Getting Started with HR Analytics

When it comes to small business HR and staying innovative and competitive, one area of focus should be on analytics.

Below, we delve into what HR analytics is and how to start using this data to strengthen your workforce and your business.

The Basics of HR Analytics

First, analytics simply means that you’re gathering data and then using it for performance improvement and decision-making.

With HR analytics, in particular, some of the metrics that are assessed include retention rate and how long it takes to fill an open position.

HR analytics can help with onboarding new hires, keeping people onboard and growing and developing them for maximum organizational impact, and improving your bottom line.

When you have the right technology in place to pave the way for HR analytics, you’re fueling your decisions with data and facts.

It should be noted that just keeping records isn’t the same as HR analytics. HR analytics means that you’re turning the data you’re collecting into valuable insight.

There are also people analytics which is sometimes a term used interchangeably with HR analytics. People analytics is all-things employee-related. HR analytics, more specifically, hones in on things like recruitment, training, and education planning.

Descriptive vs. Predictive Analytics

When it comes to HR analytics, it can be further divided into two categories—descriptive and predictive.

Descriptive analytics is a gathering of data representing either current or past events.

You can look at what’s currently happening with descriptive analytics, for example.

Predictive analytics is a way to forecast future events or values.

You’re not looking at what’s happening, but instead, what’s likely to happen.

Predictive analytics requires an AI platform with elements of machine learning.

Analytics and Recruitment

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One way to use analytics as it pertains to HR is for recruitment.

For example, you can pair background checks with tools that will forecast a candidate’s likelihood to bring toxic behaviors into the workplace, like bullying or sexual harassment, integrating online information and data.

There are also platforms that can predict the likelihood of someone accepting a job, and then using those predictive analytics, you can then create a tailored offer to increase the chances they’ll take the position.

As a platform gains more data over time, it becomes more adept at predicting acceptance rates and gives more details on how to improve those chances.

Other Common Metrics in HR Analytics

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Along with using HR analytics as part of your recruitment to create better, more targeted offers and a safer, better overall workplace, the following are some specific metrics that are frequently used:

• Revenue per employee—this metric is simple to measure. You take the company revenue and divide it by the number of employees. This simple metric actually has a lot of analytical value for an organization because it gives you a quick snapshot of what employees are producing and generating.
• Acceptance rate—this somewhat ties in with what was above, as far as the use of analytics for recruitment. You can get a measure of the number of accepted formal job offers, divided by your total number of offers. If your rate is too low, you need to rethink how you approach acquisition. 
• Training expenses—get this number by dividing your total training expenses by your total number of employees.

Other metrics to use include time to hire, absenteeism, and involuntary turnover rate.

How Can You Get Started?

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If you understand the value of HR analytics for your organization, the following are steps to get started.

• Gather all of your employee data and centralize it. Choosing an HR platform is the best way to do this. If you’re entirely new to HR analytics within your organization, you may find that your data is all over the place in different systems, including paper records and spreadsheets. Just the process of accessing it all is time-consuming, but you need to get it in a single access point. That in and of itself is going to help you make better data-driven decisions.
• Then, once you have your data in a central place, you need a dashboard that will allow you to visualize it quickly.
• From there, you can start to deploy your actual analytics capabilities, which, again, will stem from your choice of technology.

Finally, once you have a strong foundation, you can start putting what you learn from your analytics into practice.

You can identify specific problems that you need to solve, and set goals and metrics, and then use your analytics in very granular ways.

The goal overall with any analytics initiative is to link your analytics to very specific and measurable business outcomes.

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