Defense planning faces significant uncertainties. This report applies robust decision making (RDM) to the air-delivered munitions mix challenge. RDM is quantitative, decision support methodology designed to inform decisions under conditions of deep uncertainty and complexity. This proof-of-concept demonstration suggests that RDM could help defense planners make plans more robust to a wide range of hard-to-predict futures.

Strategy and Defence Planning: Meeting the Challenge of Uncertainty explores and examines why and how security communities prepare purposefully for their future defence. Professor Gray argues that our understanding of human nature, of politics, and of strategic history, does allow us to make prudent choices in defence planning.

It is still easy to underestimate how much the collapse of the Soviet Union and the end of the Cold War?--and then the terrorist attacks of September 11, 2001?--transformed the task of American foreign and defense policymaking. In place of predictability (if a sometimes terrifying predictability), the world is now very unpredictable. In place of a single overriding threat and benchmark by which all else could be measured, a number of possible threats have arisen, not all of them states. In place of force-on-force engagements, U.S. defense planners have to assume "asymmetric" threats?--ways not to defeat U.S. power but to render it irrelevant. This book frames the challenges for defense policy that the transformed world engenders, and it sketches new tools for dealing with those challenges?--from new techniques in modeling and gaming, to planning based on capabilities rather than threats, to personnel planning and making use of "best practices" from the private sector.

Current defense planning methods do not ensure a direct connection between national security objectives and military tasks. The Strategy-to-Task method provides a framework for solving this deficiency by establishing a hierarchy, starting from national objectives, through military objectives and missions to military tasks. Below these tasks, performance standards can be used for estimating the utility of a given task. This hierarchical approach helps decision-makers understand these important linkages. It could also serve as a framework for prioritizing the different tasks and contribute to better resource allocation, by analyzing different alternatives in a multi-attribute space. There are two decision-supporting methods for setting up priorities within this hierarchy of multi-attribute objectives. The first one, Multi-Attribute Utility Function Analysis, is a useful method for cases when performance standards can easily be established. This method could be used under both certainty and uncertainty and can address dependence and independence among the attributes or their utilities. The second method, the Analytic Hierarchy Process, could be used in cases when performance standards are difficult to establish as is typically the case in the higher levels of the hierarchy. The hierarchical approach and the two methods are illustrated through the case of Hungary's participation in NATO peace-operations.

This definitive study on defense planning in the new era covers alternative strategies and structures for post-Cold War defense planning and planning under uncertainty.

Superior defense plans fuse political, economic, military, technological, and sociological power in ways that cover state interests, while conserving resources to the greatest prudent extent. Poor products can increase costs without reducing risks, because forces and funds that support slipshod schemes often fail to furnish security. This critical appraisal of the U.5. defense planning system seeks to serve a five-fold purpose: set assessment standards, appraise U.S. planning in principle, appraise U.5. planning in practice, identify U.S. planning problems and present optional courses of corrective action. The study shows how domestic and foreign policy inputs from the White House, National 5ecurity Council, and State Department affect defense planning.