Lessons from the NFL: Studying People Analytics One Draft Pick at a Time
In 1999, pro football fans eagerly anticipated the NFL’s annual player draft with more excitement than usual. Most experts were raving about the quality of the quarterbacks graduating from college that spring — including Donovan McNabb from Syracuse and Kentucky’s Tim Couch — as well as the top running back, Heisman Trophy winner Ricky Williams from Texas. That apparent wealth of talent posed a real dilemma for teams with the highest draft picks in deciding whom to select.
For Cade Massey, now a professor of practice in Wharton’s Operations, Information and Decisions Department, and a West Texas native with football in his veins, watching that year’s draft was more than just a fun weekend diversion. It would be a life-altering experience.
Then a graduate student in economics, Massey realized that the NFL draft, and the data surrounding the performance of players who were ultimately picked, offered a remarkable window into how high-stakes personnel decisions are made. “I thought, ‘Let’s take this as an opportunity to test psychology in a real world environment,’” says Massey.
His research over the next decade — which showed that teams that accumulate multiple draft choices are better off than teams that trade up for one high pick in search of a superstar — led him to become a leader in the rising field of “people analytics” — using hard data to make human-resource decisions once made by pure instinct. The $10 billion-a-year National Football League — where attracting and retaining the best talent takes place under a national spotlight — is also proving to be an almost ideal learning lab for everything from how managers should evaluate skilled talent to how communication styles can motivate the workforce.
Massey shares his research with participants in a number of Wharton Executive Education programs, including the Advanced Management Program and the Executive Negotiation Workshop. He says the tools of sports analytics — for example, drilling deep into player statistics to come up with an ideal baseball lineup, as dramatized in the film “Moneyball” — are now flowing to major American corporations and their HR decisions. “It’s a short hop,” he says, “from talking about the NFL draft to talking to the School of Management at Yale about their admissions policy, or to Google about their recruiting processes.”
He noted the earlier adapters of people analytics have tended to be businesses that generate data from things such as sales figures or the number of investment banking deals, but firms that numerically rate employee performance are also generating useful data over a number of years.
But, he says, there’s no better example of smart people analytics than the NFL. “These guys run $120-to-$130 million payrolls, and everything they do is observed and critiqued by millions of people and this is where they have evolved — toward highly analytical evaluations of players in an effort to get it right. I think we can learn a lot from these organizations.”