Application of Machine Learning for Prediction of Employees at Risk of Leaving Organization


This practice presents a scientific approach in identifying the talent at risk enabling the organization to respond proactively. The model takes a group of statistically significant factors that correlate to an employee’s decision to leave and further uses Machine Learning algorithms to Predict employee’s probability to quit organization with an accuracy of over ~80%. The impact of the model has been multi-fold on the organization, this assisted leadership to arrive at a macro level decision to revamp the Rewards, Incentive schemes & Promotion policies. Further with the model’s capacity to deliver risk probability with the individual predictor (reasons) for each employee has further helped project managers to act at a micro level resulting in proactive retention of employees.

Presented and Published in: Proceedings of the Sixth International Conference on Business Analytics and Intelligence, December 2018, IISc, India


Phaneendra Akula

Senior Manager DataScience, Sunrise Systems, Inc.

Abhilash Bodanapu

People Analytics Global Head, Group HR, Capgemini

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