For all of my working career, I’ve argued that HR needs to get more analytical, so I’ve welcomed HR’s growing interest in data based analysis and benchmarking. I have been something of a flag-waver for data driven HR for many years. I’m thrilled to see the increasing sophistication in workforce analytics. The posse of machine learning, predictive, big data, and artificial intelligence is going to transform HR in ways we can’t imagine today.
But for analytics to work, to add business value, and to be fair and just, it needs to be based on robust methodologies. The analytics are only as good as the frameworks and models they are built with. No matter how compelling the charts and graphics, if the models are weak, we risk doing the business and its employees a massive disservice.
Employee engagement is a hot topic in HR circles. Start ups, HR tech vendors and consultancies of all sizes and shapes are building solutions and practices focusing on improving and measuring employee engagement. Gallup’s survey though, is the granddaddy of them all. It is used for as the justification for all sorts of HR interventions.
So, why is this bothering me? I am a social scientist and expect clarity as all good social scientists do. Published scientific results must be replicable so that others could repeat studies in the same manner. Empirical methods and outcomes not being communicated in a clear way are useless in the eyes of the scientific community.
When algorithms are hidden behind the firewall of intellectual property, it makes it hard to really know how robust they are. If we are to base major decisions on poll data, it is beholden on us to make sure that we know how the results are derived.
After the failure of polls to effectively predict politics, it is time for a lot more scrutiny and indeed scepticism. Not just for this survey, but for the whole industry.
I am always nervous when mentioning physics and psychology in the same blog post, but the words of Richard Feynman popped up in my twitter feed as I was writing this, so I couldn’t help myself.
You should, in science, believe logic and arguments, carefully drawn, and not authorities. pic.twitter.com/BerxDIOFRV
— Richard Feynman (@ProfFeynman) December 2, 2017
(Cross-posted @ Vendorprisey)