Optimal Incentive-based Plans to Reduce Absenteeism

Abstract

Employee absenteeism and the shift to work from home have become pressing issues, particularly after the recent global pandemic. These human-resource crises are increasingly affecting business productivity across economies worldwide. In this article, we explore incentive-based strategies that have the potential to encourage employees to return to in-office work. We propose an optimization-driven framework designed to make optimal incentive-based decisions. Our framework integrates a predictive model within our optimization model to account for individual employee characteristics, while also taking into consideration the company’s budgetary limitations that often dictate incentives. We formulate the resulting problem as a non-convex optimization model, which we solve to global optimality using a dynamic programming algorithm. To validate our approach, we present a numerical case study based on publicly available data of a courier company in Brazil. The results of the case study clearly indicate that our framework significantly reduces absenteeism.