Analytics Is About Analysis, Not Statistics

Today’s post comes to us from advisory board member David Creelman, chief executive officer of Creelman Research.

People analytics has hit a lull, somehow not quite living up to the early expectations. University of Southern California professor Alec Levenson has an explanation and, perhaps, a bit of a cure. Levenson says analytics is mainly about analysis, not statistics.

Let’s start with the “statistics” part of that statement. A lot of the hype around people analytics came from the promise that the combination of big data and advanced mathematical techniques would allow us to do predictive analytics. The problem with that promise is that it’s quite rare for HR to have large, high-quality data sets that are relevant to the issue it’s addressing. If a people analytics department is built around the idea that its value will come from predictive analytics, then it is bound to disappoint stakeholders. An undue focus on statistical expertise can send people analytics in the wrong direction.

Analysis, on the other hand, simply involves thinking very hard about a problem. For example, if managers are complaining about a lack of agility, then it takes a lot of thinking to determine where exactly this “agility” matters to the business and which of many possible barriers is hurting agility. Levenson in particular thinks we should spend a lot more time analyzing — that is, thinking about — which issues have a crucial strategic impact because there are hundreds or thousands of things you could potentially improve in the organization, and you can only focus your attention on a few.

Once you have thought through a problem, then you’ll be able to gather up relevant data to help inform your decision. More often than not, the mathematics of the analysis is pretty simple. Managers need answers to questions such as how many, is it getting worse, and which is biggest and by how much? You need data to answer those questions, but it is rare that you need deep expertise in statistics.

The main barrier to doing analysis is not HR’s skill set but the time HR has for thinking. Like most people in modern organizations, an HR professional’s time is consumed with doing things. They are in meetings, answering emails, reading reports, or filling in forms. What they don’t have much time to do is sit and think — which is what analysis requires. For a people analytics function to be successful, it needs to create an environment where the analytics pro has time to work with stakeholders to analyze problems.

A big part of that analysis involves patience. The goal can’t be to get to a solution as quickly as possible because you’ll probably come up with a solution to the wrong problem. It takes patience to ask over and over again, who cares about this, why is this important to them, and is this even the most important issue we should focus on?

We don’t want to forget about the value of good data sets and well-deployed mathematical tools. However, the future of people analytics lies in professionals who have the time and patience to do analysis, not statistics.