A presentation delivered by Dr. Peter Hartmann, from Maersk Drilling, at the Workforce Analytics Summit in Amsterdam in March 2015. He talks about Maersk’s journey from descriptive to linkage to predictive analytics.
He begins with a general framework and working model for HR Analytics. Thereafter he delves into building a basic understanding of statistics terminology for the audience of analytical projects.
In the first stage, he describes the facilitation of descriptive statistics through design and documentation of HR Metrics by following the steps of Align, Simplify, Standardize, Automate and Display.
The second level of analytics is about exploring linkages between variables. The examples he covers here are :
i) Finding the drivers to employee engagement and the behaviors that are in turn driven by engagement levels;
ii) Linking manager and leader personality profiles with their ability to keep their teams engaged and drive performance;
iii) Mutual impact of engagement levels and performance;
iv) Assessing the impact of training programs on performance
The third level of analytics is predictive analytics. The application discussed here are:
i) Workplace safety, where they try to find predictor of safety incidents and what factors help avoid mishaps.
ii) Predicting which managers will end up in the bottom of the pile of employee engagement scores.
iii) He also discusses building a model to predict how incremental increase in factors affecting engagement scores is going to impact the engagement index.
iv) What kind of training targets should businesses set keeping in mind the performance improvement they want to achieve.
v) Impact of changes in benefits.
Finally he takes us through the lessons learned in this journey of establishing a HR Analytics function.