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The use of non‐time series information in sales forecasting: A case study
Author(s) -
Edmundson Bob,
Lawrence Michael,
O'Connor Marcus
Publication year - 1988
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980070305
Subject(s) - product (mathematics) , extrapolation , time series , series (stratigraphy) , consensus forecast , computer science , point (geometry) , sales forecasting , demand forecasting , econometrics , operations research , marketing , business , economics , statistics , mathematics , machine learning , paleontology , geometry , biology
Abstract The contribution of product and industry knowledge to the accuracy of sales forecasting was investigated by examining the company forecasts of a leading manufacturer and marketer of consumable products. The company forecasts of 18 products produced by a meeting of marketing, sales, and production personnel were compared with those generated by the same company personnel when denied specific product knowledge and with the forecasts of selected judgemental and statistical time series methods. Results indicated that product knowledge contributed significantly to forecast accuracy and that the forecast accuracy of company personnel who possessed industry forecasting knowledge (but not product knowledge) was not significantly different from the time series based methods. Furthermore, the company forecasts were more accurate than averages of the judgemental and statistical time series forecasts. These results point to the importance of specific product information to forecast accuracy and accordingly call into question the continuing strong emphasis on improving extrapolation techniques without consideration of the inclusion of non‐time series knowledge.