The Power (And Peril) of Predictive Analytics

According to a new study, a growing number of new hires -- as well as top-performing employees -- are choosing not to stick around for long.

The 2014 PwC Saratoga U.S. Human Capital Effectiveness Report, which is based on a survey of 375 employers, finds the percentage of employee headcount for new external hires increased by nearly 40 percent from 2010 to 2013. Unfortunately, more of those new hires are leaving before their one-year anniversary: The report finds that first-year-of-service turnover increased for the second consecutive year, from 22.6 percent in 2012 to 34.1 percent in 2013. It also finds the separation rate among high-performing employees has risen to its highest level in 10 years, from 5 percent in 2012 to 6 percent last year.

The report finds that some organizations are turning to predictive analytics to boost their "quality of hire," and thus reduce the likelihood of first-year turnover by ensuring a better fit between job candidates and open positions, says Ranjan Dutta, a director of PwC Saratoga and an author of the report.

"If employees join an organization and leave within the first year, whether it's involuntary or not, it's indicative of poor selection and poor onboarding," he says.

Smart companies are turning to predictive analytics to do a better job of selecting candidates, says Dutta. Predictive analytics may help HR identify candidates who are most likely to stay (and thrive) with the company by identifying the characteristics of top performers who've held pivotal roles and then looking for those characteristics in candidates for those positions, according to the report. These tools can examine data from inside and outside the company, as well as input by the candidates via pre-hire assessments.

The use of predictive analytics for hiring is a natural occurrence, given the sheer amounts of data that technology has allowed companies to amass, says Jason Corsello, vice president of corporate development and strategy at Santa Monica, Calif.-based talent-management vendor Cornerstone OnDemand.

"Companies are sitting on more data than ever: They know who their people are, what skills they have, their educational backgrounds, their job performance," says Corsello. "The other part of the equation is that advances in technology mean that the cost of gathering all this data has gone way down."

Companies' use of predictive analytics in areas besides hiring has generated some controversy, however. In his 2012 bestselling book, The Power of Habit: Why We Do What We Do in Life and Business, New York Times reporter Charles Duhigg drew attention to the use of PA by major retailers such as Target to predict what their customers will buy.

"The use of big data such as predictive analytics can be very powerful in terms of predicting what someone's going to do," says David Walton, a shareholder at Cozen O'Connor in Philadelphia.

It can also be used for questionable purposes, he adds, citing a Belgian firm that uses big data to create credit profiles of potential bank customers.

"If they can do that with credit monitoring, then what can they do with employment practices, and what are the potential implications? It's scary and amazing at the same time."

The use of PA to make hiring decisions could lead to discrimination if not used properly, says Dutta.

"Organizations need to be very careful in how they're using this software," he says.

None of the three employment-law attorneys interviewed for this story knew of any current or recent employment-discrimination litigation concerning the use of predictive analytics for hiring. However, all agreed that the potential for adverse impact exists.

Proponents of predictive analytics say the software can actually dispel myths that often stand in the way of people with certain backgrounds getting hired.

Michael Housman, Evolv's chief analytics officer, says the predictive analytics his firm provides to its clients allow them to "hire and promote in a data-driven way."

"We've been able to dispel a lot of myths around what predicts success in these roles," says Housman.

For example, Evolv has discovered that applicants with a history of job hopping or long-term unemployment perform just as well and stay just as long as others.

"It's not a matter of where you've been, but whether you're a good fit for the job you're applying for now," he says.

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