HR Analytics: 3 Best Practices for Integrating Data Into Your People Management Process

Back in the late 80s and early 90s, analytics made their first appearance in human resources offices around the country. Back then, the data points were things like head count and retention rate. Those metrics look quaint compared to the analytics capabilities available today.

Companies across all industries are now leveraging the power of data to get a better handle on their people management process. According to a recent Deloitte report, 35 percent of surveyed companies said they were implementing data capabilities into their HR operation.

From reigning in healthcare costs to predicting employee advancement and turnover to analyzing the effectiveness of training, analytics can have a massive impact on the effectiveness of your HR operation, and it can help your executives and managers make more informed decisions.

The challenge is to use analytics in the right way. When not used correctly, your analytics process could be a drain of resources. If not communicated in the right way, it could be viewed as an invasion of privacy.

Below are a few best practices on how to plan, implement, and manage your HR analytics operation. If you’re not following these guidelines, you may want to rethink how you’re using HR analytics in your business.

Start with the problem, not the data.

When you first install software or implement a system to gather data on your workforce, you may be overwhelmed by the volumes of data available for analysis. It may be hard to decide which data to focus on, and you might find yourself pulled in many different directions. From predictive data to demographic information to cost efficiency numbers, every piece of data may feel like a shiny new object demanding your attention.

Here’s a good rule of thumb to use as you begin to analyze people data: Just because you have a specific data point, doesn’t mean you should use it.

Instead of starting with the data and creating analysis and reports based off that information, start with a specific problem and find the data that is most relevant. For instance, maybe you want to manage healthcare costs. You might find data relating to workforce health that can help you tweak your wellness plan. Or perhaps you could offer incentives for workers to stop smoking or get an annual physical.

When you start with a problem, you ensure that you’re only using the data that is necessary to solve the issue. When you start with data and analyze it just because you can, you run the risk of invading privacy and crossing an ethical line. You also could waste time and other resources analyzing irrelevant information.

Start with the problem and then use only the data necessary to solve that problem.

Be transparent.

Employees are often naturally skeptical of any efforts to gather information about their activity. Many employees have an expectation of privacy, even if it’s not warranted. For example, employees may feel that their emails are private even when the company tech policy explicitly says that emails on the work server are subject to review.

As you can imagine, your workforce could have a very negative initial reaction when they learn that you are gathering data on their activity, behavior, and even their health. It’s important that you are transparent about your efforts and over-communicate the why and how of the program.

For instance, make it clear that in instances involving sensitive data, such as healthcare issues, you are looking at the group, not at individuals. Let them know that the data isn’t replacing human decision making. Rather it’s just another input for managers to consider. Share when you rely on data, how you gather the data, and how it factors into the decision-making process.

Use it as an informative tool, not a final decision.

You may find that your data is remarkably accurate as a predictive tool. However, that doesn’t mean you should use the data to reach your final decision.

Google has been on the leading edge of data with regard to people management. Several years ago, they developed an algorithm that determined with 90 percent accuracy which engineers should receive promotions.

And yet, they didn’t use the algorithm to make the promotion decisions. Why? The hiring managers still wanted to have the final say in who received promotions and who didn’t. The algorithm might have been a helpful tool, but it couldn’t be used to make the ultimate decision.

If Google - a company built on data - doesn’t rely solely upon their analytics for people decisions, neither should you. Use it as a tool and an additional piece of information, but don’t let it replace your people in the decision-making process.

Used properly, HR analytics could improve your recruiting efforts, retention rates, people costs, and more. However, used incorrectly, it could alienate your workforce and even become a costly distraction. Before you implement a data program, develop a plan and process for exactly how and when the data will be used.

At People Phase, we help companies find the right organizational structures and policies for their team. Contact us today. We have an extensive network of trainers and consultants who would welcome an opportunity to help you help your team find a greater balance between their work and their personal lives.