Multiskilled Workforce Management by Utilizing Closed Chains under Uncertain Demand: A Retail Industry Case

Abstract

A new methodology is presented for structuring the multiskilling characteristics of a set of initially single-skilled employees in the context of a multi-department service sector business, more specifically in the retail industry. Assuming stochastic demand under continuous modeling of the workforce, the methodology decomposes the multiskilling problem into three stages that are then solved sequentially. The first stage delivers a novel analytic expression for estimating the number of multiskilled employees required by each store department, the second stage applies constructive heuristics to these estimates to generate a feasible set of closed chaining structures, and the third stage uses Monte Carlo simulation and a linear programming model to evaluate the chains so generated. The results show that in unbalanced systems, the solutions involve closed long chains and closed short chains of different lengths, which are robust to demand variability, minimize the expected total cost of staff shortages, and exhibit the best cost-effective performance. The methodology provides a tool for company decision makers to address the three fundamental multiskilling issues in unbalanced systems, namely, where to add multiskilling, how much to add and how it should be added.