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Integrating judgmental and quantitative forecasts: methodologies for pooling marketing and operations information

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Accurate forecasting has become a challenge for companies operating in today's business environment, characterized by high uncertainty and short response times. Rapid technological innovations and e-commerce have created an environment where historical data are often of limited value in predicting the future. In business organizations, the marketing function typically generates sales forecasts based on judgmental methods that rely heavily on subjective assessments and "soft" information, while operations rely more on quantitative data. Forecast generation rarely involves the pooling of information from these two functions. Increasingly, successful forecasting warrants the use of composite methodologies that incorporate a range of information from traditional quantitative computations usually used by operations, to marketing's judgmental assessments of markets. The purpose of this paper is to develop a framework for the integration of marketing's judgmental forecasts with traditional quantitative forecasting methods. Four integration methodologies are presented and evaluated relative to their appropriateness in combining forecasts within an organizational context. Our assessment considers human factors such as ownership, and the location of final forecast generation within the organization. Although each methodology has its strengths and weaknesses, not every methodology is appropriate for every organizational context.
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Keywords: Cross-Functional Integration; Forecasting; Quantitative Methods

Document Type: Research Article

Publication date: May 1, 2004

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