Bibliographic Details
| Title: |
Judgmental Adjustments in Demand Planning: Their Motivation and Success. |
| Authors: |
FILDES, ROBERT1 r.fildes@lancaster.ac.uk, GOODWIN, PAUL2 p.goodwin@bath.ac.uk, DE BAETS, SHARI3 shari.debaets@gmail.com |
| Source: |
Foresight: The International Journal of Applied Forecasting. 2023 Q4, Issue 71, p31-37. 7p. |
| Subject Terms: |
*Sales forecasting, Machine learning, Demand forecasting, Motivation (Psychology), Edible coatings, Statistical smoothing |
| Abstract: |
This article examines the practice of judgmental adjustments in demand planning and its impact on forecasting performance. The study analyzed six datasets from different industries and found that only about half of the adjusted forecasts were more accurate and less biased than the original forecasts. Downward adjustments were generally more successful in reducing bias and improving accuracy. The size and direction of adjustments also played a role, with smaller adjustments resulting in smaller changes in forecast performance. The article suggests that better organizational processes and forecasting support systems are needed to make judgmental adjustments more valuable. Additionally, the article discusses the need for forecasters to utilize relevant and reliable information when making adjustments, rather than relying on irrelevant or unreliable sources. The possibility of debiasing judgmental adjustments to enhance forecast accuracy is also explored. [Extracted from the article] |
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| Database: |
Business Source Complete |
