Gap & Capacity Analysis

Identifying and filling gaps in aid delivery is one of the priority functions of Cluster coordination. At its most basic, this involves mapping geographic areas of greatest need and overlaying the locations of where Cluster partners are working, or intend to work. A simple matrix will suffice for this. However, this assumes that a comprehensive needs assessment has been done, with disaggregated data down to the lowest possible (probably sub-District) level – which, in the first phase of a sudden-onset disaster, it won’t have been. Instead, the results of a rapid assessment will be all that is available.

It is useful at this stage to conduct a financial gap analysis in order to be able to advocate to donors for more funding. This assumes that partners within the Cluster are being honest in telling you of their funding situation; often, agencies will inflate needs and exaggerate their financial shortfalls in order to generate increased funding. Once the total aggregated funding available to the Cluster is known, it is possible to assess outstanding needs in terms of cost-per-beneficiary and/or unit cost for infrastructure which you have already assessed as being required. Gross assumptions about the affected population denominator will probably have to be made [Note: Collate all agency population data and use the median as the base planning figure. Census data, however out of date, can be used to disaggregate by gender and age].

The next level of sophistication demands that the capacities of each operational agency are assessed in terms of their ability to actually deliver – agencies are not the same. Also some will be conducting more labour-intensive programmes than others or will be operating in hard-to-reach places which will greatly affect cost-per-beneficiary calculations. These capacities then have to be correlated with known vulnerabilities within the disaster-affected population. These, too, are not evenly spread throughout the affected area. Which is why any map showing agency operating locations concentrated along main roads should immediately point to a problem.

Activities should be disaggregated by gender, age, and sub-sector and correlated with known need and vulnerability. The aim thereafter is to track output or coverage as a percentage of the initially assessed need. Care must be taken, however, to ensure that account is taken of relative differences in population size and/or population density – 100% of one sub-group might only amount to 25% of another.
This is is a section from Clusterwise 2. Reproduction is encouraged. It would be nice if the author, James Shepherd-Barron, and were acknowledged when doing so.

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