Optimizing a WFP warehouse in Ethiopia

Gina Malaver, Colin Regnier
Partner: United Nations World Food Programme (WFP)

Humanitarian logistic organizations struggle to make strategic and tactical decisions due to their lack of resources, the unpredictability of humanitarian events and the lack of readily available information to support these decisions; the existing tools to assist optimal decision making require large amounts of precise information. As a consequence of all these challenges, most of the work in humanitarian logistics concentrates on the operational level. However, while the work on the operational level can only offer short term benefits, optimal strategic and tactical decisions maximize the resources of humanitarian organizations making them more flexible and effective in the long term; this directly impacts the ability to help the millions of people in need.

This thesis presents a model that assists the largest humanitarian organization in the world, The World Food Programme, to make optimal strategic decisions. The model uses the Analytic Hierarchy Process, a multiple attribute decision tool that provides structure to decisions where there is limited availability of quantitative information. This methodology uses a framework that determines and prioritizes multiple criteria by using qualitative data and it scores each alternative based on these criteria. The optimal alternative will be the one that has the highest weighted score.

This model solves the challenges that The World Food Programme, as any other humanitarian organization, faces when making complex strategic decisions. Our model, not only works with easily acquired information but, it is also flexible in order to consider the ever-changing dynamics in the humanitarian field. The application of this model focuses on the optimization of warehouse locations for the World Food Programme in the Somali region of Ethiopia. However, this model can easily be scaled in order to be used in any other decision making process in the humanitarian field.

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