Get Your Talent Analytics Off The Ground

Human resource organizations that analyze data to make better decisions about talent are twice as likely to improve their recruiting efforts as those that don’t.

They’re also twice as likely to improve their leadership pipelines, three times more likely to realize cost reductions/efficiency gains, and two-and-a-half times more likely to improve talent mobility, according to a Bersin by Deloitte study.

But even though 75% of companies think using talent analytics is important, just 8% think their HR organization is strong in this area, according to a new Deloitte University Press report, “Global Human Capital Trends 2015.”

So why can’t HR leaders get off the ground with talent analytics?

“It does take first-rate technology to be able to leverage big chunks of data, and that technology is available,” says Jeff Haynes, Oracle vice president of HCM transformation. “But in order to turn that analysis into smart decisions and actions, HR needs people with a different skillset—including data scientists, economists, and even psychologists—who can take a workforce management hypothesis, develop an experiment, observe the data, come up with the analysis, and then drive that back to the business to persuade change that can drive better business outcomes.”

Secrets to Worker Success

Haynes points to the example of AMC Theaters, from an IBM Global C-suite study. HR leaders at AMC interviewed for that study believed they could best predict highly successful concession sales associates by their level of expertise with the cash register, and that high turnover in this segment was unavoidable.

Using talent analytics, the company tested which traits were the best forecasters of successful concession workers, and which most influenced retention.

What it found was that cash register adeptness did not predict which concession workers succeeded and stayed on the job. What did matter were traits such as integrity, initiative, and social sophistication—or the ability of the concession worker to engage with customers rather than just sell to them.

AMC, which factored those statistical findings into the screening of new hires and ongoing training, has since reduced turnover by 50% and increased its bottom line margin by 1.5%, according to the company.

“HR needs to make valuable strategic recommendations to the business,” Haynes says. “But you can't just snap your fingers and say, ‘I want to do that.’ You have to build a culture of experimentation and innovation, and work toward it.”

So how can HR organizations build that culture and begin implementing talent analytics?

The first step is to make sure your HR data is in order, and to know what questions you want answered. “Start to look for easy, low-hanging fruit that you can clip off,” Haynes says. “For instance, insight around turnover and predicting attrition can be gleaned pretty easily by running regression analysis and correlating some variables—stuff starts to pop up.”

Form Strategic Partners

At the same time, bring in people—and not necessarily from the outside—who have experience doing statistical analysis.

“Across your organization, there are people who have been performing these same kinds of analytics on customers for years, probably in marketing, who can function as your strategic partners,” Haynes says. “You can take their methodology around understanding perceptions and behaviors and apply it to employees instead of customers.”

The goal is to bring together people who aren’t afraid to experiment and innovate with HR data and processes. But Haynes emphasizes that HR leaders often get hung up on the perceived obstacles, such as imperfect data, a lack of resources, or common HR inertia.

“You’re never going to be perfect,” he says. “The key is to just get started. And with a few low-hanging insights or a couple of wins, you’ll start to gain credibility. The next thing you know, maybe you can start to build a business case around getting the investment for the people and technology to get your talent analytics off the ground.”

The risk of starting an analytics initiative is low, Haynes says, but there is a high risk in not doing anything.

“We are on the verge of being able to leverage all this massive workforce data, and there's power in it,” he says. “If HR is slow to start tapping talent analytics, some other corporate function will—maybe IT or finance—and then a good chunk of strategic HR runs the risk of being lost outside the function. This is the future direction of HR. It’s time to get off the ground and go.”

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