The use of analytics in the sports world has much to teach managers about alignment, performance improvement and business ecosystems.
Sports analytics are all the rage now. The Moneyball story about the Oakland A’s use of analytics has made its way into the collective consciousness, and the appetite for more knowledge about the field has steadily increased year by year. The MIT Sloan Sports Analytics Conference, for example, has grown from about 175 attendees in its first year in 2007 to more than 2,000 in 2014. Called the “Super Bowl of sports analytics” and “TED talks in cleats,” the conference has catalyzed academics, professional and college teams, and the press to focus much more heavily on analytics to understand various aspects of sports performance and business. Almost every professional baseball team now has at least one professional quantitative analyst on staff, and many basketball, football and soccer teams do, too. Even some high school teams now employ quantitative analysts. In general, however, sports teams are still lagging behind businesses in their use of analytics. For one thing, even the most successful pro teams are still relatively small businesses that can’t feasibly employ hundreds of analysts like a large bank or retailer can. Also, many old-line coaches, managers and executives don’t trust or understand sophisticated sports analytics. And, as far as its application on real teams is concerned, the discipline is still in its infancy. The Moneyball story about the Oakland A’s took place in 2002, when sports analytics was quite new. In contrast, the first analytics group I have found in businesses dates from 1954 at United Parcel Service (UPS). Despite this, businesses can still learn much from the use of analytics in the sports world. I recently interviewed more than 30 representatives of teams, sports analytics vendors and consultants for a report on the state of the art in sports analytics. (See “Further Reading.”) I focused on three different areas of activity, each of which is growing rapidly. In order of decreasing prevalence, they are: team and player performance analytics, sports business analytics, and health and injury prevention analytics. In this article, I describe five key lessons from that research that almost any business could adopt.