Human Resources News & Insights

Why you shouldn’t be afraid to jump into HR analytics

OK, so you’ve adopted an HR information system to help you handle the growing burden of talent management. But how can you put all that data to use? Guest poster and systems developer Marco L. Padovani offers some insight.


HR analytics has become a key tool for companies seeking to maximize their ROI on “human capital.”

Every company’s decision about every employee has a cost. Individual decisions such as hiring, firing, promoting, training, pay, benefits, etc., as well as ancillary ones such as workspace amenities, leave policies, etc., all have measurable direct costs.

But they also have more difficult-to-measure costs and benefits.

Do you know your true cost for recruiting and hiring? With HR analytics, you can not only measure it, but also quantitatively determine if different recruiters are more or less effective — and more or less costly.

Properly applied analytics can answer many other questions, too, such as:

  • Is your employee training program having a positive effect on performance?
  • Which of your locations has the highest turnover rate, and why?
  • Is your employee retention rate going up or down, and are their differences by location or department or some other factor?
  • Can you pinpoint the greatest risk factors for OSHA incidents?

Bringing more to the table

Sad but true: Many organizations dismiss HR as a cost center. But effective analytics can help HR pros add significant, measurable value to their organizations.

HR analytics is the process of researching what is happening with the workforce, analyzing how and why each facet is contributing to organizational performance goals, and predicting how changes will positively or negatively affect those goals.

Large companies often have people dedicated to this process, people who bring different skills to the effort: IT-oriented people bring data together from disparate systems; data-knowledgeable people ensure that the data is “clean”; business analysts know what questions to ask and what data is relevant to each question; and statisticians know how to model the more complex questions to deliver meaningful answers.

This is too large a team for all but the biggest companies. But there’s still much that can be done by HR departments or even individual HR professionals in medium and small companies. You just need some foresight and planning to get the most out of the endeavor.

The sooner you start, the sooner you will be able to deliver results. Don’t wait for somebody to ask you for an analysis before beginning, because even if you are technically capable of creating a data cube or chart, you might not have the data available or the knowledge to know what is statistically relevant.

So, start now, and consider the following as your initial steps before analyzing your first metric:

  • Start at the end. Determine your most important objectives; then determine the ideal metrics to help you meet those objectives.
    Consider long-term issues. Once you decide to address a problem, you typically will need some historical data before you can actually begin your analyses, so plan in advance to have enough time to start collecting data.
  • Understand your data. Every metric is calculated using one or more base data items.
    Some of these are readily available in your HRMS, some are available but must be regularly calculated and stored, some might only exist in external systems, and some might not (yet) be maintained anywhere.
    Moreover, for any given data item (and ultimate metric), there can be multiple definitions (calculations). Decide which definitions suit your purposes.
  • Plan and execute your data collection project(s).  There are two parts to this. First, for any of the above data that isn’t readily available, you must build the manual or automated systems that integrate it into your HRMS Analytics module.
    Second, regardless of whether data is currently available, you must execute an initial and an ongoing data cleansing project (for bad data, for incomplete data, etc.).
  • Learn your analytics tools. While you’re beginning your data collection projects, start learning your software’s functionality, the overall field of HR analytics, and even basic statistics.
    The more you know before you start, the better you will be in your job. Here are two books to consider: HR Analytics Handbook and New HR Analytics: Predicting the Economic Value of Your Company’s Human Capital Investments.

Marco L. Padovani is a systems developer at PDS, an HR, payroll, and benefits software company in Pennsylvania.

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