What do the Oakland A’s, New England Patriots and New Castle United share? They’ve each applied Moneyball techniques to their respective sports. In the book Moneyball, Michael Lewis describes how, over a five-year period, the Oakland A’s used analytics to win more regular-season games than all but one major league baseball team while spending fewer payroll dollars per win than other teams. Oakland’s data-driven approach has spread to other sports, helping teams identify predictive skills and hire talent to produce wins. In today’s labor market, many employers base their hiring decisions on characteristics that bring relatively little value to their organizations while ignoring more valid selection criteria. We’ll explore how to select employees based on more valuable and predictive characteristics to bring sustained Return on Talent Investment (RTI).
HR’s Use of the Moneyball Concept
In its simplest form, the Moneyball concept is this: quantitative statistical analysis can more precisely predict a player’s future performance than previous evaluation models. In the US, both baseball and football are using analytics to guide personnel recruitment and performance. With the lowest payroll in the American League and 94 wins, the A’s had the highest return on their talent investment for 2012. In the NFL, the New England Patriots paid the lowest cost per victory of all teams in the playoffs last season. Analytics continue to produce results in sports.
The Moneyball book and ensuing movie have spawned analytics that are now applied beyond sports and into the business world. A sport, by nature, is a zero sum arena with clear winners and losers. In business, there is not a zero sum arena. Winners and losers are measured by productivity, market share and ultimately by shareholder value.
HR is responsible for recruiting the organization’s primary assets—its workforce. For the past decade, HR professionals have worked diligently to become data-driven and to supply their CEOs, CFOs and other key decision makers with analytics for fueling better business decisions. Now and for the next three to five years, the core competency of HR will be in data analysis and workforce analytics. Metrics have been established to document processes and performance but, for many HR groups, one quantitative metric has remained elusive and even absent from their analytics: Return on Talent Investment (RTI).
Knowing your RTI is crucial because it provides a quantifiable measurement that can be compared to establish internal and external benchmarks to encourage behaviors and practices that produce desired results. Equally important, accurately measuring and reporting RTI is a powerful way to establish and reinforce the strategic value of HR to senior management—especially in today’s data-driven, cost-conscious business environment.
So what is RTI exactly, and why has it remained such an elusive metric?
Simply put, RTI is the return of a talent investment divided by its cost. The result can be expressed as a percentage or ratio that identifies the specific benefit (or gain) obtained by implementing a particular solution, program or tool. A simple expression of the RTI Formula appears in the box to the right.
Doing Is Believing
In 2011-12, the 10th largest health system in the U.S. with $9 billion in annual revenue and about 56,000 full-time staff at more than 500 facilities in 10 states, took on the challenge of applying Moneyball techniques to its under-performing talent acquisition system. “We hired people with the right fit only about 70 percent of the time,” acknowledges the VP of talent for their 8,000-employee, four-facility western Michigan region. “The industry turnover average was between 20-26%, and we were no exception. That wasn’t due to a desire to select anyone but the best, but to a lack of the right tools for selection.” In an industry pressed to cut costs and boost patient satisfaction, ineffective talent-selection processes meant trouble. “We were not assessing the knowledge, skills, and abilities that high performers need to do the complex jobs in health care, even at the entry level.”
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The organization teamed up with a workforce consultancy to reinvent their talent acquisition process and prove that evidence-based tools would deliver HR performance boosts. “I wanted to get the hiring right 95 percent of the time—a 10-fold reduction in bad decisions.” The system had to be predictive and legally defensible. The consultancy’s industrial/organizational psychologists profiled five types of jobs—from environmental services to registered nurse—that made up 40% of the region’s headcount, identifying the 20 most important attributes to perform each one. Before the pilot, there was a sense of what made a good performer and hiring was based on that. The job profiling revealed specific competencies that make the job-performance difference. The talent acquisition process was refocused on these data points.
The results of the first several months of the program suggested breakthroughs were being achieved. Some highlights include:
- Hiring managers reported that the quality of recommended candidates had improved significantly.
- Time to fill the target jobs had improved by 17%.
- The turnover rate for the new hires in the pilot was 50% better than the comparable historic rate.
It can cost $24,000 to replace an entry-level employee. Nurses can cost as much as $60,000 to replace. These are only the recruitment costs; the big expense is in orientation and onboarding a new hire where it can take several months to ramp up and reach productivity targets. The bottom line is that employee turnover has a huge price tag associated with it, and when corrected, presents a significant win for the business.
With reduced turnover, decreased time to hire and very satisfied managers, it’s no surprise that the leadership of the company elected to expand the program in 2013 to add evidence-based talent acquisition throughout the organization. This provides compelling evidence that the HR function can add value to the corporate strategy and the bottom line. Using Moneyball concepts of quantitative statistical analysis more accurately predicts future job performance and reduces counterproductive outcomes than previous talent evaluation models. Leveraging analytics works in sports and it works in talent acquisition. It’s a new ball game.