How 'Moneyball' Measures Up as an HR Approach

The corporate finance adage of “We cannot manage what we do not measure” echoes through many additional business functions and disciplines thanks to breakthroughs in data analytics, behavioral economics and the new “science” of decision-making. So it’s no wonder that the notion of applying the metrics-heavy recruiting technique that Billy Beane, general manager (GM) of the Oakland Athletics (the Oakland A’s), used to succeed in the movie “Moneyball” has piqued the interest of some analytics-centric HR professionals.

“We do so many things in HR that are done for the simple fact that ‘we’ve always done it this way,’ ” asserted Tim Sackett, SPHR, executive vice president at HRU Technical Resources, a Michigan-based IT and engineering contract staffing firm. “What Beane did with the Oakland A’s was to truly throw out the old ways in favor of looking at the ‘scientific data’—the metrics—that make up the best ballplayers. We have this same opportunity with our employees.”

Analytics in Action

Political leaders look for alternatives to gross domestic product (GDP) as a barometer of national progress. Doctors seek more effective treatments via evidence-based medicine. Scientists have redefined basic units of measure such as the meter and the kilogram. And business leaders and economists search for alternatives to traditional measures of financial and economic performance.

Today, for example, economists routinely integrate the mood of citizens, via “economic sentiment” and “consumer confidence” measurements, with other traditional data to produce their forecasts. Some business executives have begun measuring the quality of their organizational cultures thanks to new correlations between culture and innovation, retention and financial performance.

Rethinking Recruiting

The book that the movie was based on, also called Moneyball, was published in 2003 and written by former bond salesman Michael Lewis, predates Freakanomics and, like that book, serves as a seminal work on the value of rethinking conventional wisdom regarding what, and how, we measure.

In the movie “Moneyball,” Beane is forced to rethink how he scouts and hires baseball players because his small-market team cannot afford to outspend much wealthier teams such as the New York Yankees and Boston Red Sox on free agent signings. Instead, Beane and his assistant apply measurement techniques collected from the financial realm to unearth baseball players that other teams have undervalued.

While other GMs pay top dollar for high-priced baseball hitters with high batting averages, gaudy home-run numbers or the blessing of their scout’s subjective evaluations (for example, “sweet swing”), Beane seeks lower-cost players with high on-base percentages and those who force opposing pitchers to throw higher numbers of pitches. These metrics, it turns out, correlate better with games won than do traditional individual statistics and a scout’s gut feel. Beane’s approach generated some benefits, as the cash-strapped A’s made the playoffs four consecutive years while averaging an impressive 98 wins per season during that stretch.

Though critics of the book and movie have pointed out that excellent pitching, and not just efficient run-producing hitters, helped the team succeed, the willingness to look at new measurements related to success is the most valuable lesson of the story.

“Perhaps there is a way to select employees based on new, carefully honed criteria that can elevate corporate performance: better productivity and at a lower cost,” wrote two Australian business professors in the academic paper, “Can Financial Derivatives Inform HRM [HR management]?: Lessons from Moneyball.”

More companies are looking for these criteria. “HR is ripe for a similar evolution,” agreed Ravin Jesuthasan, a Chicago-based Towers Watson managing director and the author of the book Transformative HR: How Great Organizations Use Evidence-Based Change to Drive Sustainable Advantage (Wiley, 2011). “We are starting to see many progressive organizations apply analytics in the recruitment and management of talent.” Jesuthasan pointed to analytical tools such as return on improved performance curves, which he says “can help organizations analyze where improving performance of talent in different roles really makes a difference to the organization and the types of HR investments that are most effective in improving that performance.”

Using the Insights

Baseball, of course, is much more measurement-friendly than many businesses; one team wins and one loses according to a clear set of rules. In business, underperforming managers cannot be sent down to the minors or traded to another team. Plus, the components of talent that correlate to positive business outcomes vary by industry and company. That said, HR professionals, consultants and academics point to several ways in which HR managers can use “Moneyball” insights to strengthen their function’s performance, including the following:

Get analytically literate. In the book The Future of Human Resource Management: 64 Thought Leaders Explore the Critical HR Issues of Today and Tomorrow (Wiley, 2005), Mark Huselid and Brian Becker exhorted HR professionals to develop a “competency to recognize the appropriate measures, and the appropriate analysis, for the strategic questions confronting them.” This does not require an advanced degree in statistics, according to Huselid and Becker, who noted that “Moneyball” is not about senior executives personally conducting sophisticated data analysis. But it is about senior executives understanding the analytics [as Lewis writes in his book] ‘well enough to use their conclusions.’ ”

Question tradition. When you ask yourself, “Why do we do this?” and the answer is either “That’s the way we’ve always done it” or “That’s what everybody else does,” you have a potential “Moneyball” situation, said Thomas Timmerman, SPHR, professor of business management at Tennessee Technological University in Cookeville. Some of the most popular selection methods—for example, experience, unstructured interviews—are less valid that some less-popular methods—for example, intelligence testing, structured interviews, he said. In his academic paper on the application of “Moneyball” insights to HR, Timmerman cites research showing that “experience becomes a weaker (and less valuable) predictor of performance over time, but cognitive ability becomes a stronger (and more valuable) predictor of performance over time.”

Cultivate analytical understanding. Pre-employment screening and testing—a common form of HR analytics—is highly advanced and continues to improve. “If you aren’t using this screening religiously, you are missing out on making better hires for your organization,” said Sackett, who notes that many hiring managers do not trust screening tools, in large part because they do not understand the tools.

“As HR and talent professionals we do a relatively poor job at really explaining how we should be using these tools,” Sackett said. “There is no doubt, when using these tools over the long run, we will hire better talent. But once in a while, a good one will slip through the cracks.” When that occurs, HR managers should provide evidence of these tools’ effectiveness to counteract negative perceptions among hiring managers.

Achieve balance. In the movie, Beane heatedly fires his scouting director, Grady Fuson, for failing to get on board with his analytical approach. The drama played well on screen, but didn’t happen in real life: Fuson left the team on his own accord and was rehired by Beane in 2010. Fuson told the San Jose Mercury News that he and Beane had reached a “happy medium” in balancing qualitative talent scouting insights with numbers-based analytical insights. “I’d like to think now that it’s 60-40 with scouting being the 60,” Fuson said. Sackett also counsels balance, noting that some organizations “go so far into using analytics that they forget good old-fashioned common sense.”

Balance is crucial, agreed Jesuthasan. “Intuition and good judgment have often been the hallmarks of the strong HR practitioner,” he noted. “However, it is impossible to deliver the ‘evidence’ without what we would call logic-driven analytic.”

Eric Krell is a freelance writer based in Austin, Texas.​