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Solving the Stakeholder Problem
We are building a resource that allows systems-dynamics models (and other model types) to interoperate in a federation fashion, allowing the ad hoc creation of “super-models” that can run simultaneously, as if the resulting supermodel was created as a single model. At the same time, we enable the reluctant stakeholders to have their confidential models and data interoperate with models and data from other stakeholders (with perhaps conflicting interests), allowing the joint resources to be applied to a common problem without exposing sensitive data or algorithms between stakeholders. The resource we are building will also allow different model types, for instance system dynamic models and agent-based models, to interact.
Understanding Squishiness
We are building resources to visualize the findings of these interacting models. Key to this is enabling the non-scientist decision-maker to understand the implication of the results of exercising the “super-models” (above), particularly the sensitivities of those models to various inaccuracies and unknowns. This new, implicit visualization is critical to decision-making, particularly for the non-scientist decision maker faced with difficult scientific results. Our metaphor allows the non-scientific decision-maker to rapidly assess the likelihood of getting from point a to point b, through a tactile understanding of the "squishiness" of the findings.
Closing on an Informed Consensus
We apply three-dimensional Bayesian analysis techniques to quickly identify where additional research is necessary before a non-scientist manager can make an informed decision. The goal is rapid decision analysis of complex and mission-critical issues.