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Defense Planning for the Post-Cold War Era
Paul K. DavisLou Finch
其他書名
Giving Meaning to Flexibility, Adaptiveness, and Robustness of Capability
出版Rand, 1993
主題History / Military / United StatesPolitical Science / American Government / GeneralPolitical Science / Public Policy / Military PolicyTechnology & Engineering / Military Science
ISBN08330144209780833014429
URLhttp://books.google.com.hk/books?id=q-cTAQAAMAAJ&hl=&source=gbs_api
註釋This study describes a new approach to defense planning that would better integrate strategic, programmatic, and operations planning. Its thesis is that planning should focus on assuring that the U.S. has the capability to react quickly and effectively to a wide range of contingencies that do not match closely with any of the standard scenarios. There should be much less emphasis on standard scenarios and finely tuned, highly coordinated operations planning, than on having the capability in crisis to quickly develop and execute plans appropriate to the political-military needs of that crisis. This can be done now for small-scale crises, but it is clear from the Gulf War that the U.S. was in no way capable of doing so in the kind of large-scale conflict that would have occurred if Saddam Hussein had continued his invasion into Saudi Arabia. The study recommends major changes that would de-emphasize the "deliberate planning system," elevate the importance of "crisis-action planning," and use frequent, rigorous exercises to test and refine the ability to develop and execute in the development and creation of appropriate plans in crisis. The approach would depend on building-block methods that are quite comfortable to many American military officers, and which, indeed, can already be seen at work at lower levels of organization. The approach would require drastic changes in computer support. The study also recommends that strategic and programmatic planning be changed in ways that would be more consistent with planning under uncertainty and encouraging flexibility and adaptiveness rather than optimization for well-defined scenarios. With this in mind, the study recommends new methods of analysis that are will suited to planning under uncertainty.