The complex nature of ecosystem recovery in Puget Sound means that scientists and policymakers are often faced with tough decisions. Given finite resources and widespread need, where should they best focus their efforts?

Beginning this summer, Dr. Bill Labiosa will serve as a visiting scholar at the Puget Sound Institute to help develop decision science planning tools. Labiosa is currently a research scientist with the USGS Western Geographic Science Center and has a background in environmental engineering and decision analysis. He is also Vice Chair of the Puget Sound Partnership Science Panel.

As part of a 15-month inter-agency agreement with USGS and the Puget Sound Partnership, Labiosa will work with a PSI post-doctoral fellow to assist the Partnership with the development of its adaptive management framework, and to increase the Partnership’s capacity for using decision science tools.

Decision support is a hybrid field that cuts across many disciplines including probabilistic decision analysis, systems analysis, economics, game theory and even artificial intelligence to examine how people make judgments and decisions, as well as how they should make well-supported decisions. Although decision analytical approaches can be heavily reliant on quantitative models, Labiosa says they are not just about reducing highly complex decisions to more understandable models, or even quantifying the “right” answers. He says the most useful outcomes from decision support document and re-visit assumptions about how decisions are framed, examining “potentially-conflicting objectives and sources of uncertainty within the decision situation.”

According to Labiosa, a key part of the process is helping decision makers define what it is they actually want: “Framing the decision sounds simple, but it’s not. It’s the most important part.” Decision support, he says, “helps ensure that you don’t miss important stuff.”

It turns out that people are already plenty decisive—that’s not the issue. “People are really good at coming to quick decisions,” Labiosa explains. The problem is that people often make decisions heuristically, based on their own experiences and rules of thumb, while ignoring important information and missing important connections.

The systematic side of decision support comes from framing decisions in terms of what is most important, what people want to achieve, what might go wrong, and what success would look like. In the language of decision analysis, this means identifying good alternatives, defining preferences and objectives, and characterizing what might happen (uncertainty and information) precisely enough to evaluate decisions and to determine what additional information is needed. “You need to do the heavy thinking at the front end to avoid the heavy rationalizations at the back end,” says Labiosa.

Labiosa hopes to begin work at the Partnership in collaboration with the PSI as soon as this July with a plan to continue through the end of Fiscal Year 2013.