Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Classification for forecasting and stock control: a case study

Boylan, J. E., Syntetos, Argyrios and Karakostas, G. E. 2008. Classification for forecasting and stock control: a case study. Journal of the Operational Research Society 59 (4) , pp. 473-481. 10.1057/palgrave.jors.2602312

Full text not available from this repository.


Different stock keeping units (SKUs) are associated with different underlying demand structures, which in turn require different methods for forecasting and stock control. Consequently, there is a need to categorize SKUs and apply the most appropriate methods in each category. The way this task is performed has significant implications in terms of stock and customer satisfaction. Therefore, categorization rules constitute a vital element of intelligent inventory management systems. Very little work has been conducted in this area and, from the limited research to date, it is not clear how managers should classify demand patterns for forecasting and inventory management. A previous research project was concerned with the development of a theoretically coherent demand categorization scheme for forecasting only. In this paper, the stock control implications of such an approach are assessed by experimentation on an inventory system developed by a UK-based software manufacturer. The experimental database consists of the individual demand histories of almost 16 000 SKUs. The empirical results from this study demonstrate considerable scope for improving real-world systems.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HD Industries. Land use. Labor
Uncontrolled Keywords: categorization, forecasting, inventory, intermittent demand, case study
Publisher: Palgrave Macmillan
ISSN: 0160-5682
Last Modified: 04 Jun 2017 04:38

Citation Data

Cited 88 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item