Moneyball Revisited: Are You Ready to Adopt Analytics And Elevate your Business?

The beginning of March signals the start of preseason exhibition games for Major League Baseball (known as Spring Training) in winter-free Florida and Arizona. For decades, children have collected baseball cards – a pocket sized paper database of key statistics of their favourite major league players. The game is easily the most data friendly sport with hundreds of discrete events per game and a long history of accurate data; all this from over 2,000 games a year for over a century. Businesses would be thrilled to have this level of data capture and yet they struggle to capture it. When computing power exploded in the 1990s, it was no surprise that Major League Baseball became the leader of analytics in sports and essentially, the business of sports.

Yankees Roster = 114 million. Athletics Roster = 39 million

Player Budget

The most compelling example about the use of analytics in baseball comes from the novel turned motion picture, Moneyball; this concept introduced the world to the growing use of data analytics in making decisions. The Oakland Athletics, a low budget franchise, began using statistics and data mining to find undervalued players. Those who have seen the movie or read the book know that the dramatic tension came from old guard scepticism of this new data and analytics based approach. The false paradigm dramatized in Moneyball pitted a winner-take-all struggle between old school talent scouts and the new school geeky computer nerds using analytics.Since the book was published, some of the media classified baseball organizations into these two paradigms of “old school” and “new school”. All the while, many teams have been investing heavily in analytics. Amongst more recent poor performers looking for improvement, new leadership of the Chicago Cubs and the Houston Astros invested heavily in analytics; each teams focus was around player development and improving in game performance. Major League Baseball’s recent investment in telemetric systems has created reams of new data. Through analytics of PITCH F/X (which tracks ball movement and speed) the two teams have done especially well at helping middling pitchers change their approach and pitch breakdown. Both teams made the playoffs for the first time in a decade.

As in business, it comes down to cultural buy-in and systems. These firms have employed coaches willing to merge their long baseball resumes with new data from analytics. The role of the analytics group within baseball clubs work at any level of the organization with strong support from senior leadership – this may sound familiar too. The actual challenge comes from the best way to merge approaches: how do we integrate analytics into existing operations?

We encounter clients that are progressive and embrace new solutions to enhance operational performance. Then we see businesses that are reluctant to develop an analytics capability because it doesn’t fit into their current operating model, and think they are doing fine with the old methods. However, it is probably a good idea to start investing early – even if the business is doing well! – in order to gain deeper knowledge into the influences that impact key performance indicators.

The investment in analytics often pays off in unexpected ways. Applying analytics and identifying the areas of focus can dramatically enhance the visibility of your organization, especially within the supply chain and logistics sectors. Knowing how your third party contractors are performing on projects will lead to elimination of inefficiency, if you leverage the insights garnered.

The Moneyball revolution is complete in baseball. The question remains: for your industry, are you on the path to analytics success?

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