Improving service responsiveness and delivery efficiency of retail networks: A case study of Melbourne

Purpose: The purpose of this paper is to explore how a retail distribution network can be rationalised from a spatial perspective to improve service responsiveness and delivery efficiency. Design/methodology/approach: This paper applies spatial analytics to examine variability of demand, both spatially and from a service delivery perspective, for an auto-parts retail network. Spatial analytics are applied to map the location of stores and customers to represent demand and service delivery patterns and to delineate market areas. Findings: Results show significant spatial clustering in customer demand; whilst the delivery of products to customers, in contrast, is spatially dispersed. There is a substantial gap between revenue generated and costs. Market area analysis shows significant overlap, whereby stores compete with each other for business. In total, 80 per cent of customers can be reached within a 15-minute-radius, whilst only 20 per cent lies outside the market areas. Segmentation analysis of customers, based on service delivery, also shows t he prevalence of the Pareto principle or 80:20 rule whereby 80 per cent of the revenue is generated by 20 per cent of customers. Practical implications: Spatially integrated strategies are suggested to improve the efficiency of the retail network. It is recommended that less accessible and unprofitable customers could be either charged extra delivery cost or outsourced without the risk of a substantial reduction in revenue or quality of service delivery. Originality/value: Innovative application of spatial analytics is used to analyse and visualise unit-record sales data to generate practical solutions to improve retail network responsiveness and operational efficiency.