Abstract
Most, if not all, commercial enterprises require some form of demand forecasting for financial and operations planning. For financial planning, a high level, aggregate forecast (e.g., in dollar value) of major product groups or geographies is sufficient. For operations planning, a more detailed forecast, such as forecast by product or even by product-location, is necessary. A manufacturing enterprise employing a make-to-stock strategy needs a demand forecast to plan what products and how much of each to build. A make-to-order manufacturer uses a demand forecast to plan the purchase of parts and materials and its production capacity. A retailer needs a demand forecast to determine how much of each product to stock at the different retail locations. Other service enterprises utilize a demand forecast to plan and locate their capacity (for both labor and equipment). We focus on the latter situation in this chapter, namely detailed, product level forecasts that drive the planning of a supply chain.
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Batty M (1969) Monitoring an exponential smoothing forecasting system. Oper Res Q 20(3): 319–325
Bunn DW, Vassilopoulos AI (1993) Using group seasonal indices in multi-item short-term forecasting. Int J Forecast 9(4):517–526
Chambers JC, Mullick SK, Smith DD (1971) How to choose the right forecasting technique. Harvard Bus Rev, July-August 1971, 45–74
Chatfield C (1978) The Holt-Winters forecasting procedure. Appl Stat 27(3):264–279
Chatfield C, Yar M (1988) Holt-Winters forecasting: some practical issues. The Statistician 37:129–140
Fildes R, Beard C (1992) Forecasting systems for production and inventory control. Int J Oper Produc Manag 12:4–27
Fildes R, Goodwin P, Lawrence M (2006) Design features of forecasting support systems and their effectiveness. Decis Support Syst 42(1):351–361
Fliedner G (2001) Hierarchical forecasting: issues and use guidelines. Ind Manag Data Syst 101(1):5–12
Gardner ES Jr (1983) Automatic monitoring of forecast errors. J Forecast 2(1):1–21
Gardner ES Jr (1985) Exponential smoothing: the state of the art. J Forecast 4(1):1–28
Golder ER, Settle JG (1976) Monitoring schemes in short-term forecasting. Oper Res Q 27 (2, Part 2):489–501
Gung RR, Leung YT, Lin GY, Tsai RY (2002) Demand forecasting TODAY. OR/MS Today, December 2002
Harrison PJ, Davies O (1964) The use of cumulative sum (CUSUM) techniques for the control of product demand. Oper Res 12(2):325–333
Jenkins GM (1982) Some practical aspects of forecasting in organizations. J Forecast 1:31–49
Johnston FR, Boylan JE (1996) Forecasting for items with intermittent demand. J Oper Res Soc 47:113–121
Kadipasaoglu SN, Sridharan V (1995) Alternative approaches for reducing schedule instability in multistage manufacturing under demand uncertainty. J Oper Manag 13:193–211
Lasdon LS, Waren AD, Jain A, Ratner M (1978) Design and testing of a generalized reduced gradient code for nonlinear programming. ACM Trans Math Softw 4:34–50
Lee TS, Cooper FW, Adam EE Jr (1993) The effects of forecasting errors on the total cost of operations. Omega Int J Manag Sci 21(5):541–550
Leung YT, Levanoni M, Hu CW, Ramaswamy S (2002) Better demand models through data clustering. Presented at the INFORMS marketing science conference, Edmonton, Canada, June 2002
Makridakis S, Hibon M (1979) Accuracy of forecasting: an empirical investigation (with discussion). J R Stat Soc A 142:97–145
Makridakis S et al (1982) The accuracy of extrapolation (time series) methods. J Forecast 1:111–153
Makridakis S, Wheelwright SC, Hyndman RJ (1997) Forecasting: methods and applications, 3rd edn. Wiley, New York
Rycroft RS (1999) Microcomputer software of interest to forecasters in comparative review: updated again. Int J Forecast 15:93–120
Sanders NR (1997) The status of forecasting in manufacturing firms. Prod Inventory Manage J, Second Quarter, 1997, 32–36
Sanders NR, Manrodt KB (1994) Forecasting practices in US corporations: survey results. Interfaces 24(2):92–100
Smith BT (1991) Focus forecasting and DRP. Vantage Press, New York
Theil H (1966) Applied economic forecasting. North Holland, Amsterdam
Trigg DW (1964) Monitoring a forecasting system. Oper Res Q 15:271–274
West M, Harrison PJ (1986) Monitoring and adaptation in Bayesian forecasting models. J Am Stat Assoc 81(395):741–750
Yurkiewicz J (2004) Forecasting: predicting your needs. OR/MS Today, December 2004
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Leung, Y.T., Bhaskaran, K. (2011). A Practical Approach to Diagnosing and Tuning a Statistical Forecasting System. In: Kempf, K., Keskinocak, P., Uzsoy, R. (eds) Planning Production and Inventories in the Extended Enterprise. International Series in Operations Research & Management Science, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8191-2_13
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