Principal Investigator: Vicki Bier
Other Researchers: Jun Zhuang
The integration of risk information into the homeland-security decision-making process continues to be a major challenge. Homeland-security risks must be communicated to DHS leadership, the White House, Congress, and the public in a way that is easy to understand, transparent in its construction, and highlights all of the important features that may be relevant for decision-making. Managers need guidance on how to use risk information to inform strategic directions and budgeting processes, evaluate performance, and make resource-allocation decisions, but there is often not adequate data to support quantitative decision-making methods. In the absence of sufficiently accurate and/or precise data, the ability to communicate the sensitivity of residual-risk results to various analysis assumptions and alternative data sources is essential. Understanding the dynamics of residual risk under assumptions about trends, system interdependencies, and future uncertainties will allow decision makers to forecast residual-risk results for potential future environments when risk-reduction strategies will have been implemented. Therefore, we propose to develop a decision-support system to enable managers to: (1) visualize risks using state-of-the-art visualization techniques; (2) test the influence of key assumptions and the sensitivity of the results to alternative data sources; and (3) extrapolate risk results into future scenarios based on assumptions about trends, system interdependencies, and resolution of uncertainties. All of this needs to be done without requiring precise judgments of quantities that may be difficult to estimate, and using a simple graphical user interface.