What is it about?
The article offers a methodological framework for systematic and rigorous capability analysis under uncertainty while applying basic principles of capability based planning. More specifically, it focuses on determination of capability requirements against multiple generic and specific set of force development scenarios, identification of capability mismatches, operational risk assessment steaming from capability gaps and capability prioritisation techniques and procedures. Methodological framework for capability analysis is one of the outputs of the Centre for Security and Military Strategic Studies of University of Defence in Brno institutional research project “STRATAL” – Strategic Alternatives for the Development of the Czech Armed Forces. The authors offer an innovative methodology for further discussion and best practices for development of sound defence planning process and its analytical support. Successful application of this framework depends on the quality of professional military judgement and proper use of relevant analytical techniques and procedures. In addition to that, the framework interlinks efforts in several functions of overarching defence management system, and that constitutes certain risks for generating expected outcomes e.g. insufficient coordination and harmonisation of effort, unclear responsibility for final outcomes just to name a few.
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Why is it important?
The discussed Capability Analysis Framework offers the opportunity to combine scientific rigour with sound military judgement when making strategic decisions. Identifying the right set of capabilities helps creating synergies and thus achieving better defence with less capabilities when resources are getting scarce. Capability Analysis Framework establishes context and choice for senior leadership as they consider long-term strategic decisions related to future force development.
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This page is a summary of: Methodological Framework for Capability Analysis, International conference KNOWLEDGE-BASED ORGANIZATION, January 2017, De Gruyter,
DOI: 10.1515/kbo-2017-0157.
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