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At one point in Moneyball, Michael Lewis’ book on the improbable winning run of the Oakland A’s in the early 2000s, Billy Beane, general manager of the underfunded baseball outfit, makes a surprising declaration. His statistical analysis doesn’t work in the play-offs, he says — that’s down to luck.
He uses more colourful language, but the point is that Beane is aware that, for all his ingenuity in identifying undervalued players, luck or randomness is an inescapable factor in baseball, as it is in all walks of life.
Yet luck played a part in the story in more ways than one. Moneyball is often portrayed as a triumph of data analysis, but that is not sufficient to explain the success of the A’s, because data on players as well as the techniques for crunching it had been publicly available for decades. What helped swing things Beane’s way was his rivals’ tendency to reach too soon for luck as an explanation for performance.
Over many years, scouts and team managers had built up stereotypes about what good players looked like. Competent but counter-stereotypical players such as the “submarine pitcher” Chad Bradford were underestimated because managers concluded that their successes had to be down to mere luck. Such biases — and the consequent misattribution of luck — protected these “hidden gems” from discovery until Beane’s statistical approach cut through to the facts.
The result was a team that could take on the giants of the sport and reach the play-offs four seasons running. Thanks to Lewis’s book, Beane’s strategy has become widespread across baseball and has filtered into other sports.
This contrarian approach can be used in business as well, where strategy and behavioural science can be combined to exploit irrational biases. I call this “analytical behavioural strategy”: it consists in drawing on behavioural science to search for contrarian opportunities, and then using data analysis to formulate an exploitation strategy.
For instance, most people don’t anticipate regression to the mean — that is, that the exceptional will probably be followed by the average. This, though, is the likeliest outcome whenever a business’s performance — in terms of sales, say — is not entirely under the control of those in charge.
A great performance may suggest that managers are doing a great job, but it’s more likely to arise from fortunate timing — luck. By definition, luck is not going to persist: the business’s future performance will regress downward to the mean. A good contrarian strategist looks for evidence that rivals are not mindful of this.
Take “top CEOs”, for example — specifically the annual top 30 list compiled by Barron’s magazine. When I analysed the 2005-10 line-ups in terms of how the companies they led performed, a clear, inverted V-shape pattern emerged: the performance (as measured by factors such as sales growth, profitability and stock price) improved before the CEO made the list, but plummeted afterwards.
The usual explanations for such decline include complacency or hubris on the part of the CEO. A simpler explanation, however, is that the CEOs were never that special in the first place. It was luck that enabled them to attract unwarranted attention after successes. And it was (bad) luck that made many of them attract unwarranted blame after failures.
A contrarian strategist can profit from rivals’ “luck biases” in at least two ways: short sell and buy low. A salient success is rarely sustainable but the market usually believes otherwise. Consider the 50 companies featured in three of the most popular business bestsellers of the past 40 years: In Search of Excellence, Good to Great and Built to Last. Of the 50, 16 failed within five years after the books in which they starred were published, and 23 became mediocre as they underperformed in the S&P 500 index.
Next time you browse the business bestsellers section, pay attention to the companies featured. Instead of trying to emulate them, as your rivals may do, you should make these “role models” your target for short selling.
On the other hand, opportunities also lurk in the “regression upward” that often follows a notable failure. A common reaction to failure is to find scapegoats and fire them — as many ex-CEOs and sports coaches can attest. Nevertheless, the more extreme the failure, the less we should attribute it to the person, and the more to the system. Otherwise we create an opportunity for the shrewd contrarian, who can step in and hire the scapegoat.
Businesses that are aware of these biases are better placed than those that aren’t. Fortune favours the strategist with a clear-eyed view of luck.
Chengwei Liu is associate professor of strategy and behavioural science at Warwick Business School and ESMT Berlin and author of ‘Luck, A Key Idea for Business and Society’ (Routledge)
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