Geert Verstraeten is Managing Partner at Python Predictions, a Belgian niche player with expertise in the domain of Predictive Analytics. His ambition is to coach analysts and their managers to become successful with predictive analytics.

About Geert view on how absenteeism can help predicting burn-out

In the current job scenario, in which 2 of 3 workers experience stress, it is crucial to predict when can this situation escalate to burn-out, generating a high financial cost for the companies and having a negative impact on the employee’s health and motivation.  This motivated Geert to develop a model to predict burn-out basing on absenteeism.

Framing the problem in the proper way is key to use data  effectively. In this case, it involved focusing on absenteeism using payroll data and linking it to evaluation scores. This model works best when aggregated to teams, allowing organisations to have a better panorama on how their organisation is performing to build a strategy integrating different departments.

In an era in which the word “burn-out” is frequently mentioned (and feared), it is encouraging to see how data coming from different sources can be used to build healthier job environments.

Our favorite phrase from Geert’s presentation

“Make sure that you are solving  the right problem”

We hope that Geert’s insights can be used in a broader way for spotting burn-out!

Geert’s interview:

Geert’s presentation recording:

Geert’s deck:

[To be uploaded asap]

Geert’s presentation sketch: