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UN World Food Programme: Toward Zero Hunger with Analytics

Author

Listed:
  • Koen Peters

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy; Department of Econometrics and Operations Research, Tilburg University, Tilburg 5000 LE, Netherlands)

  • Sérgio Silva

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy)

  • Tim Sergio Wolter

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy)

  • Luis Anjos

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy)

  • Nina van Ettekoven

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy)

  • Éric Combette

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy)

  • Anna Melchiori

    (Supply Chain Planning and Optimization Unit, World Food Programme, Rome 00148, Italy)

  • Hein Fleuren

    (Department of Econometrics and Operations Research, Tilburg University, Tilburg 5000 LE, Netherlands)

  • Dick den Hertog

    (Faculty of Economics and Business, University of Amsterdam, Amsterdam 1001 NB, Netherlands)

  • Özlem Ergun

    (Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts 02115)

Abstract

Each year, the United Nations World Food Programme (WFP) provides food assistance to around 100 million people in more than 80 countries. Significant investments over the last decade have put planning and optimization at the forefront of tackling emergencies at WFP. A data-driven approach to managing operations has gradually become the norm and has culminated in the creation of a supply chain planning unit and savings of more than USD 150 million—enough to support two million food-insecure people for an entire year. In this paper, we describe three analytical solutions in detail: the Supply Chain Management Dashboard, which uses descriptive and predictive analytics to bring end-to-end visibility and anticipate operational issues; Optimus, which uses a mixed-integer programming model to simultaneously optimize food basket composition and supply chain planning; and DOTS, which is a data integration platform that helps WFP automate and synchronize complex data flows. Three impact studies for Iraq, South Sudan, and COVID-19 show how these tools have changed the way WFP manages its most complex operations. Through analytics, decision makers are now equipped with the insights they need to manage their operations in the best way, thereby saving and changing the lives of millions and bringing the world one step closer to zero hunger.

Suggested Citation

  • Koen Peters & Sérgio Silva & Tim Sergio Wolter & Luis Anjos & Nina van Ettekoven & Éric Combette & Anna Melchiori & Hein Fleuren & Dick den Hertog & Özlem Ergun, 2022. "UN World Food Programme: Toward Zero Hunger with Analytics," Interfaces, INFORMS, vol. 52(1), pages 8-26, January.
    • Handle: RePEc:inm:orinte:v:52:y:2022:i:1:p:8-26
    DOI: 10.1287/inte.2021.1097
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    References listed on IDEAS

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    1. Kimberly M. Thompson & Radboud J. Duintjer Tebbens & Mark A. Pallansch & Steven G.F. Wassilak & Stephen L. Cochi, 2015. "Polio Eradicators Use Integrated Analytical Models to Make Better Decisions," Interfaces, INFORMS, vol. 45(1), pages 5-25, February.
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    Cited by:

    1. Pei-Ju Wu & Yu-Shan Lin, 2023. "Reducing waste and achieving sustainable food security through optimizing surplus-food collection and meal distribution," Annals of Operations Research, Springer, vol. 328(2), pages 1537-1555, September.
    2. Stienen, Valentijn & den Hertog, Dick & Wagenaar, J.C. & de Zegher, J.F., 2022. "Enhancing Digital Road Networks for Better Operations in Developing Countries," Discussion Paper 2022-014, Tilburg University, Center for Economic Research.
    3. Stienen, Valentijn & den Hertog, Dick & Wagenaar, J.C. & de Zegher, J.F., 2022. "Enhancing Digital Road Networks for Better Operations in Developing Countries," Other publications TiSEM 745d1d0c-7af2-4759-add4-0, Tilburg University, School of Economics and Management.

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