Editor's Note: Although Big Data, Analytics and now Artificial Intelligence have arrived, and evidence-based management (seeking and using evidence to make better-informed decisions) is mainstream practice, there are still many of us (in HR and even in the field of rewards) who aren't where we should be in embracing this new reality. In today's Classic, we draw on one of the big thinkers in the rewards field, Robert Greene, and his thoughts on what is stopping us from getting where we need to be.
In his article Evidence-Based Rewards Management in WorldatWork's Journal, Robert Greene talks about the importance of moving our profession to a more evidence-based approach. He also highlights a number of the obstacles we face in getting there. I highlight and discuss a few of these below.
One obstacle: Understanding data analysis
To create and use evidence in our work, we must have a basic understanding of quantitative data analysis. The problem, as Greene notes, is that many universities do not require this as part of their coursework, even at the graduate level. Even worse, as someone who serves as a regular instructor in professional certification coursework, Greene observes that not only do many practitioners lack quantitative skills, few of us feel any need to acquire them. This conclusion is bolstered by the results of an informal study we featured here about what HR professionals want to do in their jobs, conducted by fellow blogger Sharlyn Lauby. Compensation and benefits (the most quantitative fields of HR) clearly come out as the least favorite. Sharlyn's take on the study results was that HR pros don't mind spending time on the essence of rewards (but may prefer to avoid the deep dive). Doesn't sound like a crowd eager to embrace analytics, does it?
Now I'm no expert in quantitative analysis and my skills would also benefit from an upgrade, but my second favorite class in graduate school was a course called Multiple Linear Regression. I'm not kidding; hear me out. I took it because, at the time, I was enmeshed in selling and implementing a regression-based job evaluation tool (Multicomp anyone?). I was floored by how much I enjoyed it. You dump data into a regression model and out come -- if you know how to look for them -- stories and insights. It's like CSI, only you're investigating people and pay. All that I'm saying is give predictive analytics and multiple regression a chance.
Another obstacle: Accessing and understanding research
Greene notes another underutilized opportunity -- accessing the evidence available to us through the thousands of research studies that have been done in the field of organizational behavior. He asserts that there is a problematic gap between research and practices in compensation and discusses some of the reasons for this. Many of us don't read the journals where the most rigorous research findings are published. (When was the last time you picked up a copy of Academy of Management Journal? Same here.) Further, academics have reward structures that drive them to conduct and publish research that is focused on theory and heavy on quantitative analysis -- attributes that make the research less accessible and helpful to those of use trying to make pay work in the real world. So instead, compensation and HR pros tend to draw their "evidence" from popular books and articles that often fail in their claim to be truly "research based."
Evidence abounds that evidence-based management is our future. We can either board the train or end up underneath while it roars by.
Ann Bares is the Founder and Editor of Compensation Café, Author of Compensation Force and Managing Partner of Altura Consulting Group LLC, where she provides compensation consulting and survey administration services to a wide range of client organizations. She earned her M.B.A. at Northwestern University’s Kellogg School and enjoys reading in her spare time. Follow her on Twitter at @annbares.
Creative Commons image "Data Mining" by Jim Kaskade
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