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This article describes an application of a value-of-information (VOI) analysis to a problem involving information collection and sampling costs of millions of dollars and ultimate consequences of decisions ranging in the hundreds of millions of dollars. The context of this VOI analysis was the determination of the chemical and radiological composition of nuclear waste in 177 storage tanks at the Department of Energy's (DOE) Hanford Site in southeastern Washington State. These tanks include different types of waste and knowing their composition affects important decisions about how to treat these wastes for purposes of processing, stabilization, and ultimate storage. This analysis was conducted as part of a larger "proof-in-principle" study of how VOI concepts could be used to improve the collection of data for the purpose of identifying the composition of nuclear tank wastes and for subsequent decisions about tank-waste management. The analysis showed that a VOI analysis can be very useful and it can also provide specific guidance on the problem at hand. In particular, the analysis showed that it was worth while to collect additional information for only four of 15 tanks in question and eventually, the DOE decided to act on these tanks without the additional information. At the same time the DOE decided to focus on another set of tanks, which involved more imminent risks of flammable gas explosions and focused its effort on collecting information and stabilizing these tanks.

Over the past 20 years, several epidemiological studies have found an association between exposure to electromagnetic fields (EMFs) and health effects, including childhood leukemia and adult brain cancer. However, experts strongly disagree about whether this association is causal and, if so, how strong it is. In this article, we examine several alternatives to reduce EMFs from sources of the California power grid, including undergrounding distribution and transmission lines and reconfiguring or rephasing lines. The alternatives were evaluated in terms of the potential health risk reduction, cost, impacts on service reliability, property values, and many other consequences. Because of the uncertainty about an EMF‐health link, the main effort was to determine the sensitivity of the decisions to the probability and seriousness of an EMF hazard. User‐friendly computer models were developed to allow stakeholders to change the model assumptions and parameters to analyze the impacts of their own assumptions and estimates on the decision. The analysis clearly demonstrated that only four of the many concerns raised by the stakeholders could make a difference in the decision: health risks, costs, service reliability, and property values. Whether undergrounding, moderate alternatives for EMF reduction, or no change was the best decision depended on a few key factors, including the probability that EMF exposure is a hazard, the severity of this hazard, how the EMF reduction measures are financed, and the impacts on property values. While the analysis did not resolve the EMF issues, it showed that even in the most controversial settings, a little analysis goes a long way to clarifying the issues and to focus the debate.