sociologists, corporate strategists, professors of finance, economists, and sabermetricians (those who apply statistical methods to the study of sports) all have something to contribute to the discussion.7 Unfortunately, the people within these disciplines don't always reach outside their fields. You will see ideas from each of these disciplines, and I'm hopeful that bringing them together will lead to a sounder and more balanced approach to analyzing decisions and interpreting the results.
Untangling skill and luck is an inherently tricky exercise, and there are plenty of limitations, including the quality of the data, the sizes of samples, and the fluidity of the activities under study. The argument here is not that you can precisely measure the contributions of skill and luck to any success or failure. But if you take concrete steps toward attempting to measure those relative contributions, you will make better decisions than people who think improperly about those issues or who don't think about them at all. That will give you an enormous advantage over them. Some statisticians, especially in the world of sports, come across as know-it-alls who are out of touch with the human side of things. This characterization is unfair. Statisticians who are serious about their craft are acutely aware of the limitations of analysis. Knowing what you can know and knowing what you can't know are both essential ingredients of deciding well. Not everything that matters can be measured, and not everything that can be measured matters.
While there are wide swaths of human activity where the ideas in this book are hard to apply, the ideas have concrete application in some important areas and should serve as a template for thinking about decisions beyond the scope of this book. Luck may explain that you met your future wife after your buddy lured you out on a Thursday night, but this book will have little to directly say about that or other issues of love, health, and happiness. We need to define the activity we're talking about and what measures we need to use to evaluate that activity effectively.
In his book The Theory of Gambling and Statistical Logic, Richard Epstein, a game theorist trained in physics, notes that there is no way to assure that you'll succeed if you participate in an activity that combines skill and luck. But he does say, “It is gratifying to rationalize that we would rather lose intelligently than win ignorantly.”8 Luck may or may not smile on us, but if we stick to a good process for making decisions, then we can learn to accept the outcomes of our decisions with equanimity.
CHAPTER 1
SKILL, LUCK, AND THREE EASY LESSONS
LET ME START with a story that is likely to be familiar to you.
One of the greatest computer programmers of all time grew up near Seattle, Washington. He saw an upstart company, Intel, making computers on a chip and was among the first people to see the potential of these so-called microcomputers. He dedicated himself to writing software for the new device and, by one account, “He wrote the software that set off the personal computer revolution.”1
In the mid 1970s, he founded a company to sell software for microcomputers. In the early history of the company, “the atmosphere was zany,” and “people came to work barefoot, in shorts,” and “anyone in a suit was a visitor.”2 But the company was soon highly profitable, and by 1981 its operating system had a dominant share of the market for personal computers that used Intel microprocessors.
For all of its early triumphs, the company's watershed moment came when IBM visited in the summer of 1980 to discuss an operating system for its new PC. After some negotiation, the two companies struck a deal. In August 1981, retailers offered the company's software alongside the brand new IBM PC, and the company's fate was sealed. The rest is history, as they say.
In case this story's not familiar, here's the ending. This pioneer of computer technology entered a biker bar in Monterey, California, on July 8, 1994, wearing motorcycle leathers and Harley-Davidson patches. What happened next is unclear, but he suffered a traumatic blow to the head from either a fight or a fall. He left under his own power but died three days later from the injury, complicated by his chronic alcoholism. He was fifty-two years old. He is buried in Seattle and has an etching of a floppy disk on his tombstone. His name is Gary Kildall.3
You'd be excused for thinking that the first part of the story is about Bill Gates, the multibillionaire founder of Microsoft. And it is certainly tantalizing to ask whether Gary Kildall could have been Bill Gates, who at one point was the world's richest man. But the fact is that Bill Gates made astute decisions that positioned Microsoft to prevail over Kildall's company, Digital Research, at crucial moments in the development of the PC industry.
When IBM executives first approached Microsoft about supplying an operating system for the company's new PC, Gates actually referred them to Digital Research. There are conflicting accounts of what happened at the meeting, but it's fairly clear that Kildall didn't see the significance of the IBM deal in the way that Gates did.
IBM struck a deal with Gates for a lookalike of Kildall's product, CP/M-86, that Gates had acquired. Once it was tweaked for the IBM PC, Microsoft renamed it PC-DOS and shipped it. After some wrangling by Kildall, IBM did agree to ship CP/M-86 as an alternative operating system. IBM also set the prices for the products. No operating system was included with the IBM PC, and everyone who bought a PC had to purchase an operating system. PC-DOS cost $40. CP/M-86 cost $240. Guess which won.
But IBM wasn't the direct source of Microsoft's fortune. Gates did cut a deal with IBM. But he also kept the right to license PC-DOS to other companies. When the market for IBM PC clones took off, Microsoft rocketed away from the competition and ultimately enjoyed a huge competitive advantage.
When asked how much of his success he would attribute to luck, Gates allowed that it played “an immense role.” In particular, Microsoft was launched at an ideal time: “Our timing in setting up the first software company aimed at personal computers was essential to our success,” he noted. “The timing wasn't entirely luck, but without great luck it wouldn't have happened.”4
Defining Skill and Luck
The first step in untangling skill and luck is to define the terms. This is not a simple task and can quickly devolve into heated philosophical debates.5 We can avoid those, since pragmatic definitions are all that we need to think clearly about the past, present, and future results of our actions and to improve the way we make the decisions that lead to those actions.
But first things first. Before we can speak of skill and luck, we have to settle on the specific activity we're talking about. We can analyze what athletes, executives, or investors do. We just have to be clear on what elements of performance we are considering. Next, we want to agree on the measures of performance. For athletes, it is winning games. For executives, it is developing strategies that create value. The benefit of measurement is that it allows us to assign specific values to skill and luck.
Now we can turn to definitions.
Luck
Let's start with luck.
We can probably do a bit better than the average dictionary that defines luck as “events or circumstances that work for or against an individual.”6 This is a good starting point, but we can be a little more specific. Luck is a chance occurrence that affects a person or a group (e.g., a sports team or a company). Luck can be good or bad. Furthermore, if it is reasonable to assume that another outcome was possible, then a certain amount of luck is involved. In this sense, luck is out of one's control and unpredictable.7
For example, suppose that a teacher asks her students to learn one hundred facts. One student—call him Charlie—memorizes eighty of those facts, figuring that he'll always score 80 and earn a grade of B. Charlie likes this course, but his life doesn't depend on it, as long as he doesn't
