Behavioral Challenges in Policy Analysis with Conflicting Objectives
Abstract
Public policy problems are rife with conflicting objectives: efficiency versus fairness, technical criteria versus political goals, costs versus multiple benefits. Multicriteria decision analysis provides robust methodologies to support policy makers in making tough choices and in designing better policy options when considering these conflicting objectives. However, important behavioral challenges exist in developing these models: the use of expert judgments, whenever evidence is not available; the elicitation of preferences and priorities from policy makers and communities; and the effective management of group decision processes. The extensive developments in behavioral decision research, social psychology, facilitated decision modeling, and incomplete preference models shed light on how decision analysts should address these issues so we can provide better decision support and develop high-quality decision models. In this tutorial, I discuss the main findings of this extensive but rather fragmented literature and provide a coherent and practical framework for managing behavioral issues, minimizing behavioral biases, and optimizing the quality of human judgments in policy analysis models with conflicting objectives. I illustrate these guidelines with policy analysis interventions that we have conducted over the last decade for several organizations, such as the World Health Organization, the Food and Agriculture Organization of the United Nations, the UK Department of Environment Food and Rural Affairs, the Malaria Consortium/USAID, and the UK National Audit Office, among others.
Video of this TutORial from the 2018 INFORMS Annual Meeting in Phoenix, Arizona, November 4, 2018, is available at https://youtu.be/1_DG9bSndfM.
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