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Classification for forecasting and stock control: a case study

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Classification for forecasting and stock control: a case study. / Boylan, John; Syntetos, A. A.; Karakostas, G. C.
In: Journal of the Operational Research Society, Vol. 59, No. 4, 01.04.2008, p. 473-481.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Boylan, J, Syntetos, AA & Karakostas, GC 2008, 'Classification for forecasting and stock control: a case study', Journal of the Operational Research Society, vol. 59, no. 4, pp. 473-481. https://doi.org/10.1057/palgrave.jors.2602312

APA

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

Vancouver

Boylan J, Syntetos AA, Karakostas GC. Classification for forecasting and stock control: a case study. Journal of the Operational Research Society. 2008 Apr 1;59(4):473-481. Epub 2006 Oct 18. doi: 10.1057/palgrave.jors.2602312

Author

Boylan, John ; Syntetos, A. A. ; Karakostas, G. C. / Classification for forecasting and stock control : a case study. In: Journal of the Operational Research Society. 2008 ; Vol. 59, No. 4. pp. 473-481.

Bibtex

@article{bd539517249d4d2091d8472e6cb60e91,
title = "Classification for forecasting and stock control: a case study",
abstract = "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.",
keywords = "categorization, forecasting, inventory, intermittent demand, case study",
author = "John Boylan and Syntetos, {A. A.} and Karakostas, {G. C.}",
year = "2008",
month = apr,
day = "1",
doi = "10.1057/palgrave.jors.2602312",
language = "English",
volume = "59",
pages = "473--481",
journal = "Journal of the Operational Research Society",
issn = "0160-5682",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

RIS

TY - JOUR

T1 - Classification for forecasting and stock control

T2 - a case study

AU - Boylan, John

AU - Syntetos, A. A.

AU - Karakostas, G. C.

PY - 2008/4/1

Y1 - 2008/4/1

N2 - 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.

AB - 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.

KW - categorization

KW - forecasting

KW - inventory

KW - intermittent demand

KW - case study

U2 - 10.1057/palgrave.jors.2602312

DO - 10.1057/palgrave.jors.2602312

M3 - Journal article

VL - 59

SP - 473

EP - 481

JO - Journal of the Operational Research Society

JF - Journal of the Operational Research Society

SN - 0160-5682

IS - 4

ER -