes. It is a mistake to think that one limits one’s risk by spreading too much between enterprises about which one knows little and has no reason for special confidence. One’s knowledge and experience are definitely limited and there are seldom more than two or three enterprises at any given time in which I personally feel myself entitled to put full confidence.’ – J. M. Keynes

Here are details on Keynes as an investor: https://boolefund.com/greatest-economist-defied-convention-got-rich/

Buffett explains Berkshire’s equity investment strategy by quoting its 1977 annual report:

We select our marketable equity securities in much the way we would evaluate a business for acquisition in its entirety. We want the business to be one (a) that we can understand; (b) with favorable long-term prospects; (c) operated by honest and competent people; and (d) available at a very attractive price.

Buffett then notes that, due to Berkshire’s much larger size as well as market conditions, they would now substitute ‘an attractive price’ for ‘a very attractive price.’ How do you decide what’s ‘attractive’? Buffett quotesThe Theory of Investment Value, by John Burr Williams:

‘The value of any stock, bond or business today is determined by the cash inflows and outflows – discounted at an appropriate interest rate – that can be expected to occur during the remaining life of the asset.’

Buffett comments:

The investment shown by the discounted-flows-of-cash calculation to be the cheapest is the one that the investor should purchase – irrespective of whether the business grows or doesn’t, displays volatility or smoothness in its earnings, or carries a high price or low in relation to its current earnings and book value…

Leaving the question of price aside, the best business to own is one that over an extended period can employ large amounts of incremental capital at very high rates of return. The worst business to own is one that must, or will, do the opposite – that is, consistently employ ever-greater amounts of capital at very low rates of return. Unfortunately, the first type of business is very hard to find…

Though the mathematical calculations required to evaluate equities are not difficult, an analyst – even one who is experienced and intelligent – can easily go wrong in estimating future ‘coupons.’ At Berkshire, we attempt to deal with this problem in two ways. First, we try to stick to businesses we believe we understand. That means they must be relatively simple and stable in character. If a business is complex or subject to constant change, we’re not smart enough to predict future cash flows. Incidentally, that shortcoming doesn’t bother us. What counts for most people in investing is not how much they know, but rather how realistically they define what they don’t know. An investor needs to do very few things right as long as he or she avoids big mistakes.

Second, and equally important, we insist on a margin of safety in our purchase price. If we calculate the value of a common stock to be only slightly higher than its price, we’re not interested in buying. We believe this margin-of-safety principle, so strongly emphasized by Ben Graham, to be the cornerstone of investment success.

At another point, Buffett explains concentrated, buy-and-hold investing:

Inactivity strikes us as intelligent behavior. Neither we nor most business managers would dream of feverishly trading highly profitable subsidiaries because a small move in the Federal Reserve’s discount rate was predicted or because some Wall Street pundit had reversed his views on the market. Why, then, should we behave differently with our minority positions in wonderful businesses? The art of investing in public companies successfully is little different from the art ofsuccessfully acquiring subsidiaries. In each case you simply want to acquire, at a sensible price, a business with excellent economics and able, honest management. Thereafter, you need only monitor whether these qualities are being preserved.

When carried out capably, an investment strategy of that type will often result in its practitioner owning a few securities that will come to represent a very large portion of his portfolio. This investor would get a similar result if he followed a policy of purchasing an interest in, say, 20% of the future earnings of a number of outstanding college basketball stars. A handful of these would go on to achieve NBA stardom, and the investor’s take from them would soon dominate his royalty stream. To suggest that this investor should sell off portions of his most successful investments simply because they have come to dominate this portfolio is akin to suggesting that the Bulls trade Michael Jordan because he has become so important to the team.

Buffett reiterates that he and Charlie, when buying subsidiaries or common stocks, focus on businesses and industries unlikely to change much over time:

…The reason for that is simple: Making either type of purchase, we are searching for operations that we believe are virtually certain to possess enormous competitive strength ten or twenty years from now. A fast-changing industry environment may offer the chance for huge wins, but it precludes the certainty we seek.

I should emphasize that, as citizens, Charlie and I welcome change: Fresh ideas, new products, innovative processes and the like cause our country’s standard of living to rise, and that’s clearly good. As investors, however, our reaction to a fermenting industry is much like our attitude toward space exploration: We applaud the endeavor but prefer to skip the ride.

Obviously all businesses change to some extent. Today, See’s is different in many ways from what it was in 1972 when we bought it: It offers a different assortment of candy, employs different machinery and sells through different distribution channels. But the reasons why people today buy boxed chocolates, and why they buy them from us rather than from someone else, are virtually unchanged from what they were in the 1920s when the See family was building the business. Moreover, these motivations are not likely to change over the next 20 years, or even 50.

Buffett goes on to discuss Coca-Cola and Gillette, labeling companies like Coca-Cola ‘The Inevitables.’ Buffett points out that he’s not downplaying the important work these companies must continue to do in order to maximize their results over time. He’s merely saying that all sensible observers agree that Coke will dominate worldwide over an investment lifetime. This degree of brand strength – reflected in sustainably high returns on capital – is very rare. Buffett:

Obviously many companies in high-tech businesses or embryonic industries will grow much faster in percentage terms than will The Inevitables. But I would rather be certain of a good result than hopeful of a great one.

The main danger for a great company is getting sidetracked from its wonderful core business while acquiring other businesses that are mediocre or worse.

Unfortunately, that is exactly what transpired years ago at Coke. (Would you believe that a few decades back they were growing shrimp at Coke?) Loss of focus is what most worries Charlie and me when we contemplate investing in businesses that in general look outstanding. All too often, we’ve seen value stagnate in the presence of hubris or of boredom that caused the attention of managers to wander.

***

Buffett (again) recommends index funds for most investors:

Most investors, both individual and institutional, will find that the best way to own common stocks is through an index fund that charges minimal fees. Those following this path are sure to beat the net results (after fees and expenses) delivered by the great majority of investment professionals.

For those investors seeking to pick individual stocks, the notion ofcircle of competence is crucial. Buffett and Munger are well aware of which companies they can evaluate and which they can’t. Buffett:

If we have a strength, it is in recognizing when we are operating well within our circle of competence and when we are approaching the perimeter. Predicting the long-term economics of companies that operate in fast-changing industries is simply far beyond our perimeter. If others claim predictive skill in those industries – and seem to have their claims validated by the behavior of the stock market – we neither envy nor emulate them. Instead, we just stick with what we understand.

Mistakes of the First 25 Years

Buffett first notes that the lessons of experience are not always helpful. But it’s still good to review past mistakes ‘before committing new ones.’ To that end, Buffett lists mistakes of the twenty-five years up until 1989:

** My first mistake, of course, was in buying control of Berkshire. Though I knew its business – textile manufacturing – to be unpromising, I was enticed to buy because the price looked cheap. Stock purchases of that kind had proved reasonably rewarding in my early years, though by the time Berkshire came along in 1965 I was becoming aware that the strategy was not ideal.

If you buy a stock at a sufficiently low price, there will usually be some hiccup in the fortunes of the business that gives you a chance to unload at a decent profit, even though the long-term performance of the business may be terrible. I call this the ‘cigar butt’ approach to investing. A cigar butt found on the street that has only one puff left in it may not offer much of a smoke, but the ‘bargain purchase’ will make that puff all profit.

Unless you are a liquidator, that kind of approach to buying businesses is foolish. First, the original ‘bargain’ price probably will not turn out to be such a steal after all. In a difficult business, no sooner is one problem solved than another surfaces – never is there just one cockroach in the kitchen. Second, any initial advantage you secure will be quickly eroded by the low return that the business earns…

** That leads right into a related lesson: Good jockeys will do well on good horses, but not on broken-down nags…

I’ve said many times that when a management with a reputation for brilliance tackles a business with a reputation for bad economics, it is the reputation of the business that remains intact…

**A further related lesson: Easy does it. After 25 years of buying and supervising a great variety of businesses, Charlie and I have not learned how to solve difficult business problems. What we have learned is to avoid them. To the extent we have been successful, it is because we concentrated on identifying one-foot hurdles that we could step over rather than because we acquired any ability to clear seven-footers.

The finding may seem unfair, but in both business and investments it is usually far more profitable to simply stick with the easy and obvious than it is to resolve the difficult. On occasion, tough problemsmust be tackled. In other instances, a great investment opportunity occurs when a marvelous business encounters a one-time huge, but solvable, problem as was the case many years back at both American Express and GEICO…

**My most surprising discovery: the overwhelming importance in business of an unseen force that we might call ‘the institutional imperative.’ In business school, I was given no hint of the imperative’s existence and I did not intuitively understand it when I entered the business world. I thought then that decent, intelligent, and experienced managers would automatically make rational business decisions. But I learned over time that isn’t so. Instead, rationality frequently wilts when the institutional imperative comes into play.

For example: (1) As if governed by Newton’s First Law of Motion, an institution will resist any change in its current direction; (2) Just as work expands to fill available time, corporate projects or acquisitions will materialize to soak up available funds; (3) Any business craving of the leader, however foolish, will be quickly supported by detailed rate-of-return and strategic studies prepared by his troops; and (4) The behavior of peer companies, whether they are expanding, acquiring, setting executive compensation or whatever, will be mindlessly imitated.

** After some mistakes, I learned to go into business only with people I like, trust, and admire… We’ve never succeeded in making a good deal with a bad person.

**Some of my worst mistakes were not publicly visible. These were stock and business purchases whose virtues I understood and yet didn’t make… For Berkshire’s shareholders, myself included, the cost of this thumb-sucking has been huge.

**Our consistently-conservative financial policies may appear to have been a mistake, but in my view were not. In retrospect, it is clear that significantly higher, though still conventional, leverage ratios at Berkshire would have produced considerably better returns on equity than the 23.8% we have actually averaged. Even in 1965, perhaps we could have judged there to be a 99% probability that higher leverage would lead to nothing but good. Correspondingly, we might have seen only a 1% chance that some shock factor, external or internal, would cause a conventional debt ratio to produce a result falling somewhere between temporary anguish and default.

We wouldn’t have liked those 99:1 odds – and never will. A small chance of distress or disgrace cannot, in our view, be offset by a large chance of extra returns. If your actions are sensible, you are certain to get good results; in most such cases, leverage just moves things along faster. Charlie and I have never been in a big hurry: We enjoy the process far more than the proceeds – though we have learned to live with those also.

 

INVESTMENT ALTERNATIVES

Buffett in 2011:

Investment possibilities are both many and varied. There are three major categories, however, and it’s important to understand the characteristics of each. So let’s survey the field.

Investments that are denominated in a given currency include money-market funds, bonds, mortgages, bank deposits, and other instruments. Most of these currency-based investments are thought of as ‘safe.’ In truth they are among the most dangerous of assets. Their beta may be zero but their risk is huge.

Over the past century these instruments have destroyed the purchasing power of investors in many countries, even as the holders continued to receive timely payments of interest and principal. This ugly result, moreover, will forever recur. Governments determine the ultimate value of money, and systemic forces will sometimes cause them to gravitate to policies that produce inflation. From time to time such policies spin out of control.

Even in the U.S., where the wish for a stable currency is strong, the dollar has fallen a staggering 86% in value since 1965, when I took over management of Berkshire. It takes no less than $7 today to buy what $1 did at that time. Consequently, a tax-free institution would have needed 4.3% interest annually from bond investments over that period to simply maintain its purchasing power. Its managers would have been kidding themselves if they thought of any portion of that interest as income.

Buffett then notes that it’s even worse for tax-paying investors, who would have needed 5.7% annually to hold their ground. In other words, an invisible ‘inflation tax’ has consumed 4.3% per year. Given that interest rates today (mid-2017) are very low, currency-based investments are not attractive for the long term (decades).

The second major category of investments involves assets that will never produce anything, but that are purchased in the hope that someone else – who also knows that the assets will be forever unproductive – will pay more for them in the future. Tulips, of all things, briefly became a favorite of such buyers in the 17th century.

This type of investment requires an expanding pool of buyers, who, in turn, are enticed because they believe the buying pool will expand still further. Owners are not inspired by what the asset itself can produce – it will remain lifeless forever – but rather by the belief that others will desire it even more avidly in the future.

The major asset in this category is gold, currently a huge favorite of investors who fear almost all other assets, especially paper money (of whose value, as noted, they are right to be fearful). Gold, however, has two significant shortcomings, being neither of much use nor procreative. True, gold has some industrial and decorative utility, but the demand for these purposes is both limited and incapable of soaking up new production. Meanwhile, if you own one ounce of gold for an eternity, you will still own one ounce of gold at its end.

Today, the world’s gold stock is about 170,000 metric tons. If all of this gold were melded together, it would form a cube of about 68 feet per side. (Picture it sitting comfortably within a baseball infield.) At $1,750 per ounce – gold’s price as I write this – its value would be $9.6 trillion. Call this cube pile A.

Let’s now create a pile B costing an equal amount. For that, we could buy all U.S. cropland (400 million acres with output of about $200 billion annually), plus sixteen Exxon Mobiles (the world’s most profitable company, one earning more than $40 billion annually). After these purchases, we would have about $1 trillion left over for walking-around money (no sense feeling strapped after this buying binge). Can you imagine an investor with $9.6 trillion selecting pile A over pile B?

A century from now the 400 million acres of farmland will have produced staggering amounts of corn, wheat, cotton, and other crops – and will continue to produce that valuable bounty, whatever the currency may be. Exxon Mobile will probably have delivered trillions of dollars in dividends to its owners and will also hold assets worth many more trillions (and, remember, you get 16 Exxons). The 170,000 tons of gold will be unchanged in size and still incapable of producing anything. You can fondle the cube, but it will not respond.

Admittedly, when people a century from now are fearful, it’s likely many will still rush to gold. I’m confident, however, that the $9.6 trillion current valuation of pile A will compound over the century at a rate far inferior to that achieved by pile B.

Our first two categories enjoy maximum popularity at peaks of fear: Terror over economic collapse drives individuals to currency-based assets, most particularly U.S. obligations, and fear of currency collapse drives investors to sterile assets such as gold. We heard ‘cash is king’ in late 2008, just when cash should have been deployed rather than held…

My own preference – and you knew this was coming – is our third category: investment in productive assets, whether businesses, farms, or real estate. Ideally, these assets should have the ability in inflationary times to deliver output that will retain its purchasing-power value while requiring a minimum of new capital investment. Farms, real estate, and many businesses such as Coca-Cola, IBM, and our own See’s Candy meet that double-barreled test. Certain other companies – think of our regulated utilities for example – fail it because inflation places heavy capital requirements on them. To earn more, their owners must invest more. Even so, these investments will remain superior to nonproductive or currency-based assets.

Whether the currency a century from now is based on gold, seashells, shark teeth, or a piece of paper (as today), people will be willing to exchange a couple of minutes of their daily labor for a Coca-Cola or some See’s peanut brittle. In the future the U.S. population will move more goods, consume more food, and require more living space than it does now. People will forever exchange what they produce for what others produce.

Our country’s businesses will continue to efficiently deliver goods and services wanted by our citizens… I believe that over any extended period of time this category of investing will prove to be the runaway winner among the three we’ve examined. More important, it will be by far the safest.

***

Pessimism creates low prices. But you cannot be a contrarian blindly:

The most common cause of low prices is pessimism – sometimes pervasive, sometimes specific to a company or industry. We want to do business in such an environment, not because we like pessimism but because we like the prices it produces. It’s optimism that is the enemy of the rational buyer.

None of this means, however, that a business or stock is an intelligent purchase simply because it is unpopular; a contrarian approach is just as foolish as a follow-the-crowd strategy. What’s required is thinking rather than polling. Unfortunately, Bertrand Russell’s observation about life in general applies with unusual force in the financial world: ‘Most men would rather die than think. Many do.’

 

COMMON STOCK

Transaction costs eat up an astonishing degree of corporate earnings every year. Buffett writes at length – in the 2005 letter – about how this works:

The explanation of how this is happening begins with a fundamental truth: …the most that owners in aggregate can earn between now and Judgment Day is what their businesses in aggregate earn. True, by buying and selling that is clever or lucky, investor A may take more than his share of the pie at the expense of investor B. And, yes, all investors feel richer when stocks soar. But an owner can exit only by having someone take his place. If one investor sells high, another must buy high. For owners as a whole, there is simply no magic – no shower of money from outer space – that will enable them to extract wealth from their companies beyond that created by the companies themselves.

Indeed, owners must earn less than their businesses earn because of ‘frictional’ costs. And that’s my point: These costs are now being incurred in amounts that will cause shareholders to earn far less than they historically have.

To understand how this toll has ballooned, imagine for a moment that all American corporations are, and always will be, owned by a single family. We’ll call them the Gotrocks. After paying taxes on dividends, this family – generation after generation – becomes richer by the aggregate amount earned by its companies. Today that amount is about $700 billion annually. Naturally, the family spends some of these dollars. But the portion it saves steadily compounds for its benefit. In the Gotrocks household everyone grows wealthier at the same pace, and all is harmonious.

But let’s now assume that a few fast-talking Helpers approach the family and persuade each of its members to try to outsmart his relatives by buying certain of their holdings and selling them certain others. The Helpers – for a fee, of course – obligingly agree to handle these transactions. The Gotrocks still own all of corporate America; the trades just rearrange who owns what. So the family’s annual gain in wealth diminishes, equaling the earnings of American business minus commissions paid. The more that family members trade, the smaller their share of the pie and the larger the slice received by the Helpers. This fact is not lost upon these broker-Helpers: Activity is their friend and, in a wide variety of ways, they urge it on.

After a while, most of the family members realize that they are not doing so well at this new ‘beat-my-brother’ game. Enter another set of Helpers. These newcomers explain to each member of the Gotrocks clan that by himself he’ll never outsmart the rest of the family. The suggested cure: ‘Hire a manager – yes, us – and get the job done professionally.’ These manager-Helpers continue to use the broker-Helpers to execute trades; the managers may even increase their activity so as to permit the brokers to prosper still more. Overall, a bigger slice of the pie now goes to the two classes of Helpers.

The family’s disappointment grows. Each of its members is now employing professionals. Yet overall, the group’s finances have taken a turn for the worse. The solution? More help, of course.

It arrives in the form of financial planners and institutional consultants, who weigh in to advise the Gotrocks on selecting manager-Helpers. The befuddled family welcomes this assistance. By now its members know they can pick neither the right stocks nor the right stock-pickers. Why, one might ask, should they expect success in picking the right consultant? But this question does not occur to the Gotrocks, and the consultant-Helpers certainly don’t suggest it to them.

The Gotrocks, now supporting three classes of expensive Helpers, find that their results get worse, and they sink into despair. But just as hope seems lost, a fourth group – we’ll call them the hyper-Helpers – appears. These friendly folk explain to the Gotrocks that their unsatisfactory results are occurring because the existing Helpers – brokers, managers, consultants – are not sufficiently motivated and are simply going through the motions…

The new arrivals offer a breathtakingly simple solution: Pay more money. Brimming with self-confidence, the hyper-Helpers assert that huge contingent payments – in addition to stiff fixed fees – are what each family member must fork over in order to really outmaneuver his relatives.

The more observant members of the family see that some of the hyper-Helpers are really just manager-Helpers wearing new uniforms, bearing sewn-on sexy names like HEDGE FUND or PRIVATE EQUITY. The new Helpers, however, assure the Gotrocks that this change of clothing is all-important… Calmed by this explanation, the family decides to pay up.

And that’s where we are today: A record portion of the earnings that would go in their entirety to owners – if they all just stayed in their rocking chairs – is now going to a swelling army of Helpers. Particularly expensive is the recent pandemic of profit arrangements under which Helpers receive large portions of the winnings when they are smart or lucky, and leave family members with all of the losses – and large fixed fees to boot – when the Helpers are dumb or unlucky (or occasionally crooked).

A sufficient number of the arrangements like this – heads, the Helper takes much of the winnings; tails, the Gotrocks lose and pay dearly for the privilege of doing so – may make it more accurate to call the family the Hadrocks. Today, in fact, the family’s frictional costs of all sorts may well amount to 20% of the earnings of American business. In other words, the burden of paying Helpers may cause American equity investors, overall, to earn only 80% or so of what they would earn if they just sat still and listened to no one.

Long ago, Sir Isaac Newton gave us three laws of motion, which were the work of genius. But Sir Isaac’s talents didn’t extend to investing: He lost a bundle in the South Sea Bubble explaining later, ‘I can calculate the movement of the stars, but not the madness of men.’ If he had not been traumatized by this loss, Sir Isaac might well have gone on to discover the Fourth Law of Motion: For investors as a whole, returns decrease as motion increases.

For more details, see: http://berkshirehathaway.com/letters/2005ltr.pdf

 

MERGERS AND ACQUISITIONS

The Oracle of Omaha says:

Of all our activities at Berkshire, the most exhilarating for Charlie and me is the acquisition of a business with excellent economic characteristics and a management that we like, trust, and admire. Such acquisitions are not easy to make, but we look for them constantly…

In the past, I’ve observed that many acquisition-hungry managers were apparently mesmerized by their childhood reading of the story about the frog-kissing princess. Remembering her success, they pay dearly for the right to kiss corporate toads, expecting wondrous transfigurations. Initially, disappointing results only deepen their desire to round up new toads… Ultimately, even the most optimistic manager must face reality. Standing knee-deep in unresponsive toads, he then announces an enormous ‘restructuring’ charge. In this corporate equivalent of a Head Start program, the CEO receives the education but the stockholders pay the tuition.

Not only do most acquisitions fail to create value for the acquirer; many actually destroy value. However, a few do create value. Buffett writes:

…many managerial princesses remain serenely confident about the future potency of their kisses – even after their corporate backyards are knee-deep in unresponsive toads. In fairness, we should acknowledge that some acquisition records have been dazzling. Two major categories stand out.

The first involves companies that, through design or accident, have purchased only businesses that are particularly well adapted to an inflationary environment. Such favored business must have two characteristics: (1) an ability to increase prices rather easily (even when product demand is flat and capacity is not fully utilized) without fear of significant loss of either market share or unit volume, and (2) an ability to accommodate large dollar volume increases in business (often produced more by inflation than by real growth) with only minor additional investment of capital. Managers of ordinary ability, focusing only on acquisition possibilities meeting these tests, have achieved excellent results in recent decades. However, very few enterprises possess both characteristics, and competition for those that do has now become fierce to the point of being self-defeating.

The second category involves the managerial superstars – who can recognize the rare prince who is disguised as a toad, and who have managerial abilities that enable them to peel away the disguise.

Capital allocation decisions, including value-destroying acquisitions, add up over the long term. Buffett:

Over time, the skill with which a company’s managers allocate capital has an enormous impact on the enterprise’s value. Almost by definition, a really good business generates far more money (at least after its early years) than it can use internally. The company could, of course, distribute the money to shareholders by way of dividends or share repurchases. But often the CEO asks a strategic planning staff, consultants or investment bankers whether an acquisition or two might make sense. That’s like asking your interior decorator whether you need a $50,000 rug.

The acquisition problem is often compounded by a biological bias: Many CEOs obtain their positions in part because they possess an abundance of animal spirits and ego. If an executive is heavily endowed with these qualities – which, it should be acknowledged, sometimes have their advantages – they won’t disappear when he reaches the top…

At Berkshire, our managers will continue to earn extraordinary returns from what appear to be ordinary businesses. As a first step, these managers will look for ways to deploy their earnings advantageously in their businesses. What’s left, they will send to Charlie and me. We then will try to use those funds in ways that build per-share intrinsic value. Our goal will be to acquire either part or all of businesses that we believe we understand, that have good, sustainable underlying economics, and that are run by managers whom we like, admire and trust.

Over the years, Berkshire Hathaway has become the buyer of choice for many private business owners. Buffett remarks:

Our long-avowed goal is to be the ‘buyer of choice’ for businesses – particularly those built and owned by families. The way to achieve this goal is to deserve it. That means we must keep our promises; avoid leveraging up acquired businesses; grant unusual autonomy to our managers; and hold the purchased companies through thick and thin (though we prefer thick and thicker).

Our record matches our rhetoric. Most buyers competing against us, however, follow a different path. For them, acquisitions are ‘merchandise.’ Before the ink dries on their purchase contracts, these operators are contemplating ‘exit strategies.’ We have a decided advantage, therefore, when we encounter sellers who truly care about the future of their businesses.

 

VALUATION AND ACCOUNTING

Buffett writes about Aesop and the Inefficient Bush Theory:

The formula for valuing all assets that are purchased for financial gain has been unchanged since it was first laid out by a very smart man in about 600 B.C. (though he wasn’t smart enough to know it was 600 B.C.).

The oracle was Aesop, and his enduring, though somewhat incomplete, investment insight was ‘a bird in the hand is worth two in the bush.’ To flesh out this principle, you must answer only three questions. How certain are you that there are indeed birds in the bush? When will they emerge and how many will there be? What is the risk-free interest rate (which we consider to be the yield on long-term U.S. bonds)? If you can answer these three questions, you will know the maximum value of the bush – and the maximum number of the birds you now possess that should be offered for it. And, of course, don’t literally think birds. Think dollars.

Aesop’s investment axiom, thus expanded and converted into dollars, is immutable. It applies to outlays for farms, oil royalties, bonds, stocks, lottery tickets, and manufacturing plants. And neither the advent of the steam engine, the harnessing of electricity nor the creation of the automobile changed the formula one iota – nor will the Internet. Just insert the correct numbers, and you can rank the attractiveness of all possible uses of capital throughout the universe.

Common yardsticks such as dividend yield, the ratio of price to earnings or to book value, and even growth rates have nothing to do with valuation except to the extent they provide clues to the amount and timing of cash flows into and from the business. Indeed, growth can destroy value if it requires cash inputs in the early years of a project or enterprise that exceed the discounted value of the cash that those assets will generate in later years…

Alas, though Aesop’s proposition and the third variable – that is, interest rates – are simple, plugging in numbers for the other two variables is a difficult task. Using precise numbers is, in fact, foolish; working with a range of possibilities is the better approach.

Usually, the range must be so wide that no useful conclusion can be reached. Occasionally, though, even very conservative estimates about the future emergence of birds reveal that the price quoted is startingly low in relation to value. (Let’s call this phenomenon the IBT – Inefficient Bush Theory.) To be sure, an investor needs some general understanding of business economics as well as the ability to think independently to reach a well-founded positive conclusion. But the investor does not need brilliance nor blinding insights.

At the other extreme, there are many times when the most brilliant of investors can’t muster a conviction about the birds to emerge, not even when a very broad range of estimates is employed. This kind of uncertainty frequently occurs when new businesses and rapidly changing industries are under examination. In cases of this sort, any capital commitment must be labeled speculative.

The line separating investment and speculation, which is never bright and clear, becomes blurred still further when most market participants have recently enjoyed triumphs. Nothing sedates rationality like large doses of effortless money.

Here Buffett is talking about the bubble in internet stocks in 1999. He acknowledges that, overall, much value had been created and there was much more to come. However, many individual internet companies destroyed value rather than creating it.

As noted earlier, Buffett and Munger love technological progress. But they generally don’t invest in tech companies because it doesn’t fit their buy-and-hold approach. It’s just not their game. Some venture capitalists have excelled at it, but it usually takes a statistical investment approach whereby a few big winners eventually outweigh a large number of losses.

Buffett again:

At Berkshire, we make no attempt to pick the few winners that will emerge from an ocean of unproven enterprises. We’re not smart enough to do that, and we know it. Instead, we try to apply Aesop’s 2600-year-old equation to opportunities in which we have reasonable confidence as to how many birds are in the bush and when they will emerge (a formulation that my grandsons would probably update to ‘A girl in the convertible is worth five in the phone book.’) Obviously, we can never precisely predict the timing of cash flows in and out of a business or their exact amount. We try, therefore, to keep our estimates conservative and to focus on industries where business surprises are unlikely to wreak havoc on owners. Even so, we make many mistakes: I’m the fellow, remember, who thought he understood the future economics of trading stamps, textiles, shoes and second-tier department stores.

Buffett writes about how to evaluate management:

The primary test of managerial economic performance is the achievement of a high earnings rate on equity capital employed (without undue leverage, accounting gimmickry, etc.) and not the achievement of consistent gains in earnings per share. In our view, many businesses would be better understood by their shareholder owners, as well as the general public, if managements and financial analysts modified the primary emphasis they place upon earnings per share, and upon yearly changes in that figure.

This leads to a discussion of economic Goodwill:

…businesses logically are worth far more than net tangible assets when they can be expected to produce earnings on such assets considerably in excess of market rates of return. The capitalized value of this excess return is economic Goodwill.

In 1972 (and now) relatively few businesses could be expected to consistently earn the 25% after tax on net tangible assets that was earned by See’s – doing it, furthermore, with conservative accounting and no financial leverage. It was not the fair market value of inventories, receivables or fixed assets that produced the premium rates of return. Rather it was a combination of intangible assets, particularly a pervasive favorable reputation with consumers based upon countless pleasant experiences they have had with both product and personnel.

Such a reputation creates a consumer franchise that allows the value of the product to the purchaser, rather than its production cost, to be the major determinant of selling price. Consumer franchises are a prime source of economic Goodwill. Other sources include governmental franchises not subject to profit regulation… and an enduring position as the low cost producer in an industry.

Buffett compares economic Goodwill with accounting Goodwill. As mentioned, economic Goodwill is when the net tangible assets produce earnings in excess of market rates of return. By contrast, accounting Goodwill is when company A buys company B, and the price paid is above the fair market value of net tangible assets. The difference between price paid and net tangible asset value is accounting Goodwill.

In the past, companies would amortize accounting Goodwill, typically over a 40-year period. But the current rule is that companies periodically test the value of the assets acquired. If it is determined that the acquired assets have less value than when acquired, then the accounting Goodwill is written down based on an impairment charge. This new way of measuring accounting Goodwill is what Buffett and Munger suggested.

Earlier we saw that the net present value of any business is the discounted value of its future cash flows. However, when we estimate future cash flows, it’s important to distinguish between earnings and free cash flow. Buffett uses the the termowner earnings instead offree cash flow. Buffett onowner earnings:

…These represent (a) reported earnings plus (b) depreciation, depletion, amortization, and certain other non-cash charges… less (c) the average annual amount of capitalized expenditures for plant and equipment, etc. that the business requires to fully maintain its long-term competitive position and its unit volume.

Buffett then observes that item (c), capital expenditures, usually requires a guess. Soowner earnings, or free cash flow, must also be an estimate. Nonetheless, free cash flow is what matters when estimating the intrinsic value of a business.

If a business requires heavy capital expenditures to maintain its competitive position, that’s worth less to an owner. By the same logic, if a business requires very little capital investment to maintain its competitive position, that’s clearly worth much more. The capital-light business will generally earn much higher returns on capital.

So, generally speaking, as Buffett points out, when capital expenditure requirements exceed depreciation, GAAP earnings overstate owner earnings. When capital expenditure requirements are less than depreciation, GAAP earnings understate owner earnings.

Moreover, Buffett offers a warning. Often marketers of businesses and securities present ‘cash flow’ as simply (a) plus (b), without subtracting (c). However, looking at cash flows without subtracting capital expenditures can give you a very misleading notion of what the business is worth. Every business must make some capital expenditures over time to maintain its competitive position.

Buffett sums up the discussion of owner earnings – or free cash flow – with a note on accounting:

Accounting numbers of course, are the language of business and as such are of enormous help to anyone evaluating the worth of a business and tracking its progress. Charlie and I would be lost without these numbers: they invariably are the starting point for us in evaluating our own businesses and those of others. Managers and owners need to remember, however, that accounting is but an aid to business thinking, never a substitute for it.

 

ACCOUNTING SHENANIGANS

Buffett observes that managers should try to report the essential information that investors need:

What needs to be reported is data – whether GAAP, non-GAAP, or extra-GAAP – that helps financially literate readers answer three key questions: (1) Approximately how much is this company worth? (2) What is the likelihood that it can meet its future obligations? and (3) How good a job are its managers doing, given the hand they have been dealt?

In 1998, Buffett observed that it had become common to manipulate accounting statements:

In recent years, probity has eroded. Many major corporations still play things straight, but a significant and growing number of otherwise high-grade managers – CEOs you would be happy to have as spouses for your children or as trustees under your will – have come to the view that it’s OK to manipulate earnings to satisfy what they believe are Wall Street’s desires. Indeed, many CEOs think this kind of manipulation is not only okay, but actually their duty.

These managers start with the assumption, all too common, that their job at all times is to encourage the highest stock price possible (a premise with which we adamantly disagree). To pump the price, they strive, admirably, for operational excellence. But when operations don’t produce the result hoped for, these CEOs result to unadmirable accounting strategems. These either manufacture the desired ‘earnings’ or set the stage for them in the future.

Rationalizing this behavior, these managers often say that their shareholders will be hurt if their currency for doing deals – that is, their stock – is not fully-priced, and they also argue that in using accounting shenanigans to get the figures they want, they are only doing what everybody else does. Once such an everybody’s-doing-it attitude takes hold, ethical misgivings vanish. Call this behavior Son of Gresham: Bad accounting drives out good.

The distortion du jour is the ‘restructuring charge,’ an accounting entry that can, of course, be legitimate but that too often is a device for manipulating earnings. In this bit of legerdemain, a large chunk of costs that should properly be attributed to a number of years is dumped into a single quarter, typically one already fated to disappoint investors. In some cases, the purpose of the charge is to clean up earnings misrepresentations of the past, and in others it is to prepare the ground for future misrepresentations. In either case, the size and timing of these charges is dictated by the cynical proposition that Wall Street will not mind if earnings fall short by $5 per share in a given quarter, just as long as this deficiency ensures that quarterly earnings in the future will consistently exceed expectations by five cents per share.

This dump-everything-into-one-quarter behavior suggests a corresponding ‘bold, imaginative’ approach to – golf scores. In his first round of the season, a golfer should ignore his actual performance and simply fill his card with atrocious numbers – double, triple, quadruple bogeys – and then turn in a score of, say, 140. Having established this ‘reserve,’ he should go to the golf shop and tell his pro that he wishes to ‘restructure’ his imperfect swing. Next, as he takes his new swing onto the course, he should count his good holes, but not his bad ones. These remnants from his old swing should be charged instead to the reserve established earlier. At the end of five rounds, then, his record will be 140, 80, 80, 80, 80 rather than 91, 94, 89, 94, 92. On Wall Street, they will ignore the 140 – which, after all, came from a ‘discontinued’ swing – and will classify our hero as an 80 shooter (and one who never disappoints).

For those who prefer to cheat up front, there would be a variant of this strategy. The golfer, playing alone with a cooperative caddy-auditor, should defer the recording of bad holes, take four 80s, accept the plaudits he gets for such athleticism and consistency, and then turn in a fifth card carrying a 140 score. After rectifying his earlier scorekeeping sins with this ‘big bath,’ he may mumble a few apologies but will refrain from returning the sums he has previously collected from comparing scorecards in the clubhouse. (The caddy, need we add, will have acquired a loyal patron.)

Unfortunately, CEOs who use variations of these scoring schemes in real life tend to become addicted to the games they’re playing – after all, it’s easier to fiddle with the scorecard than to spend hours on the practice tee – and never muster the will to give them up.

***

In discussing pension estimates, Buffett explains why index fund investors will do better – net of all costs – than active investors:

Naturally, everyone expects to be above average. And those helpers – bless their hearts – will certainly encourage their clients in this belief. But, as a class, the helper-aided group must be below average. The reason is simple: (1) Investors, overall, will necessarily earn an average return, minus costs they incur; (2) Passive and index investors, through their very inactivity, will earn that average minus costs that are very low; (3) With that group earning average returns, so must the remaining group – the active investors. But this group will incur high transaction, management, and advisory costs. Therefore, the active investors will have their returns diminished by a far greater percentage than will their inactive brethren. That means that the passive group – the ‘know-nothings’ – must win.

 

BERKSHIRE AT FIFTY AND BEYOND

Remarks by Buffett (in early 2015) on Berkshire’s fiftieth anniversary:

At Berkshire, we can – without incurring taxes or much in the way of other costs – move huge sums from businesses that have limited opportunities for incremental investment to other sectors with greater promise. Moreover, we are free of historical biases created by lifelong association with a given industry and are not subject to pressures from colleagues having a vested interest in maintaining the status quo. That’s important: If horses had controlled investment decisions, there would have been no auto industry.

Another major advantage we possess is an ability to buy pieces of wonderful business – a.k.a. common stocks. That’s not a course of action open to most managements. Over our history, this strategic alternative has proved to be very helpful; a broad range of options sharpens decision-making. The businesses we are offered by the stock market every day – in small pieces, to be sure – are often far more attractive than the businesses we are concurrently being offered in their entirety. Additionally, the gains we’ve realized from marketable securities have helped us make certain large acquisitions that would otherwise have been beyond our financial capabilities.

In effect, the world is Berkshire’s oyster – a world offering us a range of opportunities far beyond those realistically open to most companies. We are limited, of course, to businesses whose economic prospects we can evaluate. And that’s a serious limitation: Charlie and I have no idea what a great many companies will look like ten years from now. But that limitation is much smaller than that borne by an executive whose experience has been confined to a single industry. On top of that, we can profitably scale to a far larger size than many businesses that are constrained by the limited potential of the single industry in which they operate.

Berkshire has one further advantage that has become increasingly important over the years: We are now the home of choice for the owners and managers of many outstanding businesses. Families that own successful businesses have multiple options when they contemplate sale. Frequently, the best decision is to do nothing. There are worse things in life than having a prosperous business that one understands well. But sitting tight is seldom recommended by Wall Street. (Don’t ask the barber whether you need a haircut.)

When one part of a family wishes to sell while others wish to continue, a public offering often makes sense. But, when owners wish to cash out entirely, they usually consider one of two paths. The first is sale to a competitor who is salivating at the possibility of wringing ‘synergies’ from the combining of the two companies. The buyer invariably contemplates getting rid of large numbers of the seller’s associates, the very people who have helped the owner build his business. A caring owner, however – and there are plenty of them – usually does not want to leave his long-time associates sadly singing the old country song: ‘She got the goldmine, I got the shaft.’

The second choice for sellers is the Wall Street buyer. For some years, these purchasers accurately called themselves ‘leveraged buyout firms.’ When that term got a bad name in the early 1990s – remember RJR and Barbarians at the Gate? – these buyers hastily relabeled themselves ‘private-equity.’ The name may have changed but that was all: Equity is dramatically reduced and debt is piled on in virtually all private-equity purchases. Indeed, the amount that a private-equity purchaser offers to the seller is in part determined by the buyer assessing the maximum amount of debt that can be placed on the acquired company.

Later, if things go well and equity begins to build, leveraged buy-out shops will often seek to re-leverage with new borrowings. They then typically use part of the proceeds to pay a huge dividend that drives equity sharply downward, sometimes even to a negative figure. In truth, ‘equity’ is a dirty word for many private-equity buyers; what they love is debt. And, these buyers can frequently pay top dollar. Later the business will be resold, often to another leveraged buyer. In effect, the business becomes a piece of merchandise.

Berkshire offers a third choice to the business owner who wishes to sell: a permanent home, in which the company’s people and culture will be retained (though, occasionally, management changes will be needed). Beyond that, any business we acquire dramatically increases its financial strength and ability to grow. Its days of dealing with banks and Wall Street analysts are also forever ended. Some sellers don’t care about these matters. But, when sellers do, Berkshire does not have a lot of competition.

Buffett also observes that companies are worth more as a part of Berkshire than they would be separately. Berkshire can move funds between businesses or to new ventures instantly and without tax. Also, some costs would be duplicated if the businesses were independent entities. This includes regulatory and administrative expenses. Moreover, there are tax efficiencies, says Buffett: Certain tax credits available to Berkshire’s utilities are realizable because Berkshire generates large taxable income in other operations.

Buffett sums it up:

Today Berkshire possesses (1) an unmatched collection of businesses, most of them now enjoying favorable economic prospects; (2) a cadre of outstanding managers who, with few exceptions, are unusually devoted to both the subsidiary they operate and to Berkshire; (3) an extraordinary diversity of earnings, premier financial strength and oceans of liquidity that we will maintain under all circumstances; (4) a first-choice ranking among many owners and managers who are contemplating sale of their businesses; and (5) in a point related to the preceding item, a culture, distinctive in many ways from that of most large companies, that we have worked 50 years to develop and that is now rock-solid. These strengths provide us a wonderful foundation on which to build.

For the rest of Buffett’s comments, as well as observations by Charles T. Munger on the history and evolution of Berkshire Hathaway, see pages 34-43 of the 2014 letter:http://berkshirehathaway.com/letters/2014ltr.pdf

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here:https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Lifelong Learning


March 6, 2022

Lifelong learning–especially if pursued in a multidisciplinary fashion–can continuously improve your productivity and ability to think. Lifelong learning boosts your capacity to serve others.

Robert Hagstrom’s wonderful book,Investing: The Last Liberal Art(Columbia University Press, 2013), is based on the notion of lifelong, multidisciplinary learning.

Ben Franklin was a strong advocate for this broad-based approach to education. Charlie Munger–Warren Buffett’s business partner–wholeheartedly agrees with Franklin. Hagstrom quotes Munger:

Worldly wisdom is mostly very, very simple. There are a relatively small number of disciplines and a relatively small number of truly big ideas. And it’s a lot of fun to figure out. Even better, the fun never stops…

What I am urging on you is not that hard to do. And the rewards are awesome… It’ll help you in business. It’ll help you in law. It’ll help you in life. And it’ll help you in love… It makes you better able to serve others, it makes you better able to serve yourself, and it makes life more fun.

Hagstrom’s book is necessarily abbreviated. This blog post even more so. Nonetheless, I’ve tried to capture many of the chief lessons put forth by Hagstrom.

Here’s the outline:

  • A Latticework of Mental Models
  • Physics
  • Biology
  • Sociology
  • Psychology
  • Philosophy
  • Literature
  • Mathematics
  • Decision Making

A person 's head with the image of a brain in front.

(Image: Unfolding of the Mind, by Agsandrew)

 

A LATTICEWORK OF MENTAL MODELS

Charlie Munger has long maintained that in order to be able to solve a broad array of problems in life, you must have a latticework of mental models. This means you have to master the central models from various areas–physics, biology, social studies, psychology, philosophy, literature, and mathematics.

As you assimilate the chief mental models, those models will strengthen and support one another, notes Hagstrom. So when you make a decision–whether in investing or in any other area–that decision is more likely to be correct if multiple mental models have led you to the same conclusion.

Ultimately, a dedication to lifelong, multidiscipinary learning will make us better people–better leaders, citizens, parents, spouses, and friends.

In the summer of 1749, Ben Franklin put forward a proposal for the education of youth. The Philadelphia Academy–later called the University of Pennsylvania–would stress both classical (“ornamental”) and practical education. Hagstrom quotes Franklin:

As to their studies, it would be well if they could be taught everything that is useful and everything that is ornamental. But art is long and their time is short. It is therefore proposed that they learn those things that are likely to be most useful and most ornamental, regard being had to the several professions for which they are intended.

Franklin held that gaining the ability to think well required the study of philosophy, logic, mathematics, religion, government, law, chemistry, biology, health, agriculture, physics, and foreign languages. Moreover, says Hagstrom, Franklin viewed the opportunity to study so many subjects as a wonderful gift rather than a burden.

A painting of a man in brown and white.

(Painting by Mason Chamberlin (1762) – Philadelphia Museum of Art, via Wikimedia Commons)

Franklin himself was devoted to lifelong, multidisciplinary learning. He remained open-minded and intellectually curious throughout his life.

Hagstrom also observes that innovation often depends on multidisciplinary thinking:

Innovative thinking, which is our goal, most often occurs when two or more mental models act in combination.

 

PHYSICS

Hagstrom remarks that the law of supply and demand in economics is based on the notion of equilibrium, a fundamental concept in physics.

A person writing on the blackboard with equations

(Research scientist writing physics diagrams and formulas, by Shawn Hempel)

Many historians consider Sir Isaac Newton to be the greatest scientific mind of all time, points out Hagstrom. When he arrived at Trinity College at Cambridge, Newton had no mathematical training. But the scientific revolution had already begun. Newton was influenced by the ideas of Johannes Kepler, Galileo Galilei, and René Descartes. Hagstrom:

The lesson Newton took from Kepler is one that has been repeated many times throughout history: Our ability to answer even the most fundamental aspects of human existence depends largely on measuring instruments available at the time and the ability of scientists to apply rigorous mathematical reasoning to the data.

Galileo invented the telescope, which then proved that the heliocentric model proposed by Nicolaus Copernicus was correct, rather than the geocentric model–first proposed by Aristotle and later developed by Ptolemy. Moreover, Galileo developed the mathematical laws that describe and predict falling objects.

Hagstrom then explains the influence of Descartes:

Descartes promoted a mechanical view of the world. He argued that the only way to understand how something works is to build a mechanical model of it, even if that model is constructed only in our imagination. According to Descartes, the human body, a falling rock, a growing tree, or a stormy night all suggested that mechanical laws were at work. This mechanical view provided a powerful research program for seventeenth century scientists. It suggested that no matter how complex or difficult the observation, it was possible to discover the underlying mechanical laws to explain the phenomenon.

In 1665, due to the Plague, Cambridge was shut down. Newton was forced to retreat to the family farm. Hagstrom writes that, in quiet and solitude, Newton’s genius emerged:

His first major discovery was the invention of fluxions or what we now call calculus. Next he developed the theory of optics. Previously it was believed that color was a mixture of light and darkness. But in a series of experiments using a prism in a darkened room, Newton discovered that light was made up of a combination of the colors of the spectrum. The highlight of that year, however, was Newton’s discovery of the universal law of gravitation.

A painting of a man with long hair.

(Copy of painting by Sir Godfrey Kneller (1689), via Wikimedia Commons)

Newton’s three laws of motion unified Kepler’s planetary laws with Galileo’s laws of falling bodies. It took time for Newton to state his laws with mathematical precision. He waited twenty years before finally publishingPrincipia Mathematica.

Newton’s three laws were central to a shift in worldview on the part of scientists. The evolving scientific view held that the future could be predicted based on present data if scientists could discover the mathematical, mechanical laws underlying the data.

Prior to the scientific worldview, a mystery was often described as an unknowable characteristic of an “ultimate entity,” whether an “unmoved mover” or a deity. Under the scientific worldview, a mystery is a chance to discover fundamental scientific laws. The incredible progress of physics–which now includes quantum mechanics, relativity, and the Big Bang–has depended in part on the belief by scientists that reality is comprehensible. Albert Einstein:

The most incomprehensible thing about the universe is that it is comprehensible.

Physics was–and is–so successful in explaining and predicting a wide range of phenomena that, not surprisingly, scientists from other fields have often wondered whether precise mathematical laws or ideas can be discovered to predict other types of phenomena. Hagstrom:

In the nineteenth century, for instance, certain scholars wondered whether it was possible to apply the Newtonian vision to the affairs of men. Adolphe Quetelet, a Belgian mathematician known for applying probability theory to social phenomena, introduced the idea of “social physics.” Auguste Comte developed a science for explaining social organizations and for guiding social planning, a science he calledsociology. Economists, too, have turned their attention to the Newtonian paradigm and the laws of physics.

After Newton, scholars from many fields focused their attention on systems that demonstrate equilibrium (whether static or dynamic), believing that it is nature’s ultimate goal. If any deviations in the forces occurred, it was assumed that the deviations were small and temporary–and the system would always revert back to equilibrium.

Hagstrom explains how the British economist Alfred Marshall adopted the concept of equilibrium in order to explain the law of supply and demand. Hagstrom quotes Marshall:

When demand and supply are in stable equilibrium, if any accident should move the scale of production from its equilibrium position, there will instantly be brought into play forces tending to push it back to that position; just as a stone hanging from a string is displaced from its equilibrium position, the force of gravity will at once tend to bring it back to its equilibrium position. The movements of the scale of production about its position of equilibrium will be of a somewhat similar kind.

A man with white hair and beard wearing a suit.

(Alfred Marshall, via Wikimedia Commons)

Marshall’sPrinciples of Economics was the standard textbook until Paul Samuelson publishedEconomics in 1948, says Hagstrom. But the concept of equilibrium remained. Firms seeking to maximize profits translate the preferences of households into products. The logical structure of the exchange is a general equilibrium system, according to Samuelson.

Samuelson’s view of the stock market was influenced by the works of Louis Bachelier, Maurice Kendall, and Alfred Cowles, notes Hagstrom.

In 1932, Cowles founded the Cowles Commission for Research and Economics. Later on, Cowles studied 6,904 predictions of the stock market from 1929 to 1944. Cowles learned that no one had demonstrated any ability to predict the stock market.

Kendall, a professor of statistics at the London School of Economics, studied the histories of various individual stock prices going back fifty years. Kendall was unable to find any patterns that would allow accurate predictions of future stock prices.

Samuelson thought that stock prices jump around because of uncertainty about how the businesses in question will perform in the future. The intrinsic value of a given stock is determined by the future cash flow the business will produce. But that future cash flow is unknown.

Bachelier’s work showed that the mathematical expectation of a speculator is zero, meaning that the current stock price is in equilibrium based on an equal number of buyers and sellers.

Samuelson, building on Bachelier’s work, invented the rational expectations hypothesis. From the assumption that market participants are rational, it followed that the current stock price is the best collective guess of the intrinsic value of the business–based on estimated future cash flows.

Eugene Fama later extended Samuelson’s view into what came to be called the Efficient Markets Hypothesis (EMH). Stock prices fully reflect all available information, therefore it’s not possible–except by luck–for any individual investor to beat the market over the long term.

Many scientists have questioned the EMH. The stock market sometimes does not seem rational. People often behave irrationally.

In science, however, it’s not enough to show that the existing theory has obvious flaws. In order to supplant existing scientific theory, scientists must come up with a better theory–one that better predicts the phenomena in question.Rationalist economics, including EMH, is still the best approximation for a wide range of phenomena.

Some scientists are working with the idea of acomplex adaptive system as a possible replacement for more traditional ideas of the stock market. Hagstrom:

Every complex adaptive system is actually a network of many individual agents all acting in parallel and interacting with one another. The critical variable that makes a system both complex and adaptive is the idea that agents (neurons, ants, or investors) in the system accumulate experience by interacting with other agents and then change themselves to adapt to a changing environment. No thoughtful person, looking at the present stock market, can fail to conclude that it shows all the traits of a complex adaptive system. And this takes us to the crux of the matter. If a complex adaptive system is, by definition,continuously adapting, it is impossible for any such system, including the stock market, ever to reach a state of perfect equilibrium.

It’s much more widely accepted today that people often do behave irrationally. But Fama argues that an efficient market does not require perfect rationality or information.

Hagstrom concludes that, while the market is mostly efficient, rationalist economics is not the full answer. There’s much more to the story, although it will take time to work out the details.

 

BIOLOGY

A man holding up a dna model in front of a wall.

(Photo by Ben Schonewille)

Robert Darwin, a respected physician, enrolled his son Charles at the University of Edinburgh. Robert wanted his son to study medicine. But Charles had no interest. Instead, he spent his time studying geology and collecting insects and specimens.

Robert realized his son wouldn’t become a doctor, so he sent Charles to Cambridge to study divinity. Although Charles got a bachelor’s degree in theology, he formed some important connections with scientists, says Hagstrom:

The Reverend John Stevens Henslow, professor of botany, permitted the enthusiastic amateur to sit in on his lectures and to accompany him on his daily walks to study plant life. Darwin spent so many hours in the professor’s company that he was known around the university as “the man who walks with Henslow.”

Later, Professor Henslow recommended Darwin for the position of naturalist on a naval expedition. Darwin’s father objected, but Darwin’s uncle, Josiah Wedgewood II, intervened. When the HMSBeagle set sail on December 27, 1831, from Plymouth, England, Charles Darwin was aboard.

Darwin’s most important observations happened at the Galapagos Islands, near the equator, six hundred miles west of Ecuador. Hagstrom:

Darwin, the amateur geologist, knew that the Galapagos were classified as oceanic islands, meaning they had arisen from the sea by volcanic action with no life forms aboard. Nature creates these islands and then waits to see what shows up. An oceanic island eventually becomes inhabited but only by forms that can reach it by wings (birds) or wind (spores and seeds)…

Darwin was particularly fascinated by the presence of thirteen types of finches. He first assumed these Galapagos finches, today called Darwin’s finches, were a subspecies of the South American finches he had studied earlier and had most likely been blown to sea in a storm. But as he studied distribution patterns, Darwin observed that most islands in the archipelago carried only two or three types of finches; only the larger central islands showed greater diversification. What intrigued him even more was that all the Galapagos finches differed in size and behavior. Some were heavy-billed seedeaters; others were slender billed and favored insects. Sailing through the archipelago, Darwin discovered that the finches on Hood Island were different from those on Tower Island and that both were different from those on Indefatigable Island. He began to wonder what would happen if a few finches on Hood Island were blown by high winds to another island. Darwin concluded that if the newcomers were pre-adapted to the new habitat, they would survive and multiply alongside the resident finches; if not, their number would ultimately diminish. It was one thread of what would ultimately become his famous thesis.

A view of the ocean from above.

(Galapagos Islands, Photo by Hugoht)

Hagstrom continues:

Reviewing his notes from the voyage, Darwin was deeply perplexed. Why did the birds and tortoises on some islands of the Galapagos resemble the species found in South America while those on other islands did not? This observation was even more disturbing when Darwin learned that the finches he brought back from the Galapagos belonged to different species and were not simply different varieties of the same species, as he had previously believed. Darwin also discovered that the mockingbirds he had collected were three distinct species and the tortoises represented two species. He began referring to these troubling questions as “the species problem,” and outlined his observations in a notebook he later entitled “Notebook on the Transmutation of the Species.”

Darwin now began an intense investigation into the species variation. He devoured all the written work on the subject and exchanged voluminous correspondence with botanists, naturalists, and zookeepers–anyone who had information or opinions about species mutation. What he learned convinced him that he was on the right track with his working hypothesis that species do in fact change, whether from place to place or from time period to time period. The idea was not only radical at the time, it was blasphemous. Darwin struggled to keep his work secret.

A man sitting in a chair wearing a suit and tie.

(Photo by Maull and Polyblank (1855), via Wikimedia Commons)

It took several years–until 1838–for Darwin to put together his hypothesis. Darwin wrote in his notebook:

Being well-prepared to appreciate the struggle for existence which everywhere goes on from long-continued observation of the habits of animals and plants, it at once struck me that under these circumstances, favorable variations would tend to be preserved and unfavorable ones to be destroyed. The result of this would be the formation of new species. Here, then, I had at last got a theory–a process by which to work.

The struggle for survival was occurring not only between species, but also between individuals of the same species, Hagstrom points out. Favorable variations are preserved. After many generations, small gradual changes begin to add up to larger changes. Evolution.

Darwin delayed publishing his ideas, perhaps because he knew they would be highly controversial, notes Hagstrom. Finally, in 1859, Darwin publishedOn the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. The book sold out on its first day. By 1872,The Origin of Species was in its sixth edition.

Hagstrom writes that in the first edition of Alfred Marshall’s famous textbook,Principles of Economics, the economist put the following on the title page:

Natura non facit saltum

Darwin himself used the same phrase–which means “nature does not make leaps”–in his book,The Origin of Species. Although Marshall never explained his thinking explicitly, it seems Marshall meant to align his work with Darwinian thinking.

Less than two decades later, Austrian-born economist Joseph Schumpeter put forth his central idea ofcreative destruction. Hagstrom quotes British economist Christopher Freeman, who–after studying Schumpeter’s life–remarked:

The central point of his whole life work is that capitalism can only be understood as an evolutionary process of continuous innovation and creative destruction.

Hagstrom explains:

Innovation, said Schumpeter, is the profitable application of new ideas, including products, production processes, supply sources, new markets, or new ways in which a company could be organized. Whereas standard economic theory believed progress was a series of small incremental steps, Schumpeter’s theory stressed innovative leaps, which in turn caused massive disruption and discontinuity–an idea captured in Schumpeter’s famous phrase “the perennial gale of creative destruction.”

But all these innovative possibilities meant nothing without the entrepreneur who becomes the visionary leader of innovation. It takes someone exceptional, said Schumpeter, to overcome the natural obstacles and resistance to innovation. Without the entrepreneur’s desire and willingness to press forward, many great ideas could never be launched.

A man in suit and tie with a mustache.

(Image from the Department of Economics, University of Freiburg, via Wikimedia Commons)

Moreover, Schumpeter held that entrepreneurs can thrive only in certain environments. Property rights, a stable currency, and free trade are important. And credit is even more important.

In the fall of 1987, a group of physicists, biologists, and economists held a conference at the Santa Fe Institute. The economist Brian Arthur gave a presentation on “New Economics.” A central idea was to apply the concept of complex adaptive systems to the science of economics. Hagstrom records that the Santa Fe group isolated four features of the economy:

Dispersed interaction: What happens in the economy is determined by the interactions of a great number of individual agents all acting in parallel. The action of any one individual agent depends on the anticipated actions of a limited number of agents as well as on the system they cocreate.

No global controller: Although there are laws and institutions, there is no one global entity that controls the economy. Rather, the system is controlled by the competition and coordination between agents of the system.

Continual adaptation: The behavior, actions, and strategies of agents, as well as their products and services, are revised continually on the basis of accumulated experience. In other words, the system adapts. It creates new products, new markets, new institutions, and new behavior. It is an ongoing system.

Out-of-equilibrium dynamics: Unlike the equilibrium models that dominate the thinking in classical economics, the Santa Fe group believed the economy, because of constant change, operates far from equilibrium.

Hagstrom argues that different investment or trading strategies throughout history have competed against one another. Those that have most accurately predicted the future for various businesses and their associated stock prices have survived, while less profitable strategies have disappeared.

But in any given time period, once a specific strategy becomes profitable, then more money flows into it, which eventually makes it less profitable. New strategies are then invented and compete against one another. As a result, a new strategy becomes dominant and then the process repeats.

Thus, economies and markets evolve over time. There is no stable equilibrium in a market except in the short term. To go from the language of biology to the language of business, Hagstrom refers to three important books:

  • Creative Destruction: Why Companies That Are Built to Last Underperform the Market–and How to Successfully Transform Them, by Richard Foster and Sarah Kaplan of McKinsey & Company
  • The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, by Clayton Christensen
  • The Innovator’s Solution: Creating and Sustaining Successful Growth, by Clayton Christensen and Michael Raynor

Hagstrom sums up the lessons from biology as compared to the previous ideas from physics:

Indeed, the movement from the mechanical view of the world to the biological view of the world has been called the “second scientific revolution.” After three hundred years, the Newtonian world, the mechanized world operating in perfect equilibrium, is now the old science. The old science is about a universe of individual parts, rigid laws, and simple forces. The systems are linear: Change is proportional to the inputs. Small changes end in small results, and large changes make for large results. In the old science, the systems are predictable.

The new science is connected and entangled. In the new science, the system is nonlinear and unpredictable, with sudden and abrupt changes. Small changes can have large effects while large events may result in small changes. In nonlinear systems, the individual parts interact and exhibit feedback effects that may alter behavior. Complex adaptive systems must be studied as a whole, not in individual parts, because the behavior of the system is greater than the sum of the parts.

The old science was concerned with understanding the laws of being. The new science is concerned with the laws of becoming.

A coral reef with fish and other animals.

(Photo by Isabellebonaire)

Hagstrom then quotes the last passage from Darwin’sThe Origin of Species:

It is interesting to contemplate an entangled bank, clothed with many plants of many kinds, with birds singing on the bushes, with various insects flitting about, and with worms crawling through the damp earth, and to reflect that these elaborately constructed forms, so different from each other, and dependent on each other in so complex a manner, have all been produced by laws acting around us. These laws, taken in the largest sense, being Growth with Reproduction; Inheritance which is almost implied by reproduction; Variability from the indirect and direct action of the external conditions of life, and from use and disuse; a Ratio of Increase so high as to lead to a Struggle for Life, and as a consequence to Natural Selection, entailing divergence of Character and Extinction of less improved forms. Thus, from the war of nature, from famine and death, the most exalted object which we are capable of conceiving, namely, the production of higher animals, directly follows. There is grandeur in this view of life, with its several powers, having been originally breathed into a few forms or into one; and that, whilst this planet has gone cycling on according to the fixed law of gravity, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved.

 

SOCIOLOGY

Because significant increases in computer power are now making vast amounts of data about human behavior available, the social sciences may at some point get enough data to figure out more precisely and more generally the laws of human behavior. But we’re not there yet.

A black and white photo of an old man.

(Auguste Comte, via Wikimedia Commons)

The nineteenth century–despite the French philosopher Auguste Comte’s efforts to establish one unified social science–ended with several distinct specialties, says Hagstrom, including economics, political science, and anthropology.

Scottish economist Adam Smith published hisWealth of Nations in 1776. Smith argued for what is now called laissez-faire capitalism, or a system free from government interference, including industry regulation and protective tariffs. Smith also held that a division of labor, with individuals specializing in various tasks, led to increased productivity. This meant more goods at lower prices for consumers, but it also meant more wealth for the owners of capital. And it implied that the owners of capital would try to limit the wages of labor. Furthermore, working conditions would likely be bad without government regulation.

Predictably, political scientists appeared on the scene to study how the government should protect the rights of workers in a democracy. Also, the property rights of owners of capital had to be protected.

Social psychologists studied how culture affects psychology, and how the collective mind affects culture. Social biologists, meanwhile, sought to apply biology to the study of society, notes Hagstrom. Recently scientists, including Edward O. Wilson, have introducedsociobiology, which involves the attempt to apply the scientific principles of biology to social development.

Hagstrom writes:

Although the idea of a unified theory of social science faded in the late nineteenth century, here at the beginning of the twenty-first century, there has been a growing interest in what we might think of as a new unified approach. Scientists have now begun to study the behavior of whole systems–not only the behavior of individuals and groups but the interactions between them and the ways in which this interaction may in turn influence subsequent behavior. Because of this reciprocal influence, our social system is constantly engaged in a socialization process the consequence of which not only alters our individual behavior but often leads to unexpected group behavior.

To explain the formation of a social group, the theory of self-organization has been developed. Ilya Prigogine, the Russian chemist, was awarded the Nobel Prize in 1977 for his thermodynamic concept of self-organization.

Paul Krugman, winner of the 2008 Nobel Prize for Economics, studied self-organization as applied to the economy. Hagstrom:

Setting aside for the moment the occasional recessions and recoveries caused by exogenous events such as oil shocks or military conflicts, Krugman believes that economic cycles are in large part caused by self-reinforcing effects. During a prosperous period, a self-reinforcing process leads to greater construction and manufacturing until the return on investment begins to decline, at which point an economic slump begins. The slump in itself becomes a self-reinforcing effect, leading to lower production; lower production, in turn, will eventually cause return on investment to increase, which starts the process all over again.

Hagstrom notes that equity and debt markets are good examples of self-organizing, self-reinforcing systems.

If self-organization is the first characteristic of complex adaptive systems, thenemergence is the second characteristic. Hagstrom says that emergence refers to the way individual units–whether cells, neurons, or consumers–combine to create something greater than the sum of the parts.

A circular diagram of complex systems with labels.

(Collective Dynamics of Complex Systems, by Dr. Hiroki Sayama, via Wikimedia Commons)

One fascinating aspect of human collectives is that, in many circumstances–like finding the shortest way through a maze–the collective solution is better when there are both smart and not-so-smart individuals in the collective. This more diverse collective outperforms a group that is composed only of smart individuals.

This implies that the stock market may more accurately aggregate information when the participants include many different types of people, such as smart and not-so-smart, long-term and short-term, and so forth, observes Hagstrom.

There are many areas where a group of people is actually smarter than the smartest individual in the group. Hagstrom mentions that Francis Galton, the English Victorian-era polymath, wrote about a contest in which 787 people guessed at the weight of a large ox. Most participants in the contest were not experts by any means, but ordinary people. The ox actually weighed 1,198 pounds. The average guess of the 787 guessers was 1,197 pounds, which was more accurate than the guesses made by the smartest and the most expert guessers.

This type of experiment can easily be repeated. For example, take a jar filled with pennies, where only you know how many pennies are in the jar. Pass the jar around in a group of people and ask each person–independently (with no discussion)–to write down their guess of how many pennies are in the jar. In a group that is large enough, you will nearly always discover that the average guess is better than any individual guess. (That’s been the result when I’ve performed this experiment in classes I’ve taught.)

In order for the collective to be that smart, the members must be diverse and the members’ guesses must be independent from one another. So the stock market is efficient when these two conditions are satisfied. But if there is a breakdown in diversity, or if individuals start copying one another too much–what Michael Mauboussin calls an information cascade–then you could have a boom, fad, fashion, or crash.

There are some situations where an individual can be impacted by the group. Solomon Asch did a famous experiment in which the subject is supposed to match lines that have the same length. It’s an easy question that every subject–if left alone–gets right. But then Asch has seven out of eight participantsdeliberately choose the wrong answer, unbeknownst to the subject of the experiment, who is the eighth participant in the same room. When this experiment was repeated many times, roughly one-third of the subjects gave the same answer as the group, even though this answer is obviously wrong. Such can be the power of a group opinion.

Hagstrom asks about how crashes can happen. Danish theoretical physicist Per Bak developed the notion ofself-organized criticality.

According to Bak, large complex systems composed of millions of interacting parts can break down not only because of a single catastrophic event but also because of a chain reaction of smaller events. To illustrate the concept of self-criticality, Bak often used the metaphor of a sand pile… Each grain of sand is interlocked in countless combinations. When the pile has reached its highest level, we can say the sand is in a state of criticality. It is just on the verge of becoming unstable.

A blue and green circular pattern with triangles

(Computer Simulation of Bak-Tang-Weisenfeld sandpile, with 28 million grains, by Claudio Rocchini, via Wikimedia Commons)

Adding one more grain starts an avalanche. Bak and two colleagues applied this concept to the stock market. They assumed that there are two types of agents,rational agents andnoise traders. Most of the time, the market is well-balanced.

But as stock prices climb, rational agents sell and leave the market, while more noise traders following the trend join. When noise traders–trend followers–far outnumber rational agents, a bubble can form in the stock market.

 

PSYCHOLOGY

The psychologists Daniel Kahneman and Amos Tversky did research together for over two decades. Kahneman was awarded the Nobel Prize in Economics in 2002. Tversky would also have been named had he not passed away.

A man with glasses and a blue shirt is in the library

(Daniel Kahneman, via Wikimedia Commons)

Much of their groundbreaking research is contained inJudgment Under Uncertainty: Heuristics and Biases (1982).

Here you will find all the customary behavioral finance terms we have come to know and understand: anchoring, framing, mental accounting, overconfidence, and overreaction bias. But perhaps the most significant insight into individual behavior wasloss aversion.

Kahneman and Tversky discovered that how choices are framed–combined with loss aversion–can materially impact how people make decisions. For instance, in one of their well-known experiments, they asked people to choose between the following two options:

  • (a) Save 200 lives for sure.
  • (b) Have a one-third chance of saving 600 lives and a two-thirds chance of saving no one.

In this scenario, people overwhelmingly chose (a)–to save 200 lives for sure. Kahneman and Tversky next asked the same people to choose between the following two options:

  • (a) Have 400 people die for sure.
  • (b) Have a two-thirds chance of 600 people dying and a one-third chance of no one dying.

In this scenario, people preferred (b)–a two-thirds chance of 600 people dying, and a one-third chance of no one dying.

But the two versions of the problem are identical. The number of people saved in the first version equals the number of people who won’t die in the second version.

What Kahneman and Tversky had demonstrated is that people are risk averse when considering potential gains, but risk seeking when facing the possibility of a certain loss. This is the essence of prospect theory, which is captured in the following graph:

A graph with the word gains and the word losses.

(Value function in Prospect Theory, drawing by Marc Rieger, via Wikimedia Commons)

Loss aversion refers to the fact that people weigh a potential loss about 2.5 times more than an equivalent gain. That’s why the value function in the graph is steeper for losses.

Richard Thaler and Shlomo Benartzi researched loss aversion by hypothesizing that the less frequently an investor checks the price of a stock he or she owns, the less likely the investor will be to sell the stock because of temporary downward volatility. Thaler and Benartzi invented the termmyopic loss aversion.

Hagstrom writes:

In my opinion, the single greatest psychological obstacle that prevents investors from doing well in the stock market is myopic loss aversion. In my twenty-eight years in the investment business, I have observed firsthand the difficulty investors, portfolio managers, consultants, and committee members of large institutional funds have with internalizing losses (loss aversion), made all the more painful by tabulating losses on a frequent basis (myopic loss aversion). Overcoming this emotional burden penalizes all but a very few select individuals.

Perhaps it is not surprising that the one individual who has mastered myopic loss aversion is also the world’s greatest investor–Warren Buffett…

Buffett understands that as long as the earnings of the businesses you own move higher over time, there’s no reason to worry about shorter term stock price volatility. Because Berkshire Hathaway, Buffett’s investment vehicle, holds both public stocks and wholly owned private businesses, Buffett’s long-term outlook has been reinforced. Hagstrom quotes Buffett:

I don’t need a stock price to tell me what I already know about value.

Hagstrom mentions Berkshire’s investment in The Coca-Cola Company (KO), in 1988. Berkshire invested $1 billion, which was at that time the single largest investment Berkshire had ever made. Over the ensuing decade, KO stock went up ten times, while the S&P 500 Index only went up three times. But four out of those ten years, KO stock underperformed the market. Trailing the market 40 percent of the time didn’t bother Buffett a bit.

As Hagstrom observes, Benjamin Graham–the father of value investing, and Buffett’s teacher and mentor–made a distinction between the investor focused on long-term business value and the speculator who tries to predict stock prices in the shorter term. The true investor should never be concerned with shorter term stock price volatility.

A man in suit and tie sitting at a table.

(Ben Graham, Photo by Equim43, via Wikimedia Commons)

Hagstrom quotes Graham’s The Intelligent Investor:

The investor who permits himself to be stampeded or unduly worried by unjustified market declines in his holdings is perversely transforming his basic advantage into a basic disadvantage. That man would be better off if his stocks had no market quotation at all, for he would then be spared the mental anguish caused him by another person’s mistakes of judgment.

Terence Odean, a behavioral economist, has done extensive research on the investment decisions of individuals and households. Odean discovered that:

  • Many investors trade often–Odean found a 78 percent portfolio turnover ratio in his first study, which tracked 97,483 trades from ten thousand randomly selected accounts.
  • Over the subsequent 4 months, one year, and two years, the stocks that investors bought consistently trailed the market, while the stocks that investors sold beat the market.

Hagstrom mentions that people use mental models as a basis for understanding reality and making decisions. But we tend to assume that each mental model we have is equally probable, rather than working to assign different probabilities to different models.

Moreover, people typically can make models for what something is–or what is true–instead of what something is not–or what is false. Also, our mental models are usually quite incomplete. And we tend to forget details of our models, especially after time passes. Finally, writes Hagstrom, people tend to construct mental models based on superstition or unwarranted belief.

Hagstrom asks the question: Why do people tend to be so gullible in general? For instance, while there’s no evidence that market forecasts have any value, many otherwise intelligent people pay attention to them and even make decisions based on them.

The answer, states Hagstrom, is that we are wired to seek and to find patterns. We have two basic mental systems, System 1 (intuition) and System 2 (reason). System 1 operates automatically. It takes mental shortcuts which often work fine, but not always. System 1 is designed to find patterns. And System 1 seeks confirming evidence for its hypotheses (patterns).

But even System 2–which humans can use to do math, logic, and statistics–uses a positive test strategy, meaning that itseeks confirming evidence for its hypotheses (patterns), rather than disconfirming evidence.

 

PHILOSOPHY

Hagstrom introduces the chapter:

A true philosopher is filled with a passion to understand, a process that never ends.

A bust of socrates is shown in black and white.

(Socrates, J. Aars Platon (1882), via Wikimedia Commons)

Metaphysics is one area of philosophy. Aesthetics, ethics, and politics are other areas. But Hagstrom focuses his discussion of philosophy onepistemology, the study of knowledge.

Having spent a few years studying the history and philosophy of science, I would say thatepistemology includes the following questions:

  • What different kinds of knowledge can we have?
  • What constitutes scientific knowledge?
  • Is any part of our knowledge certain, or can all knowledge be improved indefinitely?
  • How does scientific progress happen?

In a sense, epistemology is thinking about thinking. Epistemology is also studying the history of science in great detail, because humans have made enormous progress in generating scientific knowledge.

Studying epistemology can help us to become better, more rigorous, and more coherent thinkers, which can make us better investors.

Hagstrom makes it clear in the Preface that his book is necessarily abbreviated, otherwise it would have been a thousand pages long. That said, had he been aware of Willard Van Orman Quine’s epistemology, Hagstrom likely would have mentioned it.

Here is a passage from Quine’sFrom A Logical Point of View:

The totality of our so-called knowledge or beliefs, from the most casual matters of geography and history to the profoundest laws of atomic physics or even of pure mathematics and logic, is a man-made fabric which impinges on experience only along the edges. Or, to change the figure, total science is like a field of force whose boundary conditions are experience. A conflict with experience at the periphery occasions readjustments in the interior of the field. Truth values have to be redistributed over some of our statements. Re-evaluation of some statements entails re-evaluation of others, because of their logical interconnections–the logical laws being in turn simply certain further statements of the system, certain further elements of the field. Having re-evaluated one statement we must re-evaluate some others, which may be statements logically connected with the first or may be the statements of logical connections themselves. But the total field is so underdetermined by its boundary conditions, experience, that there is much latitude of choice as to what statements to re-evaluate in the light of any single contrary experience. No particular experiences are linked with any particular statements in the interior of the field, except indirectly through considerations of equilibrium affecting the field as a whole.

If this view is right, it is misleading to speak of the empirical content of an individual statement–especially if it is a statement at all remote from the experiential periphery of the field. Furthermore it becomes folly to seek a boundary between synthetic statements, which hold contingently on experience, and analytic statements, which hold come what may. Any statement can be held true come what may, if we make drastic enough adjustments elsewhere in the system. Even a statement very close to the periphery can be held true in the face of recalcitrant experience by pleading hallucination or by amending certain statements of the kind called logical laws. Conversely, by the same token, no statement is immune to revision. Revision even of the logical law of the excluded middle has been proposed as a means of simplifying quantum mechanics…

A woman 's face in front of a background with dna and molecular structures.

(Image by Dmytro Tolokonov)

Quine continues:

For vividness I have been speaking in terms of varying distances from a sensory periphery. Let me now try to clarify this notion without metaphor. Certain statements, thoughabout physical objects and not sense experience, seem peculiarly germane to sense experience–and in a selective way: some statements to some experiences, others to others. Such statements, especially germane to particular experiences, I picture as near the periphery. But in this relation of “germaneness” I envisage nothing more than a loose association reflecting the relative likelihood, in practice, of our choosing one statement rather than another for revision in the event of recalcitrant experience. For example, we can imagine recalcitrant experiences to which we would surely be inclined to accomodate our system by re-evaluating just the statement that there are brick houses on Elm Street, together with related statements on the same topic. We can imagine other recalcitrant experiences to which we would be inclined to accomodate our system by re-evaluating just the statement that there are no centaurs, along with kindred statements. A recalcitrant experience can, I have urged, be accomodated by any of various alternative re-evaluations in various alternative quarters of the total system; but, in the cases which we are now imagining, our natural tendency to disturb the total system as little as possible would lead us to focus our revisions upon these specific statements concerning brick houses or centaurs. These statements are felt, therefore, to have a sharper empirical reference than highly theoretical statements of physics or logic or ontology. The latter statements may be thought of as relatively centrally located within the total network, meaning merely that little preferential connection with any particular sense data obtrudes itself.

As an empiricist, I continue to think of the conceptual scheme of science as a tool, ultimately, for predicting future experience in the light of past experience. Physical objects are conceptually imported into the situation as convenient intermediaries–not by definition in terms of experience, but simply as irreducible posits comparable, epistemologically, to the gods of Homer. For my part I do, qua lay physicist, believe in physical objects and not in Homer’s gods; and I consider it a scientific error to believe otherwise. But in point of epistemological footing the physical objects and the gods differ only in degree and not in kind. Both sorts of entities enter our conception only as cultural posits. The myth of physical objects is epistemologically superior to most in that it has proved more efficacious than other myths as a device for working a manageable structure into the flux of experience.

Physical objects, small and large, are not the only posits. Forces are another example; and indeed we are told nowadays that the boundary between energy and matter is obsolete. Moreover, the abstract entities which are the substance of mathematics–ultimately classes and classes of classes and so on up–are another posit in the same spirit. Epistemologically these are posits on the same footing with physical objects and gods, neither better nor worse except for differences in the degree to which they expedite our dealings with sense experiences.

Historically, philosophers distinguished between “analytic” statements, which were thought to be true by definition, and “synthetic” statements, which were thought to be true on the basis of certain empirical data or experiences. One of Quine’s chief points is that this distinction doesn’t hold.

Mathematics, logic, scientific theories, scientific laws, working hypotheses, ordinary language, and much else including simple observations, are all a part of science.The goal of science–which extends common sense–is to predict various future experiences–including experiments–on the basis of past experiences.

When predictions–including experiments–don’t turn out as expected, then any part of the totality of science is revisable. Often it makes sense to revise specific hypotheses, or specific statements that are close to experience. But sometimes highly theoretical statements or ideas–including the laws of mathematics, the laws of logic, and the most well-established scientific laws–are revised in order to make the overall system of science work better, i.e., predict phenomena (future experiences) better, with more generality or with more exactitude.

The chief way scientists have made–and continue to make–progress is by testing predictions that are implied by existing scientific theory or law, or that are implied by new hypotheses under consideration.

A large circular display of various lines and points.

(Top quark and anti top quark pair decaying into jets, Collider Detector at Fermilab, via Wikimedia Commons)

Because of recent advances in computing power and because of the explosion of shared knowledge, ideas, and experiments on the internet, scientific progress is probably happening much faster than ever before. It’s a truly exciting time for all curious people and scientists. And once artificial intelligence passes thesingularity threshold, scientific progress is likely to skyrocket, even beyond what we can imagine.

 

LITERATURE

Critical reading is a crucial part of becoming a better thinker.

A book is opened on the table to read.

(Photo by VijayGES2, via Wikimedia Commons)

One excellent book about how to read analytically isHow to Read a Book, by Mortimer J. Adler. The goal of analytical reading is to improve your understanding–as opposed to only gaining information. To this end, Adler suggests active readers keep the following four questions in mind:

  • What is the book about as a whole?
  • What is being said in detail?
  • Is the book true, in whole or part?
  • What of it?

Before deciding to read a book in detail, it can be helpful to read the preface, table of contents, index, and bibliography. Also, read a few paragraphs at random. These steps will help you to get a sense of what the book is about as a whole. Next, you can skim the book to learn more about what is being said in detail, and whether it’s worth reading the entire book carefully.

Then, if you decide to read the entire book carefully, you should approach it like you would approach assigned reading for a university class. Figure out the main points and arguments. Take notes if that helps you learn. The goal is to understand the author’s chief arguments, and whether–or to what extent–those arguments are true.

The final step iscomparative reading, says Hagstrom. Adler considers this the hardest step. Here the goal is to learn about a specific subject. You want to determine which books on the subject are worth reading, and then compare and contrast these books.

Hagstrom points out that the three greatest detectives in fiction are Auguste Dupin, Sherlock Holmes, and Father Brown. We can learn much from studying the stories involving these sleuths.

Auguste Dupin was created by Edgar Allan Poe. Hagstrom remarks that we can learn the following from Dupin’s methods:

  • Develop a skeptic’s mindset; don’t automatically accept conventional wisdom.
  • Conduct a thorough investigation.

Sherlock Holmes was created by Sir Arthur Conan Doyle.

A man is reading a newspaper while another man sits in front of him.

(Illustration by Sidney Paget (1891), via Wikimedia Commons)

From Holmes, we can learn the following, says Hagstrom:

  • Begin an investigation with an objective and unemotional viewpoint.
  • Pay attention to the tiniest details.
  • Remain open-minded to new, even contrary, information.
  • Apply a process of logical reasoning to all you learn.

Father Brown was created by G. K. Chesterton. From Father Brown, we can learn:

  • Become a student of psychology.
  • Have faith in your intuition.
  • Seek alternative explanations and redescriptions.

Hagstrom ends the chapter by quoting Charlie Munger:

I believe in… mastering the best that other people have figured out [rather than] sitting down and trying to dream it up yourself… You won’t find it that hard if you go at it Darwinlike, step by step with curious persistence. You’ll be amazed at how good you can get… It’s a huge mistake not to absorb elementary worldly wisdom… Your life will be enriched–not only financially but in a host of other ways–if you do.

 

MATHEMATICS

Hagstrom quotes Warren Buffett:

…the formula for valuing ALL assets that are purchased for financial gain has been unchanged since it was first laid out by a very smart man in about 600 B.C.E. The oracle was Aesop and his enduring, though somewhat incomplete, insight was “a bird in the hand is worth two in the bush.” To flesh out this principle, you must answer only three questions. How certain are you that there are indeed birds in the bush? When will they emerge and how many will there be? What is the risk-free interest rate? If you can answer these three questions, you will know the maximum value of the bush–and the maximum number of birds you now possess that should be offered for it. And, of course, don’t literally think birds. Think dollars.

Hagstrom explains that it’s the same formula whether you’re evaluating stocks, bonds, manufacturing plants, farms, oil royalties, or lottery tickets. As long as you have the numbers needed for the calculation, the attractiveness of all investment opportunities can be evaluated and compared.

So to value any business, you have to estimate the future cash flows of the business, and then discount those cash flows back to the present. This is the DCF–discounted cash flows–method for determining the value of a business.

Although Aesop gave the general idea, John Burr Williams, inThe Theory of Investment Value (1938), was the first to explain the DCF approach explicitly. Williams had studied mathematics and chemistry as an undergraduate at Harvard University. After working as a securities analyst, Williams returned to Harvard to get a PhD in economics.The Theory of Investment Value was Williams’ dissertation.

Hagstrom writes that in 1654, the Chevalier de Méré, a French nobleman who liked to gamble, asked the mathematician Blaise Pascal the following question: “How do you divide the stakes of an unfinished game of chance when one of the players is ahead?”

A pile of playing cards on top of each other.

(Photo by Rossapicci, via Wikimedia Commons)

Pascal was a child prodigy and a brilliant mathematician. To help answer de Méré’s question, Pascal turned to Pierre de Fermat, a lawyer who was also a brilliant mathematician. Hagstrom reports that Pascal and Fermat exchanged a series of letters which are the foundation of what is now calledprobability theory.

There are two broad categories of probabilities:

  • frequency probability
  • subjective probability

A frequency probability typically refers to a system that can generate a great deal of statistical data over time. Examples include coin flips, roulette wheels, cards, and dice, notes Hagstrom. For instance, if you flip a coin 1,000 times, you expect to get heads about 50 percent of the time. If you roll one 6-sided dice 1,000 times, you expect to get each number about 16.67 percent of the time.

If you don’t have a sufficient frequency of events, plus a long time period to analyze results, then you must rely on a subjective probability. A subjective probability, says Hagstrom, is often a reasonable assessment made by a knowledgeable person. It’s a best guess based a logical analysis of the given data.

When using a subjective probability, obviously you want to make sure you have all the available data that could be relevant. And clearly you have to use logic correctly.

But the key to using a subjective probability is to update your beliefs as you gain new data. The proper way to update your beliefs is by using Bayes’ Rule.

A black and white drawing of an older man.

(Thomas Bayes, via Wikimedia Commons)

Bayes’ Rule

Eliezer Yudkowsky of the Machine Intelligence Research Institute provides an excellent intuitive explanation of Bayes’ Rule:http://www.yudkowsky.net/rational/bayes

Yudkowsky begins by discussing a situation that doctors often encounter:

1% of women at age forty who participate in routine screening have breast cancer. 80% of women with breast cancer will get positive mammographies. 9.6% of women without breast cancer will also get positive mammographies. A woman in this age group had a positive mammography in a routine screening. What is the probability that she actually has breast cancer?

Most doctors estimate the probability between 70% and 80%, which is wildly incorrect.

In order to arrive at the correct answer, Yudkowsky asks us to think of the question as follows. We know that 1% of women at age forty who participate in routine screening have breast cancer. So consider 10,000 women who participate in routine screening:

  • Group 1: 100 womenwithbreast cancer.
  • Group 2: 9,900 womenwithoutbreast cancer.

After the mammography, the women can be divided into four groups:

  • Group A: 80 womenwith breast cancer, and apositive mammography.
  • Group B: 20 womenwith breast cancer, and anegative mammography.
  • Group C: 950 womenwithout breast cancer, and apositivemammography.
  • Group D: 8,950 womenwithoutbreast cancer, and anegative mammography.

So the question again: If a woman out of this group of 10,000 women has a positive mammography, what is the probability that she actually has breast cancer?

The total number of women who hadpositive mammographies is 80 + 950 = 1,030. Of that total, 80 women hadpositive mammographies AND have breast cancer. In looking at the total number of positive mammographies (1,030), we know that 80 of them actually have breast cancer.

So if a woman out of the 10,000 has a positive mammography, the chances that she actually has breast cancer = 80/1030 or 0.07767 or 7.8%.

That’s the intuitive explanation. Now let’s look atBayes’Rule:

P(A|B) = [P(B|A)P(A)] /P(B)

Let’s apply Bayes’ Rule to the same question above:

1% of women at age forty who participate in routine screening have breast cancer. 80% of women with breast cancer will get positive mammographies. 9.6% of women without breast cancer will also get positive mammographies. A woman in this age group had a positive mammography in a routine screening. What is the probability that she actually has breast cancer?

P(A|B) = the probability that the woman has breast cancer (A), given a positive mammography (B)

Here is what we know:

P(B|A) = 80% – the probability of a positive mammography (B), given that the woman has breast cancer (A)

P(A) = 1% – the probability that a woman out of the 10,000 screened actually has breast cancer

P(B) = (80+950) / 10,000 = 10.3% – the probability that a woman out of the 10,000 screened has a positive mammography

Bayes’ Rule again:

P(A|B) = [P(B|A)P(A)] /P(B)

P(A|B) = [0.80*0.01] / 0.103 = 0.008 / 0.103 = 0.07767 or 7.8%

Derivation of Bayes’ Rule:

Bayesians consider conditional probabilities as more basic than joint probabilities. You can define P(A|B) without reference to the joint probability P(A,B). To see this, first start with the conditional probability formula:

P(A|B) P(B) = P(A,B)

but by symmetry youget:

P(B|A) P(A) = P(A,B)

It follows that:

P(A|B) = [P(B|A)P(A)] /P(B)

which isBayes’ Rule.

In conclusion, Hagstrom makes the important observation that there is much we still don’t know about nature and about ourselves. (The question mark below is by Khaydock, via Wikimedia Commons.)

Nothing is absolutely certain.

One clear lesson from history–whether the history of investing, the history of science, or some other area–is that very often people who are “absolutely certain” about something turn out to be wrong.

A question mark made of many small black and white numbers.

Economist and Nobel laureate Kenneth Arrow:
  • Our knowledge of the way things work, in society or in nature, comes trailing clouds of vagueness. Vast ills have followed a belief in certainty.

Investor and author Peter Bernstein:

The recognition of risk management as a practical art rests on a simple cliché with the most profound consequences: when our world was created, nobody remembered to include certainty. We are never certain; we are always ignorant to some degree. Much of the information we have is either incorrect or incomplete.

 

DECISION MAKING

Take a few minutes and try answering these three problems:

  • A bat and a ball cost $1.10. The bat costs one dollar more than the ball. How much does the ball cost?
  • If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets?
  • In a lake, there is a patch of lily pads. Every day the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long will it take for the patch to cover half the lake?

Roughly 75 percent of the Princeton and Harvard students got at least one problem wrong. These questions form the Cognitive Reflection Test, invented by Shane Frederick, an assistant professor of management science at MIT.

Recall that System 1 (intuition) is quick, associative, and operates automatically all the time. System 2 (reason) is slow and effortful–it requires conscious activation and sustained focus–and it can learn to solve problems involving math, statistics, or logic.

To understand the mental mistake that many people–including smart people–make, let’s consider the first of the three questions:

  • A bat and a ball cost $1.10. The bat costs one dollar more than the ball. How much does the ball cost?

After we read the question, our System 1 (intuition) immediately suggests to us that the bat costs $1.00 and the ball costs 10 cents. But if we slow down just a moment and engage System 2, we realize that if the bat costs $1.00 and the ball costs 10 cents, then the bat costs only 90 cents more than the ball. This violates the condition stated in the problem that the bat costs one dollar more than the ball. If we think a bit more, we see that the bat must cost $1.05 and the ball must cost 5 cents.

System 1 takes mental shortcuts, which often work fine. But when we encounter a problem that requires math, statistics, or logic, we have to train ourselves to slow down and to think through the problem. If we don’t slow down in these situations, we’ll often jump to the wrong conclusion.

A poster of the cognitive bias zones

(Cognitive Bias Codex, by John Manoogian III, via Wikimedia Commons. For a closer look, try this link:https://upload.wikimedia.org/wikipedia/commons/1/18/Cognitive_Bias_Codex_-_180%2B_biases%2C_designed_by_John_Manoogian_III_%28jm3%29.jpg)

It’s possible to train your intuition under certain conditions, according to Daniel Kahneman. Hagstrom:

Kahneman believes there are indeed cases where intuitive skill reveals the answer, but that such cases are dependent on two conditions. First, “the environment must be sufficiently regular to be predictable” second, there must be an “opportunity to learn these regularities through prolonged practice.” For familiar examples, think about the games of chess, bridge, and poker. They all occur in regular environments, and prolonged practice at them helps people develop intuitive skill. Kahneman also accepts the idea that army officers, firefighters, physicians, and nurses can develop skilled intuition largely because they all have had extensive experience in situations that, while obviously dramatic, have been repeated many times over.

Kahneman concludes that intuitive skill exists mostly in people who operate in simple, predictable environments and that people in more complex environments are much less likely to develop this skill. Kahneman, who has spent much of his career studying clinicians, stock pickers, and economists, notes that evidence of intuitive skill is largely absent in this group. Put differently, intuition appears to work well in linear systems where cause and effect is easy to identify. But in nonlinear systems, including stock markets and economies, System 1 thinking, the intuitive side of our brain, is much less effectual.

Experts in fields such as investing, economics, and politics have, in general, not demonstrated the ability to make accurate forecasts or predictions with any reliable consistency.

Philip Tetlock, professor of psychology at the University of Pennsylvania, tracked 284 experts over fifteen years (1988-2003) as they made 27,450 forecasts. The results are no better than “dart-throwing chimpanzees,” as Tetlock describes inExpert Political Judgment: How Good Is It? How Can We Know? (Princeton University Press, 2005).

Hagstrom explains:

It appears experts are penalized, like the rest of us, by thinking deficiencies. Specifically, experts suffer from overconfidence, hindsight bias, belief system defenses, and lack of Bayesian process.

Hagstrom then refers to an essay by Sir Isaiah Berlin, “The Hedgehog and the Fox: An Essay on Tolstoy’s View of History.” Hedgehogs view the world using one large idea, while Foxes are skeptical of grand theories and instead consider a variety of information and experiences before making decisions.

A small hedgehog is curled up on the floor.

(Photo of Hedgehog, by Nevit Dilmen, via Wikimedia Commons)

Tetlock found that Foxes, on the whole, were much more accurate than Hedgehogs. Hagstrom:

Why are hedgehogs penalized? First, because they have a tendency to fall in love with pet theories, which gives them too much confidence in forecasting events. More troubling, hedgehogs were too slow to change their viewpoint in response to discomfirming evidence. In his study, Tetlock said Foxes moved 59 percent of the prescribed amount toward alternate hypotheses, while Hedgehogs moved only 19 percent. In other words, Foxes were much better at updating their Bayesian inferences than Hedgehogs.

Unlike Hedgehogs, Foxes appreciate the limits of their knowledge. They have better calibration and discrimination scores than Hedgehogs. (Calibration, which can be thought of as intellectual humility, measures how much your subjective probabilities correspond to objective probabilities. Discrimination, sometimes called justified decisiveness, measures whether you assign higher probabilities to things that occur than to things that do not.)

A red fox sitting on the ground in front of some bushes.

(Photo of Fox, by Alan D. Wilson, via Wikimedia Commons)

Hagstrom comments thatFoxes have three distinct cognitive advantages, according to Tetlock:

  • They begin with “reasonable starter” probability estimates. They have better “inertial-guidance” systems that keep their initial guesses closer to short-term base rates.
  • They are willing to acknowledge their mistakes and update their views in response to new information. They have a healthy Bayesian process.
  • They can see the pull of contradictory forces, and, most importantly, they can appreciate relevant analogies.

Hagstrom concludes that the Fox “is the perfect mascot for The College of Liberal Arts Investing.”

Many people with high IQ have difficulty making rational decisions. Keith Stanovich, professor of applied psychology at the University of Toronto, invented the term dysrationalia to refer to the inability to think and behave rationally despite high intelligence, remarks Hagstrom. There are two principal causes of dysrationalia:

  • a processing problem
  • a content problem

Stanovich explains that people are lazy thinkers in general, preferring to think in ways that require less effort, even if those methods are less accurate. As we’ve seen, System 1 operates automatically, with little or no effort. Its conclusions are often correct. But when the situation calls for careful reasoning, the shortcuts of System 1 don’t work.

Lack of adequate content is amindware gap, says Hagstrom.Mindware refers to rules, strategies, procedures, and knowledge that people possess to help solve problems. Harvard cognitive scientist David Perkins coined the termmindware. Hagstrom quotes Perkins:

What is missing is the metacurriculum–the ‘higher order’ curriculum that deals with good patterns of thinking in general and across subject matters.

Perkins’ proposed solution is amindware booster shot, which means teaching new concepts and ideas in “a deep and far-reaching way,” connected with several disciplines.

Of course, Hagstrom’s book,Investing: The Last Liberal Art, is a great example of amindware booster shot.

 

Hagstrom concludes by stressing the vital importance of lifelong, continuous learning. Buffett and Munger have always highlighted this as a key to their success.

A statue of ben franklin sitting on top of a pedestal.

(Statue of Ben Franklin in front of College Hall, Philadelphia, Pennsylvania, Photo by Matthew Marcucci, via Wikimedia Commons)

Hagstrom:

Although the greatest number of ants in a colony will follow the most intense pheromone trail to a food source, there are always some ants that are randomly seeking the next food source. When Native Americans were sent out to hunt, most of those in the party would return to the proven hunting grounds. However, a few hunters, directed by a medicine man rolling spirit bones, were sent in different directions to find new herds. The same was true of Norwegian fishermen. Each day most of the ships in the fleet returned to the same spot where the previous day’s catch had yielded the greatest bounty, but a few vessels were also sent in random directions to locate the next school of fish. As investors, we too must strike a balance between exploiting what is most obvious while allocating some mental energy to exploring new possibilities.

Hagstrom adds:

The process is similar to genetic crossover that occurs in biological evolution. Indeed, biologists agree that genetic crossover is chiefly responsible for evolution. Similarly, the constant recombination of our existing mental building blocks will, over time, be responsible for the greatest amount of investment progress. However, there are occasions when a new and rare discovery opens up new opportunities for investors. In much the same way that mutation can accelerate the evolutionary process, so too can new ideas speed us along in our understanding of how markets work. If you are able to discover a new building block, you have the potential to add another level to your model of understanding.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The Second Machine Age


February 20, 2022

Erik Brynjolfsson and Andrew McAfee are the authors ofThe Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies(Norton, 2014). It’s one of the best books I’ve read in the past few years.

The second machine age is going to bring enormous progress to economies and societies. Total wealth – whether defined narrowly or much more broadly – will increase significantly. But we do have to ensure that political and social structures are properly adjusted so that everyone can benefit from massive technological progress.

The first six chapters – starting with The Big Stories, and going thru Artificial and Human Intelligence in the Second Machine Age – give many examples of recent technological progress.

The five subsequent chapters – four of which are covered here – discuss the bounty and the spread.

Bounty is the increase in volume, variety, and quality and the decrease in cost of the many offerings brought on by modern technological progress. It’s the best economic news in the world today.

Spread is differences among people in economic success.

The last four chapters discuss what interventions could help maximize the bounty while mitigating the effects of the spread.

Here are the chapters covered:

  • The Big Stories
  • The Skills of the New Machines: Technology Races Ahead
  • Moore’s Law and the Second Half of the Chessboard
  • The Digitization of Just About Everything
  • Innovation: Declining or Recombining?
  • Artificial and Human Intelligence in the Second Machine Age
  • Computing Bounty
  • Beyond GDP
  • The Spread
  • Implications of the Bounty and the Spread
  • Learning to RaceWith Machines: Recommendations for Individuals
  • Policy Recommendations
  • Long-term Recommendations
  • Technology and the Future

 

THE BIG STORIES

Freeman Dyson:

Technology is a gift of God. After the gift of life, it is perhaps the greatest of God’s gifts. It is the mother of civilizations, of arts and of sciences.

James Watt’s brilliant tinkering with the steam engine in 1775 and 1776 was central to the Industrial Revolution:

The Industrial Revolution, of course, is not only the story of steam power, but steam started it all. More than anything else, it allowed us to overcome the limitations of muscle power, human and animal, and generate massive amounts of useful energy at will. This led to factories and mass production, to railways and mass transportation. It led, in other words, to modern life. The Industrial Revolution ushered in humanity’s first machine age – the first time our progress was driven primarily by technological innovation – and it was the most profound time of transformation the world has ever seen. (pages 6-7)

(Note that Brynjolfsson and McAfee refer to the Industrial Revolution as “the first machine age.” And they refer to the late nineteenth and early twentieth century as the Second Industrial Revolution.)

Brynjolfsson and McAfee continue:

Now comes the second machine age. Computers and other digital advances are doing for mental power – the ability to use our brains to understand and shape our environments – what the steam engine and its descendants did for muscle power. They’re allowing us to blow past previous limitations and taking us into new territory. How exactly this transition will play out remains unknown, but whether or not the new machine age bends the curve as Watt’s steam engine, it is a very big deal indeed. This book explains how and why.

For now, a very short and simple answer: mental power is at least as important for progress and development – for mastering our physical and intellectual environment to get things done – as physical power. So a vast and unprecedented boost to mental power should be a great boost to humanity, just as the earlier boost to physical power so clearly was. (pages 7-8)

Brynjolfsson and McAfee admit that recent technological advances surpassed their expectations:

We wrote this book because we got confused. For years we have studied the impact of digital technologies like computers, software, and communications networks, and we thought we had a decent understanding of their capabilities and limitations. But over the past few years they started surprising us. Computers started diagnosing diseases, listening and speaking to us, and writing high-quality prose, while robots started scurrying around warehouses and driving cars with minimal or no guidance. Digital technologies had been laughably bad at a lot of these things for a long time – then they suddenly got very good. How did this happen? And what were the implications of this progress, which was astonishing and yet came to be considered a matter of course?

Brynjolfsson and McAfee did a great deal of reading. But they learned the most by speaking with inventors, investors, entrepreneurs, engineers, scientists, and others making or using technology.

Brynjolfsson and McAfee report that they reached three broad conclusions:

The first is that we’re living at a time of astonishing progress with digital technologies – those that have computer hardware, software, and networks at their core. These technologies are not brand-new; businesses have been buying computers for more than half a century… But just as it took generations to improve the steam engine to the point that it could power the Industrial Revolution, it’s also taken time to refine our digital engines.

We’ll show why and how the full force of these technologies has recently been achieved and give examples of its power. ‘Full,’ though, doesn’t mean ‘mature.’ Computers are going to continue to improve and do new and unprecedented things. By ‘full force,’ we mean simply that the key building blocks are already in place for digital technologies to be as important and transformational for society and the economy as the steam engine. In short, we’re at an inflection point – a point where the curve starts to bend a lot – because of computers. We are entering a second machine age.

Our second conclusion is that the transformations brought about by digital technology will be profoundly beneficial ones. We’re heading into an era that won’t just be different; it will be better, because we’ll be able to increase both the variety and the volume of our consumption… we don’t just consume calories and gasoline. We also consume information from books and friends, entertainment from superstars and amateurs, expertise from teachers and doctors, and countless other things that are not made of atoms. Technology can bring us more choice and even freedom.

When these things are digitized – when they’re converted into bits that can be stored on a computer and sent over a network – they acquire some weird and wonderful properties. They’re subject to different economics, where abundance is the norm rather than scarcity. As we’ll show, digital goods are not like physical ones, and these differences matter.

…Digitization is improving the physical world, and these improvements are only going to become more important. Among economic historians, there’s wide agreement that, as Martin Weitzman puts it, ‘the long-term growth of an advanced economy is dominated by the behavior of technical progress.’ As we’ll show, technical progress is improving exponentially.

Our third conclusion is less optimistic: digitization is going to bring with it some thorny challenges… Technological progress is going to leave behind some people, perhaps even a lot of people, as it races ahead. As we’ll demonstrate, there’s never been a better time to be a worker with special skills or the right education, because these people can use technology to create and capture value. However, there’s never been a worse time to be a worker with only ‘ordinary’ skills and abilities to offer, because computers, robots, and other digital technologies are acquiring these skills and abilities at an extraordinary rate. (pages 9-11)

 

THE SKILLS OF THE NEW MACHINES: TECHNOLOGY RACES AHEAD

Arthur C. Clarke:

Any sufficiently advanced technology is indistinguishable from magic.

Computers are symbol processors, noteBrynjolfsson and McAfee: Their circuitry can be interpreted in the language of ones and zeroes, or as true or false, or as yes or no.

Computers are especially good at following rules or algorithms. So computers are especially well-suited for arithmetic, logic, and similar tasks.

Historically, computers have not been very good at pattern recognition compared to humans. Brynjolfsson and McAfee:

Our brains are extraordinarily good at taking in information via our senses and examining it for patterns, but we’re quite bad at describing or figuring out how we’re doing it, especially when a large volume of fast-changing information arrives at a rapid pace. As the philosopher Michael Polanyi famously observed, ‘We know more than we can tell.’ (page 18)

Driving a car is an example where humans’ ability to recognize patterns in a mass of sense data was thought to be beyond a computer’s ability. DARPA – the Defense Advanced Research Projects Agency – held a Grand Challenge for driverless cars in 2004. It was a 150-mile course through the Mojave Desert in California. There were fifteen entrants. Brynjolfsson and McAfee:

The results were less than encouraging. Two vehicles didn’t make it to the starting area, one flipped over in the starting area, and three hours into the race, only four cars were still operational. The ‘winning’ Sandstorm car from Carnegie Mellon University covered 7.4 miles (less than 5 percent of the total) before veering off the course during a hairpin turn and getting stuck on an embankment. The contest’s $1 million prize went unclaimed, and Popular Science called the event ‘DARPA’s Debacle in the Desert.’ (page 19)

Within a few years, however, driverless cars became far better. By 2012, Google driverless cars had covered hundreds of thousands of miles with only two accidents (both caused by humans). Brynjolfsson and McAfee:

Progress on some of the oldest and toughest challenges associated with computers, robots, and other digital gear was gradual for a long time. Then in the past few years it became sudden; digital gear started racing ahead, accomplishing tasks it had always been lousy at and displaying skills it was not supposed to acquire any time soon. (page 20)

Another example of an area where it was thought fairly recently that computers wouldn’t become very good is complex communication. But starting around 2011, computers suddenly seemed to get much better at using human languages to communicate with humans. Robust natural language processing has become available to people with smartphones.

For instance, there are mobile apps that show you an accurate map and that tell you the fastest way for getting somewhere. Also, Google’s translations on twitter have gotten much better recently (as of mid-2017).

In 2011, IBM’s supercomputer Watson beat Ken Jennings and Brad Rutter atJeopardy! This represented another big advance in which a computer combined pattern matching with complex communication. The game involves puns, rhymes, wordplay, and more.

Jennings had won a record seventy-four times in a row in 2004. Rutter beat Jennings in the 2005 Ultimate Tournament of Champions. The early versions of IBM’s Watson came nowhere close to winningJeopardy! But when Watson won in 2011, it had three times as much money as either human opponent. Jennings later remarked:

Just as factory jobs were eliminated in the twentieth century by new assembly-line robots, Brad and I were the first knowledge-industry workers put out of work by the new generation of ‘thinking’ machines. (page 27)

Robotics is another area where progress had been gradual, but recently became sudden, observeBrynjolfsson and McAfee. Robot entered the English language via a 1921 Czech play, R.U.R. (Rossum’s “Universal” Robots), by Karel Capek. Isaac Asimov coined the term robotics in 1941.

Robots have still lagged in perception and mobility, while excelling in many computational tasks. This dichotomy is known as Moravec’s paradox, described on Wikipedia as:

the discovery by artificial intelligence and robotics researchers that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills require enormous computational resources. (pages 28-29)

Brynjolfsson and McAfee write that, at least until recently, most robots in factories could only handle items that showed up in exactly the same location and configuration each time. To perform a different task, these robots would need to be reprogrammed.

In 2008, Rodney Brooks founded Rethink Robotics. Brooks would like to create robots that won’t need to be programmed by engineers. These new robots could be taught to do a task, or re-taught a new one, by shop floor workers. At the company’s headquarters in Boston,Brynjolfsson and McAfee got a sneak peak at a new robot – Baxter. It has two arms with claw-like grips. The head is an LCD face. It has wheels instead of legs. Each arm can be manually trained to do a wide variety of tasks.

Brynjolfsson and McAfee:

Kiva, another young Boston-area company, has taught its automatons to move around warehouses safely, quickly, and effectively. Kiva robots look like metal ottomans or squashed R2-D2’s. They scuttle around buildings at about knee-height, staying out of the way of humans and one another. They’re low to the ground so they can scoot underneath shelving units, lift them up, and bring them to human workers. After these workers grab the products they need, the robot whisks the shelf away and another shelf-bearing robot takes its place. Software tracks where all the products, shelves, robots, and people are in the warehouse, and orchestrates the continuous dance of the Kiva automatons. In March of 2012, Kiva was acquired by Amazon – a leader in advanced warehouse logistics – for more than $750 million in cash. (page 32)

Boston Dynamics, another New England startup, has built dog-like robots to support troops in the field.

A final example is the Double, which is essentially an iPad on wheels. It allows the operator to see and hear what the robot does.

Brynjolfsson and McAfee present more evidence of technological progress:

On the Star Trek television series, devices called tricorders were used to scan and record three kinds of data: geological, meteorological, and medical. Today’s consumer smartphones serve all these purposes; they can be put to work as seismographs, real-time weather radar maps, and heart- and breathing-rate monitors. And, of course, they’re not limited to these domains. They also work as media players, game platforms, reference works, cameras, and GPS devices. (page 34)

Recently, the company Narrative Science was contracted with by Forbes.com in order to write earnings previews that are indistinguishable from human writing.

Brynjolfsson and McAfee conclude:

Most of the innovations described in this chapter have occurred in just the past few years. They’ve taken place where improvement had been frustratingly slow for a long time, and where the best thinking often led to the conclusion that it wouldn’t speed up. But then digital progress became sudden after being gradual for so long. This happened in multiple areas, from artificial intelligence to self-driving cars to robotics.

How did this happen? Was it a fluke – a confluence of a number of lucky, one-time advances? No, it was not. The digital progress we’ve seen recently certainly is impressive, but it’s just a small indication of what’s to come. It’s the dawn of the second machine age. To understand why it’s unfolding now, we need to understand the nature of technological progress in the era of digital hardware, software, and networks. In particular, we need to understand its three characteristics: that it is exponential, digital, and combinatorial. The next three chapters will discuss each of these in turn. (page 37)

 

MOORE’S LAW AND THE SECOND HALF OF THE CHESSBOARD

Moore’s Law roughly says that computing power per dollar doubles about every eighteen months. It’s not a law of nature, noteBrynjolfsson and McAfee, but a statement about the continued productivity of the computer industry’s engineers and scientists. Moore first made his prediction in 1965. He thought it would only last for ten years. But it’s now lasted almost fifty years.

Brynjolfsson and McAfee point out that this kind of sustained progress hasn’t happened in any other field. It’s quite remarkable.

Inventor and futurist Ray Kurzweil has told the story of the inventor and the emperor. In the 6th century in India, a clever man invented the game of chess. The man went to the capital city, Pataliputra, to present his invention to the emperor. The emperor was so impressed that he asked the man to name his reward.

The inventor praised the emperor’s generosity and said, “All I desire is some rice to feed my family.” The inventor then suggested they use the chessboard to determine the amount of rice he would receive. He said to place one grain of rice on the first square, two grains on the second square, four grains on the third square, and so forth. The emperor readily agreed.

If you were to actually do this, you would end up with more than eighteen quintillion grains of rice. Brynjolfsson and McAfee:

A pile of rice this big would dwarf Mount Everest; it’s more rice than has been produced in the history of the world. (pages 45-46)

Kurzweil points out that when you get to the thirty-second square – which is the first half of the chessboard – you have about 4 billion grains of rice, or one large field’s worth. But when you get to the second half of the chessboard, the result of sustained exponential growth becomes clear.

Brynjolfsson and McAfee:

Our quick doubling calculation also helps us understand why progress with digital technologies feels so much faster these days and why we’ve seen so many recent examples of science fiction becoming business reality. It’s because the steady and rapid exponential growth of Moore’s Law has added up to the point that we’re now in a different regime of computing: we’re now in the second half of the chessboard. The innovations we described in the previous chapter – cars that drive themselves in traffic; Jeopardy!-champion supercomputers; auto-generated news stories; cheap, flexible factory robots; and inexpensive consumer devices that are simultaneously communicators, tricorders, and computers – have all appeared since 2006, as have countless other marvels that seem quite different from what came before.

One of the reasons they’re all appearing now is that the digital gear at their hearts is finally both fast and cheap enough to enable them. This wasn’t the case just a decade ago. (pages 47-48)

Brynjolfsson and McAfee later add:

It’s clear that many of the building blocks of computing – microchip density, processing speed, storage capacity, energy efficiency, download speed, and so on – have been improving at exponential rates for a long time. (page 49)

For example, in 1996, the ASCI Red supercomputer cost $55 million to develop and took up 1,600 square feet of floor space. It was the first computer to score above one teraflop – one trillion floating point operations per second – on the standard test for computer speed, note Brynjolfsson and McAfee. It used eight hundred kilowatts per hour, roughly as much as eight hundred homes. By 1997, it reached 1.8 teraflops.

Nine years later, the Sony PlayStation 3 hit 1.8 teraflops. It cost five hundred dollars, took up less than a tenth of a square meter, and used about two hundred watts, observe Brynjolfsson and McAfee.

Exponential progress has made possible many of the advances discussed in the previous chapter. IBM’s Watson draws on a plethora of clever algorithms, but it would be uncompetitive without computer hardware about one hundred times more powerful than Deep Blue, its chess-playing predecessor that beat the human world champion, Garry Kasparov, in a 1997 match. (page 50)

SLAM

Researchers in artificial intelligence have long been interested in SLAM – simultaneous localization and mapping. As of 2008, computers weren’t able to do this well for large areas.

In November 2010, Microsoft offered Kinect – a $150 accessory – as an addition to its Xbox gaming platform.

The Kinect could keep track of two active players, monitoring as many as twenty joints on each. If one player moved in front of the other, the device made a best guess about the obscured person’s movements, then seamlessly picked up all joints once he or she came back into view. Kinect could also recognize players’ faces, voices, and gestures and do so across a wide range of lighting and noise conditions. It accomplished this with digital sensors including a microphone array (which pinpointed the source of sound better than a single microphone could), a standard video camera, and a depth perception system that both projected and detected infrared light. Several onboard processors and a great deal of proprietary software converted the output of these sensors into information that game designers could use. (page 53)

After its release, Kinect sold more than eight million units in sixty days, which makes it the fastest-selling consumer electronics device of all time. But the Kinect system could do far more than its video game applications. In August 2011, at the SIGGRAPH (the Association of Computing Machinery’s Special Interest Group on Graphics and Interactive Techniques) in Vancouver, British Columbia, a Microsoft team introduced KinestFusion as a solution to SLAM.

In a video shown at SIGGRAPH 2011, a person picks up a Kinect and points it around a typical office containing chairs, a potted plant, and a desktop computer and monitor. As he does, the video splits into multiple screens that show what the Kinect is able to sense. It immediately becomes clear that if the Kinect is not completely solving the SLAM for the room, it’s coming close. In real time, Kinect draws a three-dimensional map of the room and all the objects in it, including a coworker. It picks up the word DELL pressed into the plastic on the back of the computer monitor, even though the letters are not colored and only one millimeter deeper than the rest of the monitor’s surface. The device knows where it is in the room at all times, and even knows how virtual ping-pong balls would bounce around if they were dropped into the scene. (page 54)

Microsoft made available (in June 2011) a Kinect software development kit. Less than a year later, a team led by John Leonard of MIT’s Computer Science and Artificial Intelligence Lab announced Kintinuous, a ‘spatially extended’ version of KinectFusion. Users could scan large indoor volumes and even outdoor environments.

Another fascinating example of powerful digital sensors:

A Google autonomous car incorporates several sensing technologies, but its most important ‘eye’ is a Cyclopean LIDAR (a combination of ‘LIght’ and ‘raDAR’) assembly mounted on the roof. This rig, manufactured by Velodyne, contains sixty-four separate laser beams and an equal number of detectors, all mounted in a housing that rotates ten times a second. It generates about 1.3 million data points per second, which can be assembled by onboard computers into a real-time 3D picture extending one hundred meters in all directions. Some early commercial LIDAR systems around the year 2000 cost up to $35 million, but in mid-2013 Velodyne’s assembly for self-navigating vehicles was priced at approximately $80,000, a figure that will fall much further in the future. David Hall, the company’s founder and CEO, estimates that mass production would allow his product’s price to ‘drop to the level of a camera, a few hundred dollars.’ (page 55)

 

THE DIGITIZATION OF JUST ABOUT EVERYTHING

As of March 2017, Android users could choose from 2.8 million applications while Apple users could choose from 2.2 million. One example of a free but powerful app – a version of which is available from several companies – is one that gives you a map plus driving directions. The app tells you the shortest route available now.

Digitization is turning all kinds of information and bits into the language of computers – ones and zeroes. What’s crucial about digital information is that it’s non-rival and it has close to zero marginal cost of reproduction. In other words, it can be used over and over – it doesn’t get ‘used up’ – and it’s extremely cheap to make another copy. (Rival goods, by contrast, can only be used by one person at a time.)

In 1991, at the Nineteenth General Conference on Weights and Measures, the set of prefixes was expanded to include ayotta, representing one septillion, or 10^24. As of 2012, there were 2.7 zettabytes of digital data – or 2.7 sextillion bytes. This is only one prefix away from ayotta.

The explosion of digital information, while obviously not always useful, can often lead to scientific advances – i.e., understanding and predicting phenomena more accurately or more simply. Some search terms have been found to have predictive value. Same with some tweets. Culturonomics makes use of digital information – like scanned copies of millions of books written over the centuries – to study human culture.

 

INNOVATION: DECLINING OR RECOMBINING?

Linus Pauling:

If you want to have good ideas, you must have many ideas.

Innovation is the essential long-term driver of progress. As Paul Krugman said:

Productivity isn’t everything, but in the long run it is almost everything. (page 72)

Improving the standard of living over time depends almost entirely on raising output per worker, Krugman explained. Brynjolfsson and McAfee write that most economists agree with Joseph Schumpeter’s observation:

Innovation is the outstanding fact in the economic history of capitalist society… and also it is largely responsible for most of what we would at first sight attribute to other factors. (page 73)

The original Industrial Revolution resulted in large part from the steam engine. The Second Industrial Revolution depended largely on three innovations: electricity, the internal combustion engine, and indoor plumbing with running water.

Economist Robert Gordon, a widely respected researcher on productivity and economic growth, has concluded that by 1970, economic growth stalled out. The three main inventions of the Second Industrial Revolution had their effect from 1870 to 1970. But there haven’t been economically significant innovations since 1970, according to Gordon. Some other economists, such as Tyler Cowen, agree with Gordon’s basic view.

The most economically important innovations are calledgeneral purposes technologies (GPTs). GPTs, according to Gavin Wright, are:

deep new ideas or techniques that have the potential for important impacts on many sectors of the economy. (page 76)

‘Impacts,’ note Brynjolfsson and McAfee, mean significant boosts in output due to large productivity gains. They noticeably accelerate economic progress. GPTs, economists have concurred, should be pervasive, improving over time, and should lead to new innovations.

Isn’t information and communication technology (ICT) a GPT? Most economic historians think so. Economist Alexander Field compiled a list of candidates for GPTs, and ICT was tied with electricity as the second most common GPT. Only the steam engine was ahead of ICT.

Not everyone agrees. Cowen argues basically that ICT is coming up short on the revenue side of things.

The ‘innovation-as-fruit’ view, say Brynjolfsson and McAfee, is that there are discrete inventions followed by incremental improvements, but those improvements stop being significant after a certain point. The original inventions have been used up.

Another way to look at innovation, however, is not coming up with something big and new, but recombining things that already exist. Complexity scholar Brian Arthur holds this view of innovation. So does economist Paul Romer, who has written that we, as humans, nearly always underestimate how many new ideas have yet to be discovered.

The history of physics may serve as a good illustration of Romer’s point. At many different points in the history of physics, at least some leading physicists have asserted that physics was basically complete. This has always been dramatically wrong. As of 2017, is physics closer to 10% complete or 90% complete? Of course, no one knows for sure. But how much more will be discovered and invented if we have AI with IQ 1,000,000+ being handled by genetically engineered scientists? In my view, physics is probably closer to 10% complete.

Brynjolfsson and McAfee point out that ICT leads to recombinant innovation, perhaps like nothing else has.

…digital innovation is recombinant innovation in its purest form. Each development becomes a building block for future innovations. Progress doesn’t run out; it accumulates… Moore’s Law makes computing devices and sensors exponentially cheaper over time, enabling them to be built economically into more and more gear, from doorknobs to greeting cards. Digitization makes available massive bodies of data relevant to almost any situation, and this information can be infinitely reproduced and reused because it is non-rival. As a result of these two forces, the number of potentially valuable building blocks is exploding around the world, and the possibilities are multiplying as never before. We’ll call this the ‘innovation-as-building-block’ view of the world; it’s the one held by Arthur, Romer, and the two of us. From this perspective, unlike the innovation-as-fruit view, building blocks don’t ever get eaten or otherwise used up. In fact, they increase the opportunities for future recombinations.

…In his paper, ‘Recombinant Growth,’ the economist Martin Weitzman developed a mathematical model of new growth theory in which the ‘fixed factors’ in an economy – machine tools, trucks, laboratories, and so on – are augmented over time by pieces of knowledge that he calls ‘seed ideas,’ and knowledge itself increases over time as previous seed ideas are recombined into new ones. (pages 81-82)

As the number of seed ideas increases, the combinatorial possibilities explode quickly. Weitzman:

In the early stages of development, growth is constrained by number of potential new ideas, but later on it is constrained only by the ability to process them.

ICT connects nearly everyone, and computing power continues to follow Moore’s Law. Brynjolfsson and McAfee:

We’re interlinked by global ICT, and we have affordable access to masses of data and vast computing power. Today’s digital environment, in short, is a playground for large-scale recombination. (page 83)

…The innovation scholars Lars Bo Jeppesen and Karim Lakhani studied 166 scientific problems posted to Innocentive, all of which had stumped their home organizations. They found that the crowd assembled around Innocentive was able to solve forty-nine of them, for a success rate of nearly 30 percent. They also found that people whose expertise was far away from the apparent domain of the problem were more likely to submit winning solutions. In other words, it seemed to actually help a solver to be ‘marginal’ – to have education, training, and experience that were not obviously relevant for the problem. (page 84)

Kaggle is similar to Innocentive, but Kaggle is focused on data-intensive problems with the goal being to improve the baseline prediction. The majority of Kaggle contests, says Brynjolfsson and McAfee, are won by people who are marginal to the domain of the challenge. In one problem involving artificial intelligence – computer grading of essays – none of the top three finishers had any formal training in artificial intelligence beyond a free online course offered by Stanford AI faculty, open to anyone in the world.

 

ARTIFICIAL AND HUMAN INTELLIGENCE IN THE SECOND MACHINE AGE

Previous chapters discussed three forces – sustained exponential improvement in most aspects of computing, massive amounts of digitized information, and recombinant invention – that are yielding significant innovations. But, state Brynjolfsson and McAfee, when you consider also that most people on the planet are connected via the internet and that useful artificial intelligence (AI) is emerging, you have to be even more optimistic about future innovations.

Digital technologies will restore hearing to the deaf via cochlear implants. Digital technologies will likely restore sight to the fully blind, perhaps by retinal implants. That’s just the beginning, to say nothing of advances in biosciences. Dr. Watson will become the best diagnostician in the world. Another supercomputer will become the best surgeon in the world.

Brynjolfsson and McAfee summarize:

The second machine age will be characterized by countless instances of machine intelligence and billions of interconnected brains working together to better understand and improve our world. (page 96)

 

COMPUTING BOUNTY

Milton Friedman:

Most economic fallacies derive from the tendency to assume that there is a fixed pie, that one party can gain only at the expense of another.

Productivity growth comes from technological innovation and from improvements in production techniques. The 1940s, 1950s, and 1960s were a time of rapid productivity growth. The technologies of the first machine age, such as electricity and the internal combustion engine, were largely responsible.

But in 1973, things slowed down. What’s interesting is that computers were becoming available during this decade. But like the chief innovations of the first machine age, it would take a few decades before computing would begin to impact productivity growth significantly.

The internet started impacting productivity within a decade after its invention in 1989. And even more importantly, enterprise-wide IT systems boosted productivity in the 1990s. Firms that used IT throughout the 1990s were noticeably more productive as a result.

Brynjolfsson and McAfee:

The first five years of the twenty-first century saw a renewed wave of innovation and investment, this time less focused on computer hardware and more focused on a diversified set of applications and process innovations… In a statistical study of over six hundred firms that Erik did with Lorin Hitt, he found that it takes an average of five to seven years before full productivity benefits of computers are visible in the productivity of the firms making the investments. This reflects the time and energy required to make the other complementary investments that bring a computerization effort success. In fact, for every dollar of investment in computer hardware, companies need to invest up to another nine dollars in software, training, and business process redesign. (pages 104-105)

Brynjolfsson and McAfee conclude:

The explanation for this productivity surge is in the lags that we always see when GPTs are installed. The benefits of electrification stretched for nearly a century as more and more complementary innovations were implemented. The digital GPTs of the second machine age are no less profound. Even if Moore’s Law ground to a halt today, we could expect decades of complementary innovations to unfold and continue to boost productivity. However, unlike the steam engine or electricity, second machine age technologies continue to improve at a remarkably rapid exponential pace, replicating their power with digital perfection and creating even more opportunities for combinatorial innovation. The path won’t be smooth… but the fundamentals are in place for bounty that vastly exceeds anything we’ve ever seen before. (page 106)

 

BEYOND GDP

Brynjolfsson and McAfee note that President Hoover had to rely on data such as freight car loadings, commodity prices, and stock prices in order to try to understand what was happening during the Great Depression.

The first set of national accounts was presented to Congress in 1937 based on the pioneering work of Nobel Prize winner Simon Kuznets, who worked with researchers at the National Bureau of Economic Research and a team at the U.S. Department of Commerce. The resulting set of metrics served as beacons that helped illuminate many of the dramatic changes that transformed the economy throughout the twentieth century.

But as the economy has changed, so, too, must our metrics. More and more what we care about in the second machine age are ideas, not things – mind, not matter; bits, not atoms; and interactions, not transactions. The great irony of this information age is that, in many ways, we know less about the sources of value in the economy than we did fifty years ago. In fact, much of the change has been invisible for a long time simply because we did not know what to look for. There’s a huge layer of the economy unseen in the official data and, for that matter, unaccounted for on the income statements and balance sheets of most companies. Free digital goods, the sharing economy, intangibles and changes in our relationships have already had big effects on our well-being. They also call for new organizational structures, new skills, new institutions, and perhaps even a reassessment of some of our values. (pages 108-109)

Brynjolfsson and McAfee write:

In addition to their vast library of music, children with smartphones today have access to more information in real time via the mobile web than the president of the United States had twenty years ago. Wikipedia alone claims to have over fifty times as much information as Encyclopaedia Britannica, the premier compilation of knowledge for most of the twentieth century. Like Widipedia but unlike Britannica, much of the information and entertainment available today is free, as are over one million apps on smartphones.

Because they have zero price, these services are virtually invisible in the official statistics. They add value to the economy but not dollars to GDP. And because our productivity data are, in turn, based on GDP metrics, the burgeoning availability of free goods does not move the productivity dial. There’s little doubt, however, that they have real value. (pages 110-111)

Free products can push GDP downward. A free online encyclopedia available for pennies instead of thousands of dollars makes you better off, but it lowers GDP, observe Brynjolfsson and McAfree. GDP was a good measure of economic growth throughout most of the twentieth century. Higher levels of production generally led to greater well-being. But that’s no longer true to the same extent due to the proliferation of digital goods that do not have a dollar price.

One way to measure the value of goods that are free or nearly free is to find out how much people would be willing to pay for them. This is known asconsumer surplus, but in practice it’s extremely difficult to measure.

New goods and services have not been fully captured in GDP figures.

For the overall economy, the official GDP numbers miss the value of new goods and services added to the tune of about 0.4 percent of additional growth each year, according to economist Robert Gordon. Remember that productivity growth has been in the neighborhood of 2 percent per year for most of the past century, so contribution of new goods is not a trivial portion. (pages 117-118)

GDP misses the full value of digital goods and services. Similarly, intangible assets are not fully measured.

Just as free goods rather than physical products are an increasingly important share of consumption, intangibles also make up a growing share of the economy’s capital assets. Production in the second machine age depends less on physical equipment and structures and more on the four categories of intangible assets: intellectual property, organizational capital, user-generated content, and human capital. (page 119)

Paul Samuelson and Bill Nordhaus have observed that GDP is one of the great inventions of the twentieth century. But as Brynjolfsson and McAfee indicate, digital innovation means that we also need innovation in our economic metrics.

The new metrics will differ both in conception and execution. We can build on some of the existing surveys and techniques researchers have been using. For instance, the human development index uses health and education statistics to fill in some of the gaps in official GDP statistics; the multidimensional poverty index uses ten different indicators – such as nutrition, sanitation, and access to water – to assess well-being in developing countries. Childhood death rates and other health indicators are recorded in other periodic household surveys like the Demographic and Health Surveys.

There are several promising projects in this area. Joe Stiglitz, Amartya Sen, and Jean-Paul Fitoussi have created a detailed guide for how we can do a comprehensive overhaul of our economic statistics. Another promising project is the Social Progress Index that Michael Porter, Scott Stern, Roberto Lauria, and their colleagues are developing. In Bhutan, they’ve begun measuring ‘Gross National Happiness.’ There is also a long-running poll behind the Gallup-Healthways Well-Being Index.

These are all important improvements, and we heartily support them. But the biggest opportunity is in using the tools of the second machine age itself: the extraordinary volume, variety, and timeliness of data available digitally. The Internet, mobile phones, embedded sensors in equipment, and a plethora of other sources are delivering data continuously. For instance, Roberto Rigobon and Alberto Cavallo measure online prices from around the world on a daily basis to create an inflation index that is far timelier and, in many cases, more reliable, than official data gathered via monthly surveys with much smaller samples. Other economists are using satellite mapping of nighttime artificial light sources to estimate economic growth in different parts of the world, and assessing the frequency of Google searches to understand changes in unemployment and housing. Harnessing this information will produce a quantum leap in our understanding of the economy, just as it has already changed marketing, manufacturing, finance, retailing, and virtually every other aspect of business decision-making.

As more data become available, and the economy continues to change, the ability to ask the right questions will become even more vital. No matter how bright the light is, you won’t find your keys by searching under a lamppost if that’s not where you lost them. We must think hard about what it is we really value, what we want more of, and what we want less of. GDP and productivity growth are important, but they are a means to an end and not ends in and of themselves. Do we want to increase consumer surplus? Then lower prices or more leisure might be signs of progress, even if they result in a lower GDP. And, of course, many of our goals are nonmonetary. We shouldn’t ignore the economic metrics, but neither should we let them crowd out our other values simply because they are more measurable.

In the meantime, we need to bear in mind that the GDP and productivity statistics overlook much of what we value, even when using a narrow economic lens. What’s more, the gap between what we measure and what we value grows every time we gain access to a new good or service that never existed before, or when existing goods become free as they so often do when they are digitized. (pages 123-124)

 

THE SPREAD

Brynjolfsson and McAfee:

…Advances in technology, especially digital technologies, are driving an unprecedented reallocation of wealth and income. Digital technologies can replicate valuable ideas, insights, and innovations at very low cost. This creates bounty for society and wealth for innovators, but diminishes the demand for previously important types of labor, which can leave many people with reduced incomes.

The combination of bounty and spread challenges two common though contradictory worldviews. One common view is that advances in technology always boost incomes. The other is that automation hurts workers’ wages as people are replaced by machines. Both of these have a kernel of truth, but the reality is more subtle. Rapid advances in our digital tools are creating unprecedented wealth, but there is no economic law that says all workers, or even a majority of workers, will benefit from these advances.

For almost two hundred years, wages did increase alongside productivity. This created a sense of inevitability that technology helped (almost) everyone. But more recently, median wages have stopped tracking productivity, underscoring the fact that such a decoupling is not only a theoretical possibility but also an empirical fact in our current economy. (page 128)

Statistics on how the median worker is doing versus the top 1 percent are revealing:

…The year 1999 was the peak year for real (inflation-adjusted) income of the median American household. It reached $54,932 that year, but then started falling. By 2011, it had fallen nearly 10 percent to $50,054, even as overall GDP hit a record high. In particular, wages of unskilled workers in the United States and other advanced countries have trended downward.

Meanwhile, for the first time since the Great Depression, over half the total income in the United States went to the top 10 percent of Americans in 2012. The top 1 percent earned over 22 percent of income, more than doubling their share since the early 1980s. The share of income going to the top hundredth of one percent of Americans, a few thousand people with annual incomes over $1 million, is now at 5.5 percent, after increasing more between 2011 and 2012 than any year since 1927-1928. (page 129)

Technology is changing economics. Brynjolfsson and McAfee point out two examples: digital photography and TurboTax.

At one point, Kodak employed 145,300 people. But recently, Kodak filed for bankruptcy. Analog photography peaked in the year 2000. As of 2014, over 2.5 billion people had digital cameras and the vast majority of photos are digital. At the same time, Facebook has a market value many times what Kodak ever did. And Facebook has created at least several billionaires, each of whom has a net worth more than ten times what George Eastman – founder of Kodak – had. Also, in 2012, Facebook had over one billion users, despite employing only 4,600 people (roughly 1,000 of whom are engineers).

Just as digital photography has made it far easier for many people to take and store photos, so TurboTax software has made it much more convenient for many people to file their taxes. Meanwhile, tens of thousands of tax preparers – including those at H&R Block – have had their jobs and incomes threatened. But the creators of TurboTax have done very well – one is a billionaire.

The crucial reality from the standpoint of economics is that it takes a relatively small number of designers and engineers to create and update a program like TurboTax. As we saw in chapter 4, once the algorithms are digitized they can be replicated and delivered to millions of users at almost zero cost. As software moves to the core of every industry, this type of production process and this type of company increasingly populates the economy. (pages 130-131)

Brynjolfsson and McAfee report that most Americans have become less wealthy over the past several decades.

Between 1983 and 2009, Americans became vastly wealthier overall as the total value of their assets increased. However, as noted by economists Ed Wolff and Sylvio Allegretto, the bottom 80 percent of the income distribution actually saw a net decrease in their wealth. Taken as a group, the top 20 percent got not 100 percent of the increase, but more than 100 percent. Their gains included not only the trillions of dollars of wealth newly created in the economy but also some additional wealth that was shifted in their direction from the bottom 80 percent. The distribution was also highly skewed even among relatively wealthy people. The top 5 percent got 80 percent of the nation’s wealth increase; the top 1 percent got over half of that, and so on for ever-finer subdivisions of the wealth distribution…

Along with wealth, the income distribution has also shifted. The top 1 percent increased their earnings by 278 percent between 1979 and 2007, compared to an increase of just 35 percent for those in the middle of the income distribution. The top 1 percent earned over 65 percent of the income between 2002 and 2007. (page 131)

Brynjolfsson and McAfee then add:

As we discussed in our earlier book Race Against the Machine, these structural economic changes have created three overlapping pairs of winners and losers. As a result, not everyone’s share of the economic pie is growing. The first two sets of winners are those who have accumulated significant quantities of the right capital assets. These can be either nonhuman capital (such as equipment, structures, intellectual property, or financial assets), or human capital (such as training, education, experience, and skills). Like other forms of capital, human capital is an asset that can generate a stream of income. A well-trained plumber can earn more each year than an unskilled worker, even if they both work the same number of hours. The third group of winners is made up of the superstars among us who have special talents – or luck. (pages 133-134)

The most basic economic model, write Brynjolfsson and McAfee, treats technology as a simple multiplier on everything else, increasing overall productivity evenly for everyone. In other words, all labor is affected equally by technology. Every hour worked produces more value than before.

A slightly more complex model allows for the possibility that technology may not affect all inputs equally, but rather may be ‘biased’ toward some and against others. In particular, in recent years, technologies like payroll processing software, factory automation, computer-controlled machines, automated inventory control, and word processing have been deployed for routine work, substituting for workers in clerical tasks, on the factory floor, and doing rote information processing.

By contrast, technologies like big data and analytics, high-speed communications, and rapid prototyping have augmented the contributions made by more abstract and data-driven reasoning, and in turn have increased the value of people with the right engineering, creative, and design skills. The net effect has been to decrease demand for less skilled labor while increasing the demand for skilled labor. Economists including David Autor, Lawrence Katz and Alan Krueger, Frank Levy and Richard Murnane, Daren Acemoglu, and many others have documented this trend in dozens of careful studies. They call it skill-biased technical change. By definition, skill-biased technical change favors people with more human capital. (page 135)

Skill-biased technical change can be seen in the growing income gaps between people with different levels of education.

Furthermore, organizational improvements related to technical advances may be even more significant than the technical advances themselves.

…Work that Erik did with Stanford’s Tim Bresnahan, Wharton’s Lorin Hitt, and MIT’s Shinkyu Yang found that companies used digital technologies to reorganize decision-making authority, incentives systems, information flows, hiring systems, and other aspects of their management and organizational processes. This coinvention of organization and technology not only significantly increased productivity but tended to require more educated workers and reduce demand for less-skilled workers. This reorganization of production affected those who worked directly with computers as well as workers who, at first glance, seemed to be far from the technology…

Among the industries in the study, each dollar of computer capital was often the catalyst for more than ten dollars of complementary investments in ‘organizational capital,’ or investments in training, hiring, and business process redesign. The reorganization often eliminates a lot of routine work, such as repetitive order entry, leaving behind a residual set of tasks that require relatively more judgment, skills, and training.

Companies with the biggest IT investments typically made the biggest organizational changes, usually with a lag of five to seven years before seeing the full performance benefits. These companies had the biggest increase in the demand for skilled work relative to unskilled work….

This means that the best way to use new technologies is usually not to make a literal substitution of a machine for each human worker, but to restructure the process. Nonetheless, some workers (usually the less skilled ones) are still eliminated from the production process and others are augmented (usually those with more education and training), with predictable effects on the wage structure. Compared to simply automating existing tasks, this kind of organizational coinvention requires more creativity on the part of entrepreneurs, managers, and workers, and for that reason it tends to take time to implement the changes after the initial invention and introduction of new technologies. But once the changes are in place, they generate the lion’s share of productivity improvements.(pages 137-138)

Brynjolfsson and McAfee explain thatskill-biased technical change can be somewhat misleading in the context of jobs eliminated as companies have reorganized. It’s more accurate to say that routine tasks – whether cognitive or manual – have been replaced the most by computers. One study by Nir Jaimovich and Henry Siu found that the demand for routine cognitive tasks such as cashiers, mail clerks, and bank tellers and routine manual tasks such as machine operators, cement masons, and dressmakers was not only falling, but falling at accelerating rate.

These jobs fell by 5.6 percent between 1981 and 1991, 6.6 percent between 1991 and 2001, and 11 percent between 2001 and 2011. In contrast, both nonroutine cognitive work and nonroutine manual work grew in all three decades. (pages 139-140)

Since the early 1980s, when computers began to be adopted, the share of income going to labor has declined while the share of income going to owners of physical capital has increased. However, as new capital is added cheaply at the margin, the rewards earned by capitalists may not automatically grow relative to labor, observe the authors.

 

IMPLICATIONS OF THE BOUNTY AND THE SPREAD

Franklin D. Roosevelt:

The test of our progress is not whether we add more to the abundance of those who have much; it is whether we provide enough for those who have little.

Like productivity, state Brynjolfsson and McAfee, GDP, corporate investment, and after-tax profits are also at record highs. Yet the employment-to-population ratio is lower than at any time in at least two decades. This raises three questions:

  • Will the bounty overcome the spread?
  • Can technology not only increase inequality but also create structural unemployment?
  • What about globalization, the other great force transforming the economy – could it explain recent declines in wages and employment?

Thanks to technology, we will keep getting ever more output from fewer inputs like raw materials, capital, and labor. We will benefit from higher productivity, but also from free digital goods. Brynjolfsson and McAfee:

… ‘Bounty’ doesn’t simply mean more cheap consumer goods and empty calories. As we noted in chapter 7, it also means simultaneously more choice, greater variety, and higher quality in many areas of our lives. It means heart surgeries performed without cracking the sternum and opening the chest cavity. It means constant access to the world’s best teachers combined with personalized self-assessments that let students know how well they’re mastering the material. It means that households have to spend less of their total budget over time on groceries, cars, clothing, and utilities. It means returning hearing to the deaf and, eventually, sight to the blind. It means less need to work doing boring, repetitive tasks and more opportunity for creative, interactive work. (page 166)

However, technological progress is also creating ever larger differences in important areas – wealth, income, standards of living, and opportunities for advancement. If the bounty is large enough, do we need to worry about the spread? If all people’s economic lives are improving, then is increasing spread really a problem? Harvard economist Greg Mankiw has argued that the enormous income of the ‘one percent’ may reflect – in large part – the rewards of creating value for everyone else. Innovators improve the lives of many people, and the innovators often get rich as a result.

The high-tech industry offers many examples of this happy phenomenon in action. Entrepreneurs create devices, websites, apps, and other goods and services that we value. We buy and use them in large numbers, and the entrepreneurs enjoy great financial success…

We particularly want to encourage it because, as we saw in chapter 6, technological progress typically helps even the poorest people around the world. Careful research has shown that innovations like mobile telephones are improving people’s incomes, health, and other measures of well-being. As Moore’s Law continues to simultaneously drive down the cost and increase the capability of these devices, the benefits they bring will continue to add up. (pages 167-168)

Those who believe in the strong bounty argument think that unmeasured price decreases, quality improvements, and other benefits outweigh the lost ground in other areas, such as the decline in the median real income.

Unfortunately, however, some important items such as housing, health care, and college have gotten much more expensive over time. Brynjolfsson and McAfee cite research by economist Jared Bernstein, who found that while median family income grew by 20 percent between 1990 and 2008, prices for housing and college grew by about 50 percent, and health care by more than 150 percent. Moreover, median incomes have been falling in recent years.

Brynjolfsson and McAfee then add:

That many Americans face stagnant and falling income is bad enough, but it is now combined with decreasing social mobility – an ever lower chance that children born at the bottom end of the spread will escape their circumstances and move upward throughout their lives and careers…This is exactly what we’d expect to see as skill-biased technical changes accelerates. (pages 170-171)

Based on economic theory and supported by most of the past two hundred years, economists have generally agreed that technological progress has created more jobs than it has destroyed. Some workers are displaced by new technologies, but the increase in total output creates more than enough new jobs.

Regarding economic theory, there are three possible arguments: inelastic demand, rapid change, and severe inequality.

If lower costs leads to lower prices of goods, and if lower prices leads to increased demand for the goods, then this may lead to an increase in the demand for labor. It depends on the elasticity of demand.

For some goods, such as lighting, demand is relatively inelastic: price declines have not led to a proportionate increase in demand. For other goods, demand has been relatively elastic: price declines have resulted in an even greater increase in demand. One example, write Brynjolfsson and McAfee, is the Jevons paradox: more energy efficiency can sometimes lead to greater total demand for energy.

If elasticity is exactly equal to one – so a 1 percent decline in price leads to a 1 percent increase in demand – then total revenues (price times quantity) are unchanged, explain Brynjolfsson and McAfee. In this case, an increase in productivity, meaning less labor needed for each unit of output, will be exactly offset by an increase in total demand, so that the overall demand for labor is unchanged. Elasticity of one, it can be argued, is what happens in the overall economy.

Brynjolfsson and McAfee remark that the second, more serious, argument for technological unemployment is that our skills, organizations, and institutions cannot keep pace with technological change. What if it takes ten years for displaced workers to learn new skills? What if, by then, technology has changed again?

Faster technological progress may ultimately bring greater wealth and longer lifespans, but it also requires faster adjustments by both people and institutions. (page 178)

The third argument is that ongoing technological progress will lead to a continued decline in real wages for many workers. If there’s technological progress where only those with specific skills, or only those who own a certain kind of capital, benefit, then the equilibrium wage may indeed approach a dollar an hour or even zero. Over history, many inputs to production, from whale oil to horses, have reached a point where they were no longer needed even at zero price.

Although job growth has stopped tracking productivity upward in the past fifteen years or so, it’s hard to know what the future holds, say the authors.

Brynjolfsson and McAfee then ask: What if there were an endless supply of androids that never break down and that could do all the jobs that humans can do, but at essentially no cost? There would be an enormous increase in the volume, variety, and availability of goods.

But there would also be severe dislocations to the labor force. Entrepreneurs would continue to invent new products and services, but they would staff these companies with androids. The owners of androids and other capital assets or natural resources would capture all the value in the economy. Those with no assets would have only labor to sell, but it would be worthless. Brynjolfsson and McAfee sum it up: you don’t want to compete against close substitutes when those substitutes have a cost advantage.

But in principle, machines can have very different strengths and weaknesses than humans. When engineers work to amplify these differences, building on the areas where machines are strong and humans are weak, then the machines are more likely to complement humans rather than substitute for them. Effective production is more likely to require both human and machine inputs, and the value of the human inputs will grow, not shrink, as the power of the machines increases. A second lesson of economics and business strategy is that it’s great to be a complement to something that’s increasingly plentiful. Moreover, this approach is more likely to create opportunities to produce goods and services that could never have been created by unaugmented humans, or machines that simply mimicked people, for that matter. These new goods and services provide a path for productivity growth based on increased output rather than reduced inputs.

Thus in a very real sense, as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren’t thinking hard enough about what needs doing. We aren’t being creative enough about solving the problems we have using the freed-up time and energy of the people whose old jobs were automated away. We can do more to invent technologies and business models that augment and amplify the unique capabilities of humans to create new sources of value, instead of automating the ones that already exist. As we will discuss further in the next chapters, this is the real challenge facing our policy makers, our entrepreneurs, and each of us individually. (page 182)

 

LEARNING TO RACE WITH MACHINES: RECOMMENDATIONS FOR INDIVIDUALS

Pablo Picasso on computers:

But they are useless. They can only give you answers.

Even where digital machines are far ahead of humans, humans still have important roles to play. IBM’s Deep Blue beat Garry Kasparov in a chess match in 1997. And nowadays even cheap chess programs are better than any human. Does that mean humans no longer have anything to contribute to chess? Brynjolfsson and McAfee quote Kasparov’s comments on ‘freestyle’ chess (which involves teams of humans plus computers):

The teams of human plus machine dominated even the strongest computers. The chess machine Hydra, which is a chess-specific supercomputer like Deep Blue, was no match for a strong human player using a relatively weak laptop. Human strategic guidance combined with the tactical acuity of a computer was overwhelming.

The surprise came at the conclusion of the event. The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and ‘coaching’ their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably superior to a strong human + machine + inferior process. (pages 189-190)

Brynjolfsson and McAfee explain:

The key insight from freestyle chess is that people and computers don’t approach the same task the same way. If they did, humans would have had nothing to add after Deep Blue beat Kasparov; the machine, having learned how to mimic human chess-playing ability, would just keep riding Moore’s Law and racing ahead. But instead we see that people still have a great deal to offer the game of chess at its highest levels once they’re allowed to race with machines, instead of purely against them.

Computers are not as good as people at being creative:

We’ve never seen a truly creative machine, or an entrepreneurial one, or an innovative one. We’ve seen software that could create lines of English text that rhymed, but none that could write a true poem… Programs that can write clean prose are amazing achievements, but we’ve not yet seen one that can figure out what to write about next. We’ve also never seen software that could create good software; so far, attempts at this have been abject failures.

These activities have one thing in common: ideation, or coming up with new ideas or concepts. To be more precise, we should probably say good new ideas or concepts, since computers can easily be programmed to generate new combinations of preexisting elements like words. This however, is not recombinant innovation in any meaningful sense. It’s closer to the digital equivalent of a hypothetical room full of monkeys banging away randomly on typewriters for a million years and still not reproducing a single play of Shakespeare’s.

Ideation in its many forms is an area today where humans have a comparative advantage over machines. Scientists come up with new hypotheses. Journalists sniff out a good story. Chefs add a new dish to the menu. Engineers on a factory floor figure out why a machine is no longer working properly. [Workers at Apple] figure out what kind of tablet computer we actually want. Many of these activities are supported or accelerated by computers, but none are driven by them.

Picasso’s quote at the head of this chapter is just about half right. Computers are not useless, but they’re still machines for generating answers, not posing interesting new questions. That ability still seems to be uniquely human, and still highly valuable. We predict that people who are good at idea creation will continue to have a comparative advantage over digital labor for some time to come, and will find themselves in demand. In other words, we believe that employers now and for some time to come will, when looking for talent, follow the advice attributed to the Enlightenment sage Voltaire: ‘Judge a man by his questions, not his answers.’

Ideation, innovation, and creativity are often described as ‘thinking outside the box,’ and this characterization indicates another large and reasonably sustainable advantage of human over digital labor. Computers and robots remain lousy at doing anything outside the frame of their programming… (pages 191-192)

Futurist Kevin Kelly:

You’ll be paid in the future based on how well you work with robots. (page 193)

Brynjolfsson and McAfee sum it up:

So ideation, large-frame pattern recognition, and the most complex forms of communication are cognitive areas where people still seem to have the advantage, and also seem likely to hold onto it for some time to come. Unfortunately, though, these skills are not emphasized in most educational environments today. (page 194)

Sociologists Richard Arum and Josipa Roksa have found in their research that many American college students today are not good at critical thinking, written communication, problem solving, and analytic reasoning. In other words, many college students are not good at ideation, pattern recognition, and complex communication. Arum and Roksa came to this conclusion after testing college students’ ability to read background documents and write an essay on them. A major reason for this shortcoming, say Arum and Roksa, is that college students spend only 9 percent of their time studying, while spending 51 percent of their time socializing, recreating, etc.

Brynjolfsson and McAfee emphasize that the future is uncertain:

We have to stress that none of our predictions and recommendations here should be treated as gospel. We don’t project that computers and robots are going to acquire the general skills of ideation, large-frame pattern recognition, and highly complex communication any time soon, and we don’t think that Moravec’s paradox is about to be fully solved. But one thing we’ve learned about digital progress is never say never. Like many other observers, we’ve been surprised over and over as digital technologies demonstrated skills and abilities straight out of science fiction.

In fact, the boundary between uniquely human creativity and machine capabilities continues to change. Returning to the game of chess, back in 1956, thirteen-year-old child prodigy Bobby Fischer made a pair of remarkably creative moves against grandmaster Donald Byrne. First he sacrificed his knight, seemingly for no gain, and then exposed his queen to capture. On the surface, these moves seemed insane, but several moves later, Fischer used these moves to win the game. His creativity was hailed at the time as the mark of genius. You today if you program that same position into a run-of-the-mill chess program, it will immediately suggest exactly the moves that Fischer played. It’s not because the computer has memorized the Fischer-Byrne game, but rather because it searches far enough ahead to see that these moves really do pay off. Sometimes, one man’s creativity is another machine’s brute-force analysis.

We’re confident that more surprises are in store. After spending time working with leading technologists and watching one bastion of human uniqueness after another fall before the inexorable onslaught of innovation, it’s becoming harder and harder to have confidence that any given task will be indefinitely resistant to automation. That means people will need to be more adaptable and flexible in their career aspirations, ready to move on from areas that become subject to automation, and seize new opportunities where machines complement and augment human capabilities. Maybe we’ll see a program that can scan the business landscape, spot an opportunity, and write up a business plan so good it’ll have venture capitalists ready to invest. Maybe we’ll see a computer that can write a thoughtful and insightful report on a complicated topic. Maybe we’ll see an automatic medical diagnostician with all the different kinds of knowledge and awareness of a human doctor. And maybe we’ll see a computer that can walk up the stairs to an elderly woman’s apartment, take her blood pressure, draw blood, and ask if she’s been taking her medication, all while putting her at ease instead of terrifying her. We don’t think any of these advances is likely to come any time soon, but we’ve also learned that it’s very easy to underestimate the power of digital, exponential, and combinatorial innovation. So never say never. (pages 202-204)

 

POLICY RECOMMENDATIONS

Brynjolfsson and McAfee affirm that Economics 101 still applies because digital labor is still far from a complete substitute for human labor.

For now the best way to tackle our labor force challenges is to grow the economy. As companies see opportunity for growth, the great majority will need to hire people to seize them. Job growth will improve, and so will workers’ prospects. (page 207)

Brynjolfsson and McAfee also note that there is broad agreement among conservative and liberal economists when it comes to the government policies recommended by Economics 101.

(1) Education

The more educated the populace is, the more innovation tends to occur, which leads to more productivity growth and thus faster economic growth.

The educational system can be improved by using technology. Consider massive open online courses (MOOCs), which have two main economic benefits.

  • The first and most obvious one is that MOOCs enable low-cost replication of the best teachers, content, and methods. Just as we can all listen to the best pop singer or cellist in the world today, students will soon have access to the most exciting geology demonstrations, the most insightful explanations of Renaissance art, and the most effective exercises for learning statistical techniques.
  • The second, subtler benefit from the digitization of education is ultimately more important. Digital education creates an enormous stream of data that makes it possible to give feedback to both teacher and student. Educators can run controlled experiments on teaching methods and adopt a culture of continuous improvement. (pages 210-211)

Brynjolfsson and McAfee then add:

The real impact of MOOCs is mostly ahead of us, in scaling up the reach of the best teachers, in devising methods to increase the overall level of instruction, and in measuring and finding ways to accelerate student improvement… We can’t predict exactly which methods will be invented and which will catch on, but we do see a clear path for enormous progress. The enthusiasm and optimism in this space is infectious. Given the plethora of new technologies and techniques that are now being explored, it’s a certainty that some of them – in fact, we think many of them – will be significant improvements over current approaches to teaching and learning. (pages 211-212)

On the question of how to improve the educational system – in addition to using technology – it’s what you might expect: attract better teachers, lengthen school years, have longer school days, and implement a no-excuses philosophy that regularly tests students. Surprise, surprise: This is what has helped places like Singapore and South Korea to rank near the top in terms of education. Of course, while some teachers should focus on teaching testable skills, other teachers should be used to teach hard-to-measure skills like creativity and unstructured problem solving, observe Brynjolfsson and McAfee.

(2) Startups

Brynjolfsson and McAfee:

We champion entrepreneurship, but not because we think everyone can or should start a company. Instead, it’s because entrepreneurship is the best way to create jobs and opportunity. As old tasks get automated away, along with demand for their corresponding skills, the economy must invent new jobs and industries. Ambitious entrepreneurs are best at this, not well-meaning government leaders or visionary academics. Thomas Edison, Henry Ford, Bill Gates, and many others created new industries that more than replaced the work that was eliminated as farming jobs vanished over the decades. The current transformation of the economy creates an equally large opportunity. (page 214)

Joseph Schumpeter argued that innovation is central to capitalism, and that it’s essentially a recombinant process. Schumpeter also held that innovation is more likely to take place in startups rather than in incumbent companies.

…Entrepreneurship, then, is an innovation engine. It’s also a prime source of job growth. In America, in fact, it appears to be the only thing that’s creating jobs. In a study published in 2010, Tim Kane of the Kauffman Foundation used Census Bureau data to divide all U.S. companies into two categories: brand-new startups and existing firms (those that had been around for at least a year). He found that for all but seven years between 1977 and 2005, existing firms as a group were net job destroyers, losing an average of approximately one million jobs annually. Startups, in sharp contrast, created on average a net three million jobs per year. (pages 214-215)

Entrepreneurship in America remains the best in the world, but it appears to have stagnated recently. One factor may be a decline in would-be immigrants. Immigrants have been involved in a high percentage of startups, but this trend appears to have slowed recently. Moreover, excessive regulation seems to be stymieing startups.

(3) Job Matching

It should be easier to match people with jobs. Better databases can be developed. So can better algorithms for identifying the needed skills. Ratings like TopCoder scores can provide objective metrics of candidate skills.

(4) Basic Science

Brynjolfsson and McAfee:

After rising for a quarter-century, U.S. federal government support for basic academic research started to fall in 2005. This is cause for concern because economics teaches that basic research has large beneficial externalities. This fact creates a role for government, and the payoff can be enormous. The Internet, to take one famous example, was born out of U.S. Defense Department research into how to build bomb-proof networks. GPS systems, touchscreen displays, voice recognition software like Apple’s Siri, and many other digital innovations also arose from basic research sponsored by the government. It’s pretty safe to say, in fact, that hardware, software, networks, and robots would not exist in anything like the volume, variety, and forms we know today without sustained government funding. This funding should be continued, and the recent dispiriting trend of reduced federal funding for basic research in America should be reduced. (pages 218-219)

For some scientific challenges, offering prizes can help:

Many innovations are of course impossible to describe in advance (that’s what makes them innovations). But there are also cases where we know exactly what we’re looking for and just want somebody to invent it. In these cases, prizes can be especially effective. Google’s driverless car was a direct outgrowth of a Defense Advanced Research Projects Agency (DARPA) challenge that offered a one-million-dollar prize for a car that could navigate a specific course without a human driver. Tom Kalil, Deputy Director for Policy of the United States Office of Science and Technology Policy, provides a great playbook for how to run a prize:

  • Shine a spotlight on a problem or opportunity
  • Pay only for results
  • Target an ambitious goal without predicting which team or approach is most likely to succeed
  • Reach beyond usual suspects to tap top talent
  • Stimulate private-sector investment many times greater than the prize purse
  • Bring out-of-discipline perspectives to bear
  • Inspire risk-taking by offering a level playing field
  • Establish clear target metrics and validation protocols

Over the past decade, the total federal and private funds earmarked for large prizes have more than tripled and now surpass $375 million. This is great, but it’s just a tiny fraction of overall government spending on government research. There remains great scope for increasing the volume and variety of innovation competitions. (pages 219-220)

(5) Upgrade Infrastructure

Brynjolfsson and McAfee write that, like education and scientific research, infrastructure has positive externalities. That’s why nearly all economists agree that the government should be involved in building and maintaining infrastructure – streets and highways, bridges, ports, dams, airports and air traffic control systems, and so on.

Excellent infrastructure makes a country a more pleasant place to live, and also a more productive place in which to do business. Ours, however, is not in good shape. The American Society of Civil Engineers (ASCE) gave the United States an overall infrastructure grade of D+ in 2013, and estimated that the country has a backlog of over $3.6 trillion in infrastructure investment…

Bringing U.S. infrastructure up to an acceptable grade would be one of the best investments the country could make in its own future. (pages 220-221)

Economists also agree on the importance of maximizing the potential inflow of legal immigrants, especially those who are highly skilled.

Any policy shift advocated by both the libertarian Cato Institute and the progressive Center for American Progress can truly be said to have diverse support. Such is the case for immigration reform, a range of proposed changes with the broad goal of increasing the number of legal foreign-born workers and citizens in the United States. Generous immigration policies really are part of the Econ 101 playbook; there is wide agreement among economists that they benefit not only the immigrants themselves but also the economy of the country they move to. (page 222)

Brynjolfsson and McAfee continue:

…Since 2007, it appears that net illegal immigration to the United States is approximately zero, or actually negative. And a study by the Brookings Institution found that highly educated immigrants now outnumber less educated ones; in 2010, 30 percent had at least a college education, while only 28 percent lacked the equivalent of a high school degree.

Entrepreneurship in America, particularly in technology-intensive sectors of the economy, is fueled by immigration to an extraordinary degree… As economist Michael Kremer demonstrated in a now classic paper, increasing the number of immigrant engineers actually leads to higher, not lower, wages for native-born engineers because immigrants help creative ecosystems flourish. It’s no wonder that wages are higher for good software designers in Silicon Valley, where they are surrounded by others with similar and generally complementary skills, rather than in more isolated parts of the world.

Today, immigrants are having this large and beneficial effect on the country not because of America’s processes and policies but often despite them. Immigration to the United States is often described as slow, complex, inefficient, and highly bureaucratic… (pages 222-223)

A green card should be stapled to every advanced diploma awarded to an immigrant, say Brynjolfsson and McAfee. Furthermore, a separate ‘startup visa’ category should be created making it easier for entrepreneurs – especially those who have already attracted funding – to launch their ventures in the United States.

(6) Tax Wisely

Obviously we should tax pollution, which is a negative externality. Same goes for things like traffic congestion. Singapore has implemented an Electronic Road Pricing System that has virtually eliminated congestion, note the authors.

Also, land could be taxed more. So could government-owned oil and gas leases. Finally, the top marginal income tax could be increased without harming the economy.

 

LONG-TERM RECOMMENDATIONS

Voltaire:

Work saves a man from three great evils: boredom, vice, and need.

Brynjolfsson and McAfee first point out that technological progress shouldn’t be opposed. Productivity growth is central to economic growth. Overall, things continue to get better. So we should encourage ongoing innovation and deal with the associated challenges as they come up.

We are also skeptical of efforts to come up with fundamental alternatives to capitalism. By ‘capitalism’ here, we mean a decentralized economic system of production and exchange in which most of the means of production are in private hands (as opposed to belonging to the government), where most exchange is voluntary (no one can force you to sign a contract against your will), and where most goods have prices that vary based on relative supply and demand instead of being fixed by a central authority. All of these features exist in most economies around the world today. Many are even in place in today’s China, which is still officially communist.

These features are so widespread because they work so well. Capitalism allocates resources, generates innovation, rewards effort, and builds affluence with high efficiency, and these are extraordinarily important things to do well in a society. As a system, capitalism is not perfect, but it’s far better than the alternatives. Winston Churchill said that, ‘Democracy is the worst form of government except for all those others that have been tried.’ We believe the same about capitalism. (page 231)

What’s likely to change, though, remark Brynjolfsson and McAfee, are concepts related to income and money.

The idea of a basic income is that everyone receives a minimum standard of living. People are free to improve on it by working, investing, starting a company, or other such activities. English-American activist Thomas Paine argued for a form of basic income. Later supporters have included the philosopher Bertrand Russell and civil rights leader Martin Luther King, Jr.

Many economists on both the left and the right have agreed with King. Liberals including James Tobin, Paul Samuelson, and John Kenneth Galbraith and conservatives like Milton Friedman and Friedrich Hayek have all advocated income guarantees in one form or another, and in 1968 more than 1,200 economists signed a letter in support of the concept addressed to the U.S. Congress.

The president elected that year, Republican Richard Nixon, tried throughout his first term in office to enact it into law. In a 1969 speech he proposed a Family Assistance Plan that had many features of a basic income program. The plan had support across the ideological spectrum, but it also faced a large and diverse group of opponents. (page 233)

In any case, basic income – especially on its own – is not the answer. Referring to Voltaire’s quote, basic income saves a person from need, but not from boredom or vice. Work is extremely important for human beings. Brynjolfsson and McAfee mention that Daniel Pink, inDrive, identifies three major motivations: mastery, autonomy, and purpose.

It seems that all around the world, people want to escape the evils of boredom, vice, and need and instead find mastery, autonomy, and purpose by working. (page 235)

Work gives a great many individuals their sense of meaning. What’s true for individuals is also true for communities. Research has shown that people are happier and better off in communities where people work.

Brynjolfsson and McAfee then point out that economists have developed reliable ways to encourage and reward work. Moreover, innovators and entrepreneurs are developing technologies that not only substitute for human labor, but also complement it. The bottom line is that we should continue to try to create and maintain as many jobs as possible.

Perhaps a better way to help the poor is with a ‘negative income tax,’ which the conservative economist Milton Friedman suggested. Say the negative income tax was 50%. Friedman gave an example (in 1968) of $3,000 in income as the cutoff. Someone making $3,000 (again in 1968 dollars) would neither pay a tax nor receive a negative income tax. If a person made only $1,000, then they would get an additional $1,000 as a negative income tax, for a total of $2,000. If the same person made $2,000, they would get an additional $500, for a total of $2,500. Overall, the negative income tax combines a guaranteed minimum income with an incentive to work.

Brynjolfsson and McAfee also point out that taxes on labor are not ideal because they discourage labor. Of course, we need some income taxes. But it may be possible to raise other kinds of taxes – including Pigovian taxes on pollution and other negative externalities, consumption taxes, and the value-added tax (VAT). With a VAT, companies pay based on the difference between their costs (labor, raw materials, etc.) and the prices they charge customers. A VAT is easy to collect, and it’s adjustable and lucrative, observe the authors. The United States is the only country out of the thirty-four in the OECD that doesn’t have a VAT.

 

TECHNOLOGY AND THE FUTURE

Brynjolfsson and McAfee:

After surveying the landscape, we are convinced that we are at an inflection point – the early stages of a shift as profound as that brought on by the Industrial Revolution. Not only are the new technologies exponential, digital, and combinatorial, but most of the gains are still ahead of us…

Our generation will likely have the good fortune to experience two of the most amazing events in history: the creation of true machine intelligence and the connection of all humans via a common digital network, transforming the planet’s economics. Innovators, entrepreneurs, scientists, tinkerers, and many other types of geeks will take advantage of this cornucopia to build technologies that astonish us, delight us, and work for us. Over and over again, they’ll show how right Arthur C. Clarke was when he observed that a sufficiently advanced technology can be indistinguishable from magic. (page 251)

Material needs and wants will become less important over time. Brynjolfsson and McAfee:

We will increasingly be concerned with questions about catastrophic events, genuine existential risks, freedom versus tyranny, and other ways that technology can have unintended or unexpected side effects…

Until recently, our species did not have the ability to destroy itself. Today it does. What’s more, that power will reach the hands of more and more individuals as technologies become both more powerful and cheaper – and thus more ubiquitous. Not all of those individuals will be both sane and well intentioned. As Bill Joy and others have noted, genetic engineering and artificial intelligence can create self-replicating entities. That means that someone working in a basement laboratory might someday use one of these technologies to unleash destructive forces that affect the entire planet. The same scientific breakthroughs in genome sequencing that can be used to cure disease can also be used to create a weaponized version of the smallpox virus. Computer programs can also self-replicate, becoming digital viruses, so the same global network that spreads ideas and innovations can also spread destruction. The physical limits on how much damage any individual or small group could do are becoming less and less constrained. Will our ability to detect and counteract destructive uses of technology advance rapidly enough to keep us safe? That will be an increasingly important question to answer. (pages 252-253)

Is the Singularity Near?

In utopian versions of digital consciousness, we humans don’t fight with machines; we join with them, uploading our brains into the cloud and otherwise becoming part of a ‘technological singularity.’ This is a term coined in 1983 by science-fiction author Vernor Vinge, who predicted that, ‘We will soon create intelligences greater than our own… When this happens, human history will have reached a kind of singularity, an intellectual transition as impenetrable as the knotted space-time at the center of a black hole, and the world will move far beyond our understanding.’

Progress towards such a singularity, Vinge and others have argued, is driven by Moore’s Law. Its accumulated doubling will eventually yield a computer with more processing and storage capacity than the human brain. Once this happens, things become highly unpredictable. Machines could become self-aware, humans and computers could merge seamlessly, or other fundamental transitions could occur… (pages 254-255)

As far as when such a singularity may happen, we simply don’t know. Many have predicted the occurrence of such a singularity in 2050 or later. But as Brynjolfsson and McAfee remind us, with all things digital, never say never. If a supercomputer learns to re-write its own source code repeatedly – thus evolving rapidly – then what?

However, note Brynjolfsson and McAfee, the science-fiction of supercomputers and autonomous cars can be misleading:

…We humans build machines to do things that we see being done in the world by animals and people, but we typically don’t build them the same way that nature built us. As AI trailblazer Frederick Jelinek put it beautifully, ‘Airplanes don’t flap their wings.’

It’s true that scientists, engineers, and other innovators often take cues from biology as they’re working, but it would be a mistake to think that this is always the case, or that major recent AI advances have come about because we’re getting better at mimicking human thought. Journalist Stephen Baker spent a year with the Watson team to research his bookFinal Jeopardy!. He found that, ‘The IBM team paid little attention to the human brain while programming Watson. Any parallels to the brain are superficial, and only the result of chance.’

As we were researching this book we heard similar sentiments from most of the innovators we talked to. Most of them weren’t trying to unravel the mysteries of human consciousness or understand exactly how we think; they were trying to solve problems and seize opportunities. As they did so, they sometimes came up with technologies that had human-like skills and abilities. But these tools themselves were not like humans at all. Current AI, in short, looks intelligent, but it’s an artificial resemblance. That might change in the future. We might start to build digital tools that more closely mimic our minds, perhaps even drawing on our rapidly improving capabilities for scanning and mapping brains. And if we do so, those digital minds will certainly augment ours and might even eventually merge with them, or become self-aware on their own. (pages 255-256)

Brynjolfsson and McAfee remain optimistic about the future:

Even in the face of all these challenges – economic, infrastructural, biological, societal, and existential – we’re still optimistic. To paraphrase Martin Luther King, Jr., the arc of history is long but it bends towards justice. We think the data support this. We’ve seen not just vast increases in wealth but also, on the whole, more freedom, more social justice, less violence, and less harsh conditions for the least fortunate and greater opportunities for more and more people.

Of course, our values and choices will determine our future:

In the second machine age, we need to think much more deeply about what it is we really want and what we value, both as individuals and as a society. Our generation has inherited more opportunities to transform the world than any other. That’s a cause for optimism, but only if we’re mindful of our choices. (page 257)

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here:https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The Most Important Thing Illuminated


February 13, 2022

The Most Important Thing Illuminated (Columbia Business School, 2013) is an update of Howard Marks’ outstanding book on value investing,The Most Important Thing (2011). The revision includes the original text plus comments from top value investors Christopher Davis, Joel Greenblatt, and Seth Klarman. There are also notes from Howards Marks himself and from Columbia professor Paul Johnson.

The sections covered here are:

  • Second-Level Thinking
  • Understanding Market Efficiency
  • Value
  • The Relationship Between Price and Value
  • Understanding Risk
  • Recognizing Risk
  • Controlling Risk
  • Being Attentive to Cycles
  • Combating Negative Influences
  • Contrarianism
  • Finding Bargains
  • Patient Opportunism
  • Knowing What You Don’t Know
  • Appreciating the Role of Luck
  • Investing Defensively
  • Reasonable Expectations

 

SECOND-LEVEL THINKING

Nearly everyone can engage in first-level thinking, which is fairly simplistic. But few can engage in second-level thinking. Second-level thinking incorporates a variety of considerations, says Marks:

  • What is the range of likely future outcomes?
  • Which outcome do I think will occur?
  • What’s the probability I’m right?
  • What does the consensus think?
  • How does my expectation differ from the consensus?
  • How does the current price of the asset comport with the consensus view of the future, and with mine?
  • Is the consensus psychology that’s incorporated in the price too bullish or too bearish?
  • What will happen to the asset’s price if the consensus turns out to be right, and what if I’m right?

In order to do better than the market index, you must have an unconventional approach that works. Joel Greenblatt comments:

The idea is that agreeing with the broad consensus, while a very comfortable place for most people to be, is not generally where above-average profits are found. (page 7)

You can do better than the market over time if you use a proven method for betting against the consensus. One way to achieve this is using a quantitative value investing strategy, which – for most of us – will produce better long-term results than trying to pick individual stocks.

 

UNDERSTANDING MARKET EFFICIENCY

Market prices are generally efficient and incorporate relevant information. Assets sell at prices that offer fair risk-adjusted returns relative to other assets. Marks says:

I agree that because investors work hard to evaluate every new piece of information, asset prices immediately reflect the consensus view of the information’s significance. I do not, however, believe the consensus view is necessarily correct. In January 2000, Yahoo sold at $237. In April 2001 it was at $11. Anyone who argues that the market was right both times has his or her head in the clouds; it has to have been wrong on at least one of those occasions. But that doesn’t mean many investors were able to detect and act on the market’s error. (page 9)

Marks then explains:

The bottom line for me is that, although the more efficient markets often misvalue assets, it’s not easy for any one person – working with the same information as everyone else and subject to the same psychological influences – to consistently hold views that are different from the consensus and closer to being correct.

That’s what makes the mainstream markets awfully hard to beat – even if they aren’t always right. (page 10)

Moreover, notes Marks, some asset classes are rather efficient. In most of these:

  • the asset class is widely known and has a broad following;
  • the class is socially acceptable, not controversial or taboo;
  • the merits of the class are clear and comprehensible, at least on surface; and
  • information about the class and its components is distributed widely and evenly.

The Boole Microcap Fund is a quantitative value fund focused on micro caps. Micro caps – because they are largely either ignored or misunderstood – are far more inefficient than small caps, mid caps, and large caps. See: https://boolefund.com/best-performers-microcap-stocks/

Value investing – properly applied – is a way to invest systematically in underpriced stocks. For details, see: https://boolefund.com/notes-on-value-investing/

Joel Greenblatt explains why value investing works:

Investments that are out of favor, that don’t look so attractive in the near term, are avoided by most professionals, who feel the need to add performance right now. (page 17)

Marks decided to focus in his career on distressed debt because it was a noticeably less efficient asset class.

 

VALUE

Marks points out that you can either look at the fundamental attributes of the company – such as earnings and cash flows – or you can look at the associated stock price, and how it has moved in the past. Value investing is the systematic purchase of businesses below their likely intrinsic values.

When you buy stock, you become a part owner of the underlying business. So you would like to figure out what the business is worth, and then pay a price well below that. Imagine if you were going to buy a laundromat or a farm. You would want to figure out how much it earned in a normal year. And you would want to estimate any future growth in those earnings.

  • Many businesses are difficult to value. The trick, says Buffett, is to stay in your circle of competence: If you focus on those businesses that you can value, you have a chance to find a few investments that will beat the market. There are thousands of tiny businesses (public and private) – like laundromats – that you probably can value.

For most of us, a more reliable way to beat the market is by adopting a quantitative value strategy, which systematically buys stocks below intrinsic value, on average. Lakonishok, Shleifer, and Vishny give a good explanation of quantitative value investing in their 1994 paper, “Contrarian Investment, Extrapolation, and Risk.” Link:http://scholar.harvard.edu/files/shleifer/files/contrarianinvestment.pdf

If you do spend time analyzing individual businesses that might be good long-term investments, then another trick is to find companies that have a sustainable competitive advantage. Buffett uses the termmoat. A business with a moat has a sustainably high ROE (return on equity), which can make for a rewarding long-term investment if you pay a reasonable price. See: https://boolefund.com/notes-on-value-investing/

Marks distinguishes between value and growth.

  • For many value investors, including Buffett, the future growth of a company’s cash flows is simply a component of its value today.

Marks points out that some investors look for a business that can grow a great deal in the future; other investors focus on the value of a business today, and buying well below that value. Marks comments that the “value” approach is more consistent, while the “growth” approach – when it works – can lead to more dramatic results. Marks identifies himself as a value investor because he cherishes consistency above drama.

For value investing to work, not only do you have to buy consistently below intrinsic value; but you also have to hold each stock long enough for the stock price to approach intrinsic value. This can often take 3 to 5 years. Meanwhile, you are very likely to be down from your initial purchase price, as Greenblatt explains:

Unless you buy at the exact bottom tick (which is next to impossible), you will be down at some point after you make every investment. (page 26)

It’s challenging to own shares of a business that remains out-of-favor for an extended period of time. One advantage of a quantitative value strategy is that it’s largely (or entirely) automated, which thereby minimizes psychological errors.

 

THE RELATIONSHIP BETWEEN PRICE AND VALUE

Marks explains:

For a value investor, price has to be the starting point. It has been demonstrated time and time again that no asset is so good that it can’t become a bad investment if bought at too high a price. And there are few assets so bad that they can’t be a good investment when bought cheap enough. (page 29)

Marks later adds:

Investor psychology can cause a security to be priced just about anywhere in the short run, regardless of its fundamentals. (page 32)

Overpriced investments are often “priced for perfection.” In this situation, investors frequently overpay and then later discover that the investment is not perfect and has flaws. By contrast, hated investments are often low risk:

The safest and most potentially profitable thing is to buy something when no one likes it. Given time, its popularity, and thus its price, can only go one way: up. (page 33)

 

UNDERSTANDING RISK

Marks quotes Elroy Dimson:

Risk means more things can happen than will happen. (page 39)

Because the market is mostly efficient, riskier investments have to offer higher potential returns in order to attract capital. However, writes Marks, riskier investments don’t always produce higher returns, otherwise they wouldn’t be riskier. In other words, riskier investments involve greater uncertainty: there are some possible scenarios – with some probability of occurring – that involve lower returns or even a loss.

Following Buffett and Munger, Marks definesrisk as the potential for permanent loss, which must be compared to the potential gain. Risk is not volatility per se, but the possibility of downward volatility where the price never rebounds.

Like other value investors, Marks believes that the lower the price you pay relative to intrinsic value the higher the potential return:

Theory says high return is associated with high risk because the former exists to compensate for the latter. But pragmatic value investors feel just the opposite: They believe high return and low risk can be achieved simultaneously by buying things for less than they’re worth. In the same way, overpaying implies both low return and high risk.

Dull, ignored, possibly tarnished and beaten-down securities – often bargains exactly because they haven’t been performing well – are often the ones value investors favor for high returns. Their returns in bull markets are rarely at the top of the heap, but their performance is generally excellent on average, more consistent than that of ‘hot’ stocks and characterized by low variability, low fundamental risk and smaller losses when markets do badly. (pages 47-48)

Risk ultimately is a subjective measure, says Marks. People have different time horizons and different concerns (for instance, worried about trailing a benchmark versus worried about a permanent loss). Marks quotes Graham and Dodd:

…the relation between different kinds of investments and the risk of loss is entirely too indefinite, and too variable with changing conditions, to permit of sound mathematical formulation.

Risk is just as uncertain after the fact, notes Marks:

A few years ago, while considering the difficulty of measuring risk prospectively, I realized that because of its latent, nonquantitative and subjective nature, the risk of an investment – defined as the likelihood of loss – can’t be measured in retrospect any more than it can a priori.

Let’s say you make an investment that works out as expected. Does that mean it wasn’t risky? Maybe you buy something for $100 and sell it a year later for $200. Was it risky? Who knows? Perhaps it exposed you to great potential uncertainties that didn’t materialize. Thus, its real riskiness might have been high. Or let’s say the investment produces a loss. Does that mean it was risky? Or that it should have been perceived as risky at the time it was analyzed and entered into?

If you think about it, the response to these questions is simple: The fact that something – in this case, loss – happened, doesn’t mean it was bound to happen, and the fact that something didn’t happen doesn’t mean it was unlikely. (page 50)

It’s essential to model the future based on possible scenarios:

The possibility of a variety of outcomes means we mustn’t think of the future in terms of a single result but rather as a range of possibilities. The best we can do is fashion a probability distribution that summarizes the possibilities and describes their relative likelihood. We must think about the full range, not just the ones that are most likely to materialize. (page 52)

Many investors make two related mistakes:

  • Assuming that the most likely scenario is certain;
  • Not imagining all possible scenarios, even highly unlikely ones (whether good or bad).

Marks describes investment results as follows:

For the most part, I think it’s fair to say that investment performance is what happens when a set of developments – geopolitical, macro-economic, company-level, technical and psychological – collide with an extent portfolio. Many futures are possible, to paraphrase Dimson, but only one future occurs. The future you get may be beneficial to your portfolio or harmful, and that may be attributable to your foresight, prudence or luck. (page 54)

Marks refers to Nassim Taleb’s concept of “alternative histories.” How your portfolio performs under the scenario that actually unfolds doesn’t tell you how it would have done under other possible scenarios.

As humans, we are subject to a set of related cognitive biases. See: https://boolefund.com/cognitive-biases/

Hindsight bias causes us to view the past as much more predictable than it actually was. The brain changes its own memories:

  • If some possible event actually happens, our brains tend to think, “I always thought that was likely.”
  • If some possible event doesn’t happen, our brains tend to think, “I always thought that was unlikely.

The fact that we view the past as more predictable than it actually was makes as view the future as more predictable than it actually is. We feel comforted – and usually overconfident – because of our tendency to view both future and past as more predictable than they actually are.

Hindsight bias not only makes us overconfident about the future. It also feeds into confirmation bias, which causes us to search for, remember, and interpret information in a way that confirms our pre-existing beliefs or hypotheses.

Thus, one of the most important mental habits for us to develop – as investors and in general – is always to seek disconfirming evidence for our hypotheses. The more we like a hypothesis, the more important it is to look for disconfirming evidence.

Charlie Munger mentions Charles Darwin in “The Psychology of Human Misjudgment” (seePoor Charlie’s Alamanack: The Wit and Wisdom of Charles T. Munger, expanded 3rdedition):

One of the most successful users of an antidote to first conclusion bias was Charles Darwin. He trained himself, early, to intensively consider any evidence tending to disconfirm any hypothesis of his, more so if he thought his hypothesis was a particularly good one…He provides a great example of psychological insight correctly used to advance some of the finest mental work ever done.

Munger sums up the lesson thus:

Any year in which you don’t destroy a best-loved idea is probably a wasted year.

 

RECOGNIZING RISK

Marks:

Recognizing risk often starts with understanding when investors are paying it too little heed, being too optimistic and paying too much for an asset as a result. High risk, in other words, comes primarily from high prices. Whether it be an individual security or other asset that is overrated and thus overpriced, or an entire market that’s been borne aloft by bullish sentiment and thus is sky-high, participating when prices are high rather than shying away is the main source of risk. (page 58)

Marks interjects a comment:

Too-high prices come from investor psychology that’s too positive, and too-high investor sentiment often stems from a dearth of risk aversion. Risk-averse investors are conscious of the potential for loss and demand compensation for bearing it – in the form of reasonable prices. When investors aren’t sufficiently risk-averse, they’ll pay prices that are too high. (page 59)

Christopher Davis points out that there are more traffic fatalities among drivers and passengers of SUVs. Because drivers of SUVs feel safer, they drive riskier. Most of us, as investors, feel more confident and less worried when prices have been going up for an extended period. Since prices that are too high are the main source of investment risk, we have to learn how to overcome our psychological tendencies. Marks elucidates:

The risk-is-gone myth is one of the most dangerous sources of risk, and a major contributor to any bubble. At the extreme of the pendulum’s upswing, the belief that risk is low and that the investment in question is sure to produce profits intoxicates the herd and causes its members to forget caution, worry, and fear of loss, and instead to obsess about the risk of missing opportunity. (page 62)

Marks again:

Investment risk comes primarily from too-high prices, and too-high prices often come from excessive optimism and inadequate skepticism and risk aversion. Contributing underlying factors can include low prospective returns on safer investments, recent good performance by risky ones, strong inflows of capital, and easy availability of credit. The key lies in understanding what impact things like these are having. (page 63)

Investors generally overvalue what seems to have low risk, while undervaluing what seems to have high risk:

  • When everyone believes something is risky, their unwillingness to buy usually reduces its price to the point where it’s not risky at all. Broadly negative opinion can make it the least risky thing, since all optimism has been driven out of its price.
  • And, of course, as demonstrated by the experience of Nifty Fifty investors, when everyone believes something embodies no risk, they usually bid it up to the point where it’s enormously risky. No risk is feared, and thus no reward for risk-bearing – no ‘risk premium’ – is demanded or provided. That can make the thing that’s most esteemed the riskiest. (page 69)

The reason for this paradox, says Marks, is that most investors believe that quality, not price, determines whether an asset is risky. However, low quality assets can be safe if their prices are low enough, while high quality assets can be risky if their prices are too high. Chris Davis adds:

I agree – there are a number of dangers that come from using a term like ‘quality.’ First, investors tend to equate ‘high-quality asset’ with ‘high-quality investment.’ As a result, there’s an incorrect presumption or implication of less risk when taking on ‘quality’ assets. As Marks rightly points out, quite often ‘high-quality’ companies sell for high prices, making them poor investments. Second, ‘high-quality’ tends to be a phrase that incorporates a lot of hindsight bias or ‘halo effect.’ Usually, people referring to a ‘high-quality’ company are describing a company that has performed very well in the past. The future is often quite different. There is a long list of companies that were once described as ‘high quality’ or ‘built to last’ that are no longer around! For this reason, investors should avoid using the word ‘quality.’ (pages 69-70)

 

CONTROLLING RISK

Risk control is generally invisible during good times. But that doesn’t mean it isn’t desirable, says Marks. No one can consistently predict the timing of bull markets or bear markets. Therefore, risk control is always important, even during long bull markets. Marks:

Bearing risk unknowingly can be a huge mistake, but it’s what those who buy the securities that are all the rage and most highly esteemed at a particular point in time – to which ‘nothing bad can possibly happen’ – repeatedly do. On the other hand, intelligent acceptance of recognized risk for profit underlies some of the wisest, most profitable investments – even though (or perhaps due to the fact that) most investors dismiss them as dangerous speculations. (page 75)

Marks later writes:

Even if we realize that unusual, unlikely things can happen, in order to act we make reasoned decisions and knowingly accept that risk when well paid to do so. Once in a while, a ‘black swan’ will materialize. But if in the future we always said, ‘We can’t do such-and-such, because the outcome could be worse than we’ve ever seen before,’ we’d be frozen in inaction. (page 79)

You can’t avoid risk altogether as an investor or you’d get no return. Therefore, you have to take risks intelligently, when you’re well paid to do so. Marks concludes:

Over a full career, most investors’ results will be determined more by how many losers they have, and how bad they are, than by the greatness of their winners. (page 80)

Daniel Pecaut and Corey Wrenn, inThe University of Berkshire Hathaway,point out a central fact about how Buffett and Munger have achieved such a remarkable track record:

More than two-thirds of Berkshire’s performance over the S&P was earned during down years. This is the fruit of Buffett and Munger’s ‘Don’t lose’ philosophy. It’s the losing ideas avoided, as much as the money made in bull markets that has built Berkshire’s superior wealth over the long run.(page xxi)

Buffett has made the same point. His best ideas have not outperformed the best ideas of other great value investors. However, his worst ideas have not been as bad, and have lost less over time, as compared with the worst ideas of other top value investors.

See:https://boolefund.com/university-berkshire-hathaway/

 

BEING ATTENTIVE TO CYCLES

Marks explains how the credit cycle works when times are good:

  • The economy moves into a period of prosperity.
  • Providers of capital thrive, increasing their capital base.
  • Because bad news is scarce, the risks entailed in lending and investing seem to have shrunk.
  • Risk averseness disappears.
  • Financial institutions move to expand their businesses – that is, to provide more capital.
  • They compete for market share by lowering demanded returns (e.g., cutting interest rates), lowering credit standards, providing more capital for a given transaction and easing covenants. (page 83)

This is a cyclical process. Overconfidence based on recent history leads to the disappearance of risk aversion. Providers of capital make bad loans. This causes the cycle to reverse:

  • Losses cause lenders to become discouraged and shy away.
  • Risk averseness rises, and along with it, interest rates, credit restrictions and covenant requirements.
  • Less capital is made available – and at the trough of the cycle, only to the most qualified of borrowers, if anyone.
  • Companies become starved for capital. Borrowers are unable to roll over their debts, leading to defaults and bankruptcies.
  • This process contributes to and reinforces the economic contraction. (page 84)

People and financial institutions become overly pessimistic based on recent history, which leads to excessive risk aversion. Many solid loans are not made. This causes the cycle to reverse again.

Marks, in agreement with Lakonishok, Shleifer, and Vishny (1994), explains why value investing can continue to work:

Investors will overvalue companies when they’re doing well and undervalue them when things get difficult. (page 86)

Marks:

When things are going well, extrapolation introduces great risk. Whether it’s company profitability, capital availability, price gains, or market liquidity, things that inevitably are bound to regress toward the mean are often counted on to improve forever. (page 87)

It’s important to point out that there can be structural changes in the economy and the stock market. For instance, interest rates may stay relatively low for a long time, in which case stocks may even be cheap today (with the S&P 500 Index over 2400).

Also, profit margins may be structurally higher:

  • There is a good Barron’s interview of Bruce Greenwald, “Channeling Graham and Dodd”. Professor Greenwald indicated that Apple, Alphabet, Microsoft, Amazon, and Facebook – the five largest U.S. companies – have far higher normalized profit margins and ROE, as a group, than most large U.S. companies in history.
  • In brief, software and related technologies are becoming much more important in the global economy. This is another key reason why U.S. stocks may not be overvalued, and may even be cheap. See: http://www.barrons.com/articles/bruce-greenwald-channeling-graham-and-dodd-1494649404

 

COMBATING NEGATIVE INFLUENCES

Marks discusses the importance of psychology:

The desire for more, the fear of missing out, the tendency to compare against others, the influence of the crowd and the dream of a sure thing – these factors are near universal. Thus they have a profound collective impact on most investors and most markets. The result is mistakes, and those mistakes are frequent, widespread, and recurring. (page 97)

Marks observes that the biggest mistakes in investing are not analytical or informational, but psychological. At the extremes, people get too greedy or too fearful:

Greed is an extremely powerful force. It’s strong enough to overcome common sense, risk aversion, prudence, caution, logic, memory of painful past lessons, resolve, trepidation, and all the other elements that might otherwise keep investors out of trouble. Instead, from time to time greed drives investors to throw in their lot with the crowd in pursuit of profit, and eventually they pay the price.

The counterpart of greed is fear – the second psychological factor we must consider. In the investment world, the term doesn’t mean logical, sensible risk aversion. Rather fear – like greed – connotes excess. Fear, then, is more like panic. Fear is overdone concern that prevents investors from taking constructive action when they should. (page 99)

The third factor Marks mentions is the willing suspension of disbelief. We are all prone to overconfidence, and in general, we think we’re better than we actually are. Charlie Munger quotes Demosthenes:

Nothing is easier than self-deceit. For what each man wishes, that he also believes to be true.

Or as the physicist Richard Feynman put it:

The first principle is that you must not fool yourself, and you are the easiest person to fool.

Marks later quotes Warren Buffett’s remark to Congress on June 2, 2010:

Rising prices are a narcotic that affects the reasoning power up and down the line.

The fourth psychological tendency is conformity with the crowd. Swarthmore’s Solomon Asch conducted a famous experiment in the 1950’s. The subject is shown two lines of obviously different lengths. There are a few other people – shills – pretending to be subjects.

All the participants are asked if the lines are the same length. (In fact, they obviously aren’t.) The shills all say yes. In a high percentage of the cases, the actual subject of the experiment disregards the obvious evidence of his own eyes and conforms to the view of the crowd.

So it is with the consensus view of the market. Most people simply go along with the view of the crowd. That’s not to say the crowd is necessarily wrong. Often the crowd is right when it comes to the stock market. But occasionally the crowd is very wrong about specific stocks, or even about the market itself.

The fifth psychological influence Marks notes is envy. As Buffett remarked, “It’s not greed that drives the world, but envy.” Munger has observed that envy is particularly stupid because there’s no upside. Buffett agrees, joking: “Gluttony is a lot of fun. Lust has its place, too, but we won’t get into that.” Marks:

People who might be perfectly happy with their lot in isolation become miserable when they see others do better. In the world of investing, most people find it terribly hard to sit by and watch while others make more money than they do. (page 102)

The sixth psychological influence is ego. Investment results are compared. In good times, aggressive and imprudent decisions often lead to the best results. And the best results bring the greatest ego rewards, observes Marks.

Finally, Marks highlights the phenomenon of capitulation. Consider the tech bubble in the late 90’s:

…The guy sitting next to you in the office tells you about an IPO he’s buying. You ask what the company does. He says he doesn’t know, but his broker told him it’s going to double on its day of issue. So you say that’s ridiculous. A week later he tells you it didn’t double… it tripled. And he still doesn’t know what it does. After a few more of these, it gets hard to resist. You know it doesn’t make sense, but you want protection against continuing to feel like an idiot. So, in a prime example of capitulation, you put in for a few hundred shares of the next IPO… and the bonfire grows still higher on the buying from converts like you. (page 106)

Technological innovation drives economic progress. But that doesn’t mean every innovative company is a good investment. Joel Greenblatt comments:

Buffett’s famous line about the economics of airlines comes to mind. Aviation is a huge and valuable innovation. That’s not the same thing as saying it’s a good business. (page 108)

 

CONTRARIANISM

Sir John Templeton:

To buy when others are despondently selling and to sell when others are euphorically buying takes the greatest courage, but provides the greatest profit.

Most investors are basically trend followers, writes Marks. This works as long as the trend continues.

Marks quotes David Swensen’s Pioneering Portfolio Management (2000):

Investment success requires sticking with positions made uncomfortable by their variance with popular opinion. Casual commitments invite casual reversal, exposing portfolio managers to the damaging whipsaw of buying high and selling low. Only with the confidence created by a strong decision-making process can investors sell speculative excess and buy despair-driven value.

…Active management strategies demand uninstitutional behavior from institutions, creating a paradox that few can unravel. Establishing and maintaining an unconventional investment profile requires acceptance of uncomfortably idiosyncratic portfolios, which frequently appear downright imprudent in the eyes of conventional wisdom. (page 115)

Marks sums it up:

The ultimately most profitable investment actions are by definition contrarian: you’re buying when everyone else is selling (and thus the price is low) or you’re selling when everyone else is buying (and thus the price is high). (page 116)

Marks concludes:

The one thing I’m sure of is that by the time the knife has stopped falling, the dust has settled and the uncertainty has been resolved, there’ll be no great bargains left. When buying something has become comfortable again, its price will no longer be so low that it’s a great bargain.

Thus, a hugely profitable investment that doesn’t begin with discomfort is usually an oxymoron.

It’s our job as contrarians to catch falling knives, hopefully with care and skill. That’s why the concept of intrinsic value is so important. If we hold a view of value that enables us to buy when everyone else is selling – and if our view turns out to be right – that’s the route to the greatest rewards earned with the least risk. (page 121)

It’s important to emphasize again what can happen when certain assets become widely ignored or despised: The lower the price goes below probable intrinsic value, the lower the risk and the higher the reward. For value investors, some of the highest-returning investments can simultaneously have the lowest risk. Modern finance theory regards this situation as impossible. According to modern finance, higher rewardsalways require higher risk.

 

FINDING BARGAINS

Marks repeats an important concept:

Our goal isn’t to find good assets, but good buys. Thus, it’s not what you buy; it’s what you pay for it.

A high-quality asset can constitute a good or bad buy, and a low-quality asset can constitute a good or bad buy. The tendency to mistake objective merit for investment opportunity, and the failure to distinguish between good assets and good buys, get most investors into trouble. (pages 124-125)

What creates bargains? Marks answers:

  • Unlike assets that become the subject of manias, potential bargains usually display some objective defect. An asset class may have weaknesses, a company may be a laggard in its industry, a balance sheet may be over-levered, or a security may afford its holders inadequate structural protection.
  • Since the efficient-market process of setting fair prices requires the involvement of people who are analytical and objective, bargains usually are based on irrationality or incomplete understanding. Thus, bargains are often created when investors either fail to consider an asset fairly, or fail to look beneath the surface to understand it thoroughly, or fail to overcome some non-value-based tradition, bias or stricture.
  • Unlike market darlings, the orphan asset is ignored or scorned. To the extent it’s mentioned at all by the media and at cocktail parties, it’s in unflattering terms.
  • Usually its price has been falling, making the first-level thinker ask, ‘Who would want to own that?’ (It bears repeating that most investors extrapolate past performance, expecting the continuation of trends rather than the far-more-dependable regression to the mean. First-level thinkers tend to view past price weakness as worrisome, not as a sign that the asset has gotten cheaper.)
  • As a result, a bargain asset tends to be one that’s highly unpopular. Capital stays away from it or flees, and no one can think of a reason to own it. (pages 125-126)

Marks continues by explaining that to find an undervalued asset, a good place to start looking is among things that are:

  • little known and not fully understood;
  • fundamentally questionable on the surface;
  • controversial, unseemly or scary;
  • deemed inappropriate for ‘respectable’ portfolios;
  • unappreciated, unpopular and unloved;
  • trailing a record of poor returns; and
  • recently the subject of disinvestment, not accumulation. (pages 127-128)

In brief:

To boil it all down to just one sentence, I’d say the necessary condition for the existence of bargains is that perception has to be considerably worse than reality. That means the best opportunities are usually found among things most others won’t do. (page 128)

Seth Klarman:

Generally, the greater the stigma or revulsion, the better the bargain.

 

PATIENT OPPORTUNISM

Buffett has always stressed that, over time, you should compare the results of what you do as an investor to what would have happened had you done absolutely nothing. Often the best thing to do as a long-term value investor is absolutely nothing.

Buffett has also observed that investing is like baseball except that in investing, there are no called strikes. You can wait for as long as it takes until a fat pitch appears. Absent a fat pitch, there’s no reason to swing. Buffett mentioned in Berkshire Hathaway’s 1997 Letter to Shareholders that Ted Williams, one of the greatest hitters ever, studied his hits and misses carefully. Williams broke the strike zone into 77 baseball-sized ‘cells’ and analyzed his results accordingly. Buffett explained:

Swinging only at balls in his ‘best’ cell, he knew, would allow him to bat .400; reaching for balls in his ‘worst’ spot, the low outside corner of the strike zone, would reduce him to .230. In other words, waiting for the fat pitch would mean a trip to the Hall of Fame; swinging indiscriminately would mean a ticket to the minors.

See:http://berkshirehathaway.com/letters/1997.html

 

KNOWING WHAT YOU DON’T KNOW

John Kenneth Galbraith:

There are two classes of forecasters: Those who don’t know – and those who don’t know they don’t know.

Marks studied forecasts. Some forecasters always extrapolate the recent past. But that’s not useful. Outside of that, there are virtually no forecasters who are both non-consensus and regularly correct. Marks writes:

One way to get to be right sometimes is to always be bullish or always be bearish; if you hold a fixed view long enough, you may be right sooner or later. And if you’re always an outlier, you’re likely to eventually be applauded for an extremely unconventional forecast that correctly foresaw what no one else did. But that doesn’t mean your forecasts are regularly of any value…

It’s possible to be right about the macro-future once in a while, but not on a regular basis. It doesn’t do any good to possess a survey of sixty-four forecasts that includes a few that are accurate; you have to know which ones they are. And if the accurate forecasts each six months are made by different economists, it’s hard to believe there’s much value in the collective forecasts. (page 145)

Marks restates the case in the following points:

  • Most of the time, people predict a future that is a lot like the recent past.
  • They’re not necessarily wrong: most of the time, the future largely is a rerun of the recent past.
  • On the basis of these two points, it’s possible to conclude that forecasts will prove accurate much of the time: They’ll usually extrapolate recent experience and be right.
  • However, the many forecasts that correctly extrapolate past experience are of little value. Just as forecasters usually assume a future that’s a lot like the past, so do markets, which usually price in a continuation of recent history. Thus if the future turns out to be like the past, it’s unlikely big money will be made, even by those who foresaw correctly that it would.
  • Once in a while, however, the future turns out to be very different from the past.
  • It’s at these times that accurate forecasts would be of great value.
  • It’s also at these times that forecasts are least likely to be correct.
  • Some forecasters may turn out to be correct at these pivotal moments, suggesting that it’s possible to correctly forecast key events, but it’s unlikely to be the same people consistently.
  • The sum of this discussion suggests that, on balance, forecasts are of very little value. (pages 145-146)

As an example, Marks asks who correctly predicted the credit crisis and bear market of 2007-2008. Of those who correctly predicted it, how many of them also correctly predicted the recovery and massive bull market starting in 2009? Very, very few. Marks:

…Those who got 2007-2008 right probably did so at least in part because of a tendency toward negative views. As such, they probably stayed negative for 2009. The overall usefulness of those forecasts wasn’t great… even though they were partially right about some of the most momentous financial events in the last eighty years.

So the key question isn’t ‘are forecasts sometimes right?’ but rather ‘are forecasts as a whole – or any one person’s forecasts – consistently actionable and valuable?’ No one should bet much on the answer being affirmative.

Marks then notes that you could have found some people predicting a bear market before 2007-2008. But if these folks had a negative bias, as well as a track record full of incorrect predictions, then you wouldn’t have had much reason to listen. Or as Buffett put it in the Berkshire Hathaway 2016 Letter to Shareholders:

American business – and consequently a basket of stocks – is virtually certain to be worth far more in the years ahead. Innovation, productivity gains, entrepreneurial spirit and an abundance of capital will see to that. Ever-present naysayers may prosper by marketing their gloomy forecasts. But heaven help them if they act on thenonsense they peddle. (page 6)

See:http://berkshirehathaway.com/letters/2016ltr.pdf

Marks has a description for investors who believe in the value of forecasts. They belong to the “I know” school, and it’s easy to identify them:

  • They think knowledge of the future direction of economies, interest rates, markets and widely followed mainstream stocks is essential for investment success.
  • They’re confident it can be achieved.
  • They know they can do it.
  • They’re aware that lots of other people are trying to do it too, but they figure either (a) everyone can be successful at the same time, or (b) only a few can be, but they’re among them.
  • They’re comfortable investing based on their opinions regarding the future.
  • They’re also glad to share their views with others, even though correct forecasts should be of such great value that no one would give them away gratis.
  • They rarely look back to rigorously assess their record as forecasters. (page 147)

Marks contrasts theconfident“I know” folks with theguarded“I don’t know” folks. The latter believe you can’t predict the macro-future, and thus the proper goal for investing is to do the best possible job analyzing individual securities. If you belong to the “I don’t know” school, eventually everyone will stop asking you where you think the market’s going.

You’ll never get to enjoy that one-in-a-thousand moment when your forecast comes true and theWall Street Journalruns your picture. On the other hand, you’ll be spared all those times when forecasts miss the mark, as well as the losses that can result from investing based on overrated knowledge of the future. (page 148)

Marks continues by noting that no one likes investing on the assumption that the future is unknowable. But if the futureISlargely unknowable, then it’s far better as an investor to acknowledge that fact than to pretend otherwise.

Furthermore, says Marks, the biggest problems for investors tend to happen when investors forget the difference between probability and outcome (i.e., the limits of foreknowledge):

  • when they believe the shape of the probability distribution is knowable with certainty (and that they know it),
  • when they assume the most likely outcome is the one that will happen,
  • when they assume the expected result accurately represents the actual result, or
  • perhaps most important, when they ignore the possibility of improbable outcomes. (pages 148-149)

Marks sums it up:

Overestimating what you’re capable of knowing or doing can be extremely dangerous – in brain surgery, transocean racing or investing. Acknowledging the boundaries of what you can know – and working within those limits rather than venturing beyond – can give you a great advantage. (page 150)

 

APPRECIATING THE ROLE OF LUCK

Professor Paul Johnson explains the main point:

Learn to be honest with yourself about your successes and failures [as an investor]. Learn to recognize the role luck has played in all outcomes. Learn to decide which outcomes came because of skill and which because of luck. Until one learns to identify the true source of success, one will be fooled by randomness. (page 161)

Once again, we consider Nassim Taleb’s concept of “alternative histories.” Marks quotes Taleb:

Clearly my way of judging matters is probabilistic in nature; it relies on the notion of what could have probably happened…

If we have heard of [history’s great generals and inventors], it is simply because they took considerable risks, along with thousands of others, and happened to win. They were intelligent, courageous, noble (at times), had the highest possible obtainable culture in their day – but so did thousands of others who live in the musty footnotes of history. (pages 162-163)

In investing, you probably need many decades of results before you can determine how much is due to skill. And here we’re talking mainly about long-term value investing, where stocks are held for at least a year on average.

Similarly, to judge individual investment decisions, you have to know much more than whether a specific decision worked or not. You have to understand the process by which the investor made the decision. You have to know which facts were available and which were used in the decision. You have to estimate the probability of success of the investment decision, whether or not it actually worked. This means you have to account for all the possible scenarios that could have unfolded, not just the one scenario that did unfold.

Marks gives the example of backgammon. A certain aggressive player may need to roll double sixes in order to win. The probability of that happening is one out of thirty-six. Say the player accepts the cube – doubling the stakes – and gets his boxcars. Many will consider the player brilliant. But was it a wise bet?

You could find similar situations in other games of chance, such as bridge or poker. There are many situations in which you can calculate the probabilities of various scenarios. So you can figure out if the player is making the most profitable decision, averaged out over time. Some percentage of the time the decision will work. Some percentage of the time it won’t. A skillful player will consistently make the the most profitable long-term decision.

Value investing is similar. Good value investors are right 60% of the time and wrong 40% of the time. If their process for selecting cheap stocks is solid, then risks and losses will be minimized while gains are simultaneously maximized.

Marks writes:

The actions of the ‘I know’ school are based on a view of a single future that is knowable and conquerable. My ‘I don’t know’ school thinks of future events in terms of a probability distribution. That’s a big difference. In the latter case, we may have an idea which outcome is most likely to occur, but we also know there are many other possibilities, and those other outcomes may have a collective likelihood much higher than the one we consider most likely. (page 168)

As Buffett advised, we have to focus on what’s knowable and important. That means focusing on individual companies and industries within our circle of competence. Many companies may be beyond our ability to value. They go in the “too hard” pile. Focus on those companies we can understand and value.

 

INVESTING DEFENSIVELY

As in some sports, in investing you have to decide if you want to emphasize offense, emphasize defense, or use a balanced approach. Marks:

…investors should commit to an approach – hopefully one that will serve them through a variety of scenarios. They can be aggressive, hoping they’ll make a lot on the winners and not give it back on the losers. They can emphasize defense, hoping to keep up in good times and excel by losing less than others in bad times. Or they can balance offense and defense, largely giving up on tactical timing but aiming to win through superior security selection in both up and down markets. (page 174)

The vast majority of investors should invest in quantitative value funds or in low-cost broad market index funds. Most of us will probably maximize our multi-decade results using one or both of these approaches. Buffett:https://boolefund.com/warren-buffett-jack-bogle/

Regarding the balance of offense versus defense, Marks observes:

And, by the way, there’s no right choice between offense and defense. Lots of possible routes can bring you to success, and your decision should be a function of your personality and leanings, the extent of your belief in your ability, and the peculiarities of the markets you work in and the clients you work for. (page 175)

Marks believes that a focus on avoiding losses will lead more dependably to consistently good returns over time. As we noted earlier, Buffett has said that his best ideas have not outperformed the best ideas of other value investors; but his worst ideas have not done as poorly as the worst ideas of other value investors. So minimizing losses – especially avoiding big losses – has been central to Buffett becoming arguably the best value investor of all time.

 

REASONABLE EXPECTATIONS

Setting reasonable expectations can play a pivotal role in designing and applying your investment strategy. Marks points out that you can’t simply think about high returns without also considering risk. In investing, if you aim too high, you’ll end up taking too much risk.

Similarly, when buying assets that are declining in price, you should have a reasonable strategy. Marks:

I try to look at it logically. There are three times to buy an asset that has been declining: on the way down, at the bottom, or on the way up. I don’t believe we ever know when the bottom has been reached, and even if we did, there might not be much for sale there.

If we wait until the bottom has passed and the price has started to rise, the rising price often causes others to buy, just as it emboldens holders and encourages them from selling. Supply dries up and it becomes hard to buy in size. The would-be buyer finds it’s too late.

That leaves buying on the way down, which we should be glad to do. The good news is that if we buy while the price is collapsing, that fact alone often causes others to hide behind the excuse that ‘it’s not our job to catch falling knives.’ After all, it’s when knives are falling that the greatest bargains are available.

There’s an important saying attributed to Voltaire: ‘The perfect is the enemy of the good.’ This is especially applicable to investing, where insisting on participating only when conditions are perfect – for example, buying only at the bottom – can cause you to miss out on a lot. Perfection in investing is generally unobtainable; the best we can hope for is to make a lot of good investments and exclude most of the bad ones. (page 212)

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time. See the historical chart here:https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps. Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals. We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio. The size of each position is determined by its rank. Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost). Positions are held for 3 to 5 years unless a stock approachesintrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods. We also aim to outpace the Russell Microcap Index by at least 2% per year (net). The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed.No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Notes on Value Investing

February 6, 2022

Today we review some of the central concepts in value investing.  In order to learn, some repetition is required, especially when the subject may be difficult or counter-intuitive for many.

Here’s the outline:

  • Index Funds or Quant Value Funds
  • The Dangers of DCF
  • Notes on Ben Graham
  • Value vs. Growth
  • The Superinvestors of Graham-and-Doddsville

 

INDEX FUNDS OR QUANT VALUE FUNDS

The first important point is that the vast majority of investors are best off buying and holding a broad market, low-cost index fund.  Warren Buffett has repeatedly made this observation.  See: https://boolefund.com/warren-buffett-jack-bogle/

In other words, most of us who believe that we can outperform the market over the long term (decades) are wrong.  The statistics on this point are clear.  For instance, see pages 21-25 of Buffett’s 2016 Berkshire Hathaway Shareholder Letter: http://berkshirehathaway.com/letters/2016ltr.pdf

A quantitative value investment strategy””especially if focused on micro caps””is likely to do better than an index fund over time.  If you understand why this is the case, then you could adopt such an approach, at least for part of your portfolio.  (The Boole Microcap Fund is a quantitative value fund.)  But you have to be able to stick with it over the long term even though there will sometimes be multi-year periods of underperforming the market.  Easier said than done.  Know Thyself.

We all like to think we know ourselves.  But in many ways we know ourselves much less than we believe we do.  This is especially true when it comes to probabilistic decisions or complex computations.  In these areas, we suffer from cognitive biases which generally cause us to make suboptimal or erroneous choices.  See: https://boolefund.com/cognitive-biases/

The reason value investing””if properly implemented””works over time is due to the behavioral errors of many investors.  Lakonishok, Shleifer, and Vishny give a good explanation of this in their 1994 paper, “Contrarian Investment, Extrapolation, and Risk.”  Link: http://scholar.harvard.edu/files/shleifer/files/contrarianinvestment.pdf

Lakonishok, Shleifer, and Vishny (LSV) offer three reasons why investors follow “naive” strategies:

  • Investors often extrapolate high past earnings growth too far into the future.  Similarly, investors extrapolate low past earnings growth too far into the future.
  • Investors overreact to good news and to bad news.
  • Investors think a well-run company is automatically a good investment.

LSV then state that, for whatever reason, investors overvalue stocks that have done well in the past, causing these “glamour” or “growth” stocks to be overpriced in general.  Similarly, investors undervalue stocks that have done poorly in the past, causing these “value” stocks to be underpriced in general.

Important Note:  Cognitive biases””such as overconfidence, confirmation bias, and hindsight bias””are the main reason why investors extrapolate past trends too far into the future.  For simple and clear descriptions of cognitive biases, see: https://boolefund.com/cognitive-biases/

 

THE DANGERS OF DCF

For most businesses, it’s very difficult””and often impossible””to predict future earnings and free cash flows.  One reason Warren Buffett and Charlie Munger have produced such an outstanding record at Berkshire Hathaway is because they focus on businesses that are highly predictable.  These types of businesses usually have a sustainable competitive advantage, which is what makes their future earnings and cash flows more certain.  As Buffett put it:

The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage.

Most businesses do not have a sustainable competitive advantage, and thus are not predictable 5 or 10 years into the future.

Buffett calls a sustainable competitive advantage a moat, which defends the economic “castle.”  Here’s how he described it at the Berkshire Hathaway Shareholder Meeting in 2000:

So we think in terms of that moat and the ability to keep its width and its impossibility of being crossed as the primary criterion of a great business.  And we tell our managers we want the moat widened every year.  That doesn’t necessarily mean the profit will be more this year than it was last year because it won’t be sometimes.  However, if the moat is widened every year, the business will do very well.  When we see a moat that’s tenuous in any way – it’s just too risky.  We don’t know how to evaluate that.  And, therefore, we leave it alone.  We think that all of our businesses – or virtually all of our businesses – have pretty darned good moats.

There’s a great book, The Art of Value Investing (Wiley, 2013), by John Heins and Whitney Tilson, which is filled with quotes from top value investors.  Here’s a quote from Bill Ackman, which shows that he strives to invest like Buffett and Munger:

We like simple, predictable, free-cash-flow generative, resilient and sustainable businesses with strong profit-growth opportunities and/or scarcity value.  The type of business Warren Buffett would say has a moat around it.  (page 131)

If the future earnings and cash flows of a business are not predictable, then DCF valuation may not be very reliable.  Moreover, it’s often hard to calculate the cost of capital (the discount rate).

  • DCF refers to “discounted cash flows.”  You can value any business if you can estimate future free cash flow with reasonable accuracy.  To get the present value of the business, the free cash flow in each future year must be discounted back to the present by the cost of capital.

To determine the cost of capital, Buffett and Munger use the opportunity cost of capital, which is the next best investment with a similar level of risk.

  • To illustrate, say they’re considering an investment in Company A, which they feel quite certain will return 15% per year.  To figure out the value of this potential investment, they will find their next best investment – which they may already own – that has a similar level of risk.  Perhaps they own Company N and they feel equally certain that its future returns will be 17% per year.  In that case, if possible, they would prefer to buy more of Company N rather than buying any of Company A.  (Often there are other considerations.  But that’s the gist of it.)

The academic definition of cost of capital includes “beta,” which measures how volatile a stock price has been in the past.  But for value investors like Buffett and Munger, all that matters is how much free cash flow the business will produce in the future.  The degree of volatility of a stock in the past generally has no logical relationship with the next 20-30 years of cash flows.

If a business lacks a true moat and if, therefore, DCF probably won’t work, is there any other way to evaluate a business?  James Montier, in Value Investing (Wiley, 2009), mentions three alternatives to DCF that do not require forecasting:

  • Reverse-engineered DCF
  • Asset Value
  • Earnings Power

In a reverse-engineered DCF, instead of forecasting future growth, you take the current share price and figure out what that implies about future growth.  Then you compare the implied future growth of the business against some reasonable benchmark, like growth of a close competitor.  (You still have to determine a cost of capital.)

As for asset value and earnings power, these were the two methods of valuation suggested by Ben Graham.  For asset value, Graham often suggested using liquidation value, which is usually a conservative estimate of asset value.  If the business could be sold as a going concern, then the assets would probably have a higher value than liquidation value.

Regarding earnings power, Montier quotes Graham from Security Analysis:

What the investor chiefly wants to learn… is the indicated earnings power under the given set of conditions, i.e., what the company might be expected to earn year after year if the business conditions prevailing during the period were to continue unchanged.

Montier again quotes Graham:

It combines a statement of actual earnings, shown over a period of years, with a reasonable expectation that these will be approximated in the future, unless extraordinary conditions supervene.  The record must be over a number of years, first because a continued or repeated performance is always more impressive than a single occurrence, and secondly because the average of a fairly long period will tend to absorb and equalize the distorting influences of the business cycle.

Montier mentions Bruce Greenwald’s excellent book, Value Investing: From Graham to Buffett and Beyond (Wiley, 2004), for a modern take on asset value and earnings power.

 

NOTES ON BEN GRAHAM

When studying Graham’s methods as presented in Security Analysis””first published in 1934″”it’s important to bear in mind that Graham invented value investing during the Great Depression.  Therefore, some of Graham’s methods are arguably overly conservative.  Particularly if you think the Great Depression was caused in part by mistakes in fiscal and monetary policy that are unlikely to be repeated.  Charlie Munger put it as follows:

I don’t love Ben Graham and his ideas the way Warren does.  You have to understand, to Warren””who discovered him at such a young age and then went to work for him””Ben Graham’s insights changed his whole life, and he spent much of his early years worshiping the master at close range.

But I have to say, Ben Graham had a lot to learn as an investor.  His ideas of how to value companies were all shaped by how the Great Crash and the Depression almost destroyed him, and he was always a little afraid of what the market can do.  It left him with an aftermath of fear for the rest of his life, and all his methods were designed to keep that at bay.

That being said, Warren Buffett has always maintained that Chapters 8 and 20 of Ben Graham’s The Intelligent Investor””first published in 1949″”contain the three fundamental precepts of value investing:

  • Owning stock is part ownership of the underlying business.
  • Market prices are there to serve you, not to instruct you.  When prices drop a great deal, it may be a good opportunity to buy.  When prices rise quite a bit, it may be a good time to sell.  At all other times, it’s best to focus on the operating results of the businesses you own.
  • The margin of safety is the difference between the price you pay and your estimate of the intrinsic value of the business.  Price is what you pay;  value is what you get.  If you think the business is worth $40 per share, then you would like to pay $20 per share.  (Value investors refer to a stock that’s selling for half its intrinsic value as a “50-cent dollar.”)

The purpose of the margin of safety is to minimize the effects of bad luck, human error, and the vagaries of the future.  Good value investors are right about 60% of the time and wrong 40% of the time.  By systematically minimizing the impact of inevitable mistakes and bad luck, a solid value investing strategy will beat the market over time.  Why?

Here’s why:  As you increase your margin of safety, you simultaneously increase your potential return.  The lower the risk, the higher the potential return.  When you’re wrong, you lose less on average.  When you’re right, you make more on average.

For instance, assume again that you estimate the intrinsic value of the business at $40 per share.

  • If you can pay $20 per share, then you have a good margin of safety.  And if you are right about intrinsic value, then you will make 100% on your investment when the price eventually moves from $20 to $40.
  • What if you managed to pay $10 per share for the same stock?  Then you have an even larger margin of safety relative to the estimated intrinsic value of $40.  As well, if you’re right about intrinsic value, then you will make 300% on your investment when the price eventually moves from $10 to $40.

The notion that you can increase your safety and your potential returns at the same time runs directly contrary to what is commonly taught in modern finance.  In modern finance, you can only increase your potential return by increasing your risk.

A final point about Buffett and Munger’s evolution as investors.  Munger realized early in his career that it was better to buy a high-quality business at a reasonable price, rather than a low-quality business at a cheap price.  Buffett also realized this””partly through Munger’s influence””after experiencing a few failed investments in bad businesses purchased at cheap prices.  Ever since, Buffett and Munger have expressed the lesson as follows:

It’s better to buy a wonderful company at a fair price than a fair company at a wonderful price.

The idea is to pay a reasonable price for a company with a high ROE (return on equity) that can be sustained””due to a moat.  If you hold a high-quality business like this, then over time your returns as an investor will approximate the ROE.  High-quality businesses can have sustainably high ROE’s that range from 20% to over 100%.

Note:  Buffett and Munger also insist that the companies they invest in have low debt (or no debt).  Even a great business can fail if it has too much debt.

 

VALUE vs. GROWTH

One of the seminal academic papers on value investing””which was mentioned earlier””is Lakonishok, Shleifer, and Vishny (1994), “Contrarian Investment, Extrapolation, and Risk.”  Link: http://scholar.harvard.edu/files/shleifer/files/contrarianinvestment.pdf

Lakonishok, Shleifer, and Vishny (LSV) show that value investing””buying stocks at low multiples (P/B, P/CF, and P/E)””outperformed glamour (growth) investing by about 10-11% per year from 1968 to 1989.

Here’s why, say LSV:  Investors expect the poor recent performance of value stocks to continue, causing these stocks to trade at lower multiples than is justified by subsequent performance.  And investors expect the recent good performance of glamour stocks to continue, causing these stocks to trade at higher multiples than is justified by subsequent performance.

Interestingly, La Porta (1993 paper) shows that contrarian value investing based directly on analysts’ forecasts of future growth can produce even larger excess returns than value investing based on low multiples.  In other words, betting on the stocks for which analysts have the lowest expectations can outperform the market by an even larger margin.

Moreover, LSV demonstrate that value investing is not riskier.  First, excess returns from value investing cannot be explained by excess volatility.  Furthermore, LSV show that value investing does not underperform during market declines or recessions.  If anything, value investing outperforms during down markets, which makes sense because value investing involves paying prices that are, on average, far below intrinsic value.

In conclusion, LSV ask why countless investors continue to buy glamour stocks and to ignore value stocks.  One chief reason is that buying glamour stocks””generally stocks that have been doing well””may seem “prudent” to many professional investors.  After all, glamour stocks are unlikely to become financially distressed in the near future, whereas value stocks are often already in distress.

In reality, a basket of glamour stocks is not prudent because it will far underperform a basket of value stocks over a sufficiently long period of time.  However, if professional investors choose a basket of value stocks, then they will not only own many stocks experiencing financial distress, but they also risk underperforming for several years in a row.  These are potential career risks that most professional investors would rather avoid.  From that point of view, it may indeed be “prudent” to stick with glamour stocks, despite the lower long-term performance of glamour compared to value.

  • An individual value stock is likely to be more distressed””and thus riskier””than either a glamour stock or an average stock.  But LSV have shown that value stocks, as a group, far outperform both glamour stocks and the market in general, and do so with less risk.  This finding that value stocks, as a group, outperform has been confirmed by many academic studies, including Fama and French (1992).
  • If you follow a quantitative value strategy focused on micro caps, one of the best ways to improve long-term performance is by using the Piotroski F_Score.  It’s a simple measure that strengthens a micro-cap value portfolio by reducing the number of “cheap but weak” companies and increasing the number of “cheap and strong” companies.  See: https://boolefund.com/joseph-piotroski-value-investing/

 

THE SUPERINVESTORS OF GRAHAM-AND-DODDSVILLE

Buffett gave a talk at Columbia Business School in 1984 entitled, “The Superinvestors of Graham-and-Doddsville.”  Link: http://www8.gsb.columbia.edu/rtfiles/cbs/hermes/Buffett1984.pdf

According to the EMH (Efficient Markets Hypothesis), investors who beat the market year after year are just lucky.  In his talk, Buffett argues as follows:  fifteen years before 1984, he knew a group of people who had learned the value investing approach from Ben Graham and David Dodd.  Now in 1984, fifteen years later, all of these individuals have produced investment track records far in excess of the S&P 500 Index.  Moreover, each of these investors applied the value investing approach in his own way””there was very little overlap in terms of which companies these investors bought.  Buffett simply asks whether this could be due to pure chance.

As a way to think about the issue, Buffett says to imagine a national coin-flipping contest in which all 225 million Americans (the population in 1984) participate.  It is one dollar per flip on the first day, so roughly half the people lose and pay one dollar to the other half who won.  Each day the contest is repeated, but the stakes build up based on all previous winnings.  After 10 straight mornings of this contest, there will be about 220,000 flippers left, each with a bit over $1,000.  Buffett jokes:

Now this group will probably start getting a little puffed up about this, human nature being what it is.  They may try to be modest, but at cocktail parties they will occasionally admit to attractive members of the opposite sex what their technique is, and what marvelous insights they bring to the field of flipping.  (page 5)

In another 10 days, there will be about 215 people left who had correctly called the toss of a coin 20 times in a row.  Each would have a little over $1,000,000.  Buffett quips:

By then, this group will really lose their heads.  They will probably write books on ‘How I Turned a Dollar into a Million Working Thirty Seconds a Morning.’  Worse yet, they’ll probably start jetting around the country attending seminars on efficient coin-flipping and tackling skeptical professors with, ‘If it can’t be done, why are there 215 of us?’

But then some business school professor will probably be rude enough to bring up the fact that if 225 million orangutans had engaged in a similar exercise, the results would be much the same””215 egotistical orangutans with 20 straight winning flips.

But assume that the original 225 million orangutans were distributed roughly like the U.S. population.  Buffett then asks:  what if 40 of the 215 winning orangutans were discovered to all be from the same zoo in Omaha?  This would lead one to want to identify common factors for these 40 orangutans.  Buffett says (humorously) that you’d probably ask the zookeeper about their diets, what books they read, etc.  In short, you’d try to identify causal factors.

Buffett remarks that scientific inquiry naturally follows this pattern.  He gives another example:  If there was a rare type of cancer, with 1,500 cases a year in the United States, and 400 of these cases happened in a little mining town in Montana, you’d investigate the water supply there or other variables.  Buffett explains:

You know that it’s not random chance that 400 come from a small area.  You would not necessarily know the causal factors, but you would know where to search.  (page 6)

Buffett then draws the simple, logical conclusion:

I think you will find that a disproportionate number of successful coin-flippers in the investment world came from a very small intellectual village that could be called Graham-and-Doddsville.  A concentration of winners that simply cannot be explained by chance can be traced to this particular intellectual village.

Again, Buffett stresses that the only thing these successful investors had in common was adherence to the value investing philosophy.  Each investor applied the philosophy in his own way.  Some, like Walter Schloss, used a very diversified approach with over 100 stocks chosen purely on the basis of quantitative cheapness (low P/B).  Others, like Buffett or Munger, ran very concentrated portfolios and included stocks of companies with high ROE.  And looking at this group on the whole, there was very little overlap in terms of which stocks each value investor decided to put in his portfolio.

Buffett observes that all these successful value investors were focused only on one thing:  price vs. value.  Price is what you pay;  value is what you get.  There was no need to use any academic theories about covariance, beta, the EMH, etc.  Buffett comments that the combination of computing power and mathematical training is likely what led many academics to study the history of prices in great detail.  There have been many useful discoveries, but some things (like beta or the EMH) have been overdone.

Buffett goes through the nine different track records of the market-beating value investors.  Then he summarizes:

So these are nine records of ‘coin-flippers’ from Graham-and-Doddsville.  I haven’t selected them with hindsight from among thousands.  It’s not like I am reciting to you the names of a bunch of lottery winners””people I had never heard of before they won the lottery.  I selected these men years ago based upon their framework for investment decision-making”¦ It’s very important to understand that this group has assumed far less risk than average;  note their record in years when the general market was weak”¦.

Buffett concludes that, in his view, the market is far from being perfectly efficient:

I’m convinced that there is much inefficiency in the market.  These Graham-and-Doddsville investors have successfully exploited gaps between price and value.  When the price of a stock can be influenced by a ‘herd’ on Wall Street with prices set at the margin by the most emotional person, or the greediest person, or the most depressed person, it is hard to argue that the market always prices rationally.  In fact, market prices are frequently nonsensical.

Buffett also states that value investors view risk and reward in opposite terms to the way academics view risk and reward.  The academic view is that a higher potential reward always requires taking greater risk.  But (as discussed in above in “Notes on Ben Graham”) value investors, having made the distinction between price and value, hold that the lower the risk, the higher the potential reward.  Buffett:

If you buy a dollar bill for 60 cents, it’s riskier than if you buy a dollar bill for 40 cents, but the expectation of reward is greater in the latter case.  The greater the potential for reward in the value portfolio, the less risk there is.

Buffett offers an example:

The Washington Post Company in 1973 was selling for $80 million in the market.  At the time, that day, you could have sold the assets to any one of ten buyers for not less than $400 million, probably appreciably more”¦

Now, if the stock had declined even further to a price that made the valuation $40 million instead of $80 million, it’s beta would have been greater.  And to people who think beta [or, more importantly, downside volatility] measures risk, the cheaper price would have made it look riskier.  This is truly Alice in Wonderland.  I have never been able to figure out why it’s riskier to buy $400 million worth of properties for $40 million than $80 million”¦.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here: https://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.