The Right Call: How Emergency Managers Make Storm Response Decisions Under Conditions of Uncertainty

We interviewed ten (10) emergency management practitioners in the state of Rhode Island, U.S.A., asking them to tell us how they make local storm response decisions and what data and tools would help them reduce uncertainty in their decision-making process. This study is part of a larger implementation research work to facilitate uptake of the Coastal Hazards Analysis, Modeling, and Prediction (CHAMP) system and other decision support tools to improve storm outcomes.m In the days leading to a hurricane, tropical storm, or nor’easter’s landfall, emergency managers (EMs) make critical response decisions meant to protect lives and property and minimize avoidable consequences. Often these choices are made under stressful conditions with decision making constrained by insufficient time, incomplete information, cognitive constraints, and organizational limits. Shifting storm characteristics, expanding coastal populations, growing dependence on vulnerable critical infrastructure, and rising recovery costs are increasing the risks hurricanes and tropical storms pose for coastal communities while making it more difficult for emergency managers to access data they need to make good choices about storm response. Uncertainty is a given in EMs’ storm response decision process, often requiring the local EM to lean on instinct and experience when empirical data is lacking. But making choices under such conditions can encourage cognitive shortcuts, ad hoc judgments, and biased decision making that lead to suboptimal choices. To develop better decision support tools, researchers need a deeper understanding of the choices EMs make when responding to storms under conditions of uncertainty. We present findings from ten (10) interviews with emergency management practitioners in the State of Rhode Island, U.S.A., designed to learn more about EM’s storm-related decisions. Our results identify pre-landfall response choices EMs make at the local level and explore the data gaps EMs encounter when making such decisions. We apply Simon’s theory of bounded rationality to examine emergency managers’ storm-related decision in high-stakes, time-constrained, uncertain environments, and validate prior studies showing that EMs often rely on bounded rationality to balance a lack of information and time when making such decisions. Lastly, we explore how simulation-based decision support tools can help EMs overcome these barriers to improve storm outcomes.