Thought Leadership Meets Moneyball in the 2014 World Series

Michael Lewis, the financial journalist who became famous describing his experiences selling mortgage-backed bonds in Liar’s Poker in 1989, became more broadly famous with 2003’s Moneyball: The Art of Winning an Unfair Game.

Moneyball was a huge if unlikely hit in the business world. Unlikely, because it was about baseball. Not about how horsehide heroes hit titanic home runs to win epic contests, but how Billy Beane, general manager of the underfunded Oakland A’s, built a competitive team after losing several stars to better-funded organizations. He did so (as Lewis wrote) by using statistical analysis to identify what really won ball games. Through that analysis (inspired by the work of Bill James, the pioneer of empirical, data-based baseball analytics, known as sabermetrics), Beane stocked his team with low-cost players who were cheap because they possessed under-valued skill sets (primarily guys who could draw walks, get on base, and score runs) instead of what he considered over-valued (and therefore highly-priced) stars who mashed homers, were defensive wizards, and hit for high averages.

Beane also ordered his team to play in a way that outraged traditionalists: the A’s eschewed the bunt (moving a runner to second was not worth wasting an out to do so), rarely stole bases (the risk-reward analysis was unfavorable), and took a rather casual attitude toward defense (hard to measure and therefore hard to value).   

It seemed to work. The A’s, with one of the lowest payrolls in baseball, went to the playoffs and became a perennial contender.

Business leaders, especially in HR, embraced the concept of Moneyball as thought leadership and for a while almost every white paper or article about competing for talent or analyzing the skills that really counted in running an organization referenced Lewis’s book. (You can find some examples from HBR here, here, and here.)   

Moneyball, by the Bloom Group’s definition, here, was, indeed, thought leadership. It had a novel thesis (what most people thought won ball games did not); it was relevant to many teams (revenue inequality is significant and widespread in baseball); the thesis was proven on the field; it could be implemented by any team (and, in fact, even the rich teams did); its logic was consistent and clear.

But as other, better-funded teams adopted the strategy, Beane’s strategic advantage waned.

And then, of course, the Kansas City Royals happened.

The 2014 World Series is beginning and it’s between a small-market team (the Royals) with a low payroll that bunts, steals bases, and emphasizes defense – both of which James maintained were relatively unimportant – and the San Francisco Giants, a more traditionally constructed nine.   

This match-up has caused the sabermetricians to start scrambling, whining about how much randomness and luck is involved in winning ball games, and insisting that bunting is still stupid, here. (Some, however, some have begun to reconsider the bunt, here.)

My colleague Tim Parker, who knows nothing about baseball (he’s a Brit), suggests that the sabermetrician’s error may be confusing correlation with causality; that is, statistics showed that teams that bunted a lot did not win a lot. But inferring that bunting was a cause of losing was unwarranted.

But even if the Royal’s success just comes down to luck, and Beane’s and James’s thesis is still solid, it will never confer the competitive advantage it once did.  Thought leadership, unlike diamonds, is not forever.

Michael Porter, whose 1980 book, Competitive Strategy, was voted one of the most influential management books of the 20th century by the Fellows of the Academy of Management, lately has seen his theories of competitive advantage (and how to achieve it) come under fire as the world he wrote about – the pre-Internet world – has changed in ways great and small. As Rita Gunther McGrath wrote, “Competitive advantage is dead.” And Porter has responded, here, incorporating connected devices into his theory of competitive advantage, emphasizing the importance of building a smart data stack that will allow organizations to participate in the “Internet of things.”

Porter wasn’t wrong in 1980. But he may not be right now, and he’s working on it. The moral is this: Thought leadership withers when it stays static. Thought leaders must be ready and even eager to change and adapt to new conditions, weighing new evidence and testing their theories against it. Holding fast to the past leaves you like the Oakland A’s – bounced out of the playoffs again this year by the faster, more competitive Royals, a team with a new idea.

It may not be a better one, but for this season, at least, it has shown itself to be a more successful one. 

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