What would be the optimum pre-positioned stock?

This pillar focuses on defining the optimum pre-positioned stock in each location, based on a combination of historical disaster response data, a set of humanitarian logistics information (price per ton per kilometre), and other variables which are relevant to the humanitarian context (i.e. absorption capacity, replenishment times, etc).

Stock data are analysed through a mathematical model elaborated in partnership with Penn State University and other academic institutions.

The models provide two outcomes: Assessment and Guidance.

1. Assessment: the model assesses the current pre-positioned stock, highlighting gaps and overlays in inventories at different warehouses both in terms of number of items and in terms of locations.

2. Guidance: based on this, as well as on the stock reports collected through the Data collection pillar and the STOCKHOLM platform, the model also provides insights on the recommended stock quantities to store in each location in order to be able to respond to a certain percentage of disasters occurring in country. These recommendations can be provided for each core relief item.

These data, in turn, inform the decisions of in-country authorities and partners on better coordination as well as the elaboration of more effective pre-positioning strategies, at country level. The final goal of such strategies is helping humanitarian actors to optimise average response times and costs.

The Data Analysis work:

  • Is carried out by academic researchers in close collaboration with humanitarian practitioners
  • Is based on historical data about disasters size, impact and locations as well as on key logistical variables such as time to contract transportation, distances, price per ton per kilometre, absorption capacity, etc.
  • Covers core relief items to store, quantities and locations
  • Allows users to make informed decisions towards the definition of a coordinated pre-positioning strategy