Bull Whip Effect

The Impact of Forecasting Methods on Bullwhip Effect in Supply Chain Management
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HX Sun1, YT Ren2

Department of Industrial and Systems Engineering, National University of Singapore, Singapore Schoo of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore

Abstract—Recently there has been a surge of interest and research on a phenomenon popularly called the bullwhip effect in supply chain management. The focus of this paper is the impact of demand forecasting on the bullwhip effect. Based on a thorough literature review, we classify existing researches into different categories in terms of modeling methods. Then we show quantification results of the bullwhip effect for simple, two-stage, supply chains consisting of a single retailer and a single manufacturer. Order-up-to inventory policy is assumed. The modeling results of three important forecasting methods (moving average, exponential smoothing, and minimum mean square error) are studied. A comparison is made between these forecasting methods, and some practical guidelines are developed to help managers to select a forecasting method that yields the greatest desired benefit. Finally, possible future research directions in this area are proposed. Keywords—Bullwhip effect, forecasting method, supply chain management

is only recently that some authors begin to study the magnitude of the bullwhip effect given some stochastic demand pattern, a forecasting method, and an ordering policy [8,9,10,11]. Forecasting methods play an important role in supply chain management. This focus of this paper is the impact of different forecasting methods, such as moving average (MA), exponential smoothing (ES), and minimum mean square error (MMSE) method, on the bullwhip effect. This paper is organized as following: first we conduct a through literature review in Section 2, and then in Section