Most of us assume we've done enough for our organizations related to putting our talent in a place where it can be successful. We found the best talent for what we could afford, recruited and signed them, gave them the tools and even did a half-day orientation. What more could they need to succeed?
More organizations are turning to intense data mining to understand what individuals on their teams make the best decisions, as well as what circumstances need to be in place to enable great performance and solid decision-making. It'll be awhile before this makes it to you at ACME Inc., but take a look below at the lengths the Houston Rockets will go in order to control Kobe Bryant:
Remember Moneyball? That was about new ways of valuing talent in professional sports and identifying undervalued assets through the "new talent math". The new Moneyball isn't about acquiring talent, it's about gaining a competitive advantage via data for the talent once it's acquired.
More on the new form of Moneyball in the NBA from Michael Lewis at the New York Times:
"People often say that Kobe Bryant has no weaknesses to his game, but that's not really true. Before the game, Shane Battier was given his special package of information. "He's the only player we give it to," Morey says. "We can give him this fire hose of data and let him sift. Most players are like golfers. You don't want them swinging while they're thinking." The data essentially broke down the floor into many discrete zones and calculated the odds of Bryant making shots from different places on the court, under different degrees of defensive pressure, in different relationships to other players - how well he scored off screens, off pick-and-rolls, off catch-and-shoots and so on. Battier learns a lot from studying the data on the superstars he is usually assigned to guard. For instance, the numbers show him that Allen Iverson is one of the most efficient scorers in the N.B.A. when he goes to his right; when he goes to his left he kills his team. The Golden State Warriors forward Stephen Jackson is an even stranger case. "Steve Jackson," Battier says, "is statistically better going to his right, but he loves to go to his left - and goes to his left almost twice as often." The San Antonio Spurs' Manu Ginóbili is a statistical freak: he has no imbalance whatsoever in his game -- there is no one way to play him that is better than another. He is equally efficient both off the dribble and off the pass, going left and right and from any spot on the floor.
Bryant isn't like that. He is better at pretty much everything than everyone else, but there are places on the court, and starting points for his shot, that render him less likely to help his team. When he drives to the basket, he is exactly as likely to go to his left as to his right, but when he goes to his left, he is less effective. When he shoots directly after receiving a pass, he is more efficient than when he shoots after dribbling. He's deadly if he gets into the lane and also if he gets to the baseline; between the two, less so. "The absolute worst thing to do," Battier says, "is to foul him." It isn't that Bryant is an especially good free-throw shooter but that, as Morey puts it, "the foul is the worst result of a defensive play." One way the Rockets can see which teams think about the game as they do is by identifying those that "try dramatically not to foul." The ideal outcome, from the Rockets' statistical point of view, is for Bryant to dribble left and pull up for an 18-foot jump shot; force that to happen often enough and you have to be satisfied with your night. "If he has 40 points on 40 shots, I can live with that," Battier says. "My job is not to keep him from scoring points but to make him as inefficient as possible." The court doesn't have little squares all over it to tell him what percentage Bryant is likely to shoot from any given spot, but it might as well.
The reason the Rockets insist that Battier guard Bryant is his gift for encouraging him into his zones of lowest efficiency. The effect of doing this is astonishing: Bryant doesn't merely help his team less when Battier guards him than when someone else does. When Bryant is in the game and Battier is on him, the Lakers' offense is worse than if the N.B.A.'s best player had taken the night off."
It's pretty impressive, and all done in the name of providing Battier an edge in his head-to-head with Kobe. Like I said at the jump, it will be awhile before this approach makes it to you and me, but from a development perspective, what data can you provide your talent to make better decisions in head-to-head interaction with competitors, as well as the decisions they make about their own career development? What about the daily decisions they make in what to work on?
Until you and I have a plan, we're really just doing the workplace equivalent of hoping that Kobe misses a lot of shots on his own - without thinking about what WE can do to influence the performance outcome.
And that's humbling...