The American Customer Satisfaction Index (ACSI) is a new type of market-based performance measure for firms, industries, economic sectors, and national economies. The authors discuss the nature and...

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The American Customer Satisfaction Index: Nature, Purpose, and Findings

The bullwhip effect occurs when the demand order variabilities in the supply chain are amplified as they moved up the supply chain. Distorted information from one end of a supply chain to the other can lead to tremendous inefficiencies. Companies can effectively counteract the bullwhip effect by thoroughly understanding its underlying causes. Industry leaders are implementing innovative strategies that pose new challenges: 1. integrating new information systems, 2. defining new organizational relationships, and 3. implementing new incentive and measurement systems. Distorted information from one end of a supply chain to the other can lead to tremendous inefficiencies: excessive inventory investment, poor customer service, lost revenues, misguided capacity plans, inactive transportation, and missed production schedules. How do exaggerated order swings occur? What can companies do to mitigate them? Not long ago, logistics executives at Procter & Gamble (PG it, in turn, created additional exaggerations of order swings to suppliers. In the past few years, the Efficient Consumer Response (ECR) initiative has tried to redefine how the grocery supply chain should work. One motivation for the initiative was the excessive amount of inventory in the supply chain. Various industry studies found that the total supply chain, from when 1 Copyright Sloan Management Review Association, Alfred P. Sloan School of Management Spring 1997 The Bullwhip Effect In Supply Chains 2 products leave the manufacturers' production lines to when they arrive on the retailers' shelves, has more than 100 days of inventory supply. Distorted information has led every entity in the supply chain the plant warehouse, a manufacturer's shuttle warehouse, a manufacturer's market warehouse, a distributor's central warehouse, the distributor's regional warehouses, and the retail store's storage space to stockpile because of the high degree of demand uncertainties and variabilities. It's no wonder that the ECR reports estimated a potential $30 billion opportunity from streamlining the inefficiencies of the grocery supply chain. Figure 1 Increasing Variability of Orders up the Supply Chain Other industries are in a similar position. Computer factories and manufacturers' distribution centers, the distributors' warehouses, and store warehouses along the distribution channel have inventory stockpiles. And in the pharmaceutical industry, there are duplicated inventories in a supply chain of manufacturers such as Eli Lilly or Bristol-Myers Squibb, distributors such as McKesson, and retailers such as Longs Drug Stores. Again, information distortion can cause the total inventory in this supply chain to exceed 100 days of supply. With inventories of raw materials, such as integrated circuits and printed circuit boards in the computer industry and antibodies and vial manufacturing in the pharmaceutical industry, the total chain may contain more than one year's supply. In a supply chain for a typical consumer product, even when consumer sales do not seem to vary much, there is pronounced variability in the retailers' orders to the wholesalers (see Figure 1). Orders to the manufacturer and to the manufacturers' supplier spike even more. To solve the problem of distorted information, companies need to first understand what creates the bullwhip effect so they can counteract it. Innovative companies in different industries have found that they can control the bullwhip effect and improve their supply chain performance by coordinating information and planning along the supply chain. The Bullwhip Effect In Supply Chains 3 Causes of the Bullwhip Effect Perhaps the best illustration of the bullwhip effect is the well-known "beer game." In the game, participants (students, managers, analysts, and so on) play the roles of customers, retailers, wholesalers, and suppliers of a popular brand of beer. The participants cannot communicate with each other and must make order decisions based only on orders from the next downstream player. The ordering patterns share a common, recurring theme: the variabilities of an upstream site are always greater than those of the downstream site, a simple, yet powerful illustration of the bullwhip effect. This amplified order variability may be attributed to the players' irrational decision making. Indeed, Sterman's experiments showed that human behavior, such as misconceptions about inventory and demand information, may cause the bullwhip effect. In contrast, we show that the bullwhip effect is a consequence of the players' rational behavior within the supply chain's infrastructure. This important distinction implies that companies wanting to control the bullwhip effect have to focus on modifying the chain's infrastructure and related processes rather than the decision makers' behavior. We have identified four major causes of the bullwhip effect: 1. Demand forecast updating 2. Order batching 3. Price fluctuation 4. Rationing and shortage gaming Each of the four forces in concert with the chain's infrastructure and the order managers' rational decision making create the bullwhip effect. Understanding the causes helps managers design and develop strategies to counter it. Demand Forecast Updating Every company in a supply chain usually does product forecasting for its production scheduling, capacity planning, inventory control, and material requirements planning. Forecasting is often based on the order history from the company's immediate customers. The outcomes of the beer game are the consequence of many behavioral factors, such as the players' perceptions and mistrust. An important factor is each player's thought process in projecting the demand pattern based on what he or she observes. When a downstream operation places an order, the upstream manager processes that piece of information as a signal about future product demand. Based on this signal, the upstream manager readjusts his or her demand forecasts and, in turn, the orders placed with the suppliers of the upstream operation. We contend that demand signal processing is a major contributor to the bullwhip effect. For example, if you are a manager who has to determine how much to order from a supplier, you use a simple method to do demand forecasting, such as exponential smoothing. With exponential smoothing, future demands are continuously updated as the new daily demand data become available. The order you send to the supplier reflects the amount you need to replenish the stocks to meet the requirements of future demands, as well as the necessary safety stocks. The future demands and the associated safety stocks are updated using the smoothing technique. With long lead times, it is not uncommon to have weeks of safety stocks. The result is that the fluctuations in the order quantities over time can be much greater than those in the demand data. Now, one site up the supply chain, if you are the manager of the supplier, the daily orders from the manager of the previous site constitute your demand. If you are also using exponential smoothing to update your forecasts and safety stocks, the orders that you place with your supplier will have even bigger swings. For an example of such fluctuations in demand, see Figure 2. As we can see from the figure, the orders placed by the dealer to the manufacturer have much greater variability than the The Bullwhip Effect In Supply Chains 4 consumer demands. Because the amount of safety stock contributes to the bullwhip effect, it is intuitive that, when the lead times between the resupply of the items along the supply chain are longer, the fluctuation is even more significant.

The bullwhip effect in supply chains

Are monetary savings the only explanation for consumer response to a sales promotion? If not, how do the different consumer benefits of a sales promotion influence its effectiveness? To address the first question, this research builds a framework of the multiple consumer benefits of a sales promotion. Through a series of measurement studies, the authors find that monetary and nonmonetary promotions provide consumers with different levels of three hedonic benefits (opportunities for value expression, entertainment, and exploration) and three utilitarian benefits (savings, higher product quality, and improved shopping convenience). To address the second question, the authors develop a benefit congruency framework, which argues that a sales promotion’s effectiveness is determined by the utilitarian or hedonic nature of the benefits it delivers and the congruence these benefits have with the promoted product. Among other results, two choice experiments show that, as predicted for high-equity brands, monetary promotions are more effective for utilitarian products than for hedonic products. The authors then discuss the implications of the multibenefit and the benefit congruency frameworks for understanding consumer responses to sales promotions, reexamining the value of everyday-low-price policies, and designing more effective sales promotions.

A Benefit Congruency Framework of Sales Promotion Effectiveness

Are monetary savings the only explanation for consumer response to a sales promotion? If not, how do the different consumer benefits of a sales promotion influence its effectiveness? To address the first question, this research builds a framework of the multiple consumer benefits of a sales promotion. Through a series of measurement studies, the authors find that monetary and nonmonetary promotions provide consumers with different levels of three hedonic benefits (opportunities for value expression, entertainment, and exploration) and three utilitarian benefits (savings, higher product quality, and improved shopping convenience). To address the second question, the authors develop a benefit congruency framework, which argues that a sales promotion’s effectiveness is determined by the utilitarian or hedonic nature of the benefits it delivers and the congruence these benefits have with the promoted product. Among other results, two choice experiments show that, as predicted for high-equity brands, ...

A benefit congruency framework of sales promotion effectiveness

In this article, the authors examine the roles that price, performance, and expectations play in determining satisfaction in a discrete service exchange. The authors maintain that the price fluctua...

W. J. Salmon

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