Policy decisions are highly complex and increasingly technical. In light of this, there has been tremendous effort to formulate best practice guidelines for Decision Analysis, Regulatory Impact Assessment, Benefit Cost Analysis, and other technical policy analysis tools. Such guidelines are aimed at ensuring the results of analysis are valid even in the midst of complex issues. However, effective use of policy analytics requires not only strong methodological principles, but making clear the biases and assumptions of methods. It also requires providing a more thorough understanding of how policy analytic methods are used in decision making processes. In light of these needs, this panel focuses on four specific research questions. 1) How can the measures and metrics used in policy analytics be improved? (2) How can policy makers navigate the value-based assumptions inherent to policy analytic tools? (3) How have past analyses been factored into policy decisions? and (4) How do methodological differences change the resultant policy decisions? The first paper provides a critical evaluation of the Value of Statistical Life (VSL) based on the Fatality Analysis Reporting System. Through utilization of instrumental variables and difference and difference estimators to evaluate the VSL based on truck driver deaths, the paper demonstrates that unobserved time-invariant factors considerably bias cross-section VSL estimates. Thus, the first paper demonstrates that the econometric underpinnings of analysis require continual refinement. The second paper moves beyond any one methodology, and provides decision makers with a tools to parse the assumptions and values across a range of policy outcomes. The proliferation of diverse methods obscures the critical assumptions of specific methodologies, thus limiting the usefulness of analytics in decisions. By providing a framework for understanding assumptions in policy analytics, the paper demonstrates that the assumptions behind an analysis drive values. As an outcome, the paper provides a guide for decision makers attempting to apply a policy analytic method in their decision process. The third paper paper provides an evaluation of the role of policy analysis in shaping regulatory decisions regarding drunk driving. The paper provides a theoretical approach in its analysis of the role that analyses play across a wide range of policy makings regarding drunk driving. By utilizing congressional testimonies about analysis, the paper provides evidence as to why a divide often exists between policy analysis and policy applications. In the final paper Ryan Scott strives to quantify the connection between analysis formalization and procedural/decision outcomes. By analyzing rulemaking data from the Washington State Department of Ecology, the paper demonstrates how methodological differences in BCA have important impacts for duration of rulemaking processes and likely outcomes of the process. By bridging the gap from individual metrics to analytic tools, and then to the impact of such tools on the decision space, this panel strives to connect methods to outcomes in a manner that illustrates the importance of methods to policymaking. The conclusions of this panel engage theory regarding proper methodology, accurate valuation, and the interaction of politics and analysis, while providing useful conclusions for policy applicators.