Improving the robustness of retail workforce management with a labor flexibility strategy and consideration of demand uncertainty

This article examines the challenge of personnel scheduling problem by incorporating a labor flexibility approach that integrates annualized hours, multiskilled employees, and overtime within an uncertain demand environment. To address this problem, a two-stage stochastic optimization model is developed to determine the optimal workforce size, structure a targeted training program using a 2-chaining approach, and allocate weekly working hours, both regular and overtime, while explicitly considering demand variability. The proposed approach is assessed through multiple experiments to analyze the impact of incorporating multiskilling and different levels of demand fluctuations. Furthermore, the workforce configuration—comprising staff size and training structure— resulting from the stochastic model is compared with that obtained using a deterministic framework. The findings indicate that the stochastic model yields more robust and cost-effective solutions under demand uncertainty, significantly reducing training costs and minimizing expected labor costs related to overstaffing, understaffing, and wages. Additionally, the results reinforce the synergistic relationship between multiskilling and overtime in mitigating workforce imbalances caused by demand uncertainty. Finally, this research offers strategic insights for managers in retail and service industries aiming to optimize workforce planning and adaptability while maintaining cost efficiency in the face of fluctuating and uncertain demand.