Crosscriteria

Crosscriteria is a concept used in decision analysis to describe the practice of evaluating options across multiple interacting criteria. It emphasizes examining how performance on one criterion relates to performance on others, and often involves constructing a cross-criteria matrix that catalogs scores or judgments for each option against each criterion. The approach supports a holistic view of alternatives rather than a single-criterion focus.

In multi-criteria decision analysis (MCDA), crosscriteria analysis is a central step: decision makers specify criteria, determine scales, normalize scores, and assign weights to reflect relative importance. The crosscriteria perspective focuses on performance profiles, enabling the identification of trade-offs and Pareto-efficient options. It helps reveal how improvements on one criterion may impact others and clarifies the overall suitability of each alternative.

Common methods within a crosscriteria framework include normalization and weighting, followed by aggregation to produce overall scores, such as weighted sums. Techniques like TOPSIS, PROMETHEE, or Analytic Hierarchy Process (AHP) may be used to derive rankings while preserving cross-criterion relationships. Sensitivity analysis is often conducted to assess how results change with different weights or scales.

Applications of crosscriteria approaches span supplier selection, product design, project prioritization, policy evaluation, and risk assessment. They are valued for transparency and the ability to reveal how changes in one criterion influence overall judgments. Limitations include dependence on the choice of criteria, scales, and weights, as well as potential distortions from correlated criteria and data quality issues.