Retail store workforce scheduling by expected operating income maximization

Abstract

We address the problem of retail store sales personnel scheduling by casting it in terms of an expected operating income maximization. In this framework, salespeople are no longer only responsible for operating costs, but also contribute to operating revenue. We model the marginal impact of an additional staff by making use of historical sales and payroll data, conditioned on a store-, date- and time-dependent traffic forecast. The expected revenue and its uncertainty are then fed into a constraint program which builds an operational schedule maximizing the expected operating income. A case study with a medium-sized retailer suggests that revenue increases of 7% and operating income increases of 3% are possible with the approach. © 2011 Springer-Verlag Berlin Heidelberg.