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Robust Decision Making

This Policy Brief (Note 3) provides a summary of robust decision making, including a synthesis of the approach, its strengths and weaknesses, how it considers uncertainty, and case study examples.
Multiple Authors

There is increasing policy interest in the appraisal of options, as adaptation moves from theory to practice. At the same time, it is recognised that the appraisal of climate change adaptation involves a number of major challenges, particularly the consideration of uncertainty. In response, a number of existing and new decision support tools are being considered for adaptation.

This Policy Brief (Note 3) provides a summary of robust decision making. It provides a brief synthesis of the approach, its strengths and weaknesses, the relevance for adaptation, how it considers uncertainty, and presents case study examples. It is stressed that this note only provides an overview: more detailed information is available in MEDIATION deliverables, and sources and links on the MEDIATION Adaptation Platform.

Key Messages

  • There is increasing interest in the appraisal of options, as adaptation moves from theory to practice. In response, a number of existing and new decision support tools are being considered, including methods that address uncertainty.
  • The FP7 MEDIATION project has undertaken a detailed review of these tools, and has tested them in a series of case studies. It has assessed their applicability for adaptation and analysed how they consider uncertainty. The findings have been used to provide • information and guidance for the MEDIATION Adaptation Platform and are summarised in a set of policy briefing notes.

  • One of the tools widely recommended for adaptation is Robust Decision Making (RDM). RDM aims to identify robust options • or strategies, i.e. those which perform well over a wide range of futures. It aims to support decision making under conditions of deep uncertainty, i.e. when little or no probabilistic information is available.

  • RDM has been widely applied as analytic, scenario-based approach for decision support. The formal application is undertaken in a computer modelling interface that adopts data sampling algorithms to analyse strategies over very large ensembles. However, the concepts of the approach can also be used in a simpler application, which tests how options or strategies perform against climate uncertainty.

  • RDM has high relevance for adaptation, and aligns strongly with the concepts of adaptive management, by targeting policies or options that are robust rather than optimal.

  • The review has considered the strengths and weakness of the approach for adaptation. The key strength is the quantitative analysis of robustness, and the fact that the method can be applied when future uncertainties are poorly characterised or probabilistic information is limited or unavailable. The approach can also work with quantitative or economic data.

  • The potential weaknesses of the formal application relate to the high data and resource needs (for quantitative information, computing power, stakeholder engagement and analysis) and the associated expert input required. The data and scenario inputs can also be somewhat subjective, influenced by stakeholders’ perception. However, many of these aspects can be overcome with informal applications of the approach, particularly when focused on climate uncertainty alone.

  • Previous applications of ROA for adaptation have been reviewed, and adaptation case studies are summarised. Most of the recent adaptation applications have focused on water management, and these include both formal and informal examples.

  • The review and case studies provide useful information on the types of adaptation problem types where RDM might be appropriate, as well as data needs, resource requirements and good practice lessons. RDM is particularly applicable under situations of high uncertainty, where probabilistic information is low or missing. The approach can use physical or economic information, thus it has broad applicability from detailed economic appraisal through to the consideration of non-market sectors where valuation may be challenging. It has high potential for identifying low and no regret options, and near-term adaptation strategies that enhance long-term resilience.

  • Ideally the approach should be used to consider multiple sources of uncertainty, but this increases the resources needed. The application to climate change uncertainty alone therefore provides a ‘lighter touch’ approach to test options for climate robustness. In such applications, the larger the climate uncertainties explored, the better. Where resource constraints are high, such exercises can prove valuable for helping to identify robust solutions and move towards adaptive management.

Suggested Citation

Watkiss, P. and Dynzynski, J (2013). Robust Decision Making: Decision Support Methods for Adaptation, MEDIATION Project, Briefing Note 3.

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 244012.

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