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Impact of information sharing and forecast combination on fast-moving-consumer-goods demand forecast accuracy

  • Dazhi Yang*
  • , Allan N. Zhang
  • *Corresponding author for this work
  • Agency for Science, Technology and Research, Singapore

Research output: Contribution to journalArticlepeer-review

Abstract

This article empirically demonstrates the impacts of truthfully sharing forecast information and using forecast combinations in a fast-moving-consumer-goods (FMCG) supply chain. Although it is known a priori that sharing information improves the overall efficiency of a supply chain, information such as pricing or promotional strategy is often kept proprietary for competitive reasons. In this regard, it is herein shown that simply sharing the retail-level forecasts-this does not reveal the exact business strategy, due to the effect of omni-channel sales-yields nearly all the benefits of sharing all pertinent information that influences FMCG demand. In addition, various forecast combination methods are used to further stabilize the forecasts, in situations where multiple forecasting models are used during operation. In other words, it is shown that combining forecasts is less risky than "betting" on any component model.

Original languageEnglish
Article number260
JournalInformation (Switzerland)
Volume10
Issue number8
DOIs
StatePublished - 1 Aug 2019
Externally publishedYes

Keywords

  • Fast moving consumer goods
  • Forecasting
  • Hierarchical reconciliation
  • Information sharing

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