Academic journal article The Journal of Business Forecasting Methods & Systems

Forecasting in Consumer and Industrial Markets

Academic journal article The Journal of Business Forecasting Methods & Systems

Forecasting in Consumer and Industrial Markets

Article excerpt

Consumer and industrial market firms are inherently different. By definition, consumer market firms pursue individual consumers and families/households who buy for personal consumption; industrial market firms pursue organizations that acquire goods (and/or services) to use in the production or offering of other products (services). In general, the differences between these two types of firms include the following: industrial market firms have fewer buyers than consumer market firms; industrial market firms reflect a closer relationship between customers and seller; and industrial market firms typically have inelastic demand in the short run, but in the long run, industrial market demand can fluctuate drastically as a result of slight fluctuations in end-user demand.

Naturally, these differences translate into unique business practices for each type of firm. Because sales forecasting is a key activity for any type of business, the question of concern is whether sales forecasting practices actually do differ between consumer market firms and industrial market firms?

Past research has suggested that sales forecasting practices of consumer market firms and industrial market firms do differ. Dalrymple found that industrial firms have a stronger preference for the sales force composite method than consumer firms--the explanation being that the close relationship between industrial salespeople and their customers encourages industrial firms to use their sales force to forecast. This study also found industrial firms to have greater preferences for leading indicators, econometric models, and multiple regression.

Herbig, Milewicz, and Golden also found that industrial market firms prefer to use the sales force composite method more than consumer market firms. In addition, results showed that industrial market firms rate their forecasting process as easier to understand, contrasting consumer market firms who found the process harder to comprehend. Surprisingly, consumer market firms expressed the belief that their forecasting processes were more accurate, while industrial market firms felt that their forecasting processes were less accurate.

Though not studied by these prior studies, additional differences may include forecasters' familiarity and satisfaction with techniques. It is possible that firms may differ on technique familiarity as a result of standard sales forecasting practices within consumer versus industrial markets. Similarly, satisfaction with techniques may differ across firms in each market due to a particular technique's greater success in predicting market fluctuations--those techniques that can adapt quickly to market fluctuations will provide more satisfaction to consumer markets since demand fluctuates more rapidly at the individual consumer level. There also may be differences in the roles of electronic data interchange (EDI), distribution requirements planning (DRP), materials requirement planning (MRP), aid management information systems (MIS) in the forecasting process and how these technologies affect the forecasting process. EDI, MRP, DRP, and MIS should be more prevalent in consumer markets since the volatility of consumer markets places a premium on demand foresight.


To study the differences between consumer and industrial market firms, a mail survey was sent to 478 forecasting executives. The survey questionnaire included measures of familiarity, satisfaction, usage, and application of forecasting techniques; the accuracy achieved; and the use of information technologies (i.e., EDI, MRP, DRP, and MIS). Prior to mailing the survey, a pretest was undertaken with forecasting managers from nine companies to check the appearance and comprehensibility of the questionnaire and cover letter.

Following two survey waves, 208 questionnaires were returned for a 43.5% response rate. This response rate is deemed quite acceptable since it exceeds the response rates of many previous forecasting surveys. …

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