Tuesday, February 5, 2013
The Impact of Bullwhip Effect in SCM and How to Manage It
From the case study, in the early 1990s, P&G faced a problem of extreme demands variation for its Pamper diapers. Although the purchase rate somehow remain steady at the customer end, it has been found that the variation of order rates amplify up the supply chain, from the retailer level to the distributor level. This phenomenon is called bullwhip effect, and the distorted information from one end of a supply chain to the other can lead to tremendous inefficiencies, such as excessive inventory investment, poor customer service, lost revenues, misguided capacity plans, inactive transportation, and missed production schedules.[i]
In learning supply chain management, the most classical beer game[ii] has been used to demonstrate the same phenomenon. Here is a video that introduce the general concept, and just take 1 minute you will easily understand what is bullwhip effect.
Then, P&G attributed the huge variation in orders to reasons like infrequent placing of orders, distributors placing multiple orders, and the most important is because of lacking information of the actual customer demand on the upstream end. According to the relevant materials I have read for this week, I would like to provide some technological advances to help P&G manage the bullwhip effect more efficiently.
P&G took next steps to update its supply chain model and inventory system. Managing the bullwhip effect is minimizing the fluctuation and variation of the demand through the supply chain, and one of the keys is to share information with other members of the supply chain. The Internet, for its information sharing capabilities and Radio frequency identification (RFID) could be used.[iii] However, P&G still need to be careful when use the information sharing, because it is only an initial step to reduce the bullwhip effect within a supply chain, if use it from other stages continuously will lead to other problems.[iv]For instance, the POS data for a cosmetics store of P&G is not useful for suppliers of Pamper diapers. Moreover, if P&G cannot ensure its short order lead time, information sharing could be redundant because its supply chain is not capable of capitalizing on that information.[v] Coordination in the supply chain is the next primary technique. Besides the Vendor-Managed Inventory (VMI) which P&G has already applied, the Collaborative Planning, Forecasting, and Replenishment (CPFR) could also be used to moderate the bullwhip effect, as well as to reduce cost (i.e., inventory, transportation).[vi]
Finally, I’d like to talk about the impact of demand forecasting in the bullwhip effect. Since P&G encouraged the whole supply chain work together to get an aligned picture of demand, it made decision to ensure the entire supply chain driven by demand which requires demand forecasting. An intelligent demand forecasting would lead to less inventory, better order fulfillment, higher profit margins, even better decision making. However, the forecasting demand will inevitably lead to bullwhip effect has already been proven, and the size of the impact does depend on the demand forecasting methods. [vii] For example, the bullwhip effect can be reduced, but not completely eliminated, by centralizing customer demand information. [viii]
In order to get more accurate demand forecasting for better decision making in its supply chain management, I also recommend P&G to take more action to refine its demand forecasting methods, and pay more attention on the inputs rather than only focusing on the outcomes in the metric model. Examing different key variables to get a range of possible outcomes will provide better reference for the decision making of supply chain upstream under the uncertainty of future.
It seems that by using sophisticated computing method could generate high quality demand forecasting, thus moderate the bullwhip effect. However, does every participant in supply chain really act rationally, as our logical model designed, in the real world? How can we minimizing the risk due to the inherent irrational behavior of people? Like, a manager in P&G, who has a tendency to be over-optimistic, may exert imperceptible influence on shifting the model to get a biased optimistic outcome. And also, consumers rarely make rational consumption may cause the demand variation.
[i] Lee, Hau L., V. Padmanabhan, and Seungjin Whang. "The Bullwhip Effect In Supply Chains1." Sloan management review 38.3 (1997): 93-102.
[ii] J. D. Sterman, “Modeling managerial behavior: misperceptions of feedback in a dynamic decision making experiment,” Management Science, vol. 35, pp. 321–339, 1989.
[iii] Lee, H.L., V. Padmanabhan, and S. Whang. “Comments on ‘Information Distortion in a Supply Chain: The Bullwhip Effect,’” Management Science, 50(12), 1887-1893, 2004.
[iv] Wilck, Joseph H. "Managing the Bullwhip Effect." Unpublished Ph. D. Dual Degree, Industrial Engineering and Operations Research, College of Engineering (available at< http://www. engr. psu. edu/symposium2006/papers/Session% 203D% 20-% 20Modeling% 20and% 20Engineering% 20Applications/Wilck. pdf>, accessed July 2009) (2006).
[v] Gilbert, K. “An ARIMA Supply Chain Model,” Management Science, 51(2), 305-310, 2005.
[vi] Chopra, S. and P. Meindl. Supply Chain Management. Second Edition, Prentice Hall, 478-504, 2004.
[vii]  Dejonckheere, J., S.M. Disney, M.R. Lambrecht, and D.R. Towill. “Measuring and Avoiding the Bullwhip Effect: A Control Theoretic Approach,” European Journal of Operational Research, 147, 567-590, 2003.
[viii] Chen, Frank, et al. "Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information." Management science 46.3 (2000): 436-443.