Chapter 10: Supply Chain Coordination - PDF Guide
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This textbook chapter focuses on supply chain coordination. It covers the bullwhip effect, obstacles to coordination, and managerial solutions. Learn how to improve supply chain responsiveness, reduce costs, and enhance overall performance.
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Here is the converted markdown format of the document: # Chapter 10: Coordination in a Supply Chain ## Learning Objectives After reading this chapter, you will be able to: * 10.1 Describe supply chain coordination and the bullwhip effect, and their impact on supply chain performance. * 10.2...
Here is the converted markdown format of the document: # Chapter 10: Coordination in a Supply Chain ## Learning Objectives After reading this chapter, you will be able to: * 10.1 Describe supply chain coordination and the bullwhip effect, and their impact on supply chain performance. * 10.2 Identify obstacles to coordination in a supply chain. * 10.3 Discuss managerial levers that help improve coordination in a supply chain. * 10.4 Understand some practical approaches to improve coordination in a supply chain. In this chapter, we extend the ideas from Chapter 9 and focus on improving coordination across the supply chain. We discuss how lack of coordination leads to a degradation of responsiveness and an increase in cost within a supply chain. We describe various obstacles that lead to this lack of coordination and exacerbate variability through the supply chain. We then identify appropriate managerial levers that can help overcome the obstacles and improve coordination. In particular, we discuss how collaboration can improve supply chain performance. ## 10.1 Describe supply chain coordination and the bullwhip effect, and their impact on supply chain performance. ### Lack of Supply Chain Coordination and its Impact on Performance Supply chain coordination improves if all stages of the chain take actions that are aligned and increase total supply chain surplus. Supply chain coordination requires each stage of the supply chain to share information and take into account the impact its actions have on other stages. A lack of coordination occurs either because different stages of the supply chain have local objectives that conflict or because information moving between stages is delayed and distorted. Different stages of a supply chain may have conflicting objectives if each stage tries to maximize its own profits, resulting in actions that often diminish total supply chain profits (see Chapters 11, 13, and 15). Today, supply chains consist of stages with different owners. For example, Ford Motor Company has thousands of suppliers, from Goodyear to Motorola, and each of these suppliers has many suppliers in turn. Not only does each stage focus on its own objectives, but information is also often distorted as it moves across the supply chain because complete information is not shared between stages. This distortion is exaggerated by the fact that supply chains today produce a large variety of products. Ford produces different models, with several options for each model. The increased variety makes it difficult for Ford to coordinate information exchange with thousands of suppliers and dealers. The fundamental challenge today is for supply chains to achieve coordination in spite of multiple ownership and increased product variety. One outcome of the lack of supply chain coordination is the *bullwhip effect*, in which fluctuations in orders increase as they move up the supply chain from retailers to wholesalers to manufacturers to suppliers, as shown in Figure 10-1. The bullwhip effect distorts demand information within the supply chain, with each stage having a different estimate of what demand looks like. Procter & Gamble (P&G) has observed the bullwhip effect in the supply chain for Pampers diapers (Lee, Padmanabhan, and Whang, 1997). The company found that raw material orders from P&G to its suppliers fluctuated significantly over time. Farther down the chain, when sales at retail stores were studied, the fluctuations, though present, were small. It is reasonable to assume that the consumers of diapers (babies) at the last stage of the supply chain used them at a steady rate. Although consumption of the end product was stable, orders for raw material were highly variable, increasing costs and making it difficult to match supply and demand. A set of four line charts illustrates demand fluctuation at different stages of a supply chain: 1. Consumer Sales at Retailer: Shows a relatively stable demand pattern over time. 2. Retailer's Orders to Wholesaler: Displays slightly more variability in order quantities compared to consumer sales. 3. Wholesaler's Orders to Manufacturer: Presents increased fluctuations in order sizes. 4. Manufacturer's Orders with Supplier: Exhibits the most significant variability in order quantities. Hewlett-Packard (HP) also found that the fluctuation in orders increased significantly as they moved from the resellers up the supply chain to the printer division to the integrated circuit division (ibid.). Once again, although product demand showed some variability, orders placed with the integrated circuit division were much more variable. This made it difficult for HP to fill orders on time and increased the cost of doing so. Studies of the apparel and grocery industries have shown a similar phenomenon: The fluctuation in orders increases as one moves upstream in the supply chain from retail to manufacturing. Barilla, an Italian manufacturer of pasta, observed that weekly orders placed by a local distribution center fluctuated by up to a factor of 70 in the course of the year, whereas weekly sales at the distribution center (representing orders placed by supermarkets) fluctuated by a factor of less than three (Hammond, 1994). Barilla was thus facing demand from the distribution center that was much more variable than customer demand. This led to increased inventories, poorer product availability, and a drop in profits. A similar phenomenon, over a longer time frame, has been observed in several industries that are quite prone to "boom and bust" cycles. A good example is the production of memory chips for personal computers. Between 1985 and 1998, at least two cycles occurred during which prices of memory chips fluctuated by a factor of more than three. These large fluctuations in price were driven by either large shortages or surpluses in capacity. The shortages were exacerbated by panic buying and overordering that was followed by a sudden drop in demand. The lack of coordination in a supply chain increases variability and hurts the supply chain surplus. We discuss the impact of the bullwhip effect on costs and responsiveness in the context of the P&G diaper supply chain. #### Manufacturing Cost The lack of coordination increases manufacturing cost in the supply chain. As a result of the bullwhip effect, P&G and its suppliers must satisfy a stream of orders that is much more variable than customer demand. P&G can respond to the increased variability by either building excess capacity or holding excess inventory (see Chapter 8), both of which increase the manufacturing cost per unit produced. #### Inventory Cost The lack of coordination increases inventory cost in the supply chain. To handle the increased variability in demand, P&G must carry a higher level of inventory than would be required if the supply chain were coordinated. As a result, inventory costs in the supply chain increase. The high levels of inventory also increase the warehousing space required and thus the warehousing cost incurred. #### Replenishment Lead Time Lack of coordination increases replenishment lead times in the supply chain. The increased variability as a result of the bullwhip effect makes scheduling at P&G and supplier plants much more difficult than when demand is level. There are times when the available capacity and inventory cannot supply the orders coming in. This results in higher replenishment lead times. #### Transportation Cost The lack of coordination increases transportation cost in the supply chain. The transportation requirements over time at P&G and its suppliers are correlated with the orders being filled. As a result of the bullwhip effect, transportation requirements fluctuate significantly over time. This raises transportation cost because surplus transportation capacity needs to be maintained to cover high-demand periods. #### Labor Cost for Shipping and Receiving The lack of coordination increases labor costs associated with shipping and receiving in the supply chain. Labor requirements for shipping at P&G and its suppliers fluctuate with orders. A similar fluctuation occurs for the labor requirements for receiving at distributors and retailers. The various stages have the option of carrying excess labor capacity or varying labor capacity in response to the fluctuation in orders. Either option increases total labor cost. #### Level of Product Availability Lack of coordination hurts the level of product availability and results in more stockouts in the supply chain. The large fluctuations in orders make it harder for P&G to supply all distributor and retailer orders on time. This increases the likelihood that retailers will run out of stock, resulting in lost sales for the supply chain. #### Relationships Across the Supply Chain Lack of coordination has a negative effect on performance at every stage and thus hurts the relationships among different stages of the supply chain. There is a tendency to assign blame to other stages of the supply chain because each stage thinks it is doing the best it can. The lack of coordination thus leads to a loss of trust among different stages of the supply chain and makes any potential coordination efforts more difficult. From the earlier discussion, it follows that lack of coordination has a significant negative impact on the supply chain's performance by increasing cost and decreasing responsiveness. The impact of the lack of coordination on different performance measures is summarized in Table 10-1. #### Summary of Learning Objective 1 Supply chain coordination requires all stages to take actions that maximize total supply chain profits. A lack of coordination results if different stages focus on optimizing their local objectives or if information is distorted as it moves across the supply chain. The phenomenon that fluctuation in orders increases as one moves up the supply chain from retailers to wholesalers to manufacturers to suppliers is referred to as the bullwhip effect. This effect results in an increase in all costs in the supply chain and a decrease in customer service levels. The bullwhip effect moves all parties in the supply chain away from the efficient frontier and results in a decrease of both customer satisfaction and profitability within the supply chain. **Table 10-1** Impact of the Lack of Coordination on Supply Chain Performance *Test Your Understanding* * 10.1.1 The bullwhip effect causes * \[ \] maximization of supply chain surplus. * \[ \] improved accuracy of demand information within the supply chain. * \[ \] different stages of the supply chain to have a very different estimate of what demand looks like. * \[ \] less need for aggregate planning. * 10.1.2 Long-term boom and bust cycles that mimic the bullwhip effect have been seen within the following product groups: * \[ \] calendars and greeting cards. * \[ \] cat food. * \[ \] university textbooks. * \[ \] memory chips for personal computers. ## 10.2 Identify obstacles to coordination in a supply chain. ### Obstacles to Coordination in a Supply Chain Any factor that leads to either local optimization by different stages of the supply chain or an increase in information delay, distortion, and variability within the supply chain is an obstacle to coordination. If managers in a supply chain are able to identify the key obstacles, they can then take suitable actions to improve coordination. We divide the major obstacles into five categories: * Incentive obstacles * Information-processing obstacles * Operational obstacles * Pricing obstacles * Behavioral obstacles #### Incentive Obstacles Incentive obstacles occur in situations when incentives offered to different stages or participants in a supply chain lead to actions that increase variability and reduce total supply chain profits. ##### Local Optimization Within Functions or Stages of a Supply Chain Incentives that focus only on the local impact of an action result in decisions that do not maximize total supply chain surplus. For example, if the compensation of a transportation manager at a firm is linked to the average transportation cost per unit, the manager is likely to take actions that lower transportation costs even if they increase inventory costs or hurt customer service. It is natural for any participant in the supply chain to take actions that optimize performance measures along which they are evaluated. For example, managers at a retailer such as Carrefour make all their purchasing and inventory decisions to maximize Carrefour profits, not total supply chain profits. Buying decisions based on maximizing profits at a single stage of the supply chain lead to ordering policies that do not maximize supply chain profits (see Chapters 11, 13, and 15). ##### Sales Force Incentives Improperly structured sales force incentives are a significant obstacle to coordination in a supply chain. In many firms, sales force incentives are based on exceeding sales thresholds during an evaluation period of a month or quarter. The sales typically measured by a manufacturer are the quantity sold to distributors or retailers (sell-in), not the quantity sold to final customers (sell-through). Measuring performance based on sell-in is often justified on the grounds that the manufacturer's sales force does not control sell-through. For example, Barilla offered incentives to its sales force based on the quantity sold to distributors during a four- to six-week promotion period. To maximize their bonuses, the Barilla sales force urged distributors to buy more pasta toward the end of the evaluation period, even if distributors were not selling as much to retailers. The sales force offered discounts they controlled to spur end-of-period sales. This increased variability in the order pattern, with a jump in orders toward the end of the evaluation period followed by few orders at the beginning of the next evaluation period. Order sizes from distributors to Barilla fluctuated by a factor of up to 70 from one week to the next. A sales force incentive based on sell-in thus results in order variability being larger than customer demand variability because the sales force tends to push product toward the end of the incentive period. #### Information-Processing Obstacles Information-processing obstacles occur when demand information is distorted as it moves between different stages of the supply chain, leading to increased variability in orders within the supply chain. ##### Forecasting Based on Orders and Not Customer Demand When stages within a supply chain make forecasts that are based on orders they receive, any variability in customer demand is magnified as orders move up the supply chain to manufacturers and suppliers. In supply chains where the fundamental means of communication among different stages are the orders that are placed, information is distorted as it moves up the supply chain (see Chen, Drezner, Ryan, and Simchi-Levi [2000] for a good quantitative analysis). Each stage views its primary role within the supply chain as one of filling orders placed by its downstream partner. Thus, each stage views its demand as the stream of orders received and produces a forecast based on this information. In such a scenario, a small change in customer demand becomes magnified as it moves up the supply chain in the form of customer orders. Consider the impact of a random increase in customer demand at a retailer. The retailer may interpret part of this random increase as a growth trend. This interpretation will lead the retailer to order more than the observed increase in demand because the retailer expects growth to continue into the future and thus orders a quantity large enough to cover for anticipated growth during the lead time. The increase in the order placed with the wholesaler is thus larger than the observed increase in demand at the retailer. Part of the increase is a one-time increase. The wholesaler, however, has no way to interpret the order increase correctly. The wholesaler simply observes a jump in the order size and infers a growth trend. The growth trend inferred by the wholesaler will be larger than that inferred by the retailer (recall that the retailer increased the order size to account for future growth during the lead time). The wholesaler will thus place an even larger order with the manufacturer. As we go farther up the supply chain, the order size is magnified. Now assume that periods of random increase are followed by periods of random decrease in demand. Using the same forecasting logic as earlier, the retailer will now anticipate a declining trend and reduce order size. This reduction will also become magnified as we move up the supply chain. ##### Lack of Information Sharing The lack of information sharing between stages of the supply chain magnifies the information distortion. A retailer such as Carrefour may increase the size of a particular order because of a planned promotion. If the manufacturer is not aware of the planned promotion, it may interpret the larger order as a permanent increase in demand and place orders with suppliers accordingly. The manufacturer and suppliers thus have much inventory right after Carrefour finishes its promotion. Given the excess inventory, as future Carrefour orders return to normal, manufacturer orders will be smaller than before. The lack of information sharing between the retailer and manufacturer thus leads to a large fluctuation in manufacturer orders. #### Operational Obstacles Operational obstacles occur when actions taken in the course of placing and filling orders lead to an increase in variability. ##### Ordering in Large Lots When a firm places orders in lot sizes that are much larger than those in which demand arises, variability of orders is magnified up the supply chain. Firms may order in large lots because a significant fixed cost is associated with placing, receiving, or transporting an order (see Chapter 11). Large lots may also occur if the supplier offers quantity discounts based on lot size (see Chapter 11). A combination line and bar graph illustrates demand and order stream with orders every five weeks. The x-axis represents "Week" and the y-axis represents "Demand/Order". ##### Large Replenishment Lead Times Information distortion is magnified if replenishment lead times between stages are long. Consider a situation in which a retailer has misinterpreted a random increase in demand as a growth trend. If the retailer faces a lead time of two weeks, it will incorporate the anticipated growth over two weeks when placing the order. In contrast, if the retailer faces a lead time of two months, it will incorporate into its order the anticipated growth over two months (which will be much larger). The same applies when a random decrease in demand is interpreted as a declining trend. ##### Rationing and Shortage Gaming Rationing schemes that allocate limited production in proportion to the orders placed by retailers lead to a magnification of information distortion. This can occur when a popular product is in short supply. In such a situation, manufacturers come up with a variety of mechanisms to ration the scarce supply of product among various distributors or retailers. One commonly used rationing scheme is to allocate the available supply of product based on orders placed. Under this rationing scheme, if the supply available is 75 percent of the total orders received, each retailer receives 75 percent of its order. This rationing scheme results in a game in which retailers try to increase the size of their orders to increase the amount supplied to them. A retailer needing 75 units orders 100 units in the hope of getting 75. The net impact of this rationing scheme is to artificially inflate orders for the product. In addition, a retailer ordering based on what it expects to sell gets less and as a result loses sales, whereas a retailer that inflates its order is rewarded. If the manufacturer is using orders to forecast future demand, it will interpret the increase in orders as an increase in demand, even though customer demand is unchanged. The manufacturer may respond by building enough capacity to be able to fill all orders received. Once sufficient capacity becomes available, orders return to their normal level because they were inflated in response to the rationing scheme. The manufacturer is now left with a surplus of product and capacity. These boom-and-bust cycles thus tend to alternate. This phenomenon is fairly common in the electronics industry, in which alternating periods of component shortages followed by a component surplus are often observed. #### Pricing Obstacles Pricing obstacles arise when the pricing policies for a product lead to an increase in variability of orders placed. ##### Lot-Size-Based Quantity Discounts Lot-size-based quantity discounts increase the lot size of orders placed within the supply chain (see Chapter 11) because lower prices are offered for larger lots. As discussed earlier, the resulting large lots magnify the bullwhip effect within the supply chain. ##### Price Fluctuations Trade promotions and other short-term discounts offered by a manufacturer result in forward buying, by which a wholesaler or retailer purchases large lots during the discounting period to cover demand during future periods. Forward buying results in large orders during the promotion period followed by very small orders after that (see Chapter 11). A graph illustrates retailer sales and manufacturer shipments of soup. The x-axis represents "Weeks" and the y-axis represents units in "100s". Observe that the shipments during the peak period are higher than the sales during the peak period because of a promotion offered. The peak shipment period is followed by a period of low shipments from the manufacturer, indicating significant forward buying by distributors. #### Behavioral Obstacles Behavioral obstacles are problems in learning within organizations that contribute to information distortion. These problems are often related to the supply chain structure and the communications among different stages. Some of the behavioral obstacles are as follows: 1. Each stage of the supply chain views its actions locally and is unable to see the impact of its actions on other stages. 2. Different stages of the supply chain react to the current local situation rather than trying to identify the root causes. 3. Based on local analysis, different stages of the supply chain blame one another for the fluctuations, with successive stages in the supply chain becoming enemies rather than partners. 4. No stage of the supply chain learns from its actions over time because the most significant consequences of its actions occur elsewhere. The result is a vicious cycle in which actions taken by one stage create the very problems that the stage blames on others. 5. A lack of trust among supply chain partners causes them to be opportunistic at the expense of overall supply chain performance. The lack of trust also results in significant duplication of effort. More important, information available at different stages either is not shared or is ignored because it is not trusted. #### Summary of Learning Objective 2 A key obstacle to coordination in the supply chain is misaligned incentives that result in different stages optimizing local objectives instead of total supply chain profits. Other obstacles include lack of information sharing, operational inefficiencies leading to large replenishment lead times and large lots, sales force incentives that encourage forward buying, rationing schemes that encourage inflation of orders, promotions that encourage forward buying, and a lack of trust that makes any effort toward coordination difficult. *Test Your Understanding* * 10. 2. 1 Improperly structured sales force incentives * \[ \] help create stable demand. * \[ \] have very little effect on the timing of customer orders. * \[ \] tend to create spikes in customer orders. * \[ \] ensure that orders are quickly and accurately entered and communicated to other affected supply chain processes. * 10. 2. 2 The fact that each stage in a supply chain forecasts demand based on the stream of orders received from the downstream stage results in * \[ \] a magnification of fluctuations in demand as we move up the supply chain from the retailer to the manufacturer. * \[ \] a reduction in demand as we move up the supply chain from the retailer to the manufacturer. * \[ \] forecasts based on actual consumer demand patterns. * \[ \] an increase in forecast accuracy. ## 10.3 Discuss managerial levers that help improve coordination in a supply chain. ### Managerial Levers to Improve Coordination Having identified obstacles to coordination, we now focus on actions a manager can take to help overcome the obstacles and improve coordination in the supply chain. The following managerial actions increase total supply chain profits and moderate information distortion: * Aligning goals and incentives * Improving information visibility and accuracy * Improving operations to synchronize supply and demand * Designing pricing strategies to stabilize orders * Building strategic partnerships and trust #### Aligning Goals and Incentives Managers can improve coordination within the supply chain by aligning goals and incentives so every participant in supply chain activities works to maximize total supply chain profits. ##### Aligning Goals Across the Supply Chain Coordination requires every stage of the supply chain to focus on the supply chain surplus or the total size of the pie rather than just its individual share. A key to coordination is coming up with mechanisms that allow the creation of a win-win scenario in which the supply chain surplus grows along with the profits for all supply chain stages. An example of such a mechanism occurs when Walmart pays Hewlett-Packard (HP) for each printer sold and gives HP the power to make replenishment decisions while specifying the service level to be achieved at a store. This setup improves coordination because both parties gain if the supply of printers at a store matches demand. ##### Aligning Incentives Across Functions One key to coordinated decisions within a firm is to ensure that the objective any function uses to evaluate a decision is aligned with the firm's overall objective. All facility, transportation, and inventory decisions should be evaluated based on their effect on profitability or total costs, not functional costs. This helps prevent situations such as a transportation manager making decisions that lower transportation cost but increase overall supply chain costs (see Chapter 14). ##### Pricing for Coordination In many instances, suitable pricing schemes can help coordinate the supply chain. A manufacturer can use lot-size-based quantity discounts to achieve coordination for commodity products if the manufacturer has large fixed costs associated with each lot (see Chapter 11 for a detailed discussion). For products for which a firm has market power, a manufacturer can use two-part tariffs and volume discounts to help achieve coordination (see Chapter 11 for a detailed discussion). Given demand uncertainty, manufacturers can use buyback, revenue-sharing, and quantity flexibility contracts to spur retailers to provide levels of product availability that maximize total supply chain profits (see Chapter 15 for a detailed discussion). Buyback contracts have been used in the publishing industry to increase total supply chain profits. Quantity flexibility contracts have helped Benetton increase supply chain profits. ##### Altering Sales Force Incentives from Sell-in to Sell-through Any change that reduces the incentive for a salesperson to push product to the retailer reduces the bullwhip effect. Manufacturers should link incentives for the sales staff to sell-through by the retailer rather than sell-in to the retailer. This action eliminates any motivation the sales staff may have to encourage forward buying. Elimination of forward buying helps reduce fluctuations in the order stream. If sales force incentives are based on sales over a rolling horizon, the incentive to push product is further reduced. This helps reduce forward buying and the resulting fluctuation in orders. #### Improving INformation Visibility and Accuracy Managers can improve coordination by improving the visibility and accuracy of information available to different stages in the supply chain. ##### Sharing Customer Demand Data Sharing customer demand data across the supply chain can help reduce the bullwhip effect. A primary cause for information distortion is the fact that each stage of the supply chain uses orders to forecast future demand. Given that orders received by different stages vary, forecasts at different stages also vary. In reality, the only demand that the supply chain needs to satisfy is that from the final customer. If retailers share demand data with other supply chain stages, all stages can forecast future demand based on customer demand. Sharing of demand data helps reduce information distortion because all stages now respond to the same change in customer demand. Observe that sharing aggregate demand data is sufficient to dampen information distortion. It is not necessary to share detailed point-of-sale (POS) data. Walmart has routinely shared its POS data with its suppliers. Dell shares demand data as well as current inventory positions of components with many of its suppliers via the Internet, thereby helping avoid unnecessary fluctuations in supply and orders placed. P&G has convinced many retailers to share demand data. P&G, in turn, shares the data with its suppliers, improving coordination in the supply chain. ##### Implementing Collaborative Forecasting and Planning Once customer demand data are shared, different stages of the supply chain must forecast and plan jointly if complete coordination is to be achieved. Without collaborative planning, sharing of demand data does not guarantee coordination. A retailer may have observed large demand in the month of January because it ran a promotion. If no promotion is planned in the upcoming January, the retailer's forecast will differ from the manufacturer's forecast even if both have past POS data. The manufacturer must be aware of the retailer's promotion plans to achieve coordination. The key is to ensure that the entire supply chain is operating with a common forecast. To facilitate this type of coordination in the supply chain environment, the Voluntary Inter industry Commerce Standards (VICS) Association set up a Collaborative Planning, Forecasting, and Replenishment (CPFR) Committee that identified best practices and design guidelines for collaborative planning and forecasting. These practices are detailed later in the chapter. ##### Designing Single-Stage Control of Replenishment Designing a supply chain in which a single stage controls replenishment decisions for the entire supply chain can help diminish information distortion. As we mentioned earlier, a key cause of information distortion is that each stage of the supply chain uses orders from the previous stage as its historical demand. As a result, each stage views its role as one of replenishing orders placed by the next stage. In reality, the key replenishment is at the retailer, because that is where the final customer purchases. When a single stage controls replenishment decisions for the entire chain, the problem of multiple forecasts is eliminated and coordination within the supply chain improves. Several industry practices, such as continuous replenishment programs (CRPs) and vendor-managed inventories (VMIs) detailed later in the chapter, provide a single-point control over replenishment. Walmart typically assigns one of its suppliers as a leader for each major product category to manage store-level replenishment. This gives suppliers visibility into sales and a single decision maker for replenishment decisions. #### Improving Operations to Synchronize Supply and Demand Managers can help dampen information distortion by improving operational performance and rationing schemes to better synchronize supply and demand. ##### Reducing Replenishment Lead Time By reducing the replenishment lead time, managers can decrease the uncertainty of demand during the lead time (see Chapter 12). A reduction in lead time is especially beneficial for seasonal items because it allows for multiple orders to be placed with a significant increase in the accuracy of the forecast (see Chapter 13). If lead times are short enough, replenishment can be scheduled to actual consumption, thus eliminating the need for a forecast. Managers can take a variety of actions at different stages of the supply chain to help reduce replenishment lead times. Ordering electronically, either online or through electronic data interchange (EDI), can significantly cut the lead time associated with order placement and information transfer. If every stage shares its long-term plans with suppliers, potential orders can be scheduled into production well in advance, with the precise quantity being determined closer to actual production. This reduces the scheduling time, which is often the largest component of lead time. At manufacturing plants, increased flexibility and cellular manufacturing can be used to achieve a significant reduction in lead times. A dampening of information distortion further reduces lead times because of stabilized demand and, as a result, improved scheduling. This is particularly true when manufacturing produces a large variety of products. Advance shipping notices (ASNs) can be used to reduce the lead time as well as efforts associated with receiving. Cross-docking can be used to reduce the lead time associated with moving the product between stages in the supply chain. Walmart has used many of these approaches to significantly reduce lead time within its supply chain. ##### Reducing Lot Sizes Managers can reduce information distortion by implementing operational improvements that reduce lot sizes. A reduction of lot sizes decreases the amount of fluctuation that can accumulate between any pair of stages of a supply chain, thus decreasing distortion. To reduce lot sizes, managers must take actions that help reduce the fixed costs associated with ordering, transporting, and receiving each lot (see Chapter 11). Walmart and Seven-Eleven Japan have been very successful at reducing replenishment lot sizes by aggregating deliveries across many products and suppliers. Computer-assisted ordering (CAO) refers to the substitution through technology of the functions of a retail order clerk through the use of computers that integrate information about product sales, market factors affecting demand, inventory levels, product receipts, and desired service levels. CAO and EDI help reduce the fixed costs associated with placing each order. In some cases, managers can simplify ordering by eliminating the use of purchase orders. In the auto industry, some suppliers are paid based on the number of cars produced, eliminating the need for individual purchase orders. This eliminates the order-processing cost associated with each replenishment order. Information systems also facilitate the settlement of financial transactions, eliminating the cost associated with individual purchase orders. The large gap in the prices of truckload (TL) and less-than-truckload (LTL) shipping encourages shipment in TL quantities. In fact, with the efforts to reduce order-processing costs, transportation costs are now the major barrier to smaller lots in most supply chains. Managers can reduce lot sizes without increasing transportation costs by filling a truck using smaller lots from a variety of products (see Chapter 11). P&G, for example, requires all orders from retailers to be a full TL. The TL, however, may be built from any combination of products. A retailer can thus order small lots of each product as long as a sufficiently large variety of products are included on each truck. Seven-Eleven Japan has used this strategy with combined trucks, in which consolidation is by the temperature at which the truck is maintained. All products to be shipped at a particular temperature are on the same truck. This has allowed Seven-Eleven Japan to reduce the number of trucks sent to retail outlets while keeping product variety high. Some firms in the grocery industry use trucks with different compartments, each at a different temperature and carrying a variety of products, to help reduce lot sizes. Managers can also reduce lot sizes by using milk runs that combine shipments for several retailers on a single truck, as discussed in Chapter 14. In many cases, third-party transporters combine shipments to competing retail outlets on a single truck. This reduces the fixed transportation cost per retailer and allows each retailer to order in smaller lots. In Japan, Toyota uses a single truck from a supplier to supply multiple assembly plants, which enables managers to reduce the lot size received by any one plant. Managers can also reduce lot sizes by combining shipments from multiple suppliers on a single truck. In the United States, Toyota uses this approach to reduce the lot size it receives from any one supplier. As smaller lots are ordered and delivered, both the pressure on and the cost of receiving can grow significantly. Thus, managers must implement technologies that simplify the receiving process and reduce the cost associated with receiving. For example, ASNs identify shipment content, count, and time of delivery electronically and help reduce unloading time and increase cross-dock efficiency. ASNs can be used to update inventory records electronically, thus reducing the cost of receiving. Bar coding of pallets and the use of radio frequency identification (RFID) can further simplify receiving. Another simple way to minimize the impact of batching is to break any synchronization of orders. Frequently, customers that order once a week tend to do so on either a Monday or Friday. Customers that order once a month tend to do so either at the beginning or the end of the month. In such situations, it is better to distribute customers ordering once a week evenly across all days of the week, and customers ordering once a month across all days of the month. In fact, regular ordering days may be scheduled in advance for each customer to level out the order stream arriving at the manufacturer. ##### Rationing Based on Past Sales and Sharing Information to Limit Gaming To diminish information distortion, managers can design rationing schemes that discourage retailers from artificially inflating their orders in case of a shortage. One approach, referred to as turn-and-earn, is to allocate the available supply based on past retailer sales rather than current retailer orders. Tying allocation to past sales removes any incentive a retailer may have to inflate orders. In fact, during low-demand periods, the turn-and-earn approach pushes retailers to try to sell more to increase the allocation they receive during periods of shortage. Several firms, including General Motors, have historically used the turn-and-earn mechanism to ration available product in case of a shortage. Others, such as HP, have historically allocated based on retailer orders but are now switching to using past sales. Other firms have tried to share information across the supply chain to minimize shortage situations. Firms such as Sport Obermeyer offer incentives to their large customers to preorder at least a part of their annual order. This information allows Sport Obermeyer to improve the accuracy of its own forecast and allocate production capacity accordingly. Once capacity has been allocated appropriately across different products, it is less likely that shortage situations will arise, thus dampening the inflation of orders. The availability of flexible capacity can also help in this regard, because flexible capacity can easily be shifted from a product whose demand is lower than expected to one whose demand is higher than expected. #### Designing Pricing Strategies To Stabilize Orders Managers can reduce information distortion by devising pricing strategies that encourage retailers to order in smaller lots and reduce forward buying. ##### Moving from Lot-Size-Based to Volume-Based Quantity Discounts When offered lot-size-based quantity discounts, retailers increase their lot size to take full advantage of the discount. Offering volume-based quantity discounts eliminates the incentive to increase the size of a single lot because volume-based discounts consider the total purchases during a specified period (say, a year) rather than purchases in a single lot (see Chapter 11). Volume-based quantity discounts result in smaller lot sizes, thus reducing order variability in the supply chain. Volume-based discounts with a fixed end date at which discounts will be evaluated may lead to large lots close to the end date. Offering the discounts over a rolling time horizon helps dampen this effect. ##### Stabilizing Pricing Managers can dampen the bullwhip effect by eliminating promotions and using everyday low pricing (EDLP). The elimination of promotions removes forward buying by retailers and results in orders that match customer demand. P&G, Campbell Soup, and several other manufacturers have implemented EDLP to dampen the bullwhip effect. Managers can place limits on the quantity that may be purchased during a promotion to decrease forward buying. This limit should be retailer specific and linked to historical sales by the retailer. Another approach is to tie the promotion dollars paid to the retailer to the amount of sell-through rather than the amount purchased by the retailer. As a result, retailers obtain no benefit from forward buying and purchase more only if they can sell more. Promotions based on sell-through significantly reduce information distortion. #### Building Strategic Partnerships and Trust Managers find it easier to use the levers discussed earlier to achieve coordination if trust and strategic partnerships are built within the supply chain. Sharing of accurate information that is trusted by every stage results in a better matching of supply and demand throughout the supply chain. A better relationship also tends to lower the transaction cost between supply chain stages. For example, a supplier can eliminate its forecasting effort if it trusts orders and forecast information received from the retailer. Similarly, the retailer can lessen the receiving effort by decreasing counting and inspections if it trusts the supplier's quality and delivery. In general, stages in a supply chain can eliminate duplicated effort on the basis of improved trust and a better relationship. This lowering of transaction cost, along with accurate shared information, helps improve coordination. Walmart and P&G have tried to build a strategic partnership that will better coordinate their actions and be mutually beneficial. Research by Kumar (1996) showed that the more retailers trusted their suppliers, the less likely they were to develop alternate sources while significantly increasing sales of their products. In general, a high level of trust allows a supply chain to become more responsive at lower cost. Actions such as information sharing, changing of incentives, operational improvements, and stabilization of pricing typically help improve the level of trust. Growing the level of cooperation and trust within a supply chain requires a clear identification of roles and decision rights for all parties, effective contracts, and good conflict resolution mechanisms. For trust to be built in practice, it is important