Multi-Criteria analysis

Example

MCA in the Planer-Client Application

For a city-planner, when deciding which one of the planning alternatives is the best, the decision-making process is not a simple one. That is why (sometimes) only a single-criterion analysis result is not relevant enough. The decision-making process takes place in a multi-disciplinary and multi-participatory environment. For a given goal several solutions may exist that provide different level of satisfaction for different issues, such as hydrological / hydraulic, financial, social, ecological, economical etc.

Depending on the complexity of the whole decision problem, on all participants in the decision, the algorithm might change. Probably a final algorithm will be chosen during the project, after deciding this together with all the persons involved.

Assessment

The usefulness of MCA is most apparent when one option emerges as the dominant one in the matrix with respect to all the criteria. However, the methodology has several shortcomings:

  • How can one judge whether a good performance against one objective would compensate for poor performance against another?

This, again, is a question of trade-off which occupies a central place in decision-making having multi-dimensional aspects. Weighting or ranking becomes necessary to handle such cases.

  • But how does one determine weights?

This becomes the most critical question to which no satisfactory answer is available. Weights determined by experts cannot be regarded as free from subjective biases. Weights determined by the concerned public are may be done without full awareness of environmental attributes. Hence, the problems of weighting in MCA procedures are similar to the problems faced by a comprehensive CBA.

Notwithstanding the above shortcomings, MCA can be very useful for shortlisting options, which can then be subjected to the more rigorous CBA for a final decision. In this respect MCA is best understood as a complementary approach to CBA.


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Multi-Criteria analysis