The impact of information sharing and forecasting in capacitated industrial supply chains: A case study

This paper models and analyses the effect of information sharing and forecasting on the performance parameters of an actual industrial supply chain consisting of Small-To-Medium sized enterprises. The paper reports on the industrial supply chain studied, which was undergoing a Business Process Re-engineering (BPR) exercise. The aim of the BPR exercise was the streamlining of existing unstructured processes, ultimately culminating in the introduction of an ERP system into the organisation to improve information sharing between the supply chains echelons. The paper reviews previous work in this area and expands this work to address the issues posed by a more complex real industrial example. The model itself has been developed for a complex supply chain structure. This supply chain has multiple customers, distributors and product families, with customers and distributors face differing demand patterns. This model and its associated experimentation highlights the significant benefits achievable through the use of improved information sharing and forecasting techniques on the supply chain performance parameters. Potential total supply chain cost savings of up to 9.7% have been shown, with increased savings occurring with reduced system capacity. The model also quantifies the impact of collaboration between all partners in the study and shows that gains are achievable by all parties in the supply chain.