Key Messages 
  • Qualitative metrics are particularly useful when data gaps exist which is very often the case for climate adaptation. 
  • The use of non-monetary metrics through Multi-criteria analysis (MCA) in adaptation is most useful where a large range of dimensions need to be considered that cannot be easily represented through costs, benefits or effectiveness criteria.
  • In Multi-criteria analyses certain general criteria are applicable: e.g. effectiveness, costs, co-benefits, synergies/conflicts. Further criteria should be added for analysis of adaptation options. Especially criteria focused on uncertainties due to climate change (e.g. the robustness and flexibility of options), the long-term scope of climate change, the urgency for implementing of the options, and synergies or conflicts of climate mitigation and adaptation measures.


The most commonly used economic assessment is the Cost-benefit analysis (CBA), which is based on the monetary valuation of all relevant (financial and economic) costs and benefits to government and society of all available options under consideration. CBA works best if parameters are clearly determined which is problematic in the context of climate change adaptation where high uncertainties exist. Applying CBA to climate change scenarios may rely on many assumptions and is further compounded by the fact that monetary information relevant for decision making is often difficult to apply to the environment (e.g. biodiversity loss) and social (e.g. health damage) impacts.

In this context, other types of methods can be used to better consider non-monetary metrics. These are Cost-effectiveness analysis (CEA) and Multi-criteria analysis (MCA), which belong are decision making tools seeking to achieve some degree of rationalisation to inform policy decisions. MCA systematically assesses and scores options against a range of decision criteria resulting in an overall ranking of options. As opposed to CBA and CEA, decision criteria can be expressed in quantitative or qualitative terms in either physical or monetary units. Each criterion is weighted to provide an overall ranking of options. In this factsheet we provide information on decision criteria for adaptation options that can be used for adaptation policy and decision-making.

Policy and methodological developments 

​MCA decision criteria are useful when essential data gaps exist as it is easy to use qualitative metrics. The metrics included in MCAs are relative to each other and can only be used within the scope of the MCAs when comparing options. Together with the qualitative and subjective nature of the measurement, MCA is often not seen as a stand-alone methodology. As such, the assessment of non-monetary metrics within an MCA framework is often seen as a preliminary, scoping step in the selection of adaptation. More detailed analysis, through CBAs, CEAs, or specific (qualitative or quantitative) assessments focusing on single indicators may also be necessary.

For each measure a score (e.g. number of points) against each criteria and an overall score for each measure as summary of all criteria is estimated.

For MCA some important standard decision criteria exist, which are applicable independently from the focus of the analyses, such as effectiveness, costs, co-benefits, feasibility, acceptance (see table 1 below). As adaptation brings up further challenges especially concerning uncertainties, coordination with climate mitigation activities, long-time horizon of impacts which favor e.g. flexible and robust measures further decision criteria should be integrated in the analyses. Additional adaptation related criteria would be e.g. urgency of implementing options, synergies with climate mitigation and robustness, flexibility or no-regret potential of options.

MCA metrics can easily be used during a participative assessment process that allows expert and lay knowledge to be considered. However, this strength can also be a weakness as the qualification or quantification of the criteria is highly dependent on the quality of involved experts or stakeholders. The selection and involvement of stakeholders is crucial as well as attention to explain evaluation criteria and how different weighting affects outcomes. Simple indicators and scoring system are essential.

To consider uncertainties into the analysis sensitivity analysis are suggested to use considering the impact of different levels of risks and impacts when sufficient data is available

Examples of decision criteria for MCAs in climate adaptation

In the following table, we summarized decision criteria for MCA of adaptation options and policy instruments based on a literature review.

Table 1: Decision criteria used in adaptation-related MCAs



Standard criteria in MCA


Expected capacity for achieving target, with the aim of maximising effectiveness


Costs involved in design and implementation, with the aim of minimising public and private spending


Benefits additional to those targeted or primarily sought for, with the aim of maximising co-benefits. This often refers to the protection of environmental resources and biodiversity, but can encompass other types of co-benefits such as on health, cultural heritage, etc.


Time to achieve full effectiveness, with the aim of minimising it

Implementation ease

Suitability of existing regulatory and institutional framework to facilitate implementation

Policy integration (synergies/conflicts)

Institutional coherence between measures and existing policy targets and incentives, with the aim of maximising use of the existing framework and contributing to multiple policies


Availability of data, knowledge and technical capacity to design and implement measures


Level of social and political support and acceptability

Public participation

Level of engagement with non-expert actors and the broader society, and level of integration of local/traditional knowledge with scientific knowledge

Private investment

Capacity to trigger investments from the private sector

Improve economic performance

Capacity to foster competitiveness and increase economic output


Capacity to create jobs

Spillover effects

Distribution of positive and negative impacts to other economic sectors

Distributional impacts

Distribution of positive and negative impacts to different actor group, including specific attention to vulnerable groups. This may include attention to impacts on poverty levels and inequality.

Fiscal sustainability

Capacity to contribute to fiscal sustainability through impacts on government revenues and expenditures

Additional criteria used in adaptation


Non-climate benefits exceed costs of implementation so that benefits are secured under all potential futures


Need of implementing options immediately or possibility to defer implementation at later point in time

Climate mitigation potential

Capacity to induce a reduction in greenhouse gas emissions

Extreme events

Capacity to deal with extreme climatic events such as heat waves, high wind speed, floods, and droughts


Capacity to maintain effectiveness under different climatic and socio-economic development scenarios


Capacity of an option to be adjusted,  complemented or reversed when it appears to be inappropriate at a future point in time (e.g. due to changing climatic or socio-economic conditions)

Level of autonomy

Capacity to self-govern the design and implementation of the adaptation activities

Main implications and recommendations 

MCA establishes preferences between options by reference to an explicit set of objectives for which it has established criteria to assess the extent to which the objectives are achieved. In contrast to CBA or CEA where measures are assessed against a single criterion, MCA can combine multiple quantitative and qualitative data using monetary and non-monetary units. Costs and benefits thus become only one potential criterion amongst many others. With a wide set of criteria analyses can be done, even where quantification is challenging or limited.

The UNFCCC suggests that the use of non-monetary metrics through MCA in adaptation is most useful where a large range of dimensions need to be considered that cannot be easily represented through costs, benefits or effectiveness criteria. In particular, it is able to deliver a general ranking of options when multiple criteria with multiple different metrics are relevant to assess a set of measures.