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Winning roles: Moneyball 2.0

Business can learn a lot from sports in terms of using analytics to optimize talent decisions in a predictive and strategic way. By Mike Kennedy, Analytics Evangelist & Director of Marketing, Talent Analytics, Corp.

Business can learn a lot from sports in terms of using analytics to optimize talent decisions in a predictive and strategic way. By Mike Kennedy, Analytics Evangelist & Director of Marketing, Talent Analytics, Corp.

From Billy Beane of the Oakland A’s to Daryl Morey of the Houston Rockets, there’s a new wave of analytics-consuming innovators across sports who appreciate the value of using data to gain and maintain a competitive advantage over their higher spending peers.

What are some applicable lessons to business?

Billy Beane Moves Scott Hatteberg to his Winning Role – First Base – There are a number of great examples in the 2011 movie Moneyball starring Brad Pitt as the innovative and analytics-using Billy Beane, General Manager of the Oakland A’s – but one specifically comes to mind. In this movie based on the 2003 Michael Lewis novel of the same name that brought workforce analytics to Hollywood audiences for the first time, there’s a scene where veteran A’s catcher Scott Hatteberg is struggling due to a weak throwing arm.

After considering the analytics, Beane decided to move Hatteberg to first base, where he thrives in a role that utilizes his catching ability over his throwing ability. This was Hatteberg’s “Winning Role” – where he was predicted to be most successful. Two other more “typical” approaches would have been for Beane to 1) Release Hatteberg from the team saying he was a losing player, or 2) Spend time “training, coaching and otherwise spending extraordinary effort” to make Scott Hatteberg be a great catcher. Both are failing approaches.

Winning Roles: Predictive Succession Planning & Hiring for Business

While this decision was based on a player’s physical attributes that are valuable in a baseball context, the concept of utilizing predictive analytics to move an employee to their best position based on their predicted strength is a very applicable scenario in business. Just as Beane retained Hatteberg and found a more valuable spot to utilize him with an eye towards team performance, today’s predictive analytics technologies make it possible to re-allocate an employee that was perhaps struggling in one role to a different (Winning) role where they are predicted to be most successful. Mike Kennedy is an Analytics Evangelist at Talent Analytics, Corp. Follow @talentanalytics.

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