A guide to HR analytics
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FORT LAUDERDALE, Fla. -- How does an organization get started with HR analytics? The question buzzed among attendees of Impact 2013, a talent management conference hosted by HR consultancy Bersin by Deloitte. But because HR analytics campaigns at many companies are still nascent, it's a question more easily asked than answered.
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Bersin by Deloitte talent management Lead Analyst Stacia Sherman Garr referenced this fact when introducing the session "Big data in HR: Driving improvements from insights." "For this year, I wanted to find a series of corporations that could really talk about big data in HR and that were advanced enough to give you some insights," she said. "Turns out that was really hard to do." She and other conference organizers ultimately succeeded , however, and the Impact 2013 conference features an entire track dedicated to analytics.
Despite the fact that HR analytics experts are somewhat hard to find, speakers offered up five best practices that can help HR managers build strong HR analytics campaigns.
1. Understand the difference between HR metrics and HR analytics
"Time to fill isn't an analytic -- it's a number," said Katherine Jones, Bersin by Deloitte's director and principal analyst for human capital management (HCM) technology. She described the difference between a metric and an analytic as "a block versus a Rubik's Cube," and said the goal of HR analytics is to become predictive.
Akil Walton, vice president of talent management and organizational effectiveness at Aleris International, an aluminum manufacturing company based in Beachwood, Ohio, pointed out that internal stakeholders generally aren't interested in HR metrics. "[Business leaders] care about cost and profit," he said. "Attrition, turnover -- [those are] HR things. A lot of them care more about how they are going to be profitable."
Jonathan Ferrar, IBM human resources and workforce analytics vice president, explained how a training course titled "From Data to Action" helped define the distinction between metrics and analytics for IBM's HR leaders. "Stop just responding to the data requests. How many people left my business last month? 522? So what," he said. "Why did they leave, is the trend up or down, and what is that telling me versus the employment rate [and] the GDP [gross domestic product] of the country?"
2. Confer with business leaders and start small
If business leaders aren't interested in HR metrics, then what are they interested in? Several speakers suggested that HR leaders directly ask and listen to the needs of their internal stakeholders to guide HR analytics campaigns.
"The approach I recommend -- and this may offend some folks, but I didn't start with HR," Aleris' Walton said during a panel discussion on predictive talent analytics. "I went straight to the business leaders, and I wanted to know what was going on, and how do I help provide insights that [they] don't even know about [their] own business." He suggested that HR managers ask business leaders what metrics they are being held accountable for to understand what information could help them be successful.
Walton also advised HR leaders to keep HR analytics initiatives small and simple initially, and go for a few "quick wins."
"Taking two or three measures and providing intelligence to the business leaders -- that's it. It's almost that simple once you actually sit down with the business leaders [and talk] about what their key challenges are," Walton said. "One quick win is [to look at] the number of employees you have [against the] profit plan of the business. If that profit plan says they should have 500 employees and they have 550, then you want to ask why, and what else is being impacted. [And] that's just two metrics."
IBM's Ferrar espoused a similar view for organizations just getting started. "Don't bite off too much," he said. "Focus on one business problem."
3. Align HR analytics definitions
One conference attendee, who asked not to be identified and whose company has just started doing HR analytics, said disagreement among executives and business units over the accuracy of HR data is a major barrier to adoption. Similarly, Ferrar said that even if companies can quickly and easily extract a data point from an HR system, such as the employee headcount number, an inconsistent set of definitions can lead to back and forth about whether the number is inclusive or accurate. In light of the potential confusion and wasted time, he stressed the importance of developing an explicit methodology around HR analytics.
"Make sure things are very consistent," Ferrar said. "Get down to real, real specific definitions."
4. Build a diverse HR analytics team
IBM's Ferrar identified three skill sets that need to be present in an HR analytics team: HR, statistical and consulting. He explained that a person with consulting experience is key for communicating with senior executives and discussing which questions and drivers are important and why. "I recruited someone with a consulting background who didn't mind being slightly provocative and quizzical to senior people," he said. Mayank Jain, director of analytics and reporting for global HR at eBay, agreed that a person with consulting experience can be "very helpful."
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Ferrar added that while the statistical component is often top-of-mind for leaders constructing analytics teams, an HR person is also essential to tie the campaign back to the people behind the numbers. "If you've got too much statistical, you'll miss the nuances, [and] the fact that the behaviors, competencies, motivation and culture are part of running a business."
Aleris' Walton said one of his best hires was an intern from a doctoral psychology program. "If this is not something that comes to you naturally, you want to solicit for some help," he said.
5. Make HR analytics data easy to consume
Ferrar encouraged HR leaders to use data visualization to allow senior executives to glean insights easily. During his presentation, he showed a sample color-coded attrition heat map, in which deep red blocks signified segments of employees who were highly likely to leave the company, and lighter squares represented others demonstrating lower risk. He also showed a sample of a graph his team produced plotting a bell curve of increased compensation versus attrition, and at what point the maximum benefit could be achieved. Using these charts, he explained that HR leaders can concentrate their retention efforts on valuable employees with high attrition risk instead of taking a less focused approach.
HR leaders also should "take risks with new tools," and enter into HR analytics campaigns keenly focused on business problems, Ferrar said. "What problem are you trying to solve? What's your hypothesis?" he asked. "Move from data extraction to data analytics."
Emma Snider is the associate site editor for SearchFinancialApplications.com. Follow her on Twitter: @emmajs24.
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