MCDAdriven

MCDAdriven is a decision-support framework that integrates multi-criteria decision analysis (MCDA) methods into organizational decision processes. It emphasizes transparent criteria selection, stakeholder involvement, and structured modeling to guide choices that involve trade-offs among conflicting objectives.

The framework draws on MCDA techniques such as the analytic hierarchy process, weighted sum models, and outranking methods, while promoting a modular approach that can be tailored to policy, engineering, or business contexts. Core components include problem framing, criteria definition, data collection, model construction, and result interpretation, with an emphasis on reproducibility and auditability through explicit documentation of assumptions and data sources.

Workflow typically follows these stages: define the decision problem and scope; select criteria and alternatives; gather and normalize data; apply a decision model; conduct sensitivity and scenario analyses; derive recommendations; and implement with monitoring and learning loops. Governance and risk considerations are integrated throughout the process.

Applications span government policy, healthcare, transportation planning, environmental management, product portfolio optimization, and supply chain design. Benefits include structured decision making, improved transparency, and better handling of trade-offs. Limitations involve dependence on subjective criteria weights, data quality, model choice, and the potential complexity of implementation. Adoption is supported by a range of software tools and open standards.

History and reception: MCDAdriven emerged in the early 2020s as organizations sought transparent decision processes that combine quantitative analysis with stakeholder input. It is discussed in professional and academic contexts as a framework for governance and decision support, rather than a single tool.