he research methodology to be undertaken to find answers for the research question for controlling the bullwhip effect right from manufacturer’s level to retailer’s level. And VMI is just one of the methods and the research has to a long way to identify an ideal method. .
According to the survey of the U.S. Commerce Department reported in 2002, trade in the United States is characterized by $ 1.1 trillion inventory for just $ 3.2 trillion of retail sales per year. The value of inventory in each of the supply chain is $ 400 billion at retail outlets, $ 290 billion at the wholesalers’ or distributors’ warehouses and $ 450 billion with manufacturers’ factory or warehouses locations. Where as, such a stockpile should be of a comfortable reserve in stock in trade, there is actually out-of-stock situation at all the points. It has been reported that 8.2 % of the shoppers still go without buying what they need and thus out-of-stock position represents 6.5 % of retail sales as a whole. Even if the retailers manage to supply alterative products, lost sales on account of this situation turn out to be 3.1% of the total sales. Though 3.1 % appears negligible, it is a substantial loss of retail margins at micro as well as macro level. And loss of customers’ goodwill is beside the point. It is noteworthy that this situation is not due to want of inventory or resources (Lee, 2002). This situation is brought about by what is called bullwhip effect which this research proposes to study.
The seemingly negligible impact of bullwhip effect actually translates into lost sales and loss of profit of significant proportions and is therefore an important area in a supply chain that needs to be analyzed for being avoided. Accurate demand forecasting is apparently the possible solution . Therefore aim and objective of this research is to ascertain how to reach an accurate demands forecasting to avoid bullwhip effect in the manufacturing level and loss of sales in the retailer