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Examining the Bullwhip Effect in the Supply Chain

As the name suggests bullwhip effect is an oscillation in the supply pipeline. In supply chain this effect occurs when there is a constant fluctuation in the demand. This effect also known as whiplash effect arises when minute demand fluctuations downstream result in a bigger fluctuation upstream of the supply chain. It describes how inaccurate information, non operational transparency and a disengaged production plan and real time information result in revenue loss, bad customer service, high inventory levels and unrealized profits. Incongruent information across the supply chain leads to overreact to backlog and building of excessive inventory in order to prevent stock outs (Supply Chain Management: Concepts Techniques and Practices-Enhancing Value Through Collaboration, By Ling Li; pp 191) it creates unstable production schedules that cause lead to unnecessary cost in supply chain. Companies have invested in extra capacity to meet the high variable demand. The highly variable demand increases the requirements for safety stock in the supply chain. Additionally, companies may decide to produce to stock in periods of low demands to increase productivity. If this is not managed properly it leads to excessive obsolescence. Highly variable demand also increases lead times. These inflated lead times lead to increased stocks and bullwhip effect. Thus this effect can be quite exasperating for the companies; they invest in extra capacity, extra inventory, work over time one week and stand idle the next, whilst at the retail stores the shelves of popular products are empty, and the shelves with products that aren’t selling are full (Dr. Stephen Disney, Cardiff Business School, Cardiff University) The problem of this effect in supply chain management has been a concernment for many years. Due to its non industry specific nature, it has grabbed the attention of many professionals from diverse industries and business schools. Many firms have observed the bullwhip effect in which the fluctuations in orders increase as they move up the supply chain from retailers to wholesalers to manufacturers to suppliers.(pp 478-479 ; Supply Chain Management - Strategy , Planning and Operation , 2nd Edition; Sunil Chopra & Peter Meindl) Some of the prominent cases so far noticed have been of an Italian pasta manufacturer Barilla SpA (Hammond 1994) that provides vivid illustrations of bullwhip in its supply chain. Barilla for a very long time had been offering special price discounts to the customers for bulk purchases. Such marketing policies created a highly erratic and spiky demand patterns, leading to high supply chain costs that outstripped the full truckload benefits and mismanaged inventory. Another case is of Campbell Soup’s chicken noodle soup experience (Cachon and Fisher 1997). The company is into selling only those products that have a stable demand. The manufacturer yet faced extremely variable demand on the factory level, the reason for which was found out to be forward buying practices of the customers. (FIGURE) As pointed out by Lee, Padmanabhan and Whang(1997 a,b) the expression “Bullwhip Effect” was termed by executives of P&G, the company that manufactures Pamper brand of diapers. These executives observed that while the consumer demand for Pamper’s Diapers was fairly constant over time, the orders for diapers placed by retailers to their wholesalers or distributors were quite variable i.e., exhibited significant fluctuations over time. In addition, even larger variations in order quantities were observed in the orders that P&G received from its wholesalers. This increase in the variability of the orders seen by each stage in a supply chain was called the bullwhip effect. As per Simatupang and Sridharan this situation of misalignment in demand understanding can be termed as Asymmetric Information where different parties have different states of private information about product demand, and the chain operations. The problem of this asymmetry arises because participating firms generally lack the knowledge required about each other’s plans and intentions to adequately harmonize their services and activities. Supply chain members often do not wish to share their private information completely and faithfully with all others due to the profitability of that actual or anticipated information. Thereby the whole supply chain suffers from suboptimal and opportunistic behavior. These decisions occur when the members donot have sufficient visibility to resolve various tradeoffs in decision making because lack of information causes decisions to be made in a narrow scope that cannot ensure the products flows properly to end customers. Moreover, with limited information sharing, members donot have consistent perceptions of market needs and visibility over performance at the other levels of the supply chain. As a consequence, decisions are made based on either the best estimation of the available data or an educated guess. Such decisions can be biased and prevent the individual member from attaining the optimal solution of the supply chain. For example, the manufacturer often uses incoming orders with larger variance and not sales data from the retailer as a signal about the future product demand. Asymmetric information also produces problems of vulnerability of opportunistic behavior. Specifically, adverse selection and moral hazard manifest themselves in the relationship among the supply chain members. The negative selection of adverse selection, for example, is that the member firms cannot optimize supply chain performance because they donot possess the required capability to meet the predetermined customer service level. ( Semchi levi, David, Philip Kaminsky and Edith Simichi Levi, Designing and Managing the Supply Chain, London: Mc Graw Hill, 1999, pp. 103-107)(Lee, Hau L., V Padmanabhan and Seugjin Whang, “The Bullwhip Effect in Supply Chains,” Sloan Management Review, Vol. 38, No. 3 (1997), pp 93-102) To explain this effect a very simple example of two tier supply chain, a retailer and a manufacturer, can be taken into account. The retailer observes customer demand and places orders to the manufacturer. For determination of the order quantity to place with the manufacturer, retailer will use the observed demand data of customer and a demand forecasting technique. In the 2nd stage, the manufacturer plays his role of forecasting by observing the retailers demand to place order to his suppliers. In many supply chains, the manufacturer doesn’t have access to customer’s demand data thereby making him rely on the retailer’s data to forecast. As the bullwhip effect implies (the orders placed by the retailer are significantly more variable than the customer demand observed by the retailer), the manufacturer’s forecasting and inventory control problem will be much more difficult than the retailer’s forecasting and inventory control problem. In addition, the increased variability will force the manufacturer to carry more safety stock or to maintain higher capacity than the retailer in order to meet the same service level as the retailer. Longer the supply chain of a company more the impact of bullwhip effect can be observed. This also leads to increase in amount of the inventory across the chain. The rules of ordering such as timing of order placement, the acceptance of or refusal of back orders, order quantities and lot sizes, and cancellation rights and penalties, can have an enormous impact on the total system inventory and the bullwhip effect. To understand these challenges better a simulation of beer distribution game was created by the professors of MIT, Sloan School of Management. This simulation helps to understand the challenges faced by putting the participant in a real life supply chain situation. In this exercise, students enact a four stage supply chain. The task is to produce and deliver units of beer: the factory produces and the other three stages deliver the beer units until it reaches the customer at the downstream end of the chain. The aim of the players is rather simple: each of the four groups has to fulfill incoming orders of beer by placing orders with the next upstream party. Communication and collaboration are not allowed between supply chain stages, so players invariably create the bullwhip in the pipeline or chain. Sterman (1950a) was the first one to actually test the beer game to experience the bullwhip effect to experiment the causes that result to it. He (Sterman) experienced (1) Inventory Rationing (2) order bathing and (3)Price Fluctuations. He also provides evidence on bullwhip effect that occurs due to customer’s tendency of underweighting the inventory in supply line. The customer does not keep in the account the unreceived inventory at the time of placing a new order. Due to this the orders in backlog are underweighed in the decision to order more. Peter et. al.(1940) identify 4 main causes behind building up of bull whip effect. These causes are:-

Demand Forecasting

Every company in a supply chain usually does a product forecasting for its production scheduling, capacity planning, inventory control and material requirement planning. This forecast is oftenly done on the basis of previous orders placed by the customers. A very common method of demand forecast is exponential smoothing in which future demands are continuously updated as the real demand data becomes available. The order placed reflects the amount needed to replenish the future demands aswell as safety stock. Due to long lead times the safety stock days surge resulting in greater order quantity fluctuations. Moving a level up, to the manufacturers stage if the method of forecasting is same i.e. exponential smoothing then the demand variability is even more, eventually creating a bullwhip.

Order Batching

In supply chain most of the organizations place orders with their upstream suppliers after the accumulating them. The frequency of these orders is weekly, biweekly or at times monthly depending on the product. There are several cost related and demand related reasons for this practice. This can be demystified by an example of a company that places an order once a month because of the nature of the product it deals in. The supplier faces a highly erratic stream of orders. There is a spike in demand at one time during the month, followed by no demands for the rest of the month. This variability is higher than the demands the company itself faces. This practice amplifies variability leading to bullwhip effect. Transportation economics also plays a major role in the frequency of order placements. If the truck load is not enough then the order is not released as the cost is same irrespective of the load. Therefore companies prefer to order only when accumulated requirements are enough for a truck load to fill. This period batching causes surges in demand at a particular time period, followed by the periods of time with no or little orders, and other time periods with huge demands.

Price Fluctuation

Price variation is a crucial factor that impacts the buying behavior of a person. The customer buys in quantities that donot reflect their immediate needs. They buy in bigger quantities and stock up when the prices are low and reduce the purchase when the prices are normal, thereby creating a forward buy pattern in the chain. As a result the customers buying pattern doesn’t reflect the consumption pattern and variation between the 2 grows which leads to the bullwhip effect.

Rationing and Shortage Gaming

When the product demand exceeds its supply the manufacturer is forced to ration them to the customers. Knowing that manufacturer will ration the goods, customers exaggerate their real needs at the time of ordering. Later when the variation between demand and supply plummets down, orders suddenly start to fade and cancellations pour in. This overreaction of the customer is an outcome of anticipation due to lack of information and interaction between the relevant parties. As the customer doesn’t get 100% delivery of the goods required, he exaggerates the demand in order to receive the desired amount of goods.

The above mentioned literature is comprehensible enough that all the factors or elements resulting in bullwhip effect originate from a common ground i.e. information sharing. It is evident enough that the lack of information and interaction between different stages evolve bullwhip in the system thereby plaguing the whole Supply Chain. Therefore it calls for supply chain integration where different stages upstream and downstream need to combine their operational practices by sharing information and work together towards a common objective. In this collaborative manner firms are likely to have less risk factor and more benefits to reap. Multiple researches have been done in order to prove the impact of inter firm collaboration on the performance of supply chain and attenuate the bull whip effect.

Supply Chain Collaboration

Intensive competition in the market place has forced companies to respond more quickly to customer needs through faster product development and shorter delivery time. Increasing customer awareness and preferences have led to companies that are able to deliver products with excellent quality, and on time. However the demand of customers for product variety, especially in the case of short life-cycle products such as food, apparel, toys and computers, makes it difficult for manufacturers and retailers to predict which particular variety of the products the markets will accept. To be effective in matching demand with supply, manufacturers and retailers need to collaborate in the supply chain. Each form of collaboration varies in its focus and objectives. Regardless of the collaborative approach taken, however, Simatupang and Sridharan(2003) suggest that the requirements for effective collaboration are mutual objectives, integrated policies, appropriate performance measures, a decision domain, information sharing and incentive alignment. These requirements demonstrate a need for significant planning and communication to occur between partners, and can require significant resource commitment. Additional studies (Derocher and Kilpatrick, 2000; Mentzer et al., 2000) have affirmed that strong relationships increase the likelihood that firms will exchange critical information as required to collaboratively plan and implement new supply chain strategies. In order for this sharing of critical information to occur, a high degree of trust must exist among the collaborating partners (Frankel et al., 2002). Trust refers to the extent to which supply chain partners perceive each other as credible and benevolent (Ganesan, 1994; Doney and Cannon, 1997). Credibility reflects the extent to which a firm believes their relationship partner has intentions and motives that will benefit the relationship (Ganesan, 1994). One important aspect of information sharing as it relates to collaboration is the delineation of the kind of knowledge, explicit or tactic that results from the exchange of information. Collaborative arrangements involve knowledge transfer that is both explicit (e.g. transactional) and tacit, which resides in “social interactions” (Lang, 2004). More specifically, explicit knowledge is defined by Lang (2004) and referred to here as knowledge that can be “articulated and codified” in order to be “transmitted easily.” Hoover et. al., (2001) identify the benefits of collaboration only when it is done on a larger scale. Therefore they conclude that collaboration cannot be just a solution between close partners, but needs to be implemented with a larger number of business partners. The end goal should be solutions that enable mass collaboration. Darren Peters (six sigma master black belt for Cummins Inc. and also an ex professor of Purdue University’s College of Technology) in his article on supply chain integration mentioned that a true integration of supply chain calls for a high degree of synchronization and alignment. Peters defines synchronization as information sharing; alignment, the most complex factor, reflects the collective behavior and motives of each partner within an ecosystem.

Collaborative Planning Forecasting and Replenishment (CPFR) is the most recent prolific management initiative that provides supply chain collaboration and visibility. It has lately emerged as a new paradigm for the organizations that further want to cut their operational cost and make their supply chain more agile and responsive. Supply chain collaboration involves close work relationship with upstream suppliers and downstream customers. It is a new strategy to make the supply chain more effective and efficient keeping the customer at top priority. The association of Operations Management defines CPFR as follows: Collaboration process whereby supply chain trading partners can jointly plan key supply chain activities from production and delivery of raw materials to production and delivery of final products to end costumers (The Association of Operations Management also known as the American Production and Inventory Control Society, APICS). The complexity of new products, shrinking time to market, and capital intensity have led firms to collaborate to improve access to complementary abilities (Scott 2000) to help meet competitive challenges (Kanter 1994) and to address increasing competition due to market globalization, product diversity and technological breakthroughs ( Simatupang, Wright and Sridharan 2002). A greater interconnectedness and trend of outsourcing have led to a greater need for supply chain professionals to work in alliance with firms possessing complementary skills and capabilities. Lambert et. al. (Lambert, Douglas M., Margaret A. Emmelhainz and John T. Gargner,“Building Successful Partnerships,” Journal of Business Logistics, Vol. 20, No. 1 (1999), pp. 165-181) suggest a particular degree of relationship among chain members as means to share risks and rewards that result in higher business performance than would be achieved by the forms individually. Bowersox (Bowersox, Donald J., “The Strategic Benefits Of Logistics Alliance,” Harvard Business Review, Vol. 68, No. 4 (1990), pp. 36-43) reports that logistics alliances offer opportunities to dramatically improve customer service and at the same time lower distribution and storage operating costs. Narus and Anderson (Narus, James A. and James C. Anderson, “Rethinking Distribution: Adaptive Channels, “Harvard Business Review, Vol. 74, No. 4 (1996), pp. 112-120) define a collaborative supply chain as the cooperation among independent but related firms to share resources and capabilities to meet their customers’ most extraordinary needs. As per a simplistic definition, Collaboration is nothing but a process in which people, groups and organizations work together to achieve desired results. Therefore supply chain collaboration is a business practice wherein trading partners use IT and a standard set of business procedures to combine their intelligence in planning and fulfillment of customer demand (VICS, 2004). The CPFR model created by Voluntary Interindustry Commerce Standards Association (VICS) is a promising mechanism for the forecast accuracy by having customers’ and suppliers’ participation in the forecasting process. A buyer and a seller work together as collaborators to satisfy the needs of the end customer thereby creating a win win situation. VICS 2004 proposes a model that is applicable to almost all the industries. In case of any discrepancy the vendor and the buyer can come together and rectify it by deciding upon the replenishment quantity. This kind of association or professional acquaintance offers a great potential to drastically improve supply chain performance through collaborative demand planning, synchronized production scheduling, logistics planning and new product development. The VICS Association, CPFR provides templates for supply chain collaboration in 4 stages (VICS 2004): Planning Stage: At this phase the relationship between buyers and vendors is planned and updated. It leads to front end agreement and joint business plan. Variances, whether plan to plan or plan to actual, are also addressed.

Forecasting Stage: At this stage, demand (order)/supply (sales) forecast is created and exceptions or discrepancies are identified and resolved. Forecast accuracy visibly improves by having customer and supplier involvement in the planning process and thereby making the goals compatible for both the parties.

Execution: At this stage, the order is generated, shipments are prepared and delivered, products are received and stocked on retail shelves, sales transactions are recorded and payments are made.

Analysis: At this stage, monitor planning and execution activities for exceptional situations. If a discrepancy occurs, the two trading partners can get together and share insights and adjust plans to resolve such discrepancies.

Collaboration and co-operation between producers and their customers is a key component of a modern successful supply chain. As per Tim Bennett (Former President of National Farmers Union, Texas, USA) it is imperative that the organizations develop these relationships not only to drive improvements in efficiency but to respond more effectively to customer demands. As per Aviv (2005); Schwarz (2004) this initiative not only reduces the inventory but also increases sales for both sides i.e. retailers and suppliers. This also includes sharing of data and coming up with new and innovative ideas to attain a common objective. Supply chain collaboration is oftenly defined as 2 or more chain members working together to create a competitive through sharing information, making joint decisions, and sharing benefits which result from greater profitability of satisfying end customer needs than acting alone.(Simatupang & Sridharan, 2005; Whipple and Russell, 2007). Narus and Anderson (1996) define Supply Chain Collaboration as sharing knowledge and skills by independent but related firms to meet extraordinary demands of precious customers. The major reasons for companies to collaborate their supply chain with suppliers and/or customers as the case may be, is to reap a better competitive advantage and improve the overall operational efficiency with improved profit margins. As per Wernerfelt 1984 Resource based view shows how firms develop and utilize their resources. Moreover the ownership of scarce and firm specific resources is the reasoned behind its success. Collaboration in the past has very often been interchangeably used with cooperation. Every professional and expert defines it differently. There are several driving forces that for the exchange of reliable information in the supply chain industry. One of these driving forces is competition. Merchandise retailers such as Wal-Mart and K-Mart have expanded product offerings into food items in order to enhance the value of customer service offerings through one-stop shopping. A second driver is the innovative nature of products, or the length of the life cycle and the duration of retail trends in these industries. In the apparel industry, for example, the life cycle of some garments is 6 months or less. Yet, manufacturers typically require up-front commitments from retailers that may exceed 6 months making long term fashion forecasts risky. General merchandise retailers know this year’s newest toy has a short product life cycle. It is imperative to get the latest trend in the consumer products to market quickly; otherwise, either tremendous lost revenues or markdown prices will be experienced. Long manufacturing lead times necessitate supply chain planning visibility. A third driving force is the longer, more complex supply chain given moves to offshore production. International sourcing for apparel and general merchandise has lengthened the supply chain and cycle time, and necessitating supply chain planning visibility. A fourth driving force behind CPFR is the nature of the supply chain cost structure. Global markets and more competitors are likely to move the supply chain system towards universal participation by all retailers in CPFR in an effort to cut costs (Raghunathan, 1999). All of these driving forces support the need to respond quickly to volatile demand and other market signals. These forces stimulate the development of supply chain visibility tools such as CPFR (Fisher 1997).

Identified benefits of collaboration include: revenue enhancements, cost reductions, operational flexibility to cope with demand uncertainties (Fisher, 1197; Lee, Padmanabhan, and Whang, 1997; Simatupang et al., 2005); increased sales, improved forecasts, more accurate and timely information, reduced inventory, improved customer service, (Barratt and Oliveira, 2001; Whipple et al., 2007); division of labor, exchanges of knowledge about products and processes (Kotabe, Martin, & Domoto, 2003) and cost and/or problem avoidance (Whipple, 2007).

Companies like Wal mart, Procter & Gamble and Dell computers have evidently shown that an anticipatory business model is better able to increase sales revenues and deliver profit margins meeting the shareholder expectations. This model is successful only when there is a cooperation and collaboration amongst all the members, internal aswell as external of the entire supply chain. (Supply Chain Collaboration-How to implement CPFR ;Ronald K Ireland with Colleen Crum, pg2). As per Ronald K Ireland reducing the Bull Whip effect in supply chain is not a program or a monthly initiative. It is a continuous practice to maintain a balance and to keep it to minimal due the inevitable nature. About the collaboration Ronal shares one of his experiences at Wal mart where due to some wrong program installation in the systems, purchase orders used to get blocked that lead the point of sale data to zero. The actual break down of collaborative planning happened when no queries were raised regarding the drastic change in point of sale rate. It was only when a supplier requested a Wal mart analyst to verify the forecast. This incident moralizes that it takes a team approach to eliminate the bull whip in the supply chain. Trust plays a vital role in the whole collaborative setup. Without trust and reliability on partners, supply chain collaboration is of no use. It is very important to have trust and faith in the partners to create supply chain into a value chain. Andraski (1994) reports that CPFR engages the manufacturer and retailer into exchanging the marketplace information in order to come up with a customer specific plan that can substantially reduce inventory. There are various cases or examples of CPFR implementation that prove its success. Various types of partnerships (collaborations) have been tried. Wal-Mart and Warner Lambert embarked on the first CPFR pilot, involving Listerine products. In their pilot scheme, Wal Mart and Warner Lambert used special CPFR software to exchange forecasts. Supportive data, such as past sales trends, promotion plans and even the weather, were frequently transferred in an iterative fashion to allow them to converge on a single forecast should their original forecasts differ. The pilot scheme was very successful resulting in a tremendous increase in sales, better fill rates and in a reduction of inventory investment (Cooke, 1998; Hill, 1999). Other examples of CPFR pilots include Sara Lee’s Hanes and Wal – Mart, involving 50 SKUs of underwear supplied to almost 2500 Wal Mart stores (Hill, 1999; Parks, 1999, 2001; Songini, 2001). In 1996, Hieneken USA employed CPFR to cut its order cycle time and is currently providing Collaborative planning and replenishment software to its top 100 distributors (Aviv, 2001). Procter and Gamble has several active CPFR pilots underway (Schachtman, 2000). Levi Strauss and Co. incorporates certain aspects of the CPFR business process into its retail replenishment service (e.g. by creating joint business plans and identifying exceptions) (Aviv, 2001). Additionally, in the ECR report entitled “European CPFR Insights” several CPFR pilots are described including: Unilever – Sainsbury’s GNX, Condis-Henkel-Cartisa, Kraft-Sainsbury’s GNX, Carton Scholler, Vandemoortele-Delhaize (ECR Europe, 2002). (Andraski and Haedicke, 2003) cited a major gap of misunderstanding, misuse of greater bargaining power and undue expectations in a collaborative relationship. Such gaps can be avoided if mutual agreements on extensive and timely information sharing were put in place to more precisely predict potential problems of matching supply and demand. At the same time these arrangements call for an effective governance structure to address potential economic incentive problems between contracting parties, thereby leading to more cooperation across firm level boundaries.

Information Sharing

Information is an essential part of managing operations and supply chain management. The above given review is comprehensible enough for us to realize the magnitude of information in supply chain and the repercussions if not communicated properly. It is the most crucial element in the whole CPFR frame of supply chain. Sridharan and Simatupang (2009) define information sharing as a process that facilitates the chain members to capture and disseminate timely, relevant and accurate information such that the recipient is able to plan, execute and control the supply chain operations. Likewise it should flow along with material and money across the supply chain in order to smoothly operationalize the key functions of supply chain. In the era of globalization where organizations have gone and are going multinational, the need of information sharing becomes vital for the smooth running of business. Some supply chains have the ability to share point of sale data to the end consumer with other members of the supply chain. Sophisticated supermarkets like Wal Mart use barcode scanning at the checkouts. These scanned barcodes populates electronic files that help in determining the patterns of particular products. This data is then offered to suppliers for the purpose of capacity planning activities. Utilization of this data only for the purpose of capacity planning doesn’t help to resolve the problem of bullwhip as the suppliers still donot get clarity on the fluctuating orders of retailers. The real benefit availed from this data comes from its usage in replenishment or ordering decisions. The suppliers need to be proficient enough to use this information for forecasting replenishment. Effective sharing of information provides a shared basis for concerted actions by different functions across interdependent firms (Whipple et al. 2002). Increasing the level of integration and information sharing has become a necessary tool to bring a competitive advantage to the modern supply chain. Multiple researches have been performed in this context in order to develop a strong foundation in favor of information sharing and its crucial role in the all new Integrated Supply Chain Models. According to A.T. Kearney report(Field 2005), the average manufacturer has enjoyed benefits equivalent to million in savings for every $1billion of sales by synchronizing their demand databases with their retailers. It not only improves the inter firm and intra firm relationship but also helps to build confidence in each other at different levels of supply chain. Knowledge of different levels always adds benefit to the supply chain as a whole as decisions at different department levels are always made keeping the existing facts into consideration. All the members have information about themselves but lack of information about the other members is the reason for uncertainties in the supply chain. The new paradigm of supply chain collaboration asserts information sharing where all the members internal and external need to share information with each other in order to bring down uncertainties and improve the efficiency. Bullwhip effect, first described by Lee et al., 1997 and a major concern for companies, can be controlled by sharing information within and outside the relevant departments (Disney and Towill, 2001a, b). This effect has grabbed the attention of professionals for quite some time due to several reasons which are (a) order variability that provokes the sellers at different levels to stack up inventory in order to meet boom and bust demand pattern (b) lack of synchronization at different stages leading to stock out situations and (c) blocked and increasing operational costs along with inventories. The reduction of the negative impact of bullwhip effect in supply chain however, not only depends on information integration but also to the degree at which it is shared. Increasing vertical information sharing, using EDI technology can enhance logistical performance of suppliers and greatly improve the performance of the supply chain system (Srinivasan et. al., 1994). Chen, et al., (2000) quantified the impact of bullwhip effect of supply chain and showed that this effect can be reduced by centralizing information. One of the most frequent suggestions for reducing bullwhip is to centralize information in the supply chain, i.e. to provide each stage of the supply chain with complete information on the actual customer demand. Centralizing information helps in analyzing the actual customer demand data in order to create a better forecast rather than relying on the orders received on the previous stage which can vary significantly more than the actual customer demand. (pp24; Managing the Supply chain – The definitive guide for the business professional; David Simchi – Levi, Philip Keminsky and Edith Simchi Levi). Many firms invest huge amount of capital in technology for enabling the collection and transfer of large quantities of diverse information (Ofek and Sarvary, 2001). But lack of organizational culture supporting an open attitude towards information sharing makes technology investment a waste leading to huge disappointment(Jap and Mohr, 2002). Having limited information to make important decisions is not the only concern. The bigger concern for the managers is unwillingness of supply chain members to share information with other members of the same firm or with supply chain partners. Maha Mazumdar (Vice President, manufacturing and distribution industries and supply chain marketing at Oracle) writes in her article that before collaborating with supply chain partners, organization leaders must learn to break down the internal cultural barriers among departments that prevent people from thinking beyond their own group or department. She mentions that it is unaffordable for the organization to have functional silos as they are the biggest barriers to success for the company as a whole and can even lead to business failure if left unresolved. One of the biggest examples that can be taken into account to explain this better is the famous case of Volvo, a Swedish car company that in1990s started a whole new line of green cars. Due to the huge inventory caused by poor sales of these vehicles, marketing department of the company, without providing any information to the manufacturer, started huge promotions in association with their dealers that helped them to get these cars out of the lots. As the sales started to spur, manufacturing planners assumed that there was a great demand and doubled the production which brought them to the same situation once again. Therefore it calls for the leaders to break down these silos in order to develop a one number plan enabling everyone to work toward a consistent set of business objectives. Fawcett and Magnum (2001) in their research report that, most companies have invested substantial sums of money to build formidable information systems capable of collecting, analyzing, and disseminating accurate, real time information regarding forecasts, inventory, quality, and just about anything else a manager could ask for. Unfortunately, most of these companies have found that time and money spent on hardware and software donot necessarily resolve the need for better information sharing. Many managers are simply unwilling to share valuable information. Since some managers view information as power, they hoard needed information. This is particularly true in settings where trust doesn’t abound. Several of the interviewed managers emphasized the point that a lack of willingness to share information is actually a greater barrier to supply chain integration than is poor connectivity. These managers note that it is generally easier to manage technical barriers than it is to manage behavioural issues (pp. 67-68). Therefore integrated mechanism for information requires cooperation and most importantly trust on each other. Willingness to share not only relies on the confidence on each other and belief in the common objective but also the factual clarity, advantages and disadvantages of sharing information. It is very crucial for the supply chain members to understand the true meaning of this setup. Sharing of information is oftenly confused as revealing confidential information leading to lower efficiency and profit margins of one’s own stage of the supply chain. With these kinds of misconceptions, clarity of four Ws needs to be addressed. The four Ws i.e. why, what, when and who are the questions that if addressed in a right manner, can turn into convincers to start the information sharing relationship.

Without this clarity, a partner tends to share limited information, due to which the chain members donot have consistent perceptions of market needs and visibility over performance at the other levels of the supply chain, the outcome of which is insufficient and unreliable information resulting in unachieved mutual benefits. It should be apparent that having accurate information about inventory levels, orders, production and deliver status throughout the supply chain should not make the managers of a supply chain less effective than if this information were not available. However this information provides a tremendous opportunity to improve the way the supply chain is designed and managed. This information: 1) helps reduce variability in the supply chain. 2) Helps suppliers make better forecasts, accounting for promotions and market changes. 3) Enables the coordination of manufacturing and distribution systems and strategies. 4) Enables retailers to better serve their customers by offering tools for locating desired items. 5) Enables retailers to react and adapt to supply problems more rapidly. Enables lead times reductions. ( pp 20; Managing the Supply chain – The definitive guide for the business professional; David Simchi – Levi, Philip Keminsky and Edith Simchi Levi)

The whole system’s performance can be improved if each member has access to relevant information of other partners. This cooperation mechanism for increasing information sharing among supply chain members can be called a supply chain partnership.

Information acts as an important driver that companies have used to become both more efficient and more responsive. Like all the other drivers, however, even with information, companies reach a point when they must make the trade-off between efficiency and responsiveness. Another key decision involves what information is most valuable in reducing cost and improving responsiveness within a supply chain. This decision will vary depending on the supply chain structure and the market segments served. It should be noted that despite of the crucial nature of information sharing, its impact on the performance of a supply chain depends on what information is shared, how and with whom it is shared (Byrne and Heavey, 2006; Holmberg, 2000; Li and Lin, 2006). As information is the foundation of integrated supply chain (Lee 2000), the level of integrated decisions are strongly correlated with decisions on what information should be shared and how it should be shared. Lee So and Tang (2000) in their study of information sharing in supply chain comment that the value of information sharing is high when the demand correlation and variance within each time period is high. Cooper et al. (1997) argues that the design of supply chain’s configuration is not the only determinant factor for choosing companies to get integrated with, but the nature of association to those of their partners and kind of information given access to also play a prominent role. Seidmann and Sundararajan (1998) defined four different levels of inter firm information sharing based on the impact it has on the parties that contract to share the information to support the exchange in the vertical relationship: ordering information, operational information, strategic information, strategic and competitive information. Sharing only order information between the supply chain parties tends to increase demand variability, which increases the need for safety stock (Li et al., 2001). If all parties have the Point Of Sales data available, some components of the bullwhip effect can be reduced, especially concerning the upstream members (Croson and Donahue, 2003). Similarly, sharing customer inventory information enables the supplier to synchronize its own production and delivery schedules in order to ensure a good service level (Li et al., 2001; Gavirnemi et al., 1999). This mode of operation is widely called Vendor managed inventory (VMI). Under the VMI supply chain setup, suppliers have a clear visibility of the downstream supply chain; they have a transparency of customer demand and their inventory level, the basis on which suppliers decide their replenishment activities. Continuous information from partners enables the supplier to react to demand changes but, as the responsibility for replenishments is shifted from the retailer to the supplier, the supplier can plan its operations better (Kaipia et al., 2002). However, if the retailer outsources inventory replenishment to the manufacturer, both the retailer and the manufacturer benefit through lower inventory costs. On both information sharing levels, the manufacturer obtains more benefits than the retailer (Yu et al., 2001). Clark and Scarf (1960) showed that the inventory of a multi stage system can be managed optimally as long as the central planner has knowledge of the inventory levels of all stages of the system.

Cost reduction and decrease in inventory levels can be better achieved by sharing demand information. Order information is most oftenly not in align with the actual demand and only gives a part of the picture but demand information gives a better knowledge of the market requirements. Therefore if order information and demand information are combined together, a bigger and better framework can be established for the purpose of analyzing and forecasting supply chain activities. There is a general consensus of making demand information available to every stage if the supply chain in order to reduce the magnitude of bullwhip effect. Lee et al. (1997 a p. 98) suggest that disclosing customer demand data at upstream stage from the downstream site can be remedial and help to suppress the effects of bullwhip effect. Full demand information sharing considers a demand supply network in which all stages are informed about downstream demand. This practice not only helps to reduce the bull whip effect but also the safety stocks. Time factor in terms of frequency plays an important role as to how often the demand related information is shared. Some organizations share the information on a daily basis and some on a weekly or monthly aggregate basis. Evidences prove that information shared on a daily basis is more successful in reducing the inventory level and associated costs (Bourland et al., 1996). When consumer demand variability is low, full demand information sharing makes possible a 75 percent reduction in inventory levels compared to only order information sharing (Li et al., 2001). As per the calculations and observations in the researches done previously sharing demand related information can make it possible to reduce costs by up to 35 percent (Gavirneni et. al., 1999) and decrease inventory levels by 53 percent.( Li et al., 2001), or, as Lee et. al., (2000) have calculated by up to 40 percent. The value of information sharing can be defined as the benefits derived from sharing information minus the associated costs. Typically, in research studies, it is assumed that information sharing is beneficial and investments are not considered. Furthermore, research concentrates on estimating the value of information between two supply chain partners. The approach is theoretical and simulation is used as a research method. A situation where the retailer is not willing to share information has also been studied (Fransoo et al., 2001).

Upstream operations in the light of information sharing are typically not considered. The research focus is mostly on the relationship between a manufacturer and retailer, and the position of component or raw material suppliers is ignored.

One aspect not often considered in research studies of information sharing between supply chain partners is the coverage of demand information. This can be divided into 2 viewpoints: first, how many stages in the network are sharing the information, and second, how many parties are sharing the demand information within one stage in the network. One example of the research finding is that the reduction of the manufacturer’s forecasts fluctuate less when more retailers share their demand information (Raghunathan, 2003). Some writers point out the importance of full demand information (Simichi-Levi and Simichi-Levi, 2002). However, in complicated demand-supply networks it may be difficult or resource-consuming to share all information with all parties. Additionally, increased visibility through, for example, new information sources in meaningful only when the information is used to improve operational efficiency (Hahtola, 2001). There is a need to define what the expedient coverage of demand information is.

Once the process of information sharing gets started, the organization is only few steps away from a dramatic reduction in total system inventory whilst simultaneously improving responsiveness to demand. The ability to match supply more closely with demand we call agility and the key to agility is speed. If information flows through supply chain cooperatively and continuously then the demand and supply requirements can be forecasted and met more precisely thereby leaving minimal scope for bullwhip to infect the supply chain.( Martin Christopher and Hau l. Lee, 2001)

Supply chain efficiency can be increased by coordination, truth inducing mechanisms, contractual engineering and information sharing (see Chen, 2002 and 1998; 2001a; 2001b; Chen and Yu, 2001a, Chen and Yu, 2001b; Anupindi, 1998; Porteus and Whang, 1991; Lee and Whang, 1999; Cachon et al, 1999; Zhao et al, 2002)

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