Demand forecasting with high dimensional data : the case of SKU retail sales forecasting with intra- and inter-category promotional information

Ma, Shaohui and Fildes, Robert Alan and Huang, Tao (2016) Demand forecasting with high dimensional data : the case of SKU retail sales forecasting with intra- and inter-category promotional information. European Journal of Operational Research, 249 (1). pp. 245-257. ISSN 0377-2217

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In marketing analytics applications in OR, the modeler often faces the problem of selecting key variables from a large number of possibilities. For example, SKU level retail store sales are affected by inter and intra category effects which potentially need to be considered when deciding on promotional strategy and producing operational forecasts. But no research has yet put this well accepted concept into forecasting practice: an obvious obstacle is the ultra-high dimensionality of the variable space. This paper develops a four steps methodological framework to overcome the problem. It is illustrated by investigating the value of both intra- and inter-category SKU level promotional information in improving forecast accuracy. The method consists of the identification of potentially influential categories, the building of the explanatory variable space, variable selection and model estimation by a multistage LASSO regression, and the use of a rolling scheme to generate forecasts. The success of this new method for dealing with high dimensionality is demonstrated by improvements in forecasting accuracy compared to alternative methods of simplifying the variable space. The empirical results show that models integrating more information perform significantly better than the baseline model when using the proposed methodology framework. In general, we can improve the forecasting accuracy by 12.6 percent over the model using only the SKU's own predictors. But of the improvements achieved, 95 percent of it comes from the intra-category information, and only 5 percent from the inter-category information. The substantive marketing results also have implications for promotional category management.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Additional Information:
This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 249, 1, 2015 DOI: 10.1016/j.eor.2015.08.029
Uncontrolled Keywords:
?? analyticsor in marketingforecastingretailingpromotionsmodelling and simulationmanagement science and operations researchinformation systems and management ??
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Deposited On:
01 Mar 2016 14:16
Last Modified:
24 Mar 2024 00:47