Analyzing HR metrics is currently one of the trendiest developments in the industry. KPIs based on data are required for strategic decisions, operational adjustments, and validation of the current state of an organization’s workforce. HR analytics’ challenge is setting KPIs into context and making predictions for the future that HR professionals can transform into action. Therefore, we distinguish between two types of HR analytics: descriptive and predictive. 

Let us look in detail at what they are.

Descriptive HR Analytics: „Look into the past and see where we stand. “

Your organization probably already has many systems with much raw data that can be used for HR analytics. But raw data is useless unless combined, aggregated, and interpreted. The fundamental sort of analytics you are most likely accustomed to is descriptive analytics. It involves taking historical information and distilling it into a digestible form. 

For instance, a headcount report of every company employee is an example of descriptive analytics. Even further segmenting it based on demographics would still fall under descriptive analytics. 

The same applies to more complex indicators like turnover rates or time to fill. They make use of the past and seek to justify what has already occurred. Using descriptive HR analytics is always reactive. 

Predictive HR Analytics: „Look into the future. “

Descriptive analytics look backward, and predictive analytics looks into the future. Statistical models, forecasts, and the use artificial intelligence is used to answer the question of what could happen. Predictive models are based on descriptive analytics combined through complex operations to determine where the organization is headed proactively.

Predictive analytics can help in many different ways. For example, predictive analytics can assist talent acquisition teams in determining whether a candidate would be an excellent cultural fit for the company before hiring them. An estimate of how long the individual will work for the organization might be included.

Predictive analytics can also be used to analyze how your current workforce is doing. For example, finding out which of your employees might leave next is one of the things predictive analytics can do.

How to combine them?

We at People Horizon believe that the optimal flow of using descriptive and predictive analytics is the following:

1. Train a predictive model to see where the pain is. For example, figure out who might leave your company in six months.
2. Use descriptive methods to analyze why. Reasoning helps you to find the root cause of your issues.

Some SaaS providers also talk about the third type of HR analytics: prescriptive analytics. Prescriptive analytics is said to give you suggestions on which actions you have to take.

Prescriptive insights can, in theory, help you, but the amount of training data and learning on how past actions manifested are immense. This works only for the largest companies with mature and feature-rich data sets collected for years. Many companies are today simply not there yet.

But any company can use descriptive HR analytics. For many, predictive analytics makes sense. Prescriptive is a look into the future.

If you want to explore how you could use HR analytics in your company, get in touch!

‍