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

Fotios Petropoulos, Xun Wang, Stephen M. Disney

Research output: Contribution to journalArticle

8 Citations (Scopus)
6 Downloads (Pure)

Abstract

Forecasting competitions have been a major driver not only of improvements in forecasting methods’ performances, but also of the development of new forecasting approaches. However, despite the tremendous value and impact of these competitions, they do suffer from the limitation that performances are measured only in terms of the forecast accuracy and bias, ignoring utility metrics. Using the monthly industry series of the M3 competition, we empirically explore the inventory performances of various widely used forecasting techniques, including exponential smoothing, ARIMA models, the 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 the methods that are based on combinations result in superior inventory performances, while the Naïve, Holt, and Holt-Winters methods perform poorly.

Original languageEnglish
Pages (from-to)251-265
Number of pages15
JournalInternational Journal of Forecasting
Volume35
Issue number1
Early online date27 Mar 2018
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • Bullwhip effect
  • Evaluation
  • Forecasting
  • Inventory
  • Utility metrics

ASJC Scopus subject areas

  • Business and International Management

Cite this