Diligence and Green Lumber

The other day, I was discussing a private technology company with a friend that also works in venture capital. The company was about five years old and had recently grown its revenue 100 percent to about $20 million. 

We had both discussed an investment with the company in the past and had done research on it. So we debated the product, competition, market, CEO and his team, etc.

His conclusion was that the product wasn’t a good fit given the needs of the target customers and the alternatives available from large incumbents. 

I disagreed, partly for reasons that directly addressed those points but more for the fact that the growth spoke for itself. My explanation didn’t feel as rich, though.

Both of us have done deep, rigorous research when evaluating whether to invest in a company like that with the goal of answering precisely those questions. We speak with lots of people in the market—current customers, potential customers, product managers, sales people, industry analysts, etc. Everyone shares their opinion, and we get “smarter.” 

But it’s a noisy process. Some people, product managers at other companies, say, are “deep in the weeds” and can offer insights about product, performance, etc. Others, such as industry analysts, are “higher up” and can offer insights about trends and general perception of different firms.

So, the question I’m struggling with: To what extent does the story that emerges from that research actually matter?

The company in question is a disruption taking place on a small scale when the revenue is compared to the market. $10 million going to $20 million in a $2 billion market is a drop in the ocean so to say.

Yet, the narrative we create draws from various parts of that entire market. How much does it actually explain whether the company will go on to become a large, successful company, generating significant returns on the investment? 

After the discussion, I recalled a story from Nassim Nicholas Taleb’s book Antifragile, the lesson from which he calls “The Green Lumber Fallacy.” (Added bonus: the passage below captures Taleb’s signature style—direct, confrontational, and colorful.)

In one of the rare noncharlatanic books in finance, descriptively called What I Learned Losing a Million Dollars, the protagonist makes a big discovery. He remarks that a fellow named Joe Siegel, one of the most successful traders in a commodity called “green lumber,” actually thought that it was lumber painted green (rather than freshly cut lumber, called green because it had not been dried). And he made it his profession to trade the stuff! Meanwhile the narrator was into grand intellectual theories and narratives of what caused the price of commodities to move, and went bust.

It is not just that the successful expert on lumber was ignorant of central matters like the designation “green.” He also knew things about lumber that nonexperts think are unimportant. People we call ignorant might not be ignorant.

The fact is that predicting the order flow in lumber and the usual narrative had little do with the details one would assume from the outside are important. People who do things in the field are not subjected to a set exam; they are selected in the most non-narrative manner—nice arguments don’t make much difference. Evolution does not rely on narratives, humans do. Evolution does not need a word for the color blue.

So let us call the green lumber fallacy the situation in which one mistakes a source of necessary knowledge—the greenness of lumber—for another, less visible from the outside, less tractable, less narratable. 

One has to read Taleb with a grain of salt, recognizing the caricatures he presents for what they are. The passage doesn’t stick with me because it advocates not learning about an investment. For the record, I do believe investors should learn these details. They should know the market well before investing, in fact, and learn as much as they can while evaluating an investment. Those are necessary steps to the insight needed.

Rather, I take it to mean that those insights aren’t necessarily the important aspects of the decision and that, often, the things that are the most important feel less satisfying as narratives. In other words, just because something sounds significant doesn’t mean that it is the most significant factor in a decision. If something is unknowable, making it feel more knowable by wrapping it in a narrative that sounds plausible, doesn’t make it more predictable. 

If we think about the future of the company my friend and I were discussing it is very possible that his assessment of customer needs is correct and the company could still be a smashing success. 

It is very possible that the company has found a niche in a subset of the market, where its products satisfy those customers’ needs. That niche could be large enough to sustain a high growth rate. That high growth rate allows it to improve its marketing, raise capital at attractive rates, and improve its products. The products then become attractive to more customers, and the company through improved marketing gains credibility and “mind share” with buyers. It continues to grow. Eventually, it’s an established player and a process that was unusual begins to become an accepted process and it’s the market leader. Its revenue continues to grow, and it goes public at the premium multiple typical of high growth market leaders. The investors make a killing.

It’s not clear yet that the company we were discussing will end up that way. But it’s certainly on that path. And, more importantly, many, many enterprise software companies that did end up successful heard those same arguments early in their lives and many investors passed on investing because of those arguments. 

Being wrong

I learned today, thanks to Robert Krulwich at NPR, that our solar system isn’t very typical. 

Specifically, since we knew that in our solar system we had four rocky planets closer to the sun (Mercury, Venus, Earth, and Mars) and four gaseous planets further out (Jupiter, Saturn, Uranus, and Neptune), we came up with a theory to explain that observation.

The theory had a “frost line.” The planetary dust closer to the sun would melt into minerals and form rocky planets, and the dust further out stayed “dusty,” forming gaseous giant planets. 

That sounded good. It made logical sense. It explained the observation. There was just one problem: when we looked closer at the solar systems around us, we didn’t see any solar systems like that. Krulwich’s post does a great job explaining what those other solar systems look like.

We love stories—everywhere

It’s not that the “frost line” theory was wrong. The cause and effect dynamic is probably true. It’s just that other factors (solar gravity, solar winds, interplanetary forces) play a large (possibly larger) role, and our single observation wasn’t enough to tease out those dynamics.

What I found fascinating, however, is just how surprising that discovery was. We knew we had one observation—our solar system. We logically knew that one observation isn’t enough to generalize. There were certainly rational scientists that checked their beliefs accordingly. And yet the results were still surprising.

In this case, theorizing about the structure of solar systems, you could argue the consequences of being wrong aren’t huge. We were surprised, and now we’ll continue learning. In other areas, though, where we take action based on those theories, the consequences can be worse. 

Consider the obesity epidemic that is taking a large financial toll on our country. That’s a problem a bunch of organizations, particularly government organizations, have been trying to solve. But there’s a shift taking place here as well (or an argument at the very least). 

Read Gary Taubes’ NYTimes Magazine piece "What if It’s All Been a Big Fat Lie" to get the full story, but the basic story he describes is as follows:

• Conventional wisdom today. Fat and calories matter. Eat less fat and fewer calories, and you’ll lose weight. Taubes describes the history behind this idea, both the science and the sociopolitical factors, with the latter dominating. In 1977 a Senate committee published its “Dietary Goals for the United States” to address the epidemic of “killer diseases” sweeping the country. Then in 1984, the National Institutes of Health formally recommended that Americans over the age of 2 eat less fat. I’m cutting out a lot of complexity, but essentially that led to a focus on fat, and carbohydrates, particularly sugar and high fructose corn syrup, entered the equation to fill the void.

• Emerging idea. Carbs, particularly sugar, are the problem. The simplistic idea that fat leads to fat is contradicted by a large body of evidence. Focusing on fats actually leads to the removal of good fats from the diet as well, causing hunger, which in turns leads to overeating, particularly of carbohydrates, which among the macronutrients of proteins, fats, and carbobydrates, are unique because eating them makes you want to eat more. This last point is fascinating. Taubes describes an experiments in which three groups of people tried to fatten themselves by eating one of three different diets that were either predominantly protein, fat, or carbohydrates. The first two groups couldn’t do it. They got too full. The last group succeeded because it could eat continuously. 

There is more—much more—to this story, but all that matters for now is that the conventional wisdom is wrong. To be honest, the focus on carbs is probably wrong as well. But the common theme to me here is the idea of being skeptical of common wisdom.

We need to realize we create stories. This is a central idea in Daniel Kahneman’s book Thinking Fast and Slow. We see cause and effect even where there is none. A series of drawings showing a square in motion that comes into contact with another square that immediately begins to move causes observers to believe the first caused the second to move. It leads to a very powerful “illusion of causality” that exists even for six month old infants. If they don’t see that causality, they’re surprised.

This is hardwired. Our ability to create stories to explain the world is a fundamental element of our nature. It falls in the same category as sugar, in fact. Our bodies developed an intense craving for sugar because it was rare in our environment and we needed it for energy. Similarly, our ability to create quick stories, even if they were wrong, helped us survive. The man who wondered if, in fact, the rustling bushes were due to bears or the wind didn’t survive, unlike the guy who assumed it was a bear and ran.

But like all evolutionary remnants, the tendency gets us into trouble. I wonder if, in fact, all of our modern problems can be tied to this basic idea: we evolved to live in a world that we no longer live in thanks to our remarkable success in shaping that world in our favor.

In any case, the point of all this is that we create stories that aren’t true. And remarkable failures will come about if we don’t question those stories and realize that they may be wrong.

Anything that involves humans is probably wrong

In fact, there’s some early progress in figuring out just how wrong any given story may be. Last September, the mathematician/scientiest Samuel Arbesman released a book titled The Half-life of Facts: Why Everything We Know Has an Expiration Date. It demonstrated scientifically precisely the dynamics described above of beliefs being proven false. (The Economist has a good Q&A with Arbesman here.)

Arbesman showed that each scientific discipline has a half life for its ideas, a predictable time at which half the ideas held true in that field will become obsolete.

Arbesman gives an example:

…in the area of medical science dealing with hepatitis and cirrhosis, two liver diseases, researchers actually measured how long it takes for half of the knowledge in these fields to be overturned. They gave a whole bunch of research papers from fifty years ago to a panel of experts and asked them which were still regarded as true and which had been refuted or no longer considered interesting. They plotted this on a graph. What they found is that there is a nice, smooth rate of decay; you can predict that every 45 years, half of this particular sort of knowledge gets outdated.

And there’s a difference in how fast given fields decay:

One of the slowest is mathematics, because when you prove something in mathematics it is pretty much a settled matter unless someone finds an error in one of your proofs.

…the social sciences have a much faster rate of decay than the physical sciences, because in the social sciences there is a lot more “noise” at the experimental level. For instance, in physics, if you want to understand the arc of a parabola, you shoot a cannon 100 times and see where the cannonballs land. And when you do that, you are likely to find a really nice cluster around a single location. But if you are making measurements that have to do with people, things are a lot messier, because people respond to a lot of different things, and that means the effect sizes are going to be smaller.

Startups and business are probably even more wrong

Arbesman doesn’t talk about startups and business, but I can’t help but project the idea in that direction.

Contradictions abound. For every path to success, there’s an opposite. For every conventional wisdom, someone smart is advocating the opposite:

• Enterprise software is capital intensive, or not. SuccessFactors raised $63 million on the way to its IPO. Veeva Systems raised $4 million. Others raised none.

• You should search and potentially pivot in the early stages, or not. Peter Thiel believes that entrepreneurs should have a definitive view of the future and decries what he calls the established religion of the Valley of pivoting and A/B testing.

• The success of consumer apps depends on social/viral, or not. Phil Libin, the CEO of Evernote: “We’re not social. We’re not viral.” 

• Growth over profits in the early stages is key for success, or not. Clayton Christen has a fascinating chapter in The Innovator’s Solution titled “There is Good Money and There is Bad Money.” It’s worth reading because the points are subtle and fit into a framework he builds throughout the book, but Christensen summarizes by saying “…the best money during the nascent years of a business is patient for growth but impatient for profits" (emphasis his). Christensen’s logic is that a focus on profits forces the company to "test as quickly as possible the assumption that customers will be happy to pay a profitable price for the product—that is, to see whether real products create enough real value for which customers will pay real money." He goes on to describe the death spiral that emerges if a company grows too quickly before answering this question. But this is certainly in contradiction to the conventional wisdom in Silicon Valley, particularly for consumer internet startups. 

So let’s make predictions about our world cautiously

So in thinking about the future, particularly from the standpoint of investors, I see a common theme: confidence is bad. Both Nate Silver and Philip Tetlock in their fascinating books on prediction discuss this point ("The Signal and the Noise" and "Expert Political Judgment," respectively).

I stress above “from the standpoint of investors” because the reverse is true for entrepreneurs, where I agree with Thiel: confidence, a definitive view of the future, is good. 

Change the game

Glenn Kelman, the CEO of Redfin, gave a great TEDx talk last month in which he encourages technology entrepreneurs to create “real” companies that do the hard work of delivering the full offering to end users rather than just the software layer.

A written version of Kelman’s talk, titled “The Next 50 Ideas for Billion-Dollar Software Companies,” is on LinkedIn here. 

As an example of his idea, Kelman offers the history of Redfin. Initially, Redfin had an interesting technology: showing house listings on a map. They had two options to generate revenue:

Option A: Be a media company, get traffic, sell ads to real estate agents

Option B: Become a real estate company and help people buy and sell homes

Kelman’s friend Matt Bell helped him make the decision, telling him: “You were placed on this earth to fuck with the order of the things. Change the game. Change the whole game.”

They went with option B, helping people buy and sell homes. In contrast to the real estate industry as it existed, they put the customer first, not the commission. They used technology all the way through. “We were no longer just a software company…we needed many, many real estate agents…we had to slog through market by market to build this business.”

Technology as a means to an end

What Kelman said really resonated with me, even more so than Marc Andreessen’s similar piece "Why Software Is Eating The World" (which I loved). Andreessen’s article framed the world in an inspiring way. Yet, Kelman’s talk, while still delivering the same adventurous, the-world-is-ripe-for-disruption message, does so with a touch more humility in the sense that it reflects the realities of building enduring businesses: it takes more than just killer technology. 

When I reflect on Kelman’s idea, Walmart and Zara come to mind. I’ve often thought of them as technology companies in disguise.

Consider Walmart. The company lately is losing some shine recently, given competition from Amazon and labor troubles. But for most of its history, it decimated its rivals. A (somewhat dated) HBR article by three BCG consultants gives a good summary of how much Walmart outperformed its competitors throughout its history:

And while much has been written about how Walmart did this (the HBR article goes into it in detail), one thing is clear: technology was key. Walmart did a much better job than its competitors in tying together vast, seemingly separate aspects of the business to lower their costs and ultimately their prices. Technology played a key role in this, from monitoring its inventories to understanding what was selling to minimizing warehouse stocks to communicating with suppliers. We think of Walmart as a retailer but, in many ways, they were more a technology company that happened to be a retailer. Amazon, of course, is the latest iteration of that, but I like the Walmart example because from the outside it looks like a retailer rather than a technology company. 

Zara is another example. It trounces its competitors, other global apparel retailers, in terms of revenue growth, profitability, and capital efficiency. And, more simply: people love their clothes. They did this by recognizing a reality of fashion: it changes quickly. So they built a technology infrastructure that allowed them to gather information on what people were buying at the stores. They collected not only sales data but qualitative feedback from reps on the floor about various items. They then quickly adjusted manufacturing so that they could produce more of what was selling and less of what wasn’t. This also allowed them to run experiments. They would do small runs of clothing they thought people might like based on various trends. If it sold, great—they’d produce more. If not, they’d move on. 

The common theme is that the technology reflected the realities of the business. Once those realities were recognized, both optimized technology and the non-technology pieces.

In Walmart’s case, there were major decisions to be made around, for example, how to organize the trucking fleet. They decided to build a capability in shipping logistics, owning their own trucking fleet and warehouses, which was in contrast to many retailers. By having a world-class technology layer on top of a world class logistics infrastructure, they built an unbeatable capability.

Zara, similarly, had to make many major non-technology decisions. For example, in creating an ability to respond quickly to fashion trends, technology was just one part of it. They also needed to be nimble manufacturers. Factories in China wouldn’t cut it, with their long lead times and large batch sizes. Zara’s factories were right near their headquarters. What they gave up in higher costs they more than gained in their quicker response times. 

In short, there were multiple hard problems to solve, not just in the technology, but in organizing the business to best deliver value to customers, but once those pieces were solved together, the businesses that was created was phenomenal. They delivered great value to customers—and shareholders.

More recent examples?

Uber and Warby Parker are my favorite recent examples. Uber is a taxi company. Warby Parky is a retailer of eyeglasses. Both are solving a problem we as consumers have to solve. They each have a deep technology element, but just as much, if not more so, they’re innovating in other ways.

Uber has had to build the ability to work with limousine owner/drivers and deal with the regulatory aspects of transportation. And Warby Parker has had to build a deep capability in eyeglass design and manufacturing, not to mention shipping and logistics as well as marketing. 

From the typical early stage technology business, both are pretty clear winners, but I think they’re actually just getting started. Both, by building great tech and non-tech capabilities, are going to change their respective games. I’m looking forward to seeing many more of these types of efforts and really appreciate Kelman offering this mode of thinking to innovators. 

Conviction

At SXSW, Peter Thiel talked about Mark Zuckerberg turning down Yahoo’s $1 billion acquisition offer. I liked one part in particular:

Thiel told this story to make a larger point about how the most successful entrepreneurs operate. He said that the best entrepreneurs, like Zuckerberg, have a definitive view about the future and plan for it; they don’t willy-nilly chase luck—using statistics, probability, and iterative processes—to stumble upon something, anything that flies.

"All of us have to work toward a definite future…that can motivate and inspire people to change the world," he said. In this scenario, "luck is something for us to overcome as we go along the way, but not something that becomes this absolute dominating force that stops all thought."

Thiel doesn’t subscribe to what he calls the start-up “religion” of a-b testing every tweak (until you run out of money) or incrementally-iterating at every step—to be so systematically chasing some random success that it strips out all conviction and creative ideas about the future.

— Inc.

Craftsmanship

An anecdote appears early in Walter Isaacson’s biography of Steve Jobs that has stuck with me.

When Jobs was young, his adoptive father loved building things: cars, fences, cabinets, etc. He included Jobs in these activities, and Jobs remembered the activities fondly:

"I thought my dad’s sense of design was pretty good," he said, "because he knew how to build anything. If we needed a cabinet, he would build it. When we built our fence, he gave me a hammer so I could work with him.

Fifty years later the fence still surrounds the back and side yards of the house in Mountain View. As Jobs showed it off to me, he carressed the stockade panels and recalled a lesson that his father implanted deeply in him. It was important, his father said, to craft the backs of cabinets and fences properly, even though they were hidden. “He loved doing things right. He even cared about the look of the parts you couldn’t see.”

This has stayed with me for two reasons. One, it reminded me how important it is for me as a father of two young kids to include my kids in things I do since you never know what will stick with them. Two, the idea of craftsmanship resonated with me, the love of “doing things right.”

Much has already been written about the design and craftsmanship of Apple products themselves, but it’s important to remember that at the time Apple was creating beautiful, well-designed products, computer hardware and consumer electronics were considered difficult businesses. It certainly wasn’t where a straightforward investor would have placed his bet for a company to create the sort of value that Apple ended up creating, becoming the most valuable company in the world.

In other words, there are many companies in “attractive” markets and industries that perform poorly, and there are many companies in “ugly” markets and industries that create dramatic value.

Beyond Apple, there’s Starbucks. There’s also Spanx, a bootstrapped company founded in 2000 to create shaping undergarments for women that will have revenue north of $300 million. Other startup examples include Warby Parker that is re-creating the market for eyewear.

So more and more I’m starting to move away from the market-centric view of the world of investing in “hot” markets. Markets change, and in fact, the “hot” market more often than not just means lots of noise and hype. Now this doesn’t mean you ignore markets completely. Market size does matter. Insights into market structure (buyers, sellers, fixed costs, etc.) are helpful. But now I subordinate those to understanding the entrepreneur (his or her world view, experiences, capabilities, network, and vision) and the product. 

The idea of craftsmanship sticks with me even beyond the idea of “doing things right” with regard to the product itself. I think you can expand the idea to the company itself. The best entrepreneurs think of the company itself as a product, and bring that same craftsman mindset to creating a company.

More on that later.