Technical Policy Briefing Notes - 3
Robust Decision Making
The Application to Adaptation
Policy Briefs
Robust Decision Making
The Application to Adaptation
RDM has many attributes that align with the
concept of adaptive management (Lempert and Groves, 2010) and the
approach has been widely recommended for adaptation. The MEDIATION
project has reviewed this potential application.
RDM seeks strategies (or policies or options) that are robust (‘good enough’). It therefore offers an alternative to a conventional cost-benefit analysis, which identifies optimal options on the basis of economic efficiency (in the case of climate change adaptation, using impact assessment in a predict-then-optimise framework).
It provides an alternative tool for decision-support which incorporates uncertainty explicitly, minimising regret (in contrast to maximising expected utility), and can play a role in translating the theoretical concepts of adaptive management into quantitative actions, by selecting options that are robust across a widerange of plausible (climate) futures. This is particularly valuable in cases where the climate model projections are highly uncertain, as is the case for precipitation changes (see briefing note 1).
The formal application of the approach can also be used to consider wider uncertainty (e.g. in relation to socio-economic future, impact uncertainty) and thus is a potential powerful tool for full uncertainty analysis. The formal approach can also be used with interim performance (measurement) review or evaluation, which aligns it more closely to the iterative adaptation management concepts of monitoring, research, evaluation and learning. The informal application for adaptation focuses on analysing climate uncertainty only, i.e. surrounding climate model projections or climate information.
RDM seeks strategies (or policies or options) that are robust (‘good enough’). It therefore offers an alternative to a conventional cost-benefit analysis, which identifies optimal options on the basis of economic efficiency (in the case of climate change adaptation, using impact assessment in a predict-then-optimise framework).
It provides an alternative tool for decision-support which incorporates uncertainty explicitly, minimising regret (in contrast to maximising expected utility), and can play a role in translating the theoretical concepts of adaptive management into quantitative actions, by selecting options that are robust across a widerange of plausible (climate) futures. This is particularly valuable in cases where the climate model projections are highly uncertain, as is the case for precipitation changes (see briefing note 1).
The formal application of the approach can also be used to consider wider uncertainty (e.g. in relation to socio-economic future, impact uncertainty) and thus is a potential powerful tool for full uncertainty analysis. The formal approach can also be used with interim performance (measurement) review or evaluation, which aligns it more closely to the iterative adaptation management concepts of monitoring, research, evaluation and learning. The informal application for adaptation focuses on analysing climate uncertainty only, i.e. surrounding climate model projections or climate information.
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