Evaluating the progress made in climate change adaptation using indicators of resilience, Part IV: Resilience indicators

Part 4: A Flexible Approach to Resilience Leads to Better Understanding

Having a flexible approach to the understanding and application of the term resilience helps us make the concept of resilience more operational (see Part 3). This can make the process of designing, monitoring and evaluating development and adaptation interventions both more straightforward and more effective. it can also helps us track the cumulative effects of different adaptation actions in the longer term.

For any given geographic, livelihood and development context, we can seek to identify the factors that help people anticipate, plan for, avoid, cope with, recover from and/or adapt to specific climate shocks and stresses, as well as the factors that prevent them from doing so.

This might be done through participatory surveys that ask why certain people have coped with or adapted to previous shocks and chances, while others have not. Case studies of past shocks might be employed, along with informed expert judgment of what factors are likely to facilitate or constrain adaptation to emerging or anticipated stresses.

This approach recognises that the factors that make people or systems resilient to a particular type of shock or stress are likely to be highly context specific.

It is likely to require significantly more resources than approaches based on the use of secondary data. However, the deployment of adequate resources for the identification of the key factors mediating resilience (or vulnerability) in any given context, and at any given scale, is absolutely vital if resilience is to be understood, let alone measured. 

These key factors will include ‘internal’ characteristics or attributes of the systems exposed to the hazards we are concerned with, as well as ‘external’ or contextual factors.

Internal characteristics might include things like household income, diversity of agricultural systems or livelihoods, social status, assets (see the ox example in Part 3), and capacity to access resources (e.g. transport, markets, grazing), information (e.g. forecasts) and social networks (e.g. through membership of certain groups or organisations). 

External characteristics might be related to policies, commodity prices, conflicts, and other factors that prevent or facilitate actions through which resilience might be improved (either through outside intervention or the actions of those exposed to stresses and shocks).

Measuring resilience

If the factors that affect resilience can be identified, it is – at least in principle - possible to represent them using indicators.

These indicators might be constructed using continuous variables (e.g. household income), scorecards (e.g. capturing people’s perceptions of their own ability to cope with a particular stress on a scale of one to five), or ‘yes/no’ answers (e.g. do you have access to a particular resource?).

Individual indicators might remain disaggregated, or they might be combined as composite indices (for example representing different ‘capacities’ or ‘dimensions of resilience’).

Indicators, or composite indices representing different aspects of resilience, can be tracked over time in order to determine whether resilience is increasing. For the assessment of specific interventions, resilience indicators might be measured at the start of an intervention (the baseline), at one or more points during its implementation (if appropriate), and then at its end or at some point after it has run its course (e.g. as part of an ex-post evaluation).

Of course, all the usual challenges associated with the monitoring and evaluation of development programmes, and with the use of indicators to do so, apply to interventions that focus on resilience. These include (among others) the challenge of assessing the extent to which the intervention contributed to observed changes in resilience, the problem of how to weight different indicators, and the challenge of ensuring that indicators are both practical in terms of measurement, and meaningful in terms of what the represent. 

In addition, it must be recognised that an intervention might only be able to influence a subset of factors that are important for resilience.

Evaluations of such interventions must decide which aspects of resilience are ‘relevant’ to an intervention, and to what extent ‘external’ or ‘contextual’ factors that the intervention cannot address, but which might undermine resilience, should be tracked.

When it comes to evaluating an intervention’s efficacy, this leads us to a problematic question that is both practical and philosophical in nature. If an intervention improves some aspects of resilience but other factors lead to an overall deterioration in resilience, can an intervention said to have been successful?

This blog is in 5 Parts

Part I

Part II

Part III

Part IV

Part V