The 3 Key Metrics in HR Predictive Analytics
For the past few years, every HR related trends post included predictive analytics. So, what exactly are predictive analytics? I like to think of it this way: HR metrics tell you what happened in the past. For example, time to fill. Or they’re focused on cost-containment, such as cost per hire. Both of these metrics are valuable, but it’s not all the information we might need to make business decisions.
Predictive analytics offer insights into the future. It’s focused on probabilities and impact, so it provides flexibility to the organization’s needs. I know, that sounds like a tall order. I decided that I wanted to learn more about predictive analytics so I picked up a copy of the book “Predictive Analytics for Human Resources” by Jac Fitz-enz and John Mattox. (Fitz-enz’s book “How to Measure Human Resource Management” is my go-to book for HR metrics.)
Why should HR pay attention to predictive analytics?
There are times when today’s business environment is moving so quickly that we cannot always be focused on what’s happened in the past. We have to give equal time (and some might argue more time) to what we think is going to happen in the future and plan accordingly.
That’s where predictive analytics comes in because it’s what you do with the information you gather. Predictive analytics measures the three things business people talk about the most: efficiency, effectiveness, and outcomes.
- Efficiency measurements include some we already calculate such as average number of days to fill a requisition and cost per hire.
- Effectiveness measurements might contain new hire performance ratings, engagement survey results, and exit interview data.
- Outcomes measure profitability, productivity, and retention.
Predictive analytics is about the connection between these three types of measurement. Here are a few examples:
- Number of open hires (efficiency) – Quality of hire (effectiveness) – Length of employment (outcome)
- Average cost per hire (efficiency) – Cultural fit (effectiveness) – Contribution to product quality (outcome)
- Amount of training attended (efficiency) – Hi/lo potential status (effectiveness) – Increased profit margin (outcome)
HR metrics aren’t going away. Neither are predictive analytics.
A few months ago, I wrote a post about the need for HR pros to focus on their analytical abilities. If you’re looking for a way to increase your skills, wrapping your arms around predictive analytics might be a good place to start.
An increasing number of HR departments are designing analytical roles. If you’re looking for a job in human resources, knowing something about predictive analytics will be important.
HR wants to be on the front-end of this trend. Because it’s not going away anytime soon. If ever.
Image captured by Sharlyn Lauby near the Wynwood District in Miami, FL4