Have compensation professionals, once the math and data heroes of the HR world, fallen behind the curve in analytics?
New research suggests it could be so.
In their joint report 2012 Metrics and Analytics: Patterns of Use and Value, WorldatWork and Mercer find that compensation functions continue to rely almost exclusively on benchmarking techniques and haven’t yet moved to the more advanced analytical methods, methods like simulations and predictive modeling, that many of their peer professionals are using to support decision making.
In the WorldatWork WorkspanTV video below, Mercer’s Haig Nalbantian and Brian Kelly discuss the research and its findings.
Are we stuck in an old paradigm?
In our exchange on the research, Haig Nalbantian called attention to the opportunity that he feels our profession appears to be missing (noting, as I recently did, that we seem to be stuck in an old paradigm):
It raises great concern for me that Compensation practitioners, who once led the way on use of analytics to support policy decisions, are now falling well behind their counterparts in HR and certainly in other parts of the organization where analytics are routinely deployed – Finance, Marketing, Operations, etc. This is mostly because they seem stuck in the old “compensation silo” that actually inhibits their ability to ask the right questions in the first place.
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The tools we use have not kept pace
Thus, while the discipline has evolved conceptually to adopt a total rewards perspective, the tools commonly used by rewards practitioners have not kept pace; they have not been adapted sufficiently to allow practitioners to measure how total rewards actually play out in organizations and how the various components of total rewards affect workforce and business results.
In what must be more than sheer coincidence, HR and compensation analytics have also been on the minds of many of my Compensation Cafe colleagues lately, as evidenced by some of their intriguing posts on the topic:
- Get Rich Quick! — Margaret O’Hanlon;
- Diamonds and Data Mining! — Stephanie Thomas;
- We’ve Gone Too Far with Metrics! — Stephanie Thomas;
- Out With Metrics, In With Analytics! — Jacque Vilet.
What’s your take on all of this?