Study: Leading Organizations Use HR Analytics to Establish Standards, Support Strategy

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A study of 102 business leaders found that both high- and low-performing organizations face analytical challenges.

A study by the Institute for Corporate Productivity (i4cp) of 102 business leaders found that both high- and low-performing organizations face difficulty interpreting analytical data.

For all the interest in the potential of HR analytics to bring data-driven decision-making to workforce management, a new report reveals that many HR departments are painfully unprepared to derive real value from the mountains of data they collect.

In the December 2012 paper, HR Analytics: Why We’re Not There Yet, many of the 102 business leaders surveyed the Institute for Corporate Productivity (i4cp) cite a lack of preparedness, technical and talent shortcomings and an absence of buy-in from top leadership as key impediments to making efficient use of the data they collect and analyze.

To better understand what’s preventing HR professionals from making the most of HR analytics, i4cp highlighted the differences in data strategies and practices between “high-performing organizations” and “low-performing organizations.” Cliff Stevenson, senior human capital researcher at i4cp and author of the report, shares the top four key factors separating today’s winning HR departments from its data-deficient counterparts.

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1.       High performers use HR data for strategy, not reporting.

For years, HR professionals have been collecting data like annual retention rates and employee satisfaction scores and sharing these figures with senior-level executives. High-performing organizations, however, are upping the ante by tying these statistics to the performance of training programs, recruitment strategies, and more, rather than simply reporting the numbers.

“HR is moving into an advisory role by taking HR data, analyzing it and then determining what this information actually means to the business,” says Stevenson. “That’s where we’re seeing a new level of HR and its ability to present the most value to organizations.”

In fact, the i4cp study reveals that high performers use data for strategic, long-term planning more than twice as much as low-performing organizations – 96 percent compared to 47 percent. And 91 percent of high performers rigorously assess the ROI of initiatives and programs as opposed to 59 percent of low-performing organizations.

2.       High-performing organizations have the skills to interpret data and turn it into useful information.

Computer systems collect data but it’s up to seasoned HR professionals to make sense of it all. No wonder more than half of respondents from low performers said they seriously lack the analytical and interpretive skills needed to pinpoint trends and uncover stories in the HR data they gather. A little more than a third of HR professionals from high performers say they possess these important skills sets.

“With so much data being collected, the real trick is determining what part of your data is important,” says Stevenson. “It’s a key concern I hear from HR people. They just don’t have the skills, training or ability to look at data and turn it into information.”

3. High performers establish organization-wide processes and standards.

According to the i4cp report, 68 percent of high-performing organizations rely on automated processes to ensure the accuracy and reliability of the data they collect compared to 38 percent of low performers. That’s because, unlike manual review, automation can identify errors and flag miscalculations much more readily than humans, says Stevenson. What’s more, the automated review of data frees up HR professionals to focus on core competencies rather than mundane tasks.

So too are low-performing organizations discovering the benefit of establishing data councils – multi-disciplinary teams responsible for setting policies around the collection of data, security, even the definition of HR terms.

“We’re starting to see a lot more use of data councils among public corporations,” says Stevenson, noting councils’ early beginnings in the areas of academia and government. “These companies are taking people from a number of departments across finance and operations and making sure that when they talk about variables such as headcount, they have a definition that everyone can agree on.”

4. Predictive analytic tools are underused by high and low performers alike.

If there’s one area where high-performing organizations aren’t too far ahead of low performers, it’s the use of predictive analytics. According to Stevenson, even high performers are failing to take advantage of the power of this technology “to outsmart competitors and gain a bigger market share. It’s one thing to go back in the past and recognize correlations but correlations aren’t causation.”

Stevenson says organizations need to develop their capabilities to better use predictive analytics to determine which employees are most likely to leave, which workers are ripe for promotion and what’s truly driving customer satisfaction. In the end, says Stevenson, “it’s up to HR professionals to learn these new skill sets.”

Cindy Waxer is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at  or via Twitter @Cwaxer.

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