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Essay / Research Paper Abstract
A 6 page paper discussing seasonal, Delphi, technological, time series and correlation/regression forecasting models. It concludes with an example of Maxwell, a small furniture retailer and its need to combine the result of at least two forecasting techniques, taking the average of the combined result. Bibliography lists 4 sources.
Page Count:
6 pages (~225 words per page)
File: CC6_KSmgmtForecast.rtf
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Unformatted sample text from the term paper:
given by a person who is looking out the back window. -Technological Forecasting Introduction One author explains that there are "four rights of
effective inventory management: that is, getting the right quantity of the right item to the right location at the right time" (Schreibfeder, n.d.). There are many methods of finding
the juncture of the "four rights," and the one most appropriate depends on several factors. Some forecasting methods are extensive and time consuming, while others are rather simple and
straightforward. All have their place, however, depending on the level of complexity that the organization needs. Clearly, a single-location retailer and the federal government seeking an economic forecast
have no need to use the same method of forecasting demand. Forecasting Methods Moncrief and Shipp (1997) say "there is no single best
technique for forecasting" (p. 601); they also explain that the most accurate forecasts result from combining two to four very different techniques. Seasonal
For the retailer and other sales businesses, seasonal forecasting is best done at the inventory level, ensuring that goods and services likely to be in demand during a specific season
are available for sale. Seasonal forecasting not only strives to predict expected sales, but also can be used to identify the types of products that are most likely to
be in demand. Delphi The Delphi method is a qualitative technique, a "refinement of the jury of executive or expert opinion" (Moncrief and
Shipp, 1997; p. 588). After selecting a panel of experts, each expert is asked to formulate a forecast individually and without input from others. These results are compiled
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