Provide decision analysis consultancy in making complex decisions involving uncertainty and risk using both qualitative and quantitative models (e.g., Oracle’s Crystal Ball©, Palisade’s @Risk©, Syncopation Software’s DPL©) and other proprietary software to create Monte Carlo stochastic simulations and decision trees to analyze mutually-exclusive decisions within a stage-gated decision-making process. The process is customized to the level of complexity and risk.
Key elements of decision making process include the following:
More complex decisions require increased structure and processes to insure appropriate resources are engaged to resolve uncertainty and risk
As decisions increase in complexity, the level of effort to resolve uncertainty and risk also increases.
An effective decision making process should include an analysis of the six key elements of decision quality