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Exploring the representativeness of the M5 competition data

  • Evangelos Theodorou
  • , Shengjie Wang
  • , Yanfei Kang*
  • , Evangelos Spiliotis
  • , Spyros Makridakis
  • , Vassilios Assimakopoulos
  • *Corresponding author for this work
  • National Technical University of Athens
  • Beihang University
  • University of Nicosia

Research output: Contribution to journalArticlepeer-review

Abstract

The main objective of the M5 competition, which focused on forecasting the hierarchical unit sales of Walmart, was to evaluate the accuracy and uncertainty of forecasting methods in the field to identify best practices and highlight their practical implications. However, can the findings of the M5 competition be generalized and exploited by retail firms to better support their decisions and operation? This depends on the extent to which M5 data is sufficiently similar to unit sales data of retailers operating in different regions selling different product types and considering different marketing strategies. To answer this question, we analyze the characteristics of the M5 time series and compare them with those of two grocery retailers, namely Corporación Favorita and a major Greek supermarket chain, using feature spaces. Our results suggest only minor discrepancies between the examined data sets, supporting the representativeness of the M5 data.

Original languageEnglish
Pages (from-to)1500-1506
Number of pages7
JournalInternational Journal of Forecasting
Volume38
Issue number4
DOIs
StatePublished - 1 Oct 2022

Keywords

  • Forecasting competitions
  • M5
  • Retail sales forecasting
  • Time series features
  • Time series visualization

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