Exploring the representativeness of the M5 competition data

Evangelos Theodorou, Shengjie Wang, Yanfei Kang, Evangelos Spiliotis, Spyros Makridakis, Vassilios Assimakopoulos

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)

    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
    JournalInternational Journal of Forecasting
    DOIs
    Publication statusAccepted/In press - 2021

    Keywords

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

    Fingerprint

    Dive into the research topics of 'Exploring the representativeness of the M5 competition data'. Together they form a unique fingerprint.

    Cite this