This publication offers guidance for designing M&E systems for climate change adaptation. It argues that M&E systems need to enable results-based management, promote flexibility, and support iterative learning. Achieving these goals requires development practitioners to carefully articulate their adaptation objectives, clarify the basis for their project design, and make their assumptions transparent. With this foundation, project managers can select indicators and build information systems that are able to track adaptation success.
M&E systems play two critical roles in ensuring effective adaptation: they support the long-term process of learning ‘what works’ in adaptation and they provide a tool for practitioners to manage their work in the context of the uncertainty surrounding climate change impacts. Broad early lessons on the use of M&E for adaptation are that: 1) defining adaptation success requires consideration of the context in which adaptation activities occur; 2) diverse inputs – including information and participants – contribute to successful adaptation M&E systems; and 3) it is important to track assumptions.
Practitioners can use a six-step process either to develop an M&E system for an adaptation project or programme, or to identify ways to monitor and evaluate the adaptation components of a development intervention. The steps can also help funders and practitioners to gauge the utility of existing M&E systems for adaptation initiatives. They are as follows:
- Describe the Adaptation Context – Conducting a climate vulnerability and/or climate risk assessment early in the design process can help practitioners to understand the climate and non-climate factors and populations that will affect and be affected by planned interventions.
- Identify the Contribution to Adaptation – Attribution of any given set of activities to a known outcome is impossible. Instead, possible contributions to the adaptation process could be identified in relation to: 1) adaptive capacity, 2) adaptation actions, and 3) sustained development.
- Form an Adaptation Hypothesis – To test the validity of a location-specific approach to adaptation, practitioners can formulate an adaptation hypothesis for each major expected outcome.
- Create an Adaptation Theory of Change – This can help to illustrate the relationship between an intervention’s components, expected results, and assumptions about factors that can enable or inhibit the likelihood of achieving success.
- Choose Indicators and Set a Baseline – Practitioners can characterise indicators by type of outcome, and devise a baseline to measure progress within each. For example, adaptive capacity might be described by indicators relating to ‘assets’ and ‘institutional functions’; indicators for adaptation actions might include activities and decisions that address particular ‘climate hazards’, or work to reduce ‘vulnerability drivers’. And ‘ecosystem services’ and ‘livelihoods’ indicators might help to demonstrate sustaining development in a changing climate.
- Use the Adaptation M&E System – Implementation needs to involve flexibility and learning, including through regular feedback loops and engagement with partners.
The challenges of M&E for adaptation are largely shaped by factors outside the individual project cycle. Therefore, developers of M&E systems need to move toward measuring changes in broader systems. It is also important to:
- Explore options for overcoming barriers to participation: Further work is needed to understand how technology, capacity building, and wise use of financial resources can reduce the costs of stakeholder participation in M&E, improve inclusion processes, and scale up the use of participatory approaches.
- Link existing M&E systems and strengthen connections between bottom-up and top-down information and decision making: This could help focus scarce resources.
- Promote experimentation: M&E will play an important role in helping to learn when approaches have value and how they can be adapted to specific locations.
- Face tensions and trade-offs: Open discussion can ensure that a given system is used appropriately, and that its results are not misunderstood, misinterpreted, or used for cross-purposes.
