Mercer and WorldatWork have collaborated again on a survey and report about current total rewards/compensation trends in metrics and analytics. The focus of the research was to understand what types of analytics are currently being conducted and what technologies are being used to conduct them.
It’s an interesting report – especially from the vantage point of what it says about the relationship between HR and data and HR and analytics. The survey was fielded in February, 2012 to compensation leaders who are WorldatWork members (the dataset held 560 scrubbed responses , a final 10.9% response rate), so they all have more than a passing knowledge of the total rewards function.
The big takeaways of the survey data are that:
- Rather than use sophisticated analytical approaches like projections, simulations and predictive modeling to support decision making, organizations are more likely to use ongoing reports and benchmarking from internal and external peer groups.
- Survey respondents report lack of access to and confidence in data regarding education competencies/capabilities and training investments – critical to workforce analytics.
- Compensation professionals may be falling behind their colleagues in other HR functional areas in their adoption of more sophisticated analytics methodologies.
The report discusses why adoption of more powerful analytics is low despite 67% of respondents indicating adequate skill levels to engage in higher level analytics and almost half (47%) having 1 -2 FTEs tasked with HR-related analytics. More important, 75% of the respondents reported that C-suite executives in their organizations have asked for workforce projections, simulations or predictive modeling.
Mercer and WorldatWork point out that while respondents report that some data is not available or of poor quality, 75% of respondents say their organizations are working to improve the consistency of their data. Paradoxically, 52% are unclear where responsibility for data integrity lies.
I found it interesting that the researchers suggest that “unavailable” data may result from a lack of interest in the data rather than an ability to access it. A compelling point.
From the responses outlined in the exhibit above, one could readily agree with the researchers that critical workforce information about education, competencies, prior work experience and investments in training aren’t top of mind for compensation professionals. It could easily be that compensation professionals believe these datasets and their analysis more naturally belong to other HR functions: learning/development and talent management/acquisition.
The writers argue that rewards/compensation professionals have a preoccupation with the behavioral side of rewards and overlook the “asset side” – the impact of rewards on the ability of the organization to acquire appropriate talent.
The bottom line for the researchers is to encourage rewards/compensation professionals to begin to think more expansively – and use higher levels of analytics – on the role of rewards in driving human capital development and business success and focus a little less on salary competitiveness and pay-performance sensitivity as performance drivers.
A very interesting report and very useful data as you begin to plan your 2013 budget. Stepping up your workforce analytics sophistication could be a game changer for your organization.
4 responses to “Data Analytics: Too Sophisticated for HR?”
It seems complicated and overwhelming when you are learning something new but after a few weeks, you should get the hang out it. The same can probably be said for HR running data analytics stats
The one issue to watch before emphasizing the asset side of the equation, skills, education and experience is that these things don’t necessarily equate to performance. We all know many individuals with great education, skills and many years of relevant experience who are not the top contributors in an organization
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Good read, Ron. Very interesting results and I think you summarize it perfectly here: “The bottom line for the researchers is to encourage rewards/compensation professionals to begin to think more expansively – and use higher levels of analytics – on the role of rewards in driving human capital development and business success and focus a little less on salary competitiveness and pay-performance sensitivity as performance drivers.”
Combining people and performance – quantitatively.