Moneyball and Data Analytics

Reading an article about Moneyball today made me realize the similarities in the debate that has been raging in baseball since the early 2000s and the dialogue that currently exists when companies discuss the use of customer analytics.

If you don’t know what Moneyball is, it was a highly regarded Michael Lewis book (later turned into a movie) about the Oakland A’s and how this small-market baseball team was able to outperform larger-market clubs with significantly higher payrolls. A perhaps oversimplified (but helpful) summary is that small-market teams were able to use unconventional statistics and analytics to identify ballplayers who would contribute to team wins less expensively than high-priced prospects or free agents, who were evaluated using traditional scouting concepts and methods.

While the pendulum continues to swing back and forth between camps that favor statistics versus those that favor more traditional player evaluation, one thing is clear: most people who have done much thinking about the subject believe the more consistently successful teams employ a hybrid approach.

Experience and judgment that is grounded and augmented by analytics is the winning formula, which is what we have been saying to clients for years about where customer analytics fits into business strategy and practice.

It’s less about becoming a “data-driven organization” and more about simply using the tools at your disposal to make better, more informed decisions. While successful companies must embrace the notions and mindset that comes with using customer analytics, they need not do so to the exclusion of their experience and market knowledge. Analytics vs. traditional business practices isn’t a war to be fought and won by either side. The two can (and should) work harmoniously together to achieve faster growth, higher margins, and lower business risk.

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