HR Analytics for Data-Driven Decision-Making

HR Analytics - a Definition

When used effectively, HR analytics allows you to quickly identify trends so you can respond accordingly in a timely manner. For example, data on employee sick leaves over the past six months provides a solid foundation to forecast what the next six months are likely going to look like. The same applies to KPIs such as employee turnover. All the more ground to be able to intervene early to retain talent.

Consequently, HR analytics is closely related to HR controlling but goes a step further by making predictions. Essential for this is the use of the right HR software, because despite its complexity, with the right software, you can generate relevant reports with just a few clicks.

Implementing HR Analytics

The foundation, as always, is a central data collection. It's worth remembering that analyses and predictions can only be as good as the data foundation is complete and reliable. So, the first step is to ensure that the existing personnel data is well-maintained and stored centrally.

If you've ticked this box, you're already ahead of many other companies. Now, it's about strategically using HR analytics. What personnel-related challenges are you currently facing? Are there industry-specific obstacles on the horizon? Depending on the specific issue, it always makes sense to first define a concrete problem.

Now is where data comes into play. Identify the key metrics through which you want to analyze the respective problem. With the right software, you can link data, generate reports, and make predictions. This is where HR analytics goes beyond HR controlling because it allows you to derive clear action steps.

Use Cases for HR Analytics

Enough theory - let's break this down with a practical example. Let's say you're facing the challenge of an increased number of employees having left your company over the past three months. The first step is to define the problem. In this case, we've identified an unusually high employee turnover.

We want to find out if there is a correlation and, if so, what it is. Important metrics in this case could be salary, departmental structure, and development potential. In the next step, these key performance indicators are compared, related to each other, and analyzed.

One possible explanation might be that the salaries of the affected former employees have not been increasing over an extended period, and other corporate benefits haven't compensated for it. The simplest solution could be to adjust salaries. If that's not currently feasible, introducing other benefits aligned with employee needs might be an option.

Another explanation could be that the manager in the role is overwhelmed and requires training. It might also be the case that other companies have actively poached your employees. Perhaps there was a lack of a clear career path in your organization?

As you can see, once you find answers to the problem at hand, you can take action. This is why HR analytics is so valuable.