Pallet drop-size optimisation and its effect on the supply chain using a cost-to-serve model

Abstract

The study explores the critical role of transportation within the Supply Chain, emphasising efficient planning, implementation, and control of goods and information flow from suppliers to customers. Focused on optimising the number of pallets per shipment and occurrence of the shipments to decrease secondary transport costs and environmental impact. The study is conducted with a leading Fast Moving Consumer Goods (FMCG) company in the UK by deploying the methods; Define, Measure, Analyse, Improve, Control (DMAIC) for data collection and Cost-to-Serve (CTS) for data analysis. Initially, a new Cost-to-Serve tool is developed to visualise customer performance and identify opportunities for improvement. Subsequently, a secondary tool is created to monitor the performance of identified customers. An Excel simulator is constructed to extract key performance indicators for logistics performance. Results reveal significant cost savings, with £207 K saved in the first five months of 2023 through shipment reduction of 9.09% compared to 2022. Even with inflation, the cost per pallet has remained steady, showing minimal variation from the average of 2022. This underlines the efficacy of the CTS tool in enhancing secondary transportation performance within the wider supply chain context.