Designing training plans for a multiskilled workforce under demand uncertainty: Integrating employer objectives and employee preferences

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Abstract
Multiskilling is a workforce flexibility strategy that enables employees to perform multiple tasks effectively. This paper addresses a personnel training problem by incorporating multiskilling through a k-chaining policy with k≥2, while explicitly considering three key employee training preferences. A two-stage stochastic optimization model is proposed to minimize total training costs and the expected costs associated with overstaffing and understaffing, while incorporating penalties and rewards linked to employee preferences. In this way, the model simultaneously seeks to reduce employer costs and enhance employee satisfaction. The proposed methodology is evaluated through a real-world retail case study using processed and simulated data from a Chilean store. Four experiments and nine levels of demand variability are analyzed. The results show that incorporating employee preferences, either partially or fully, does not significantly affect employer costs or overall multiskilling requirements, while substantially improving employee satisfaction. This suggests that employer and employee objectives are not necessarily conflicting, enabling the design of training plans that benefit both parties. Furthermore, sensitivity analyses on key preference parameters indicate that, although these parameters influence workforce composition, their impact on costs and multiskilling levels remains limited, confirming the stability of the proposed solution.

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