Measuring distribution efficiency of a retail network through data envelopment analysis

This paper investigates the feasibility of using data envelopment analysis (DEA) to measure efficiency and rationalise a distribution network as an alternative approach to the conventional method of optimising delivery routes and schedules through linear programming, which can be complex and data demanding. Using a part of the retail network of a major retailer in Australia as a case study and employing only transportation cost and sales data to measure store performance in distribution, DEA was applied to rationalise the network, thereby enhancing overall distribution efficiency. To support the use of DEA for distribution efficiency measurement, an optimisation technique was applied to the same dataset to corroborate the DEA results. Findings of the analysis show that, despite the different designs of the two approaches, both methods give a similar outcome leading to the identical conclusion that the network under investigation can be rationalised through merging the less efficient stores with the more efficient ones. In comparison with optimisation, which necessitates a large amount of disaggregate data to run, the DEA method requires only a small quantity of aggregate data to operate. The problem formulation is relatively simple and the implementation is comparatively easy. While DEA has been applied to compare store performance in many industries, the use of it in measuring distribution efficiency of a retail network is limited, not to mention validation of the DEA results using the conventional optimisation technique. This study has expanded the current research on retail network analysis by employing DEA as a flexible user-friendly analytical tool and corroborating the outcome with the traditional optimisation method.