In 1977, Bill James published a landmark manual that codified the empirical analysis of baseball (Sabermetrics). During the Oakland A’s 2002 season, General Manager Billy Beane famously used some of these concepts to field a team that, as a result, over-delivered on their value relative to their salaries. Beane’s innovative approach was chronicled by author Michael Lewis in Moneyball: The Art of Winning an Unfair Game. The sports data revolution was born. In 2008, five NBA teams had an analytics team; by 2016, all 30 teams had data scientists on board. From football to tennis, golf, and even little league baseball, new statistical tools are changing the game.
Becoming an organization that makes data-fueled decisions requires more than sophisticated analytical methods and tools. Fulfilling the promise of analytics requires a sustained commitment to data-driven decision making—for most companies, this means implementing a formal analytics strategy. One of the barriers to unlocking the full potential of analytics is organizational. The analytics team typically operates in its own silo, which results data-driven decisions harder to make. Because of this, data-driven decision making is unlikely within these organizations. You drive change by integrating and using analytics on a daily basis.
How well have you incorporated analytics in your decision making? Is your company using data to discover
new and innovative ways to mitigate risk? Do you have a strategic plan for analytics in place?
GOAL: Drive employee risk lower create less injury, incident, and losses.