Predictive Analytics: Is HR on Target?

Workforce analytics - Are we on Target?
This article has been doing the rounds a lot in the last week. I have seen it everywhere from my LinkedIn connections to being the focus of Stephen Colbert’s “The Word” segment.

Target uses Predictive Analytics

What Target is doing is making the most of their resources to increases sales and market share. It is very clever and has taken a lot of smarts to get things right.

But what can HR take from it? Surely we can’t predict pregnancies for our own benefit like Target did? Though it would make managing parental leave a bit easier…

There is an opportunity for HR to make a big impact through using its data to predict rather than just to describe trends or forecast*. HR has access to a lot of data sets and with the right capability they can use this to be predictive within the different HR functions.

The real questions are “what can we predict?” and “what data can we use?”

The key to predictive analysis (or any metrics for that matter) is to make it worth your while. In the Target example, they are using their data to draw customers in who are going to spend a lot of money over time. It is not just the money that they will hand over for cots, baby clothes and all things motherly, but they also aim to creating shopping habits over a lifetime. So where can HR make it worth while?

The obvious areas where HR can make an impact are recruitment and turnover. These two areas are big money spinners. There is a lot of time and money spent on filling empty spots and plenty of opportunities for keeping or gaining good talent. Another areas is leadership. The way people lead their teams can mean the difference between being productive and destructive. It can also have a big impact on whether people walk out the door or bring talented people in.

So, with a focus on areas such as retention, recruitment and leadership, how can we measure it? There are plenty of data sets – separation numbers, productivity, absence, and possibly under used, engagement and exit survey. The last two are often under valued for deep analysis because they are trickier use, especially as they are not backed by easy formula. However, they do add great context and rich information, especially when it comes to free text answers.

The tough bit is knowing how to combine this information to produce the magic. As a function, HR needs to learn these skills to provide great value to our companies. We often don’t have the skill sets or courage to take on something so ground-breaking. That’s why Target is being discussed and not a HR team.

*you might ask “what’s the difference between predicting and forecasting?” My definition is that predicting is identifying specific events, such as an individual leaving. Forecasting identifies potential future trends, ie our turnover rate will be x%


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