* Any views expressed in this opinion piece are those of the author and not of Thomson Reuters Foundation.Doing it right is crucial to efforts to help vulnerable communities cope with shocks
As we mingle with government negotiators and development agency delegations at the UN World Conference on Disaster Risk Reduction in Sendai, Japan this week, one sticky question keeps popping up from all sides. What is the best way to measure resilience?
The range of evaluation approaches for resilience programmes is expanding rapidly, but there remains little agreement on how to measure success. Reaching an agreement at Sendai is even more pressing this year, as key interlinked global policy frameworks are due to come into force. These include the post-2015 framework for Disaster Risk Reduction (DRR), the Sustainable Development Goals (SDGs) and a climate change agreement, all of which have components aimed at building resilience.
A recent paper by the Overseas Development Institute (ODI), the Centre for Research on the Epidemiology of Disasters (CRED) and Risk Management Solutions (RMS) sets out recommendations for Setting, measuring and monitoring targets for reducing disaster risk.
In addition to this, with support from the Rockefeller Foundation and the UK Department for International Development (DFID), ODI has analysed 50 frameworks to distil essential insights on measuring resilience. Based on the findings of both these analyses, we recommend the following best practice approaches to measuring resilience:
1. Draw on the key concepts of resilience: Resilience-building approaches draw on a wealth of research and thinking. These should be reflected in approaches to measurement, embedding ideas such as ‘systems thinking’ within any proposed metrics.
2. Measure often and remain flexible: Resilience thinking helps us understand complex interactions within a system, and account for continual evolution and a constant state of change. This is why gauging the degree to which a system is resilient requires a higher frequency of measurement and a frequent adjustment of approaches.
3. Collect disaggregated data: DRR monitoring and evaluation does not systematically rely on data broken down by gender, age, disability, ethnicity and socio-economic status. Data collection needs to be disaggregated in order to understand the impact of disasters on vulnerable groups and ensure that resources are targeted equitably.
4. Measure across systems and scales: Measuring the performance of different, inter-related systems across different scales is vital. This includes human and institutional systems, as well as economic, environmental or infrastructure systems. Actions to strengthen all or part of a system need to be measured in the context of the wider systems in which it operates.
5. Balance assets and processes: Frameworks should track and measure both assets (schools, savings, health infrastructure) as well as processes (good governance, transparency, inclusion) as part of a holistic approach to measuring resilience. Also, it’s vital to measure the quantity and quality of assets and processes, therefore ‘thresholds’ must receive adequate consideration in any approach to accurately gauge resilience.
6. Include the political context: What constitutes ‘good resilience’? When developing frameworks, it is critically important to ask framing questions, such as ‘resilience of whom, by whom and to what ends’. Finding ways to measure and track these over time remains a real challenge.
7. Track hazards and impacts: Assessing hazard intensity and the impact on livelihoods is necessary to accurately measure the effectiveness of resilience programmes. If impacts remain the same or reduce as hazard intensity goes up, then we can say that a household is more resilient.
8. Track risk of loss, not just losses: As major disasters happen infrequently, simply measuring deaths or economic losses over a certain time period may provide misleading results. It is therefore vital to measure the ‘risk of loss’ from a range of hazards to understand whether resilience building interventions are making progress (for instance, through the use of models to calculate risk).
9. Invest in high-resolution data: High resolution data is needed to measure risk using the real experiences of disaster losses to validate findings. Improving the availability of such data is a critical challenge, requiring increased and coordinated resources from both public and private sectors. July’s Third International Conference on Financing for Development in Addis Ababa, Ethiopia, can make an important contribution.
Good measurement is vital for the success of policies and programmes aimed at building resilience. This in turn will help support vulnerable communities to cope with, manage and respond to the shocks and stresses posed by climate change and disasters.