Measuring Resilience (No, really! Measuring Resilience!)
DFID’s Work in Somalia
DFID strives to deliver better aid quicker in some of the most complex operating environments in the world. Somalia is a case in point. We are conducting an impact evaluation of resilience-building activities as part of DFID’s multi-year humanitarian programme. It assesses longitudinal change and the impact of different combinations of interventions. We are looking to define what combination of interventions and service providers has the most demonstrable positive impact on different communities. We will then cost those combination to determine models that could be scaled -up across similar communities. In fact, we expect to find a few combinations, like food distribution, WASH, and education, that have a higher degree of positive impact across community types.
Resilience is dynamic in that a household’s resilience can crest and trough according to the nature and severity of climatic and conflict-related shocks and at much greater velocity than in development contexts.
Our approach considers when shocks occur and then gathers evidence about where households lie on the trajectory of a shock—are they preparing, withstanding, or recovering from a shock. Households may return to where they were, to a common state of equilibrium, but they should do so quicker and with fewer dire effects because of the support they receive from DFID supported programming.
Solid Technology and Innovative Statistical Analysis to Measure the Complexity
The evaluation includes a 2,600 household sample combined with paired counterfactual villages are identified as based on proximity to target villages, general demographic characteristic, and similar livelihood zones. It includes four Household Surveys that coincide with the drier seasons in Somalia.
The diversity of interventions combined with the inherent dynamism of resilience implies that direct single variable linear relationships, as compared to a control, will not suffice. We are conducting Multivariate Analysis (MVA) that allows for the analysis of standard outcomes but from a range of different interventions and counterfactual situations. This includes variance between different outputs (services/interventions in different communities) and other static and dynamic variables. In brief, MVA is a practical way to measure complex systems.
Leveraging Technology to Ensure Data Efficacy
We are using a range of technology solutions to enable the real-time quality assurance of enumerators in the field, integrated platforms for data analysis including easy export to statistical packages, and a range of data visuals that make the impact evaluation a live, actionable tool for DFID.