Prediction of Labor Absenteeism due to Incapacity: A Generalized Linear Model Approach
Abstract
Workplace absenteeism poses a critical challenge for human talent management, with significant economic implications, negative impacts on organizational reputation, and risks to business competitiveness. This article examines the factors influencing absenteeism, focusing on the prediction of two key aspects: the expected number of absence days for an employee over the next three months and the probability of registering at least one absence day during the same period. To achieve this, count and binary response models framed within generalized linear models are employed, yielding highly accurate predictions of the occurrence of work incapacities, at an individual level, in a Colombian financial institution. In addition, from both modeling perspectives, it was found that the factors that have the greatest influence on the occurrence of work incapacities are the month of the year, sex, type of contract, work area, and the history of the number of months in which the employee had already presented incapacity.
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