A recent report titled “2012 Metrics and Analytics: Patterns of Use and Value” administered by WorldatWork and Mercer, found that most compensation practitioners rely too heavily on the least effective HR analytics. With ongoing reporting, and internal and external benchmarks, being the most heavily used tools, yet the least powerful, it seems that those performing compensation functions need to reevaluate their analytic methods. The rest of HR has begun adopting the more comprehensive analytical methods, it’s time compensation practitioners follow suite.
According to the report, ongoing reporting, and internal and external benchmarks are the three least powerful analytical tools at an HR compensation pro’s disposal. Yet 87% use ongoing reporting, 95% use external bookmarking, and 89% use internal bookmarking. Predictive modeling, which is the most powerful tool according to the report, is only used by 43% of those in charge of compensation. This seems to be completely backwards. The reason for this lies in what compensation professionals perceive as being the most effective analytic tools, versus those which actually are.
The most powerful analytic tool, predictive modeling, was only “perceived to lead to better compensation decisions,” by 52% of those who participated in the survey. All the while, external benchmarking, the second least powerful tool, was perceived effective by 94% of survey takers. That’s a huge disparity between what actually provides accurate data, and what compensation practitioners think is giving them the best information.
The full report goes into why and how this came about, and I urge you to read it if you haven’t already. What’s really important to take away from these findings, is that all of the tools at the disposal of compensation pro’s need to be used, and the emphasis needs to shift. Benchmarking is fine, both internally and externally, but it isn’t even close to a full picture of how to effectively compensate employees. More in-depth analytic tools, such as simulations and predictive modeling, need to be used more often, and by more organizations, if we want to pay employees a wage they deserve. After reading this report, I’m sure some of those in compensation will begin to integrate a more thorough approach to which analytical tools they choose to utilize.