______________________________________________________________________________ Supply Chain Management- Cracking the bullwhip effect An Approach Paper By Paritosh Agarwal ________________________________________________________________________________ Page 1 of 18 ______________________________________________________________________________ Table of Contents TABLE OF CONTENTS .....................................................................................................................................2 1. INTRODUCTION.........................................................................................................................................3 2. WHAT IS BULLWHIP EFFECT? ..............................................................................................................4 3. THE BEER GAME......................................................................................................................................6 4. CAUSES OF BULLWHIP EFFECT.........................................................................................................11 5. IMPACT OF BULLWHIP EFFECT..........................................................................................................13 6. CRACKING THE BULLWHIP EFFECT..................................................................................................14 7. THE BULLWHIP EFFECT AND ITS IMPACT ON SUPPLY CHAIN ...................................................15 8. CONCLUSION..........................................................................................................................................17 9. REFERENCE ............................................................................................................................................18 ________________________________________________________________________________ Page 2 of 18 ______________________________________________________________________________ 1. Introduction Fluctuations in demand vary significantly between industries. The apparel industry, for example, is subject to major demand adjustments driven by business cycles and seasonality, while the diaper market enjoys relatively consistent demand. One would expect players in various retail supply chains to frequently misjudge demand, causing shortages or inventory surpluses at different stages in the chain. But given the consistency in diaper demand, shouldn’t the diaper supply chain be more accurate and efficient? Yes – it should. But it isn’t. Even industries with reliable demand patterns waste millions of dollars each year because they aren’t able to match production to demand. A major cause of supply chain inefficiency has been dubbed the “bullwhip effect”. ________________________________________________________________________________ Page 3 of 18 ______________________________________________________________________________ 2. What is Bullwhip Effect? Even industries with reliable demand patterns waste millions of dollars each year because they aren’t able to match production to demand. A major cause of supply chain inefficiency has been dubbed the “bullwhip effect”. Proctor & Gamble coined the term “bullwhip effect” by studying the demand fluctuations for Pampers (disposable diapers). This is a classic example of a product with very little consumer demand fluctuation. P&G observed that distributor orders to the factory varied far more than the preceding retail demand. P & G orders to their material suppliers fluctuated even more. Babies use diapers at a very predictable rate, and retail sales resemble this fact. Information is readily available concerning the number of babies in all stages of diaper wearing. Even so P&G observed that this product with uniform demand created a wave of changes up the supply chain due to very minor changes in demand. Fig 1 ________________________________________________________________________________ Page 4 of 18 ______________________________________________________________________________ Fig 2 The graphical representations above show the bullwhip effect between two supply chain partners. It can be seen that the Distributor orders to the factory experience demand fluctuate far more drastically than the retail demand. Over time as the Distributor builds inventory and fulfills orders, it communicates very different demand levels to the upstream factory by the order amounts it requests. This becomes more complicated the farther up the supply chain we go. The bullwhip effect describes how inaccurate information, a lack of transparency throughout the supply chain, and a disconnect between production and real-time supply chain information result in lost revenue, bad customer service, high inventory levels and unrealized profits. As information (usually forecast data) is passed down the supply chain, most participants only have access to data from businesses either directly above or directly below them. In industries where the entire supply chain can consist of numerous layers, this means that the majority of the information that managers use to make decisions is localized to only a few participants and hidden from those further up or downstream. Without a clear view of end-user demand, companies must rely on only that information they have access to. Unfortunately, this information is often distorted by multiple layers of forecasts and transactions. This principal is easily demonstrated through an exercise often conducted in business schools called the beer game. ________________________________________________________________________________ Page 5 of 18 ______________________________________________________________________________ 3. The Beer Game The beer game was developed at MIT by the Systems Dynamic Group in the 1960s. The game involves a simple production/distribution system for a single brand of beer. There are three players in the game including a retailer, a wholesaler, and a marketing director at the brewery. Each player's goal is to maximize profit. A truck driver delivers beer once each week to the retailer. Then the retailer places an order with the trucker who returns the order to the wholesaler. There's a four week lag between ordering and receiving the beer. The retailer and wholesaler do not communicate directly. The retailer sells hundreds of products and the wholesaler distributes many products to a large number of customers. The following represents the results of a typical beer game:- 3.1 The Retailer Week 1: Lover's Beer is not very popular but the retailer sells four cases per week on average. Because the lead time is four weeks, the retailer attempts to keep twelve cases in the store by ordering four cases each Monday when the trucker makes a delivery. Week 2: The retailer's sales of Lover's beer doubles to eight cases, so on Monday, he orders 8 cases. Week 3: The retailer sells 8 cases. The trucker delivers four cases. To be safe, the retailer decides to order 12 cases of Lover's beer. Week 4: The retailer learns from some of his younger customers that a music video appearing on TV shows a group singing "I'll take on last sip of Lover's beer and run into the sun." The retailer assumes that this explains the increased demand for the product. The trucker delivers 5 cases. The retailer is nearly sold out, so he orders 16 cases. Week 5: The retailer sells the last case, but receives 7 cases. All 7 cases are sold by the end of the week. So again on Monday the retailer orders 16 cases. Week 6: Customers are looking for Lover's beer. Some put their names on a list to be called when the beer comes in. The trucker delivers only 6 cases and all are sold by the weekend. The retailer orders another 16 cases. Week 7: The trucker delivers 7 cases. The retailer is frustrated, but orders another 16 cases. Week 8: The trucker delivers 5 cases and tells the retailer the beer is backlogged. The retailer is really getting irritated with the wholesaler, but orders 24 cases. 3.2 The Wholesaler The wholesaler distributes many brands of beer to a large number of retailers, but he is the only distributor of Lover's beer. The wholesaler orders 4 truckloads from the brewery truck driver each week and receives the beer after a 4 week lag. The wholesaler's policy is to keep 12 truckloads in inventory on a continuous basis. Week 6: By week 6 the wholesaler is out of Lover's beer and responds by ordering 30 truckloads from the brewery. Week 8: By the 8th week most stores are ordering 3 or 4 times more Lovers' beer than their regular amounts. ________________________________________________________________________________ Page 6 of 18 ______________________________________________________________________________ Week 9: The wholesaler orders more Lover's beer, but gets only 6 truckloads. Week 10: Only 8 truckloads are delivered, so the wholesaler orders 40. Week 11: Only 12 truckloads are received, and there are 77 truckloads in backlog, so the wholesaler orders 40 more truckloads. Week 12: The wholesaler orders 60 more truckloads of Lover's beer. It appears that the beer is becoming more popular from week to week. Week 13: There is still a huge backlog. Weeks 14-15: The wholesaler receives larger shipments from the brewery, but orders from retailers begin to drop off. Week 16: The trucker delivers 55 truckloads from the brewery, but the wholesaler gets zero orders from retailers. So he stops ordering from the brewery. Week 17: The wholesaler receives another 60 truckloads. Retailers order zero. The wholesaler orders zero. The brewery keeps sending beer. 3.3