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When people use information to make decisions, we can determine the value of that information by characterizing differences in socioeconomically meaningful outcomes across two worlds: one in which the improved information is available to decisionmakers and one in which the improved information is not available. This idea forms the foundation of the VALUABLES impact assessment framework we learned about in the previous, 100-level Value of Science explainer series. In some cases, these differences in outcomes can be described in nonmonetary terms. When recreational managers used satellite data to inform advisories and closures at Utah Lake as a harmful algal bloom (HAB) impacted the water in 2017, for example, we noted that no people were exposed to this potentially toxic bloom. If managers had not used the satellite data, an estimated 400 people would have gotten sick. Here, the value of the HAB information is expressed as 400 averted illnesses.

In many cases, we also can describe differences in outcomes in monetary terms, a topic we will discuss in more detail in this explainer. In the HAB example, the researchers were able to restate the social benefits associated with the 400 averted illnesses by calculating the health-care costs associated with treating the illnesses. They found that these avoided health-care costs were worth approximately $370,000. Thus, the $370,000 figure represents a monetized estimate of the value of the satellite data that were used to manage the 2017 HAB in Utah Lake.

This type of economic analysis is called cost of illness, and economists have developed many other tools to monetize the value of information. Expressing value in monetary terms can be particularly helpful for an apples-to-apples comparison of the benefits of scientific information and the cost of producing it, which often is already expressed in monetary terms. Monetization also can help us prioritize across scientific projects that have very different kinds of societal benefits. For example, the benefits of a satellite-based decision support tool that improves human health outcomes, and the benefits of a tool that helps reduce deforestation, would be very difficult to compare directly. Monetizing the value of the outcomes in these two applications—the human health improvements and the avoided deforestation—can help us determine which application is more socially beneficial.

Monetizing benefits is a complex and well-studied topic. Although it is beyond the scope of this explainer to provide a full treatment of monetization, we provide a brief summary of methods used to monetize impacts. We also list some benefit categories that are commonly associated with improvements in satellite information, some examples of monetized estimates within those categories, and links to references for further reading.