HR Moves toward Wider Use of Predictive Analytics

Pressure increases to track everything from time to hire to training budgets

By Mark Feffer October 6, 2014

In today’s corporation, data is everywhere.

Operations tracks output, marketing analyzes campaign performance, the sales department tracks leads contacted and deals closed. And although recruiting and talent management is touched by data as well, on the whole, HR typically lags behind the rest of the organization when it comes to harnessing data.

According to Deloitte’s Global Human Capital Trends 2014 report, just 14 percent of HR departments are currently using data analytics. That compares to 77 percent of operations organizations, 58 percent of sales organizations and 56 percent of marketing organizations.

The reasons for the lag vary. Some cite a tendency by HR to over-rely on surveys, intuition and experience in its work. Others argue that HR isn’t getting the technical resources it needs to compile and crunch the data. And still others say HR is drowning in transactional issues. “They’re working so hard to get stuff done that they’re not taking advantage of the systems yet,” Jayson Saba, vice president of strategy for payroll company Ceridian, said in an interview with SHRM Online.

Whatever the reasons behind it, don’t expect the lag to continue. As more businesses turn to analytics to aid their decision-making, HR is feeling increased pressure to leverage big data in ways that impact everything from time to hire to training budgets. Economics, more powerful technology and demands from elsewhere in the organization will drive HR toward a routine use of data in everything it does. The focus will be less on reporting and more on offering strategic advice to management in operations, sales, finance—and across the organization.

The Rise of Data

The key to all this, experts say, will be predictive analytics. “We’re moving into a predictive analytics world,” said Gene Pease, founder and CEO of Vestrics, a Carrboro, N.C.-based company that applies predictive analytics to workforce learning programs. In such a world, data is forward-looking, used to identify the traits that make for successful performance in a particular job, or the most effective method for delivering training to employees of a certain age in a specific working group.

No longer will it be enough to report on a department’s turnover rate, said Rishi Agarwal, national leader for workforce analytics at PricewaterhouseCoopers (PwC) Saratoga, a provider of workforce analytics services. HR will have to identify why turnover is high, and come armed with recommendations to address the root cause.

For example, San Francisco analytics startup Evolv helped Xerox reduce call center turnover by gathering and studying data on the characteristics and job performance of front-line employees, then applying what it learned to the hiring process. Evolv found that employees without call center experience were just as successful as those who had it, allowing Xerox to broaden its candidate pool. Creative personalities stayed longer than those with inquisitive personalities, as did candidates who belonged to at least one but not more than four social networks. Armed with such detailed information on what made a successful hire, Xerox was able to reduce attrition by 20 percent.

Given that it costs Xerox $5,000 to train a call center employee, that reduction had a real financial impact. And therein lies the attraction of predictive analytics: It offers a myriad of opportunities for cost savings and efficiencies related to a company's recruiting and talent management efforts. As other areas of the enterprise increasingly use analytics in their work, more pressure is being brought to bear on HR to develop the same capabilities. “There’s no longer an argument over the value of analytics,” said Pease. Bottom line: The time has arrived when HR has to adopt analytics as a tool to make better recruiting and retention decisions.

Predicting turnover and assessing flight risks is one of the key areas in which Agarwal sees predictive analytics being applied. Others include assessing the quality of hires, and forecasting the benefits and return on investment of training programs. Today, he said, many companies are still grappling with the question of how predictive analytics can improve talent management issues.

Despite a slow start, most observers agree that HR is starting to embrace data. In 2013, Deloitte reported that 57 percent of HR departments increased their investment in measurement and analytics. Agarwal said that the great majority of his clients are at least thinking about how to use data across their workforce management efforts. Mick Collins, principal consultant for workforce analytics and planning at SAP, said that a rash of media coverage of big data is creating a sense of urgency to build and deliver on analytics-based capabilities.

Overcoming Obstacles

Before that can happen, observers see a number of obstacles that need to be addressed. First, data has to be compiled from disparate systems that don’t always talk to each other and often don’t agree when they do. Pertinent data resides in systems tracking payroll, time and attendance, applications and educational programs, among other things. Today, tools to integrate that data are few and far between, an area that Michael Housman, Evolv’s chief analytics officer, described as “not sexy, but key.” Over the next several years, he expects a number of companies to be created to offer solutions.

Next, resources have to be found to develop the technical tools required to manage and analyze talent and recruitment data. That presents a challenge to many HR departments, which are rarely given the same priority as sales, marketing or operations when it comes to securing IT resources, Agarwal said. Because of that, he sees more HR organizations going out-of-house to address their needs. That’s good news for offerings like PwC Saratoga, Evolv and Vestrics, which offer tools and expertise to help clients make meaningful use of the numbers.

Perhaps the most fundamental changes involve HR itself.

While the idea of HR becoming a strategic partner to the wider organization isn’t new, the idea of using analytics to accomplish that goal is. This poses challenges both in terms of skills and addressing issues surrounding privacy and compliance. Talent data “is very different from, say, manufacturing data,” Collins pointed out, and companies need to be careful in how they present even summary information. “Organizations are still unsure about the role data should play in talent acquisition,” Collins said.

Talent management, Housman observed, is typically viewed as a “soft science,” but the increasing application of data changes that. Though he doesn’t predict a rash of economists and statisticians being hired into HR, he does believe HR professionals must become comfortable using data tools. Agarwal thinks those are learnable skills.

“You can teach an HR person analytics, but you can’t teach an analytics person HR,” Agarwal said. “HR is unique when it comes to data. There are certain nuances in its structures and hierarchies. It would be like telling a software guy to go figure out the hardware specs.”

Mark Feffer is a Pennsylvania-based writer who focuses on careers and technology.


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