The term multi-criteria analysis covers a wide range of techniques that share the aim of combining a range of positive and negative impacts into a single framework to allow easier comparison of scenarios. Essentially, it applies cost benefit thinking to cases where there is a need to present impacts that are a mixture of qualitative, quantitative and monetary data, and where there are varying degrees of certainty.
Key steps generally include
- identifying the objective
- identifying options to achieve the objective
- establishing criteria to be used to compare the options (these criteria must be measurable, at least in qualitative terms)
- assigning weights to each criterion to reflect its relative importance in the decision, using e.g. participatory techniques, ethical principles, technical grounds or an interactive procedure with the policy-makers
- scoring how well each option meets the criteria; the scoring needs to be relative to the baseline scenario
- ranking the options by combining their respective weights and scores
- perform sensitivity analysis on the scoring so as to test the robustness of the ranking.
As a first step, you should summarise the impacts of each option by area of impact (economic, social, environmental) and even by sub-impacts. In this summary, the impacts should not be aggregated; negative and positive impacts should be stated next to each other. In some cases, it may be possible to assess net impacts per area of impact and to provide an assessment of the overall net impact (positive impact minus negative impact) of each option. However, when this type of cumulative presentation of impacts is made, you should be careful not to give the impression that impacts are zero or low when, in fact, it is a case of significant positive and negative impacts of the same type having simply cancelled each other out.
Advantages of multi-criteria analysis:
- recognises multi-dimensionality of sustainability
- allows different types of data (monetary, quantitative, qualitative) to be compared and analysed in the same framework with varying degrees of certainty
- provides a transparent presentation of the key issues at stake and allows trade-offs to be outlined clearly; contrary to other approaches such as cost-benefit analysis, it does not allow implicit weighting
- enables distributional issues and trade- offs to be highlighted.
Disadvantages of multi-criteria analysis:
- includes elements of subjectivity, especially in the weighting stage where the analyst needs to assign relative importance to the criteria
- because of the mix of different types of data, cannot always show whether benefits outweigh costs
- time preferences may not always be reflected.