Abstract
Corporate decision makers in the public and private sectors must allocate scarce resources to acquire knowledge relevant to their plans and future investments. Such knowledge includes the variety of emergent sources of risks and opportunities. This thesis tests an existing method that combines scenario analysis with multi-criteria analysis for priority-setting, with an emphasis on identifying whether particular scenarios matter irrespective of their likelihoods, and whether sufficient relevant scenarios have been considered. The goal of this thesis is to generate practical results and lessons learned from the testing of this method in two case studies: (i) disaster planning in Rio de Janeiro, Brazil, and (ii) formation of a biojet fuel industry for the Commonwealth of Virginia. Scenarios of concern for the disaster case study include flooding, landslide, drought, radiological emergency, population behaviors, and terrorist attack related to the upcoming World Cup and 2016 Summer Olympics. Scenarios of concern for the fuels case study include markets, competitors, regulations, long-term availability of crude oil feedstock, and environmental change. The results in each case study include definitions of initiatives and performance criteria, generation of emergent conditions, assembly of up to five scenarios from the emergent conditions, and knowledge of which scenarios most matter to priority-setting. The results suggest to decision makers where to improve robustness of planning initiatives, what are the influences for priority-setting of combining diverse emergent and future conditions, and where additional information on scenarios would be most beneficial.
