Using clustering to improve sales forecasts in retail merchandising

Using clustering to improve sales forecasts in retail merchandising

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Article ID: iaor20101500
Volume: 174
Issue: 1
Start Page Number: 33
End Page Number: 46
Publication Date: Feb 2010
Journal: Annals of Operations Research
Authors: ,
Keywords: forecasting: applications
Abstract:

Given sales forecasts for a set of items along with the standard deviation associated with each forecast, we propose a new method of combining forecasts using the concepts of clustering. Clusters of items are identified based on the similarity in their sales forecasts and then a common forecast is computed for each cluster of items. On a real dataset from a national retail chain we have found that the proposed method of combining forecasts produces significantly better sales forecasts than either the individual forecasts (forecasts without combining) or an alternate method of using a single combined forecast for all items in a product line sold by this retailer.

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