Demand-driven forecasting : a structured approach to by Charles W. Chase

By Charles W. Chase

An up to date re-creation of the great consultant to raised company forecasting Many businesses nonetheless examine quantitative forecasting tools with suspicion, yet a brand new knowledge is rising throughout many industries as extra companies and pros realize the price of integrating call for facts (point-of-sale and syndicated scanner facts) into the forecasting approach. Demand-Driven Forecasting equips you with Read more...

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Television advertisements. 4). 4 Oven Cleaner Shipment History Several Years Later 1996 16 ▸ DEMYSTIFYING FORECASTING: MYTHS VERSUS REALITY The oven cleaner story is a great illustration of sensing demand signals and using analytics to shape future demand, not to mention shaping brand positioning and messaging. Unfortunately, the next story does not illustrate the best practices in demand forecasting but rather the worst. MORE IS NOT NECESSARILY BETTER Several years ago during a customer visit with a large national restaurant chain, the SAS team uncovered an abnormally large number of people in the demand forecasting process.

National brand team, which was responsible for growing its sports drink business. Our goal was to provide the brand team with a way to measure the effects of marketing dollars and use the findings to shape and predict future demand as an input into the monthly sales and operations planning process. We decided to develop several advanced statistical models by brand and package size to predict the effects of marketing tactics on consumer demand using Nielsen syndicated scanner data (pointof-sale [POS] data).

Trying to overcome these challenges using gut-feeling judgment does not work. An in-depth study was conducted a few years ago and published in the fall 2007 issue of Foresight: The International Journal of Applied Forecasting. Titled “Good and Bad Judgment in Forecasting: Lessons from Four Companies” by Robert Fildes (director of the Lancaster University Centre for Forecasting) and Paul Goodwin (professor of management science at the University of Bath in England) and based on their ongoing five-year investigation into corporate forecasting practices, the authors uncovered evidence of excessive use of judgmental adjustments to statistical baseline forecasts.

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