Models and Metrics to Assess Humanitarian Response Capacity

Abstract

The race to meet vital needs following sudden onset disasters leads response organizations to establish stockpiles of inventory that can be deployed immediately. These government or non-government organizations dynamically make stockpile decisions independently.

Even though the value of one organization's stock deployment is contingent on others' decisions, decision makers lack evidence regarding sector capacity to assess the marginal contribution (positive or negative) of their action. To our knowledge, there exist no metrics describing the system capacity across many agents to respond to disasters. To address this gap, our analytical approach yields new humanitarian logistics metrics based on stochastic optimization models.

Our study incorporates empirical data on inventory stored by various organizations in United Nations facilities and in their own to offer practical insights regarding the current humanitarian response capabilities and strategies. By repositioning inventory already deployed, the system could respond to disasters in the same expected time with a range of 7.4% to 20.0% lower cost for the items in our sample.

Keywords: Humanitarian logistics, inventory pre-positioning, stockpiling, metrics