The impact of misrepresentative data patterns on sales forecasting accuracy

Article Abstract:

The development of a sales forecasting system involves three major steps. The first step is to obtain prior sales data and to identify the model that will best forecast the patterns that exist in the data. The second step is to estimate parameter values for the selected model by analyzing the prior sales data. The third step is to test the accuracy of the model by use of the prior sales data. Each of the steps requires use of prior data. In all three steps, there is a basic assumption that the past data represent some underlying process that can be identified and modeled. In some cases the past data may not represent the underlying process, and the forecasting process is seriously distorted. Some frequent causes of distorted data are (1) accounting methods that are used to record or collect the data, (2) marketing tactics such as promotions which create outliers, (3) limits on production capacity that cause stockouts. This paper looks at events and actions that may distort data used for sales forecasting and at the resulting impact the events and actions may have on forecasting accuracy. (Reprinted by permission of the publisher.)

Analysis, Database administration, Parameter estimation

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Emerging issues in sales forecasting and decision support systems

Article Abstract:

There are two distinct groups of emerging issues in the area of sales forecasting and decision support systems: methodological issues and implementational issues. This paper discusses each of them. The discussion of implementational issues includes some results of a survey of forecasting practice. The paper serves as a preface to the special section on sales forecasting and decision support systems and introduces the papers included in the special section. (Reprinted by permission of the publisher.)

Management, Sales

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