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Using Analytics to Win the War for Talent


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Moneyball

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).

RTI Defined

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?

Screen shot 2013-01-14 at 7.12.16 PMSimply 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.”

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.

Kurt is a Principal and the Chief Marketing Officer of A-C-T Bridge. Kurt’s experience includes consulting, HR outsourcing and sales in product and service organizations including GM, Exult and Spherion. Kurt was a founder and Chief Sales & Marketing Officer at talent assessment leader PreVisor, Inc. He helped the company grow revenues, expand internationally, increase market share and develop branding through organic growth and a series of acquisitions.
  • http://twitter.com/mekncl Mike Kennedy

    Good read – very interesting to see Moneyball in action but I’m not sure I really agree employing I/O psychologists is an example of using analytical techniques. I don’t think Billy Beane uses psychologists to inform his decisions, so why would HR? There are far more modern and business-friendly ways to apply analytics to hiring.

  • http://twitter.com/virtualjoe Joseph P. Murphy

    I/O Psych is the discipline and science of measurement and analytics in the workplace. This is a perfect example of where and why to deploy I/O Psychs. High population jobs, complex performance demands, distributed decision making. I/O’s bring skills sets similar to Lean and Six Sigma to the business process called staffing. The hiring decision will always be an act of personal judgment. The data that supports the judgment can make all the difference. http://www.shakercg.com/blog/2011/03/alchemy-and-algorithms-%E2%80%93-recruiting-by-ego-or-evidence/

  • Andy Stanczyk

    This is a good read and I agree with the use of statistical analysis. I’d argue that the use of statistics is not the Moneyball concept. Beane and the A’s had to think differently than other teams in order to compete and statistical analysis was the differentiator that was used. Moneyball HR should be thinking and doing differently than your competition within the confines of your business operation in order to excel.

  • Kurt Ballard

    Thanks for the comments and feedback. Yes, the science of talent measurement is
    similar to Lean and Six Sigma. Using I/O experts can bright HR Analytics
    to a new and highly useful level. HR is surrounded by data and seeks a
    disciplined way to leverage it. In my view, the core competency of HR now
    and in the next 3-5 years will be data analysis and analytics. The game is
    changing. HR execs that begin to think differently about how data can drive transformational change will be the winners.

  • http://twitter.com/mekncl Mike Kennedy

    The idea of using data to inform decision making around people is good, we all agree; the problem I’ve found is often the wrong HR data is being used. Coming from a business perspective, most HR metrics track historic activities and offer very limited value or insight for anyone outside HR. Tracking competencies, headcount or attrition doesn’t really add value for the business without additional context. They simply aren’t actionable. For example, a functional executive can’t do much with knowing the “attrition rate was 24% last quarter” without knowing more details about the people who left. What did they have in common? Were they top, middle or bottom performers? Analyzing these activities in abstraction from business performance data often amounts to squeezing blood from a stone. As the business would say, “so what?”

    As for I/O experts, if they are trained in ever-evolving analytics methods and able to run regressions and correlations to generate insight that adds value for the business, more power to them. In my experience, that’s rarely if ever the case. I/O psychologist methods historically have included time consuming interviews and other qualitative methods that take hours and simply do not scale across large businesses.

    I hope you’re right Kurt and HR thinks differently about data in the next 3-5 years. Once HR executives realize numbers can actually let their business find and value it’s employees, know how to engage and retain them, I think they will be amazed at the value of analytics.

  • http://twitter.com/gregsroche gregsroche

    As Kurt stated, business is not a zero sum game, and, in addition, there are no consistent “baseball card stats” by which a person can be measured throughout their career. Many HR people have focused on what attributes successful employees have in common without knowing if the definition of a successful person in their organization is actually driving business results. Most performance management systems and processes simply measure individuals too infrequently or have too much subjectivity in their scoring. I am all for using data and analysis to improve people processes, but I think we need to focus on consistent measures of “y” before we spend all of our time on “f(x)”

  • Glen Cathey

    I’m a big believer in the ability to use data to empower “Moneyball recruiting” – I wrote a piece on the very topic back in 2011 before it became such a popular concept, and it includes many real examples of how you could truly take a Moneyball approach in talent acquisition – beyond analytics: http://booleanblackbelt.com/2011/09/big-data-data-science-and-moneyball-recruiting/