Quantile regression for workforce analytics

Abstract

Understanding the behavior of a constantly changing workforce is key to making business decisions in modern organizations. In this paper, we develop frameworks based on quantile regression to estimate the productivity and attrition profiles of employees from revenue, headcount, and incentive data. Results show the advantages of quantile-specific profiles compared to those obtained with other regression schemes. © 2013 IEEE.