Future potential matters (much) more than past performance. That's the new quantitative consensus reshaping professional sports worldwide. After looking hard at the numbers and algorithms, the smartest — and richest — general managers and franchises have made up their collective minds: They're not paying a premium for yesterday. Period. Iconic athletes from Barcelona to Manchester United to the Chicago Bears to the New England Patriots to the New York Yankees have been effectively cut loose.
Thanks for the memories. See you at the Hall of Fame induction ceremonies, dude. We simply can't — or won't — afford you anymore.
Multivariate predictive analytics render "What have you done for me lately?" an anachronistic cliché. The questions now are, "How well will you do tomorrow?" and "How can we be sure?" The better the answers, the richer the paychecks. The past is, indeed, a foreign country, albeit one with a debauched currency. This next-generation "moneyball" ethos now transforming pro sports has enormous implications for how high-performance managers will incent and inspire tomorrow's high achievers. The cultural values of loyalty and leadership are being redefined by the economic value of forecasting methodologies (PDF). "Yesterday" is a sunk cost.
"Yes, the trend is towards paying for future performance; by that I mean future 'forecasted' performance," observed Daryl Morey, General Manager of the NBA's Houston Rockets franchise and a pioneer in bringing moneyball statistical/quantitative analytics to pro basketball, in a conversation with me. "My job is to up our odds for winning games and winning championships, and those things happen going forward, not looking backward."
Exactly. Where past performance was once the best and most reliable proxy for the future, says Morey (a friend who launched MIT's successful Sports Analytics Conference), algorithmic and biomedical innovations increasingly give coaches, managers, and owners greater confidence in predicting which players have peaked and which ones will step up to greatness. "We have a luxury in sports," says Morey. "We can so clearly measure success and failure; we can know when people start fading with age...we can make a better bet on someone with talent."
Unlike for a Procter & Gamble or Unilever, Morey muses, there is no "aging curve" for marketing prowess: "We can't say that, after 50, this guy won't have another good marketing idea again."
But why not? If you're running Procter & Gamble, Unilever, Google, Exxon Mobil, or Ford, you have comparable concerns about making sure you're getting the best possible returns from your talent and human capital investments. You should be concerned about the aging curves of your marketing people; you should want to know if your tech support folks will deliver better outcomes tomorrow than today; you should be predicting which sales teams will procure the most lucrative contracts with the minimum risks. Think of it as Six Sigma predictive analytics for talent.
The catch, which Morey freely acknowledges, is that it's still very difficult to measure what role personal loyalty plays in inspiring extra efforts that yield better results. It's still very difficult to assess the positive influence of an aging leader whose physical skills have demonstrably diminished but whose acuity and character gets everyone on the team to step up their game. No one denies the reality or importance of these organizational phenomena. But that's not the direction that moneyball's metrics have been going.
"All of my actions have to be on the individual level," Morey acknowledges, while freely conceding that oftentimes a team's greatest professional challenge is chemistry and cohesion. Of course, encouraging the kind of loyalties and leadership that enhance collaboration becomes inherently more difficult when performers fear they may fall on the wrong side of the aging curve. Similarly, coaches lose credibility with their players if they champion schemes and approaches that predictive analytics might undervalue or ignore come contract time.
The classic response, of course, is to insist that, ultimately, these decisions come down to human judgments rather than computational dictatorships. But that's exactly why acknowledging the current trend is so important: The leaderships of the richest and (ostensibly) best-managed franchises in sports have effectively declared that the costs of preserving past values are too high relative to the potential for tomorrow's performance.
Bill Parcells, the Super Bowl-winning coach, was famous for saying, "You are what your record says you are." Today, that's no longer true. You are what the analytics predict you will be. That changes the social — as well as the professional — contract.
Does anyone really think a 50-year-old marketer with a terrific track record is immune from the same economic and analytic forces affecting the career of a 40-year-old pro athlete who was a two-time all-star? Does that knowledge make the marketer a better leader or more loyal employee? Or doesn't that matter anymore?
Do you know where you are on the aging curve? Does your boss?