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Moving From Predictive to Pervasive Analytics
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Most maturity models for people analytics implicitly assume that the goal is ever-increasing mathematical sophistication. I’ve argued that mathematical sophistication is a red-herring; HR leaders need to focus on ever-increasing relevance — in that it’s more important to have a simple data-backed answer to a highly relevant business question than a complex data model that answers a less relevant question.
This new approach to people analytics has a corollary. Instead of aiming for a small team of data scientists who do predictive analytics, we should be aiming for a large team of HR professionals who do simple but relevant analytics.
In other words, we want to focus on pervasive analytics, not predictive analytics.
I’ve gathered some evidence on this concept by experimenting with training programs with HR professionals to see if they can apply relevant analytics in their everyday work. The answer is yes. I’d estimate 60% to 75% of young HR pros have sufficient skills to apply basic analytics to their work. This means that an HR department can bring data-backed decision-making to most of their work.
This is quite a different volume of output than you would get from a small team of high-powered analytics specialists doing a few sophisticated projects each year.
This doesn’t mean that large companies won’t want to have a small, sophisticated analytics team. These groups do important work. However, for most companies, the emphasis should be on pervasive analytics.
There is a common perception that people go into HR because they like people more than math. There is probably some truth to this, but that doesn’t mean they aren’t competent in basic math needed for decision-making. Generally, the questions HR needs to answer inform a decision are along the lines of How many?, What’s the trend?, Where is the problem biggest?, and What’s the ratio?
I find that many HR pros are entirely capable of handling most of the math they need to do people analytics. They just need to be self-aware enough to get help if they venture into more complex terrain such as multiple regression.
The new maturity model emphasizes relevance, which is another way of saying that HR pros need business savvy. This, in my experience, is a bigger challenge for the typical HR pro than analytics savvy. It can be hard for practitioners to see the world through the eyes of a CEO, investor, or even a customer. The whole world of HR is often very inward-looking. Without business savvy, they won’t know which questions are relevant, and any time they spend on analytics will be of low value.
The vision of a small team of data scientists doing sophisticated work was misguided. The future of people analytics is for it to be relevant and pervasive. We don’t need new employees for that — we just need to train the ones we have.