Decision Consequence Analysis

The chapter explores an approach termed as Decision Consequence Analysis (DCA) that focuses on the consequences of a decision. The DCA process allows consequences to be assessed to improve the likelihood of achieving the desired outcome. This framework allows feedback and decision adjustment as decision makers move into implementation. The basic elements of DCA framework are reviewed here. These key elements include decisions regarding allocation of resources at different levels, triggers and objectives, end objective being the ultimate state of nature sought and means objective which is a step that mitigates the triggers. Performance metrics and decision models are a structured way of thinking on how to mitigate the triggers, alternatives, and uncertainties. The general process of the DCA that includes baseline physical constraints which is the compilation and evaluation of data, problems formulation, definition of elements e.g. objectives and alternatives, mapping the interaction of decisions and uncertainties which affects the options available for future decisions are summarized. The DCA process is applied in an iterative manner so the decision structure can remain intact as the situation evolves, information improves, uncertainties are resolved, and new ones arise.