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Forecasting at Scale: The Architecture of a Modern Retail Forecasting System

Author

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  • Phillip Yelland
  • Zeynep Erkin Baz
  • David Serafini

Abstract

In this first of a three-part article, Phillip Yelland, Zeynep Erkin Baz, and David Serafini, technical leads in the Data Science/AI team at Target, describe their team's efforts to construct a demand forecasting system capable of efficiently generating the nearly one billion weekly forecasts required by the Target Corporation. They highlight the interplay of challenges arising in the contexts of statistical modeling, software engineering, and business practice and explain how the team surmounted obstacles in these three fields of knowledge. Subsequent parts of the article will address the process of implementing the forecasting system and its maintenance in production.

Suggested Citation

  • Phillip Yelland & Zeynep Erkin Baz & David Serafini, 2019. "Forecasting at Scale: The Architecture of a Modern Retail Forecasting System," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 55, pages 10-18, Fall.
    • Handle: RePEc:for:ijafaa:y:2019:i:55:p:10-18
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Hoeltgebaum, Henrique & Borenstein, Denis & Fernandes, Cristiano & Veiga, Álvaro, 2021. "A score-driven model of short-term demand forecasting for retail distribution centers," Journal of Retailing, Elsevier, vol. 97(4), pages 715-725.
    3. Kolassa, Stephan, 2022. "Commentary on the M5 forecasting competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1562-1568.

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