By Charles W. Chase

ISBN-10: 1118669398

ISBN-13: 9781118669396

ISBN-10: 1118691865

ISBN-13: 9781118691861

ISBN-10: 1118735579

ISBN-13: 9781118735572

ISBN-10: 1118735641

ISBN-13: 9781118735640

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

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Extra resources for Demand-driven forecasting : a structured approach to forecasting

Example text

As a result, we created a set of business rules for future model development. The primary rule advised modelers to exclude end-cap displays in any 64-ounce bottle models to explain consumer demand. From this story, we learned that (1) demand forecasting requires a collaborative effort between a statistician and a domain knowledge expert, and (2) domain knowledge is very different from pure gutfeeling judgment. REALITY OF JUDGMENTAL OVERRIDES Many companies still value judgment over analytics, and as such, judgment is used almost exclusively to manipulate the statistical baseline demand forecast to meet their needs.

The purpose of this exercise was twofold: (1) to measure the effects of the marketing mix elements (price, advertising, merchandising, sales promotions, competitive activities, and any other external factors) on consumer demand, and (2) to use those measures to conduct what-if simulations to shape future demand, resulting in a more accurate demand forecast that reflected the sports drink brand team marketing strategy. The first series of models was developed for the sports drink 64-ounce product group.

Domain knowledge could then be used to identify the factors that affect those particular brands, product groups, and products, providing a hypothesis as to why and how they can be influencing demand. Finally, the hypothesis should be tested to determine which factors are influencing demand and incorporate them into the statistical baseline forecasts. In other words, the judgmental assumptions that are used to justify making manual overrides using data and analytics rather than someone’s opinion, or gut feelings, should be validated through the data and analytics.

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

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