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Tapping the value of big data in HR requires skills and technology

While experts say using big data in HR can have big payoffs, only a handful of companies today are achieving them.

In theory, big data in HR offers a laundry list of potential benefits for HR managers under pressure to play a more strategic role in their organizations. Successfully slicing and dicing large volumes of internal and external information promises a fast track to attracting all-star talent, enhancing employee engagement and uncovering out-of-the-box ideas for furthering business goals, according to some vendors.

Unfortunately, the reality of big data in HR doesn't yet live up to its potential, said Karen O'Leonard, vice president of benchmarking and analytics research at Bersin by Deloitte, a consulting firm based in Oakland, Calif. Only 14% of the HR functions the firm surveyed last year were utilizing advanced or predictive analytics, while the remainder were still focusing on creating traditional reports and dashboards of talent metrics. "There's a lot of potential that is largely left untapped today," Bersin's O'Leonard said.

So if big data in HR is so great, why aren't more HR organizations capitalizing on it?

O'Leonard and other industry analysts say that success hinges on more than just installing a new piece of software or enhancing the existing HR management system with a new big data module. It's also a matter of skills.

"The people who will succeed with big data are those who become good at analyzing unrelated information," said Jason Averbook, chief of business innovation at Appirio, a San Francisco-based cloud consulting company. "That means truly differentiating the business by saying, 'This is our competitive advantage, and this is how we are going to measure it.' Oftentimes that comes from combining data that initially appears to be unrelated."

Early returns of big data in HR are promising

There's growing evidence that big data and sophisticated analytics are worth the effort required for success. Though small, the group of organizations that are adept at advanced analytics have better recruiting processes and stronger leadership pipelines than the laggards, according to O'Leonard.

Analytics can also significantly reduce costs and improve efficiency, she added. For example, O'Leonard worked with one retail bank that found a link between employee theft in certain branches and the size of the district managers' territories. After adjusting regional responsibilities, the bank minimized theft at problem locations, which saved money and had ancillary benefits in better employee engagement and improved union relationships.

In addition, these organizations get a leg up when it comes to capitalizing on talent, according to David Bernstein, vice president of big data analytics at eQuest, a job-posting distribution company headquartered in San Ramon, Calif.

"Without the right people in place, you could actually fail as a business. And you can't talent-manage and grow people if you don't have the right ones to start with," Bernstein said. "If you bring the wrong people in, everything else after that is remedial training."

Skills and data quality roadblocks to using big data in HR

But doing well with big data in HR requires HR organizations to do more than just gather statistics for traditional reports that summarize employee headcount and turnover rates, analysts say.

"Companies must look beyond their internal data by analyzing information from LinkedIn and other outside sources to find new talent, for example," Appirio's Averbook said. "That's when they can say, 'We have this salesperson that we recruited from company X who excels at selling product X. Let's go back to Y to find someone else who's also good with this product.'"

For some organizations, this means adding staff members with backgrounds in statistics or industrial and organizational psychology. "Some HR managers will need to bring in folks from outside of HR, either through rotations from other departments or from other professions, who are data- and number-centric," eQuest's Bernstein said. He recommended financial analysts, economists and physicists as potential candidates.

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And in addition to finding people who are adept at gathering and analyzing large data sets, HR managers also need people who can sell the results to business leaders.

"A key differentiator for successful companies is having people with strong consulting skills," Bersin's O'Leonard said. "You might have the best data [in the] world, but if you can't explain what it means to business leaders in a language they understand, then all that fancy analysis is wasted."

Data quality can be another stumbling block. Business stakeholders must believe in the accuracy of the underlying information used for advanced analytics. "Trying to do predictive analytics on top of incomplete or garbage data may lead to outcomes that are worse than not doing the analyses," Bernstein said.

In some large organizations, improved data quality might necessitate a new data management architecture or enhanced data governance processes, O'Leonard said.

Shop carefully for big data systems

Analysts say there's no shortage of commercial big data products vying for the investment dollars of HR managers. "All of the big HR vendors are producing some type of analytics solution," O'Leonard said.

How can HR managers find the best fit for their particular needs? Bernstein said some up-front skill development may be required before organizations start shopping for systems. "First develop the right mind set for using data, then the right skill set, and only then consider the tool set," he said.

Appirio's Averbook recommended that organizations look for big data tools that complement existing IT investments. "Choose a platform that's going to work for you based on the technology you have in-house or in the cloud," he said.

Finally, once new analytics applications are in place, HR managers should cultivate a quick win to help sell further commitments in sophisticated analytics to business leaders. "Start small and focus on a single, breakthrough project," Bersin's O'Leonard said.

Examples she suggested included efforts to analyze key drivers behind employee engagement, recruitment or retention. "Once you build up credibility in one area, you'll be better able to make the leap to applying data and analytics to solve larger business problems," O'Leonard said.

About the author:
Alan Joch is a New Hampshire-based freelance writer who specializes in enterprise applications and cloud computing. Follow him on Twitter @alanallegro.

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