Predictions are a popular topic this time of the year. Predictive analytics is a trend that has been consistent in HR-related trends articles. What is predictive analytics, and why should we be paying attention?
It’s best to look at it this way: HR metrics show you the past. You might see the time it takes to fill a job or the cost per hire. These metrics are both valuable, and HR departments should calculate them. However, they don’t provide all the information we may need to make business decisions.
Predictive analytics offers insights into the future, while HR metrics give us an overview of what we have done. Predictive analytics is a tool that focuses on probability and impact. It can be customized to meet the needs of an organization. That sounds daunting. I have been looking for more information about predictive analytics, so I bought a copy of “Predictive Analysis for Human Resources” by Jac Mattox and John Mattox. (Fitzenz’s book How To Measure Human Resource Management is my favourite book on HR metrics.
Predictive analytics measures three things businesspeople discuss: effectiveness, efficiency, and outcomes.
- Efficiency Measurements include those we already calculated, such as the average time it takes to complete a requisition or the cost per hire.
- Effectiveness may include new hire performance ratings and engagement survey results. Exit interview data might also be included.
- Measures profitability, productivity, and retention.
Sometimes, today’s business environment is so fast that it’s difficult to remember what happened in the past. It is important to plan for the future with equal attention (some might argue that we should give more) and to think about what will happen in the future. Predictive analytics is where it all comes in. It is what you do HTML5_ with the data you have. Predictive analytics is the combination of these three types. Here are some examples:
- Efficiency – Number of open jobs (efficiency) – Quality of hire (effectiveness). – Duration of employment (outcome).
- Average cost per hire (efficiency). – Cultural fit (effectiveness). – Contribution towards product quality (outcome).
- Training attended (efficiency) – High/low potential status (effectiveness). – Higher profit margin (outcome).
In the past, I have written about how HR professionals need to be more focused on their analytical skills. Predictive analytics is a great place to start if you want to improve your skills. HR metrics and predictive analytics aren’t going anywhere.
An increasing number of Human Resources departments are creating analytical roles. Knowing predictive analytics is a must if you are looking for a job as a human resource professional. HR should be at the forefront of this trend. It’s not going to disappear anytime soon. It will never go away.