The book, and subsequent movie, Moneyball tells the story of how the Oakland A’s disrupted the business of professional baseball by using advanced analytics (Sabermetrics) and an innovative way of evaluating players to compete and win against teams with significantly higher payrolls. In a time when most companies are being asked to do more with less, it may be helpful to think about how to apply some of these concepts to your business.
The Oakland A’s front-office found innovative ways to predict which players would provide the most value. They did this by questioning the norms of the industry and conducting comprehensive statistical analysis to provide better predictive information about which players would add the most value for their relative cost.
Several of the business themes explored in the book include: insiders vs. outsiders (established traditionalists vs. upstart proponents of sabermetrics), the democratization of information causing a flattening of hierarchies, and “the ruthless drive for efficiency that capitalism demands”. The book also touches on Oakland’s underlying economic need to stay ahead of the curve; as other teams begin mirroring their strategies to evaluate offensive talent, diminishing the Athletics’ advantage, Oakland begins looking for other undervalued baseball skills such as defensive capabilities.
It may be helpful to take a step back to question “the way we’ve always done it” and look for creative new ways to compete and better serve your customers. The recent advancements in BigData and predictive analytics provide a powerful competitive advantage for those companies that are able to leverage it to actually drive new behaviors and decision-making.
In the Harvard Business Review article Making Advanced Analytics Work for You, they say “we have found that fully exploiting data and analytics requires three mutually supportive capabilities. First, companies must be able to identify, combine, and manage multiple sources of data. Second, they need the capability to build advanced analytics models for predicting and optimizing outcomes. Third, and most critical, management must possess the muscle to transform the organization so that the data and models actually yield better decisions. Two important features underpin those activities: a clear strategy for how to use data and analytics to compete, and deployment of the right technology architecture and capabilities.”
In Moneyball, Billy Beane (A’s General Manager) clearly had the “muscle to transform the organization” so that they actually valued and used the information provided. It drove their decision making, many times flying in the face of their established norms and hunches.
Starting with the business outcomes (e.g., What decisions could we make if we had all the information we need?, etc.) and then defining the data sources and model will lead to better outcomes than starting with the data and trying to work your way upstream.
The HBR article goes on to say “performance improvements and competitive advantage arise from analytics models that allow managers to predict and optimize outcomes… the most effective approach to building a model rarely starts with the data; instead it originates with identifying the business opportunity and determining how the model can improve performance.”
What could you do to greatly improve your customer’s experience? What if you could better predict which candidates would make better employees? What decisions could you make that would dramatically decrease your labor costs? What information would be required to best answer those questions? What data sources could be pulled together to provide more clarity?