Oakland Athletics' general manager Billy Beane rocked Major League Baseball by applying a sabermetrics-based analytical technique that identified success factors that other teams failed to appreciate. It wasn't that competitors didn't use analytical techniques or lacked the relevant data; it was that they started from inadequate assumptions and asked the wrong questions. Insurers have a similar opportunity today to leap ahead of competitors by applying prescriptive analytics, a technique that optimizes pricing through sophisticated analysis of customer demand. But like Beane, champions of prescriptive analytics must overcome internal cultural resistance.

In the 2011 film "Moneyball," Beane has a fateful encounter with Peter Brand, a Yale economics graduate student. The Brand character insists that scouts and coaches are applying the wrong criteria of success, focusing on prospects with signs of potential greatness. His insight was that cumulative team criteria such as the aggregated propensity for getting on base - known as the on-base percentage (OBP) - were more important than traditional gauges of excellence in individual players. The conventional thinking of team managers was to think in terms of buying players, Brand notes. "Your goal shouldn't be to buy players, your goal should be to buy wins," he counsels Beane. "And in order to buy wins, you need to buy runs."

Register or login for access to this item and much more

All Digital Insurance content is archived after seven days.

Community members receive:
  • All recent and archived articles
  • Conference offers and updates
  • A full menu of enewsletter options
  • Web seminars, white papers, ebooks

Don't have an account? Register for Free Unlimited Access