The inventory performance of forecasting methods: evidence from the M3-competition data

Petropoulos, Fotios, Wang, Xun ORCID: https://orcid.org/0000-0001-7800-726X and Disney, Stephen M. ORCID: https://orcid.org/0000-0003-2505-9271 2019. The inventory performance of forecasting methods: evidence from the M3-competition data. International Journal of Forecasting 35 (1) , pp. 251-265. 10.1016/j.ijforecast.2018.01.004

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Abstract

Forecasting competitions have been a major drive not only for improving the performance of forecasting methods but also for the development of new forecasting approaches. Despite the tremendous value and impact of these competitions, they suffer from the limitation is that performance is measured only in terms of forecast accuracy and bias, lacking utility metrics. Using the monthly industry series of the M3-competition, we empirically explore the inventory performance of widely used forecasting techniques, including exponential smoothing, ARIMA models, Theta method and approaches based on multiple temporal aggregation. We employ a rolling simulation approach and analyse the results for the order-up-to policy under various lead times. We find that methods based on combinations result in superior inventory performance, while Na¨ıve, Holt and Holt-Winters perform poorly.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Uncontrolled Keywords:	forecasting, inventory, evaluation, utility metrics, bullwhip effect
Publisher:	Elsevier
ISSN:	0169-2070
Date of First Compliant Deposit:	12 March 2018
Date of Acceptance:	16 January 2018
Last Modified:	22 Nov 2024 15:00
URI:	https://orca.cardiff.ac.uk/id/eprint/109815

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