Predictive Modelling of Employee Turnover in Indian IT Industry Using Machine Learning Techniques

Shikha N. Khera · Divya

83 citations0/0 files storedVision The Journal of Business Perspective

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AI and HR Technologies Online Learning and Analytics Customer churn and segmentation

Abstract

Information technology (IT) industry in India has been facing a systemic issue of high attrition in the past few years, resulting in monetary and knowledge-based loses to the companies. The aim of this research is to develop a model to predict employee attrition and provide the organizations opportunities to address any issue and improve retention. Predictive model was developed based on supervised machine learning algorithm, support vector machine (SVM). Archival employee data (consisting of 22 input features) were collected from Human Resource databases of three IT companies in India, including their employment status (response variable) at the time of collection. Accuracy results from the confusion matrix for the SVM model showed that the model has an accuracy of 85 per cent. Also, results show that the model performs better in predicting who will leave the firm as compared to predicting who will not leave the company.

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References

1995Understanding the small business sector 1998AN ORGANIZATION-LEVEL ANALYSIS OF VOLUNTARY AND INVOLUNTARY TURNOVER.2016Understanding The Small Business Sector 2011Investing in people: financial impact of human resource initiatives 2012Human Capital Investments and Employee Performance: An Analysis of IT Services Industry 2010Employee churn prediction 2010Predicting turnover intentions 2011Armstrong's Handbook of Strategic Human Resource Management

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