EPA has substantially contributed to the advancement of analytic techniques and tools to detect environmental stressors and characterize health and ecosystem impacts of those stressors. While better characterization of problems is important, it is critical that the agency apply this knowledge to primary pre-vention—that is, the design of safer and more sustainable forms of production and consumption. Like sustainability, a focus on solutions should be more than a simple mission statement. It must be linked to adequate resources, tools, and infrastructure at the highest levels of the agency.
Multiple-Criteria and Multidimensional Decision-Making
The tools of alternatives assessment, HIA, and the sustainability management approach all incorporate an array of information to arrive at a preferred solution, but this becomes increasingly challenging given numerous dimensions that often cannot be compared on the same scale. Benefit—cost analysis is a well-known example in which the multiple outcomes of a decision are monetized (if possible) and aggregated into a single indicator of economic efficiency, but it cannot provide a complete ranking of alternatives if stakeholders and environmental decision-makers are interested in other objectives (such as fairness across income classes, regions, or racial groups; generations in the distribution of burdens and benefits; or norms in the treatment of nonhuman organisms). Benefit— cost analysis is useful and sometimes mandated for regulatory impact assessments, but its value is limited in dealing with complex issues in which economic efficiency is only one of many important objectives for environmental decision-makers and their stakeholders. While deliberative approaches may be warranted in complex situations, especially when both quantitative and qualitative information are being used, analytic approaches to integrate data from multiple sources and types into a single number or range of numbers have tremendous potential.
One approach to solving problems that have multiple incommensurate dimensions is to use tools within the realm of multiple-criteria decision-making (MCDM) (Figueira et al 2005). Within the broad framework of informatics, developing and applying MCDM in conjunction with uncertainty analysis and data-mining (Shi et al. 2002) can provide a set of useful ways for using emerging science and developing evidence-supported policy-making in the agency. Like benefit—cost analysis, MCDM is an approach that creates and assigns a preference index to rank policy options on the basis of the totality of all adopted criteria. However, unlike benefit—cost analysis, MCDM was not designed to rank options based on a consumer’s preference for environmental or other goods. Instead, the method is flexible for selecting weights and it is often designed to use weights assigned by the decision-maker. This flexibility allows for the inclusion of a broader set of objectives, although the selection can be inherently contentious. The preference index value attributable to each criterion reflects the nature and importance of the criterion, for example, cost, benefits,