Decision support to a Retailer’s staffing strategy using Mixed Integer Linear Programming

Author(s): Anand Pratap Singh, Shashank Srinivasan, Moulik Sthapak, Bharathan Shamasundar

Abstract

Preparing an efficient and effective staffing roster is a challenging task for retailers. An efficient staffing schedule optimizes payroll cost, while meeting desired customer service levels. Doing this, while complying with labour laws and organizational policies makes the schedule effective. While compliance with legal requirements is mandatory, evaluating the impact of alternate organizational policies helps formulate a suitable staffing strategy. These policies present themselves in a combination of factors around shift duration, standardized shift start times, number & length of breaks during the day, off-days, etc. In this paper, we describe our evaluation of alternate organizational policies on payroll cost of a leading luxury retailer in the UK. Each candidate policy was evaluated using Mixed Integer Linear Programming (MILP), following a two-step approach. In the first step, we forecast the number of customers visiting the store at half-hourly intervals and translate it into expected staff count required on the shopfloor. In the second step, we infuse this, together with legal and organizational policy constraints, into the MILP. Our experiments revealed that flexibility in shift start times, and the mandated minimum staff strength for a store, were the primary drivers of payroll cost. More than three shift start times a day, allowed the flexibility of having a higher mix of part-timers. This translated into a 10-12% reduction in paid hours. This benefit can then be considered in the context of the overhead of managing a large part-time population, and a potential shift in organizational culture. Further, the driver of minimum staff strength highlighted the need for reviewing the store’s physical layout.

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