Binary StreamHuman resources analytics are being embraced by more and more organizations these days. HR analytics can be especially helpful in spotting trends in your company, influencing hiring decisions, and identifying career development (i.e. employee retention) and promotion opportunities.

Writing at, Margaret Rouse says there’s a need for human resources analytics because companies have enough data to make such analytics effective. But there is a problem: the data often gets spread out in various locations and isn’t gathered under one roof.

As Rouse points out, there are a lot of HR analytics software offerings. Some organizations also create their own data warehouses and incorporate human resources intelligence by using business intelligence applications in conjunction with the data warehouses. She also mentions that “[o]ther companies use data federation technology to aggregate data from disparate sources in a virtual database.”

Tracey Smith, writing at the blog, has identified five reasons people aren’t using human resources analytics and how to overcome these common objections. Topping the list is a perceived lack of quality data. Smith says we should not let that perceived lack be roadblock to the implementation of HR analytcis because data will rarely — if ever — be perfect.

Also on Smith’s list is lack of support from organizational leadership. “While 30 [percent] of new CHROs are being selected from outside of HR, the fact remains that most HR leaders came from traditional HR (aka non-analytical) backgrounds. It will take specific examples of what can be accomplished with HR analytics to help these leaders see the value,” writes Smith, who is — it should be noted — one of the “Top 50 Global Influencers in HR Analytics” and a common presenter at conferences in the U.S., Canada, and the U.K.

Another hurdle to overcome, Smith says, is a lack of skill sets. She says smaller companies might consider hiring consultants to do the analytics work that staff members are not equipped to complete. Larger companies need to identify which employees will be needed and when they will be needed, which can help these companies better use their employees’ time as the organization gets up to speed on HR analytics.

Now that we’ve covered the potential obstacles to leveraging HR analytics, we can turn to a new and equally important question: what are the right steps for implementing HR analytics?

For some advice, we can turn to the article, “Implementing Human Resources Analytics Less Daunting With These Steps,” by Albert McKeon of TechTarget. The first key bit of advice McKeon offers is to take several coordinated steps, including evaluating your current workforce analytics capabilities and unifying all HR analytics strategies.

Maybe that sounds more complicated than it should. (Then again, a lot of conventional human resources veterans would find any talk of analytics complicated.)

“Because human resources departments use varied data models, they often can’t get nuanced views of even the most basic HR data, let alone … gather every bit of data needed for proper analytics,” Helen Poitevin, a Gartner analyst, tells McKEon. “You can do analytics with practically no analytics tools, or you can hire a data scientist. But that’s difficult to do. It’s not scalable and doesn’t work across departments.”

So, how do we make things simpler? Poitevin recommends finding software specific to human resources analytics. She explains that more generic tools associated with business intelligence require defined metrics, and that can be difficult. A consensus needs to be developed among the supervising executives, and it can be cumbersome just agreeing upon the definitions for the metrics.

It can also be difficult to apply the business intelligence data on a broader scale. Specialized human resources analytics software will already have the metrics defined. That eliminates the need for testing and debate on the metrics.

McKeon cites Ron Thomas, CEO of Great Place to Work Gulf, as adding a caveat: regardless of what business intelligence software you use — even if it’s tailored specifically to human resources — you should still consider hiring a statistician to interpret the data.

“You need to build a narrative out of that data. The inability to do so is why a lot of people in the HR space are upset about analytics,” Thomas tells McKeon. “If I was [sic] a chief human resources officer, I’d bring in someone who understands the data, who understands the research and who can dig deep and build a narrative that everyone will understand.”

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