An Ideas-Based Online Magazine of the Global Network for Advanced Management

The Luck Bluff

Chance favors the bold, so the saying goes, but often when other systemic factors have cleared the path ahead.

By Tammi L. Coles

In his 2005 bestselling book Blink, Canadian journalist Malcolm Gladwell noted a seemingly bizarre fact about his work with Fortune 500 leaders. “In the U.S. population, about 14.5 percent of all men are six feet or taller. Among CEOs of Fortune 500 companies, that number is 58 percent. Even more striking, in the general American population, 3.9 percent of adult men are six foot two or taller. Among my CEO sample, almost a third were six foot two or taller.”

Were the fortunes of multibillion-dollar corporations really being left to the luck of the genetic draw?

Some ten years ago, ESMT Associate Professor Chengwei Liu was undertaking his graduate work in management studies at Cambridge when, by chance, he, too, fell into the path of luck. “When I asked entrepreneurs in the area to explain their successes, they always referred to this idea of luck,” recounted Liu. “They were very lucky at one point in their career, and that enabled their success.” Liu wanted to study the phenomenon more closely but struggled to imagine the practical implications of his research in the real-world business landscape. “What should we tell managers?” he asked, “That they should be lucky?”

Still Liu decided luck was worth a closer examination. His research into the impact of luck showed that, one, and somewhat counterintuitively, luck could be studied in systemic ways and, two, that business leaders can strategize with luck. The key, however, is not to pursue luck. “Luck by definition is an unsystematic factor beyond our control or foresight,” said Liu. “So, if we take the definition of luck seriously, there should be no way to get luckier than others, right?” Instead, the power of luck is in using others’ belief in luck to your own advantage.

Baseball, before and after Moneyball

Last year, the Washington Nationals claimed their championship in the World Series, their first in the Major League Baseball franchise. But well before the Nationals secured its place in baseball lore, the Oakland Athletics—more fondly called the Oakland A’s—changed baseball forever.

As the story goes, the A’s had far less to spend on player recruitment than their franchise peers. Rather than accept their down-on-their-luck circumstances, the Athletics general manager, Billy Beane, approached the problem in ways that seemed at least unconventional if not wrong-headed. Rather than relying on talent scouts to trust their instincts in the selection of players, focusing on perceived skills in fielding or batting, the A’s began drafting players with prowess in other areas. Rather than batting averages, they asked how often the hitters were getting to base.

The turn to using sabermetrics, the empirical analysis of baseball statistics that measures in-game activity, paid off handsomely for the Athletics. Their high game victories and low payroll payouts set them apart in baseball because, at the time, no other teams were using such statistically driven methods. This all changed with the publication of Moneyball by financial journalist Michael Lewis. The 2003 report on how the A’s had successfully used sabermetrics ripped away the magic veil to reveal the power of analytics. The A’s exploited the biases that other teams had for players with similarities to previous star players and their pursuit of luck—the chance that a scout could “spot a winner.” And what they proved is that even players who don’t have “the look” could win the day on the baseball diamond.

The Diamond in the Rough

Luck has important implications for business and for society. Should the richest be taxed? In the U.S., belief in the American Dream holds powerful economic sway. Why punish a worker who has made their wealth with the blood, sweat, and tears of hard labor? Don’t they deserve to reap what they have sown?

“The conventional wisdom of luck is that if you work harder, you’ll get luckier. But some of my research actually demonstrates that may not always be the case,” said Liu.

For the average entrepreneur, skill, effort, and persistence will lead to good product design outcomes and sustainable business models. Chance favors the bold, so the saying goes, but often when other systemic factors have cleared the path ahead. According to a 2005 report by Wojciech Kopczuk and Joseph P. Lupton of the National Bureau of Economic Research, nearly 50 percent of wealth is inherited and not self-made. “These pre-success dynamics means there’s very little we can learn from outlier or exceptional performance,” said Liu. “You can imitate everything Bill Gates did for Microsoft, but you cannot imitate his initial fortune by being born in a rich family or having the connection to the IBM president through his mother. If you imitate Gates or other billionaires, the consequence will likely be systematic disappointment.”

Liu’s research into the performance of similar cases of “brilliant randomness” delved into the music industry’s production of stars. Someone with a hit among the top three singles on Billboard would be considered by most people to be a star, worthy of pursuit by the average music producer. What Liu’s research found, however, was that these top artists performed poorly with each subsequent single released—dropping from the top to a mid-range position on Billboard. Those climbing the charts were, by contrast, the musicians who had previously only achieved a modest position.

If you’re a producer, instead of focusing on the luck of the stars who landed among the top of the charts, says Liu, invest your bets in the mid-level performers. “They have better future performance and, predictably, they are ignored or underestimated by your rivals.” As with the Oakland A’s, the return on investment is higher where data and analytics—not luck—reveal actual value.

Chengwei Liu joined ESMT Berlin as an associate professor of strategy and behavioral science in 2019. Liu’s forthcoming book, Luck, will be published by Routledge in December 2020.

This article originally appeared on the ESMT Berlin website.

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