ANALYTICS AND INSTINCTS: WHAT “MONEYBALL” SHOULD REALLY TEACH THE ARMY ABOUT DATA-RICH DECISION-MAKING
Garrett Chandler | 06.01.22
Analytics and Instincts: What “Moneyball” Should Really Teach the Army About Data-Rich Decision-Making
Numbers and statistics, forecasting and superforecasting, data analytics and data science—these are all rising buzzwords within US Army circles, and rightfully so. Using historical data helps optimize systems and processes while using forecasting tools to visualize the future improves planning. New software even takes most of the dreaded math out of the hands of users and offers simpler visualizations that help leaders make informed decisions. The Army is in a transition, becoming an increasingly data-rich system where decisions are based on historical data and informed as never before possible. Perhaps unexpectedly, then, recent years have seen a glut of commentary that encourages the Army to embrace data, emphasizing the argument with the most widely recognizable reference point for new, data-driven ways of doing business.
The story of the 2002 Oakland Athletics baseball team was popularized by Michael Lewis’s book, Moneyball, and even more so by the 2011 movie of the same name. A small-market team with a limited budget uses data analytics to optimize the efficiency of its roster, with a pair of executives aiming to reduce the team’s overall cost per win—and in doing so, to fundamentally disrupt the tried-and-true methods of scouting and signing players that teams across Major League Baseball had long adhered to. It’s an obvious analogy, and one with value in demonstrating the ways in which turning to data can illuminate previously hidden opportunities. But Moneyball holds a deeper lesson that is less often discussed—that of knowing when to turn to data and when to leverage other tools to inform decision-making. In short, the Army must find a balance between using data analytics and relying on the instincts and experiences of its decision makers. The problem is that during the massive (and much-needed) transition to a data-rich force, the Army is at risk of swinging too far onto the data-driven side of things.
https://mwi.usma.edu/analytics-and-instincts-what-moneyball-should-really-teach-the-army-about-data-rich-decision-making/
