Tactical Robust Decision-Making Methodology: Effect of Disease Spread Model Fidelity on Option Awareness

We demonstrate a method of validating the utility of simpler, more agile models for supporting tactical robust decision making. The key is a focus on the decision space rather than the situation space in decision making under deep uncertainty. Whereas the situation space is characterized by facts about the operational environment, the decision space is characterized by a comparison of the options for action. To visualize the range of options available, we can use computer models to generate the distribution of plausible consequences for each decision option. If we can avoid needless detail in these models, we can save computational time and enable more tactical decision-making, which will in turn contribute to more efficient Information Technology systems. We show how simpler low fidelity, low precision models can be proved to be sufficient to support the decision maker. This is a pioneering application of exploratory modeling to address the human-computer integration requirements of tactical robust decision making.