Читать онлайн «The Undoing Project: A Friendship That Changed Our Minds»

Back in 2003 I published a book, called Moneyball, about the Oakland Athletics’ quest to find new and better ways to value baseball players and evaluate baseball strategies. The team had less money to spend on players than other teams, and so its management, out of necessity, set about rethinking the game. In both new and old baseball data—and in the work of people outside the game who had analyzed that data—the Oakland front office discovered what amounted to new baseball knowledge. That knowledge allowed them to run circles around the managements of other baseball teams. They found value in players who had been discarded or overlooked, and folly in much of what passed for baseball wisdom. When the book appeared, some baseball experts—entrenched management, talent scouts, journalists—were upset and dismissive, but a lot of readers found the story as interesting as I had. A lot of people saw in Oakland’s approach to building a baseball team a more general lesson: If the highly paid, publicly scrutinized employees of a business that had existed since the 1860s could be misunderstood by their market, who couldn’t be? If the market for baseball players was inefficient, what market couldn’t be? If a fresh analytical approach had led to the discovery of new knowledge in baseball, was there any sphere of human activity in which it might not do the same?

In the past decade or so, a lot of people have taken the Oakland A’s as their role model and set out to use better data, and better analysis of that data, to find market inefficiencies. I’ve read articles about Moneyball for Education, Moneyball for Movie Studios, Moneyball for Medicare, Moneyball for Golf, Moneyball for Farming, Moneyball for Book Publishing(!), Moneyball for Presidential Campaigns, Moneyball for Government, Moneyball for Bankers, and so on. “All of a sudden we’re ‘Moneyballing’ offensive linemen?” an offensive line coach for the New York Jets complained in 2012. After seeing the diabolically clever data-based approach taken by the North Carolina legislature in writing laws to make it more difficult for African Americans to vote, the comedian John Oliver congratulated the legislators for having “Money-balled racism. ”

But the enthusiasm for replacing old-school expertise with new-school data analysis was often shallow. When the data-driven approach to high-stakes decision making did not lead to immediate success—and, occasionally, even when it did—it was open to attack in a way that the old approach to decision making was not. In 2004, after aping Oakland’s approach to baseball decision making, the Boston Red Sox won their first World Series in nearly a century. Using the same methods, they won it again in 2007 and 2013. But in 2016, after three disappointing seasons, they announced that they were moving away from the data-based approach and back to one where they relied upon the judgment of baseball experts.