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Winning in sports or business requires knowing and measuring the drivers of success. This is the lesson of Michael Lewis’s best-selling book, Moneyball. Moneyball tells the tale of how the Oakland A’s used advanced analytics to isolate the metric that could predict a baseball player’s potential to score runs.
For years, baseball teams unquestioningly relied on batting average to determine which players to hire. But using advanced analytics, the Oakland A’s determined that the On Base Percentage (OBP) is a better predictor of a player’s potential to score runs.
Once the A’s started basing hiring decisions on this metric, they began winning, most notably the American League division title. The A’s won because they knew what factors caused them to win.
Business results tend to be characterized into three broad buckets:
These business outcomes are caused by commercial activities that generate specific metrics such as number of calls, customer satisfaction, customer churn, revenue, and costs. For example, increasing the number of calls on a particular medical specialty may drive higher market share, or not. Higher customer satisfaction metrics may or may not result in improved customer retention.
Contemporary advanced analytics can separate out the meaningful versus the interesting metrics. We use Bayesian Belief Networks (BBNs) to examine a wide range of interacting variables that may be impacting your business results. With BBNs, we can estimate the probability that a particular metric is actually causing your business results. Specifically, we leverage AWS Data Lakes tools to have the computational power to examine millions of data points from disparate sources like claims data, medical records, prescription data, and company-generated data to establish which activities are actually producing your business results.
We have a robust process to work with our clients to answer four questions regarding their Key Business Metrics (KBMs):
