The LIFE-AR Initiative emphasises a shift from traditional, business-as-usual climate responses to more innovative, inclusive, and effective strategies. The Monitoring, Evaluation and Learning (MEL) system under LIFE-AR ensures that reporting is not a top-down exercise but is driven by the priorities and needs of the participating countries. It promotes continuous learning and adaptive management, with a focus on integrating local views and voices into the evidence-gathering process. This ensures that the most vulnerable communities are supported and are at the centre of climate adaptation and resilience-building initiatives, action and decision making.
LIFE-AR's approach to MEL is anchored within the initiative’s global theory of change (ToC). This envisions that if LDCs lead inclusive, coordinated climate resilience efforts, with at least 70% of finance directed to local-level actions, climate resilience will improve for the most vulnerable. The global ToC is driven by a global MEL plan and contextualized MEL plans for each participating country. The MEL system is embedded within the LIFE-AR management structure at all levels, and makes use of both qualitative and quantitative indicators to assess progress.
The MEL approach deliberately moves away from traditional quantitative evaluation approaches and adopts qualitative methods. This includes self-assessments, peer reviews, score cards which generate rich, in-depth data, and insights critical to improving government systems and capabilities. It provides high-level guidance to stakeholders and participating countries for setting up tailored MEL systems, mapping climate adaptation and resilience stakeholders, and collating evidence of the initiative's effectiveness, impact, coherence, and sustainability. Through adaptive management, the MEL system fosters learning across countries, strengthens Communities of Practice, and ensures that evidence-based communication highlights the transformative impact of LIFE-AR.
The MEL plan is supported by detailed results frameworks that clearly indicate the cycle for data gathering, analysis, and learning and adjustment, with roles and responsibilities clearly defined.
