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Predictive Analytics in HR: Our Crystal Ball Says …

Part II

We are continuing on with our predictions for predictive analytics in HR blog series. Now on to #2.

#2 Adoption and Change will be Slow

Adoption of predictive analytics in the HR world will be relatively slow. This may not seem like a bold prediction, but it’s certainly worth discussing.  Let’s review what we know about HR. Many HR professionals went into HR because they love working with and helping people. Not as many chose HR because they love numbers and statistics, which also means that the current analytical skill level of HR is limited.  So, many HR professionals understand that analytics can greatly help HR contribute more to the bottom line, but may not have the proper skills to effectively apply analytics. Below are our thoughts on what we think will happen due to HR professionals’ lack of deep subject matter expertise (albeit eagerness to learn!):

  • Shiny Object Syndrome: HR will get caught up in the new shiny object of data visualization and miss out on something that is greatly needed – actual, rigorous HR analytics. They may focus on things that look cool and seam sophisticated, but lack real rigor and have minimal utility in driving improved outcomes.
  • Trends=Credibility Killers: Companies will apply bad analytics that will result in bad decisions—investing based on data trends (what happened in the past), correlations, and vendor fads. This will kill HR’s credibility, as well as the credibility of companies like SMD. Unfortunately for us, some of these sub-par tools that look pretty but provide questionable analytics could actually impact legitimate analytical companies like ours.
  • Rage against the Machines: The race to apply automatic analytics (i.e., machine learning) will result in more bad predictions than good ones. Predicting human behavior is complex and difficult and even when done well it can only account for a fraction of variance in outcomes. So when a company starts telling you who to hire based on the font in the candidate’s resume, you should be VERY skeptical. Unfortunately, some of these companies will find customers to buy these very flawed tools. These looming failures will make organizations slow to adopt all analytics solutions – even the ones that will add significant value.
  • Learning Curve Sprint: On a positive note, HR will quickly increase its understanding of analytics and its ability to evaluate potential applications. Basically, HR will be forced up the learning curve quickly because they will be bombarded with so many different tools and applications that they will have to learn.

Stay tuned next week for prediction #3.

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