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HiSPEED: a system for mining performance appraisal data and text

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Abstract

Performance appraisal (PA) is a crucial HR process that enables an organization to periodically measure and evaluate every employee’s performance and also to drive performance improvements. In this paper, we describe a novel system called HiSPEED to analyze PA data using automated statistical, data mining and text mining techniques, to generate novel and actionable insights/patterns and to help in improving the quality and effectiveness of the PA process. The goal is to produce insights that can be used to answer (in part) the crucial “business questions” that HR executives and business leadership face in talent management. The business questions pertain to (1) improving the quality of the goal setting process, (2) improving the quality of the self-appraisal comments and supervisor feedback comments, (3) discovering high-quality supervisor suggestions for performance improvements, (4) discovering evidence provided by employees to support their self-assessments, (5) measuring the quality of supervisor assessments, (6) understanding the root causes of poor and exceptional performances, (7) detecting instances of personal and systemic biases and so forth. The paper discusses specially designed algorithms to answer these business questions and illustrates them by reporting the insights produced on a real-life PA dataset from a large multinational IT services organization.

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Acknowledgements

We would like to thank Dr. Ritu Anand for her unwavering support. We also thank Preeti Gulati, Amol Khanapurkar, Dharshana Ramachandran, Swapnil Hingmire, Sriram Baskaran, Amol Aaeer, and members of the TCS HR and CTO teams.

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Authors and Affiliations

  1. TCS Research, Tata Consultancy Services Ltd., Pune, 411013, India

    Girish Keshav Palshikar, Manoj Apte, Sachin Pawar & Nitin Ramrakhiyani

Authors
  1. Girish Keshav Palshikar
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  2. Manoj Apte
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  3. Sachin Pawar
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  4. Nitin Ramrakhiyani
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Corresponding author

Correspondence to Manoj Apte.

Additional information

This paper is an extended version of the DSAA’2017 application track paper titled “HiSPEED: A System for Mining Performance Appraisal Data and Text” [1]

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Palshikar, G.K., Apte, M., Pawar, S. et al. HiSPEED: a system for mining performance appraisal data and text. Int J Data Sci Anal 8, 95–111 (2019). https://doi.org/10.1007/s41060-018-0142-x

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