Billy Beane’s “Moneyball” approach to developing and staffing a professional baseball team has come under intense scrutiny as long time major league scouts and analysts take delight in sub-par performances of the Oakland Athletics. Beane however seems undaunted in using statistical analysis to undercover market place inefficiencies. Indeed, it takes courage to solve problems in a whole new—perhaps heretical—manner. And while plenty of folks take pleasure in Beane’s recent comeuppance, there’s a good chance he’s already had the last laugh.
By now, most business professionals have either read Michael Lewis’ “Moneyball” or at the very least seen Brad Pitt’s rendition of Billy Beane in Hollywood’s version. Beane’s claim to fame is that he had the courage to defy decades of “common knowledge” in assembling a winning baseball team. For many years, winning teams were accustomed to paying top dollar for the best hitters and pitchers evidenced by metrics such as batting average and earned run average respectively.
However, in the small-town Oakland market, Beane didn’t have the luxury of affording a high payroll. And if he wanted to compete, he needed to find a different (and perhaps better) method of keeping up with the likes of the Boston Red Sox and New York Yankees.
Beane knew there were “inefficiencies” in baseball markets that could be exploited; he just had to discover those undervalued metrics.
Enlisting the help of his Harvard friend Paul Depodesta, Beane used statistical analysis to discover metrics that—in his opinion were more indicative of baseball success—such as on base percentage and slugging percentage for batters, or the ability to get “outs” for pitchers. Then Beane went about acquiring a motley bunch of players that most teams discarded as near worthless, and positioned each player for success based on his analytical models.
And for a while it worked. With one of the league’s lowest payrolls the Oakland A’s competed with teams spending 2-3x in overall salaries. In fact, a Sports Illustrated article mentions; “From 2000 to 2006, (Oakland A’s) averaged 95 wins, captured four AL West titles and made five playoff appearances.”
Alas, all competitive advantage is fleeting. As Paul Depodesta left for greener pastures, and a few of Beane’s other disciples took other league jobs, major league baseball teams figured out what made Moneyball work and effectively neutralized the Oakland A’s advantage. With other teams adapting to Moneyball tactics, from 2007 and beyond, the Oakland A’s were a .500 team at best, and sometimes much worse.
And in the process of adopting Moneyball tactics, Billy Beane made plenty of enemies. The “old guard” definitely had a preferred way of defining baseball success and would often scoff at the “fat bodies” Beane employed, and laugh at the un-orthodox pitchers he would trot out in the ninth inning. And in regard to the lackadaisical record of the Oakland A’s in recent years, one scout sneered; “So much for the genius … He doesn’t look so smart anymore, does he?”
Competing on analytics takes courage. In response to analyst and pundit criticism leveled at Beane for his Moneyball approach, author Michael Lewis says; “Beane had the nerve to seize upon ideas rejected, or at least not taken too seriously, by his fellow Club members, and put them into practice.” For a while, Beane had the advantage. It might not have been pretty, but the Oakland A’s were effective at winning as many games as other prestigious teams, for half the cost.
And Beane ultimately may have the last laugh. Today, there are teams like the Boston Red Sox that take the best of Moneyball tactics and overlay them with powerful financial resources to take baseball competitiveness to a whole new level. Baseball has been changed forever from a “gut feel” business to one that’s analytically driven.
Fortunately for today’s analytical professionals, “competing on analytics” is taking hold as more companies understand they’re sitting on literal goldmines of structured and multi-structured data just begging for analysis. But analytics users be forewarned, there’s still plenty of “old guard” that will put up roadblocks, enlist subterfuge and even openly mock your new data driven approaches.
Michael Lewis notes that Beane didn’t invent sophisticated analytical analysis—he just had the courage to use it to create competitive advantage and shake up a traditionally stodgy industry. There are plenty of industries ripe and ready for the business value that analytics will eventually unlock.
The question remains—as an analytics professional—will you have the courage and fortitude to face naysayers and discover new “predictors of success” in your industry?
