Improving the Measurement of Resilience: Lessons from a RABIT Field Study

How can we measure resilience?

This is a perennial challenge for those working on resilience, and one we have faced in the field in implementing RABIT; the Resilience Assessment Benchmarking and Impact Toolkit.

Precursor challenges are first to define and conceptualise resilience.  With minor variations, definitions are often very similar to that used for RABIT: “the ability of a system to withstand, recover from and adapt to short-term shocks and longer-term change”.  But RABIT’s unique conceptualisation is to understand resilience as a set of foundational (robustness, self-organisation, learning) and enabling (redundancy, rapidity, scale, diversity, flexibility, equality) system attributes.  (For further details, see the journal paper, “Conceptualising the Link Between Information Systems and Resilience: A Developing Country Field Study”.)

To measure resilience, we identified three markers for each of the attributes, derived from prior literature and as shown in Table 1.

 Table 1. Resilience Attributes and Illustrative Markers

ISJ Table 1

We then took this model into the field, applying it in an urban community in Costa Rica’s capital, San Jose.  We used the model to benchmark both the general resilience of the community and also its “e-resilience”; that is, the impact of digital technologies on wider resilience.

Details of findings can, again, be found in the associated journal paper, but the focus here will be what we learned about the markers we had used to measure resilience.  We found a number of problems in practice:

  • There were overlaps: for example, multi-level networks and cross-level interactions under scale, and multi-level governance under robustness might have potential differences but they appeared in practice to be very similar.
  • There were gaps: for example, the markers for rapidity were narrowly conceived around resources and as a result, did not adequately reflect the need for a fast-acting detection-assessment-response sub-system.
  • There were some misallocations: for example, trust belonged with social networks rather than with leadership; and interdependency of system functions related to robustness rather than redundancy.
  • There were over-broad combinations: where rather different characteristics were combined into a single marker; often leading to only one of them being operationalised. For example, “resource access and (intra-/inter-level) partnerships” was only operationalised as “intra-level partnerships”.

Putting all these findings from the field study together, a revised set of markers was developed (see Table 2).  To operationalise them, it will be helpful to develop deductively a set of descriptors and indicators associated with each marker and inductively a set of respondent keywords/phrases associated with each marker.

We encourage others with interests in resilience to make use of this improved basis for measurement, and will be happy to discuss this process.

Table 2. Revised Resilience Markers

ISJ Table 5

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RABIT: A New Toolkit for Measuring Resilience

As the 21st century proceeds, countries – particularly developing countries – will face a growing series of short-term shocks (economic crises, climate events, violent attacks, health epidemics, etc) and long-term trends (climate change, migration, economic restructuring, new technologies, etc).  In abstract terms, we know the solution: countries must become more resilient.

That is because resilience is defined as the ability of vulnerable systems – countries, regions, communities, value chains, organisations – to withstand, recover from, adapt to, and potentially transform amid change and uncertainty.  Resilience will therefore play a crucial role in the achievement of development outcomes.  It provides a holistic and long-term approach that is rising up the development agenda.

That is the theory.  The challenge arises in practice: there are few credible guides that activists and researchers can follow which explain what resilience is, how to apply resilience metrics, and how to use those metrics to shape action.  The University of Manchester has therefore developed RABIT: the Resilience Assessment Benchmarking and Impact Toolkit.

To understand resilience, RABIT identifies nine attributes – or sub-properties – of resilience.  Three are primary foundations of resilience: robustness, self-organisation, learning.  Six are secondary enablers of resilience: redundancy, rapidity, scale, diversity, flexibility, equality.  The stronger these are in a community, the more resilient it will be[1].

Each attribute has a series of key markers: indicators that we can use to assess the strength or weakness of each attribute.  These can be measured in two main ways:

  • Resilience benchmarking: at the pre-hoc stage of project design, resilience can be benchmarked to establish key areas for resilience-building action during an intervention.
  • Resilience impact assessment: RABIT can be used to assess the impact on resilience of interventions during or after their implementation, to draw lessons learned, and to inform future programming/strategising.

Data can be gathered by document review, focus group, interview, or survey.  It is then subject to enumeration that enables a variety of different visualisations, as illustrated in Figure 1.  These identify current resilience strengths to build on, and current resilience lacunae that need to be addressed.

rabit-visualisation-examples

Based on the visualisations illustrated in Figure 1 plus further analysis, RABIT then provides the basis for prioritising future interventions which will build resilience.  A sample is shown in Table 1, with interventions identified; typically following a discussion of the visualisations with key stakeholders.  An indication is provided of which stakeholders – in this case, community-level (C), municipality-level (M) and national-level (N) – will be involved.

RABIT Intervention Priority Table Example.png

Table 1. Sample priority actions to improve resilience

For full details of the Implementation Handbook showing how to use the RABIT toolkit plus case studies of RABIT’s application, see: http://www.niccd.org/resilience

We are happy to answer questions about application of the framework, and to provide support to those seeking to implement RABIT: niccd.project@gmail.com

 

[1] Our illustration will be at the level of individual communities but RABIT is applicable to all and any of the systems described from households to nations.

Urban Resilience: Testing a New Framework on Community Informatics

There are many approaches to understanding urban resilience and an ever-growing literature seeing resilience as catalyst or metaphor, or identifying components or categories or facilitators.  But there is surprisingly little work that defines and conceptualises resilience in a systematic way.

Based on a synthesis of past work, we built a new and comprehensive model of resilience: defined as “the ability to withstand and recover from short-term shocks, and to adapt to long-term trends“ and understood as neither a structure nor a function of systems, but as a property of systems.

Our model of resilience sees it consist of three foundational attributes or sub-properties: self-organisation that allows a re-arrangement of functions; robustness to withstand external stressors; and capacity for learning via feedback.  Facilitating these are a set of enabling attributes: redundancy, rapidity, scale, diversity, flexibility, and equality.

Resilience Attributes Block Model

An initial application of the model analysed ways in which community informatics – the use of digital technology within urban districts – could strengthen and weaken community resilience.  Analysing attribute by attribute provided a systematic means to assess current evidence: geographic information systems that help planning of physical defences; use of social media to build local organising networks; application of online groups to support Learning and Action Alliances; etc on the plus side.  But also creating external dependencies that can undermine local autonomy, and exacerbating inequalities within urban communities.

This current work provides only a general proof-of-concept, showing that this new urban resilience model is viable and applicable to urban development issues.  Further work is being undertaken to roll it out in practice as part of RABIT (the Resilience Assessment Benchmarking and Impact Tookit), but we hope the model already offers an integrated and standardised approach to urban resilience.

For more details, the paper “Analysing Urban Community Informatics from a Resilience Perspective” published in the Journal of Community Informatics is available via open access at: http://www.ci-journal.net/index.php/ciej/article/view/1108/1135