Business Process ManagementJournal, Vol. 6 No. 5, 2000,pp. 392-407. # MCB UniversityPress, 1463-7154
Supply chain forecastingCollaborative forecasting supports
supply chain managementMarilyn M. Helms
Dalton State College, Dalton, Georgia, USA
Lawrence P. EttkinUniversity of Tennessee at Chattanooga, Chattanooga, Tennessee, USA, and
Sharon ChapmanBrach and Brock Confections, Chattanooga, Tennessee, USA
Keywords Supply chain, Forecasting, Supply-chain management, Demand
Abstract Supply chain management is built on the principles of partnerships and thedevelopment and use of the connections that exist between the links of the chain to provideinformation that will increase the efficiency of all members in the chain. Success stories abounddescribing lower costs, shorter lead times and increased customer service. Collaborativeforecasting applies supply chain management concepts to the forecasting function and usesavailable information and technology to force a shift from independent, forecasted demand todependent, known demand. Eventually, the future of forecasting may evolve to the point whereforecasting is not even necessary. Demand information will be supplied completely by supply chainpartners and the need to predict demand will be eliminated.
IntroductionSupply chain management has become the mantra of many companies seekinga way to meet the competitive challenges of today's business environment.Supply chain management is a broader perspective of the businessenvironment, as compared with more traditional approaches. Instead ofmanaging a business as a group of virtually separate functions, supply chainmanagement views these functions as closely connected links of a chain. Thechain extends beyond the boundaries of the organization to include suppliersand customers. Supply chain management involves the entire flow of a productfrom the purchase of raw materials from the supplier, all the way to thepurchase made by the final consumer.
The concept of supply chain management is based on several key tenets.The key principle is that all strategy, decisions and measurements are madeconsidering their effect on the entire supply chain, not just separate functionsor organizations. This broader approach is based on partnerships and thesharing of information between the links in the chain.
The goal of supply chain management is to meet the needs of the finalconsumer by supplying the right product at the right place, time and price. Thesupply chain management approach allows companies to meet this goal whilealso achieving competitive advantages. There are countless success stories inwhich companies have used supply chain management to `` replace inventory
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with information'', squeeze out costs, and improve efficiency and customerservice. The results of these improvements have also translated into healthierbottom lines. Success stories, coupled with the push of an ever more demandingcompetitive environment, and recent technological advances, are the drivingforce behind the rapidly growing number of companies implementing thesupply chain management concept.
As companies implement supply chain management, they must look at waysto bring the concept to each of the functional areas in their organization. Thisrequires making the cultural and process changes that support the concept ofsupply chain management which will ultimately lead them to the savings,efficiency and customer service levels that they seek. The forecasting functionis one area that must receive priority in these functional reviews and processchanges. The demand from the final customer is the force that drives theactivities in the supply chain. Each of the links in the supply chain operates inreaction to actual or anticipated demand from the consumer at the end of thechain. The level of accuracy and efficiency with which this demand iscommunicated up and down the chain is directly connected to inventory andcustomer service levels. Forecasting and demand planning are therefore a keyfactor in the successful implementation of a supply chain managementstrategy.
The complexity and uncertainty that exist in the supply chain make theconcept of accurate and effective forecasting an elusive target. Manycompanies are, however, making significant improvements by using anapproach that supports and facilitates the concept of supply chainmanagement. Collaborative forecasting is a way in which the entire supplychain is a participant in decisions about the demand that will drive theiractivity. Collaborative forecasting reaches internally and externally to gatherinformation that allows for the best and most timely predictions of demand.Recent technological advances are used to collect and bring the informationtogether as well as to transmit forecasts back to chain members. The number ofsuccess stories are increasing and include companies like Eastman Chemical,Reynolds Aluminium, Wal Mart, Ocean Spray and Heineken. They have beenable to dramatically reduce inventories and lead times while increasingcustomer service and forecasting accuracy. Experts now envision a day whenforecasting, as we now know it, will not be necessary. As the process improves,experts predict the need for forecasts will lessen and be replaced by themanagement of actual demand information.
Problems with the traditional forecasting processForecasting is often the most maligned department in any company regardlessof whether it is the responsibility of finance, marketing, sales or logistics. Mostcompanies know that their forecasts are inexact, but don't know what to doabout it and therefore ignore the issue, hoping the problem with solve itself.The idea that forecasts are always inaccurate and that there is nothing than canbe done about it forces companies to find ways to compensate for the
uncertainty. The most often used method of dealing with uncertainty is bybuilding inventory. Departments buffer against their lack of confidence in theforecast by building safety stocks. As each link in the chain creates its ownbuffers, inventories skyrocket. Jack Stack, president of SpringfieldRemanufacturing Corp. in Springfield, Missouri, describes the situation likethis: `` Hate to say it, but there's a good chance that right now you're creating amajority of the problems you'll be dealing with next year. How? By puttingtogether an annual sales forecast based on gut feelings and wishful thinking''(Stack, 1997, p. 7). The results of a recent study of 1,380 manufacturing andretail companies, done by KPMG Peat Marwick, said `` many companiesworldwide don't know the exact amount of goods they need to manufacture,transport and store, yet they are very sluggish to adopt the very techniques andtechnologies that would solve the problem'' (Chain Store Age, 1998, p. 97).
Overcoming the challenges involved in creating a credible forecast is anincredibly daunting task for most forecasters. The marketplace is constantlychanging. There is a constant flow of new products, promotions and changingchannels of distribution. Unfortunately, forecasters often attempt to predictsuch a volatile future using only historical data. The problem with using onlyhistorical data to predict the future is that it requires the assumption that thepatterns that have occurred in the past will occur again in the future. In today'sever changing market this may or may not be a valid assumption. Forecasterstoday need more information. Ed Wodarski, director of Global Consulting withLPA Software in Rochester, New York says, `` using a forecast based on historymakes as much sense as driving a car by looking in the rear-view mirror. Theyneed to be looking ahead, not back'' (Fulcher, 1998, p. 89).
Companies also often have to deal with the problem of the existence of manyforecasts in their organization. This problem seems to be related to the lack ofconfidence in the sales forecast and the differing needs of each forecast's users.Marketing may use forecasts with an emphasis on trends occurring in themarketplace, while finance needs a forecast with an emphasis on budgeting.Sales may adapt a forecast based on sales quotas and production may createwhat they consider to be a better forecast based on their experience andproduction capacity and efficiency. Purchasing may also adjust a forecast toreflect their viewpoints and experience and create what they consider to be abetter forecast. While in theory all these forecasts would roll up the samenumber, this is rarely the case.
The problem that is created with the existence of so many forecasts is that,as a result, no one operates from exactly the same plan. Drs Mentzer and Moonof the University of Tennessee describe the problem as `` islands of analysis''.`` Without a clear communication of how the process and systems interact,islands of analysis will develop within the forecasting process. Islands ofanalysis are systems phenomena where one individual or group develops asales forecast based upon their own information and needs, and does not sharethat information or forecast with others in the company. The resultant salesforecasts may be significantly different than forecasts developed elsewhere in
the company (other islands) and these differences lead to conflicting plans''(Mentzer et al., 1997, p. 12). In describing the results of detailed study of thestate of forecasting in the USA, Drs Mentzer and Kahn describe the fact thatusing multiple forecasts has turned into a backward planning process. `` Inmany responding companies (34 percent) the planning process is backward,i.e. the business plan is used to develop the forecast instead of the other wayaround. Apparently, management in these companies is more concerned withthe business plan than the sales forecast, even though the latter should drivethe former'' (Mentzer and Kahn, 1997, p. 12). Whether the reason is lack ofconfidence in the sales forecast or the need to develop a forecast that meetstheir particular needs, the use of many forecasts creates a moving target thatis difficult, if not impossible, to hit. Operating from many plans is a handicapthat creates misinformation, excess inventory, lack of accountability andresults in the creation of a cycle of poor forecast credibility that is difficult tobreak.
The benefits of collaborative forecastingConsidering that `` in 1996 about $700 billion of the $2.3 trillion retail supplychain was in safety stock'' or, put another way, `` almost 30 percent was tied updue to waste and inefficiency'', solutions are needed to overcome the issuessurrounding the forecasting process (Lewis, 1998, p. 17). Collaborativeforecasting is one of the ways that many companies have found to overcomesome of the inherent problems with traditional forecasting and at the sametime support the supply chain management initiative of their companies.Collaborative forecasting is a method in which the knowledge andinformation that exists internally and externally is brought together into asingle, more accurate, forecast that has the support of the entire supply chain.While specifics may differ between companies, it is an approach that seeksand uses the available information and expertise of the entire supply chain.The process of collaborative forecasting coordinates the gathering ofexpertise and information from diverse sources and the consensus buildingthat turns these inputs into a more accurate, effective forecast used by theentire supply chain.
Collaborative forecasting is an approach that breaks down the functionalsilos or `` islands of analysis'' and opens the supply chain's information flow tothe benefit of the entire chain. Inventory is replaced with information andpartnerships are formed internally and externally that support supply chainmanagement objectives. Issues of complexity are overcome by informationsharing and cooperative solution seeking. In a collaborative forecastingprocess, all supply chain members contribute their particular expertise to thedevelopment of the best possible forecast, as opposed to the former many, lessthan optimal, forecasts. Sales brings information from customers fresh from thesales field, as well as information about current promotions. Marketingcontributes the latest market trends, new products and product changes.Production and manufacturing bring their expertise about manufacturing
capacity and efficiency. Purchasing brings information from the suppliers.Forecasting brings the information from historical patterns and statisticalanalysis and ties all the pieces together.
One benefit of a collaborative forecasting approach is that it reduces acompany's reliance on historical records. The baseline of historical informationis supplemented by current knowledge about specific trends, events and otheritems than often undo the key assumption that history will repeat itself.Collaborative forecasting decreases the necessity to rely exclusively on history.Historical information remains a vital piece of the forecast as the baseline andis especially important in the longer term view where specific information maystill not be available. Eric Stellwagen, vice president of Business ForecastSystems, says, `` historical information is still a valuable asset. While long-termforecasting does have a basis in historical records, it also involves variableslike changing market share, budgets, and promotional schedules. That's why aconsensus forecast is valuable; it relies on judgement founded on specificknowledge'' (Fulcher, 1998, p. 92).
Using a collaborative or consensus forecast also helps to ensure that allfunctions are operating together as one supply chain using a single plan. Manycompanies are realizing the importance of having one forecast and are usingthe collaborative approach to achieve that objective. Terry Hisey, a principal inthe manufacturing segment of Unisys says, `` many companies are starting torealize the importance of combining the disparate parts of their forecastingculture. Now manufacturers are moving toward developing a single forecast inan effort to improve inventory management, increase accuracy, speed ordercycles and meet service level commitments'' (Dilger, 1998, p. 44).
Companies that are using some type of collaborative forecasting approachare impressed with the results. The study conducted by Drs Mentzer and Kahnfound that over half the companies that they surveyed (478), were trying sometype of negotiated or consensus based forecasting approach and that thesecompanies were more satisfied with their results (61 to 69.8 percent describedthemselves as satisfied with their forecasting approach) (Mentzer and Kahn,1997, p. 11). Wal Mart, Sears, Sara Lee and Warner Lambert are a few examplesof companies satisfied with their forecasting results. Through internal andexternal efforts they have been able to reduce time, cost and slack...