Early VfM adaptation toolkit: Delivering value-for-money adaptation with iterative frameworks & low-regret options
This 2014 DFID toolkit by Watkiss, Hunt and Savage guides advisers in designing value-for-money climate adaptation programmes. Using iterative frameworks, it sequences no- and low-regret options across six steps: risk identification, theory of change, option selection, prioritisation, programme design and economic appraisal, with Ethiopian case studies.
Please login or join for free to read more.
OVERVIEW
Introduction
The 2014 toolkit by Watkiss, Hunt and Savage supports DFID advisers designing adaptation programmes that deliver value for money (VfM). It applies iterative climate risk management, as recommended by the IPCC’s Fifth Assessment Report, across six steps. Steps 1–5 support strategic cases; Step 6 supports economists.
Adaptation cycle
Adaptation assessment has shifted from long-term impact studies to implementation over the next five to ten years. The starting point is the current “adaptation deficit”: the cost of climate variability and extremes. Nepal’s flood damages average 1.5% of GDP annually, Kenya’s variability costs reach about 2%, and Samoa’s largest cyclone losses exceed 30%. Addressing the deficit yields immediate benefits and builds future resilience.
Step 1: Identifying risk, vulnerability and impacts
Iterative frameworks need information on current variability, policy context and future climate. The toolkit advises pooling existing vulnerability studies and lists data sources such as EM-DAT and World Bank climate portals. In Ethiopia, current variability cost about US$500 million (2.5% of GDP) annually, while rainfall projections varied by ±30% over 30–40 years.
Step 2: Theory of change (The problem)
Early adaptation is rarely implemented because benefits arise mainly after mid-century, so conventional discounting seldom justifies action, and uncertainty favours inaction. The toolkit recommends a portfolio: address the current deficit, mainstream climate into long-lived decisions, and prepare for long-term change. Focusing only on the deficit risks maladaptation, although some residual risk is economically optimal.
Step 3: Identify and sequence adaptation options
A typology of no- and low-regret options covers: current variability and capacity building; building resilience to the future through robustness, flexibility and information; and early action on future challenges. Reviews report benefit:cost ratios of 5:1 for floods and 4:1 for windstorms. Advisers should check baselines: in Ethiopia, about 63% of the agriculture ministry budget (2007–2013) was planned for resilience activities, and 38 of 41 priority options already appeared in existing plans.
Step 4: Initial prioritisation of early adaptation options
Prioritisation is risk-based. Promising options include meteorological services and early warning systems (benefit:cost ratios of 2–40:1), climate-smart agriculture, ecosystem-based adaptation, building codes (7:1 in Guyana) and set-back zones. In Zanzibar, where about 25% of land and over 45% of people are in the low coastal zone, long option lists stalled progress, so a matrix mapped options against priorities. Ethiopia’s agriculture strategy shortlisted 41 options.
Step 5: Theory of change (Part 2)
Shortlisted options are mapped against programme priorities, then converted into inputs, outputs, outcomes and impacts to build the logical framework and monitoring design.
Step 6: Appraisal of adaptation
Appraisal should address market failures, including information gaps, public goods and high private discount rates. Uncertainty limits cost-benefit analysis; alternatives include cost-effectiveness, multi-criteria analysis, real options and robust decision making. VfM is assessed through economy, efficiency and effectiveness, using unit-cost benchmarks and output indicators.