The Bullwhip Effect (Forrester 1961; Lee, Padmanabhan, and Whang 1997) has been studied extensively because of its ability to explain excess inventory in supply chains. In addition, some studies have attempted to quantify the financial effects of the demand variance amplification and inventory increases that characterize the effect (Metters 1997). On the other hand, there is mixed evidence about the aggregate prevalence of the Bullwhip Effect and its consequences (Cachon et al. 2007). But even aggregate studies admit the likelihood of variance amplification as supply chain participants are positioned further from final customers. Therefore, this article’s primary objective is to develop and implement a system dynamics model that allows an analysis of the financial consequences of the Bullwhip Effect in a trans-border setting. We employed typical planning policies and reported operating and financial parameters to investigate how a relatively complete supply chain performs, both in terms of inventory and service variability (the Bullwhip Effect), and in terms of total cost including inventory and service penalty costs. To analyze the problem, we first outline a base case scenario using supply chain characteristics as reported by a real firm, in this case a Mexican electronics supplier to U.S. automobile assemblers. After establishing the financial levers embedded in this firm’s current supply chain, we use system dynamics (Forrester 1961; Towill 1996) simulation techniques to evaluate which supply chain strategies will have the largest effect on the Bullwhip Effect Index (BE) (Metters 1997), and system costs. Furthermore, sensitivity analysis suggests some interesting, counter- intuitive results. The implications of these findings are further developed as we test how lead time reduction can mitigate the Bullwhip Effect in the simulated setting. In some supply chains, the Bullwhip Effect can drive 13 %-25 % of operating costs (Lee et al. 1997). Thus “taming” the Bullwhip Effect can have a major impact on firm costs and knowing where to invest effort and resources for this purpose should be a high priority for supply chain managers. We believe that we can show some innovative approaches to an important problem. The remainder of this article will be divided as follows. The next section will review some of the literature about performance measures, cost drivers, and supply chain strategies to be analyzed. Then we will construct and analyze a simulation model that shows how these strategies affect a standard measure of the Bullwhip Effect and further affect supply chain costs. The article concludes with some thoughts on the appropriate measurement techniques for demand variance inflation, as well as the limitations of this work, and suggestions for further research.
Mendeley saves you time finding and organizing research
Choose a citation style from the tabs below