Stabilizing a three-stage supply chain with exponential smoothing forecasting method

Today supply chain is facing market dynamics dominated by demand fluctuation and other environmentally and systemically uncertainties. A supply chain competes in a market that is rapidly changing due to changing demand patterns, delays, product varieties, and technology changing. To stabilize a supply chain, researchers study various causes of the uncertainty in supply chain. One of the most increasingly noticed uncertainty is demand uncertainty. To stabilize a supply chain versus demand uncertainty, many researchers measured bullwhip effect, which implies that demand variability increases as one move up the supply chain. It is obvious that demand forecasting increases this phenomenon, because forecasting errors are imposing to system. In this paper bullwhip effect is measured in a simple three-stage supply chain consisting of a retailer, a manufacturer, and a supplier in which exponential smoothing method is used to forecast future demand. This paper is motivated by exact formulation of demand variation. We compare the results with two other forecasting methods, last demand and moving average with two latest demands. Finally, the effect of parameter on demand variations is analyzed.   Key words: Supply chain, forecast, exponential smoothing, bullwhip effect.