Quantitative analysis of historical supply chain data has proven itself as a useful tool for initiating development actions in a supply chain network. Using time-based performance metrics such as lead times, promised delivery times and delivery punctuality calculated from data extracted from operative control systems, a supply chain network can be analysed and development actions can be recommended.
Vendor managed inventory (VMI) has established itself as a practical model for implementing inter-company supply chain co-operation. Implementing VMI requires a relatively steady demand of items from supplier to customer. This demand needs to be analysed before an implementation decision is made and control parameters can be set. A quantitative analysis of historical supply chain data is useful.
The objectives of the project were:
- to use the VMI model to enhance the competitiveness of SMEs in the area of supply chain management;
- to create a (consulting) service product supported by software and with a price that can be accepted by SMEs.
The approach of the project was to find 6-8 manufacturing SMEs as partners, analyse their supply chains, create a development plan and find one SME ready and willing to implement a VMI solution. The purpose of the project was to show that the transition from the quantitative analysis to the VMI implementation is easy and useful in a situation where VMI is deemed to be the appropriate control model.
Within the timeframe of the project only two industrial partners were found. A quantitative analysis of their supply chains was performed and development plans were formulated. Both of the analysed supply chains displayed structural promise of the usefulness of a VMI implementation to integrate customers and/or suppliers. In both cases, however, the analysis revealed other, more pressing and promising developmental actions, which the partners subsequently decided to pursue. The timeframe of the project and the situational factors of the industrial partners did not allow a VMI implementation to take place and thus the main hypothesis of the project was not proven. No evidence was discovered that this hypothesis was incorrect.
Even though funding was relatively easily available to SME industrial partners, finding the partners who were willing to participate was difficult. Although many of the almost 50 companies that were spoken to expressed interest in the topic, internal priorities and lack of internal resources prevented many from acting. This is by no means something new in this research environment, but it emphasises the necessity of spawning research projects in close collaboration with the end-users, i.e. the industrial partners.
The project leaders remain convinced that the VMI control model is useful for certain supply chain management situations and that a fact-based situational assessment based on quantitative analysis of supply chain data gathered from operative control systems will help in determining the suitability of VMI in a particular situation. They recommend further research in the area of collaborative planning and forecasting (CPFR).