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.
Director of People Analytics & Insights at Cencora | MBA, SPHR®
7yGenerally agree across the board... except for that last bullet, which I've been hearing for at least a decade now it seems. Sigh.
Human Capital Strategist | Trusted Advisor | Data Driven Problem Solver
7yHR professionals have been saying "this is the year for advanced talent analytics" for a few years now. Of course, predictive analytics in HR has actually been a reality for decades, primarily in the area of selection assessment. So what is new? As you mention Scott, the introduction of new tools and technology, the use of predictive analytics in other areas of the organizations and even in our personal lives, has made advanced analytics more accessible, even expected. I agree HR has lagged behind, however now HR leaders are seeking out answers and actionable solutions to overcome barriers to their analytics capabilities. As long as they are focused on and demonstrating the business impact of their analysis, I believe we will see rapid and sustained progress. If it is simply "HR for HR" type of analysis, then it will remain a 'cool' activity with no real value to the business.
"C-Level Executive Coach"
7yDesriptive analytics, predictive analytics, prescriptive analytics, autonomous decision analytics, productive outcomes analytics and more as the analytics field evolves evolutionarily and revolutionarily. As far as I am concern, at each stage of the analytics continuum, non has yet to advance beyond the elementary stage yet; even with so much hypes and buzzes going around. The true "values" of analytics have yet to be established in terms of contributions to Organizations, communities, societies and the human race; though it seems to be heading towards the right directions.
Trusted HR Leader | HR Projects | CPA qualified
7yScott Mondore predicting human behaviour is complex and difficult- I couldn't agree more. Coupled with unconscious bias that then uses flawed PA tools to justify or validate their decisions - it's a recipe for disaster. Looking forward to your next post !