Vendor managed forecasting: A case study of small enterprise, Enterprises use supply chain management practices for improving business or supply chain performance. It is observed that supply chain technologies like VMI are now becoming an integral part of enterprise’s strategy. Even small and medium enterprises can adopt this practice and improve the performance of supply chain. This paper discusses vendor managed forecasting with the help of case study. It shows how a small enterprise improves supply chain performance by using demand related information obtained from retailer. The results obtained in the study shows that vendor managed forecasting in supply chain reduces the demand variation and improves inventory management significantly.
In recent years, many enterprises have been compelled to share demand and inventory information with their suppliers and customers to get the competitive advantage (Disney & Towill, 2003). Vendor Managed Inventory (VMI) is one of such information sharing mechanisms adopted by organizations. In VMI, the vendor or supplier is given the responsibility of managing the customer’s stock, based on the shared information between them (Jung et al., 2004). Vendor coordinates and integrates all supply chain activities into a seamless process. As a result of VMI adoption drastic improvements are observed in supply chain and business performance.
Several performance measures have been reported in the literature to measure different aspects of the supply chain performance. Usually the measures are inventory levels, service levels, order fulfillment time, total supply chain cost, forecasting accuracy, supply chain flexibility, fill rates etc. A careful study of these measures shows that the common denominator is accurate demand forecasting. If the forecast is not accurate, the quantity ordered by retailers may not reflect the demand for the period and the errors in retailers forecast may pass to the supplier in form of distorted orders (Zhao et al., 2003). Therefore forecasting results are very influential in making managerial decisions and evaluating performance of the company (Haq & Kannan, 2006).
It has been observed that, to improve the accuracy of forecasts there is an incessant need to interact with supply chain partners and share right kind of information at right time. Enterprises adopt latest information technology tools to share real-time information. However, many Enterprises experiences difficulty in adoption of IT tools. Moreover, it is found that adoption is more difficult for small and medium enterprises. In a dedicated supply chain, where small and medium enterprises are under vendor managed inventory pact with retailers; the retailers and managers at SMEs do not have a capacity and capability of forecasting the demand accurately. Rudberg et al. (2002) have suggested that collaboration and demand information sharing with supply chain partners to establish a joint forecast; could reduce demand uncertainty within the supply chain. Taking the motivation we decided to adopt Vendor managed Inventory, specifically Vendor Managed Forecasting practice in a small scale Industry. It is known that for adopting VMI, organizations use supply chain software. Supply chain software’s have an inbuilt algorithms based on statistical forecasting models which assist organizations in forecasting. The case company was not able to afford the software. Therefore, it was decided to go for traditional VMI and develop manual forecasts based on statistical models. The accuracy of the forecast highly depended on the information provided by retailers about the demand. So, information sharing mechanism was also developed.
In this paper we have studied vendor managed forecasting for a small-scale enterprise located at the central part of India. The objective of study is to show how that information sharing mechanism helps a small-scale enterprise to make a better forecast and improve the supply chain performance. In the process we have compared the forecasts obtained from different statistical models .The remaining organization of the paper is as follows. In the section 2, we have presented the literature that focuses on quantitative forecasting models. Section 3, describes the case study and action research methodology. Section 4 ponders performance measurement. Section 5 discusses the results and finally in Section 6 conclusions are drawn.