MATE is a scalable analytic framework for multi-criteria decision making in complex, dynamic, and uncertain environments. It is built upon 17+ years of research at MIT, and is 70% funded by the DoD.
The value-driven framework includes data-supported exploration and analysis of relationships between various cost and benefit metrics and solution characteristics across potential alternatives.
A MATE analysis includes defining the problem or decision space, generating the alternatives and tradespace, and exploring the tradespace through extensive visualization techniques.
MATE is relevant to problems in which decision complexity exceeds human ability to easily identify and weigh potential solutions and has been applied to a broad range of analyses in numerous domains, including energy, defense, transportation, and consumer goods.