HRIS Software, Big Data, and the Big Picture
Big Data HRIS Software

HRIS Software, Big Data, and the Big Picture

By: Dave Rietsema On: November 12, 2014
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It shouldn’t be a surprise to any HR professional that HR data can be enormously beneficial to companies seeking to improve their workforce. HRIS software is a vital tool in the collection of that data. However, big data movement is in its infancy, and not all companies that have made the move toward collecting HR data have reached the point where data collection and analysis have resulted in significant benefits, such as:

  • Enhanced ability to recruit top performers.
  • Improvement in retention of valuable employees.
  • Accurate assessment of which employees will make good leaders.
  • Development of more effective training.

But jumping into big data is more than getting, well, a mountain of data. Here are some critical steps to keep in mind as you are planning your data collection and analysis.

Step 1: Who Is Going to Analyze the Data?

Chances are that your HR staff is not loaded with analytics experts. However, certificates and degrees in analytics are available to bring your staff up to speed. You can hire experienced data analysts to assist in the effort, on a full-time or consultant basis. HR leadership must have the ability to envision what big data can do for the organization and to understand what the analysis shows.

Step 2: What Is Your Toolset?

All HRIS software packages are not created equal. Take advantage of the talent you identified in Step 1 to help select the software that will meet the needs of your organization, and to determine how to use that software to full advantage. Depending on the type and size of your business¸ certain HRIS software options will emerge as front runners.

Step 3: What Problems Are You Trying to Solve?

Before collecting data, some analysis needs to take place to ensure that the data being collected serves a business purpose. Your data collection should be targeted toward answering your biggest questions. If you identify multiple issues, prioritize those problems and your data collection needs.

Step 4: What Data Do You Need?

This step naturally follows problem identification. It also makes much more sense to ask this question before acquiring more data than you know what to do with and then trying to figure out what data has value.

Step 5: What Data Corresponds to Identified Issues?

This should be an easy step if you have already matched your data collection to your needs. If not, you can still peruse your collected data to see what applies to specific problems.

Step 6: What Is Our Plan of Action?

We are all used to making decisions based on our gut feelings or on conventional wisdom. It takes a certain amount of courage and creativity to make and implement a plan based on new data, especially if that data tells us something we didn’t expect. Just remember, big data, big rewards.

Step 7: What Does the Post-Implementation Data Tell Us?

After you’ve implemented your plan, it’s time to collect more data and draw some conclusions about the success of your plan and how it was applied. It might be time to tweak your efforts or to proceed to the next problem you want to resolve using big data.

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