Systems‐Based Guiding Principles for Risk Modeling, Planning, Assessment, Management, and Communication
Abstract:This article is grounded on the premise that the complex process of risk assessment, management, and communication, when applied to systems of systems, should be guided by universal systems‐based principles. It is written from the perspective of systems engineering with the hope and expectation that the principles introduced here will be supplemented and complemented by principles from the perspectives of other disciplines. Indeed, there is no claim that the following 10 guiding principles constitute a complete set; rather, the intent is to initiate a discussion on this important subject that will incrementally lead us to a more complete set of guiding principles. The 10 principles are as follows: First Principle: Holism is the common denominator that bridges risk analysis and systems engineering. Second Principle: The process of risk modeling, assessment, management, and communication must be systemic and integrated. Third Principle: Models and state variables are central to quantitative risk analysis. Fourth Principle: Multiple models are required to represent the essence of the multiple perspectives of complex systems of systems. Fifth Principle: Meta‐modeling and subsystems integration must be derived from the intrinsic states of the system of systems. Sixth Principle: Multiple conflicting and competing objectives are inherent in risk management. Seventh Principle: Risk analysis must account for epistemic and aleatory uncertainties. Eighth Principle: Risk analysis must account for risks of low probability with extreme consequences. Ninth Principle: The time frame is central to quantitative risk analysis. Tenth Principle: Risk analysis must be holistic, adaptive, incremental, and sustainable, and it must be supported with appropriate data collection, metrics with which to measure efficacious progress, and criteria on the basis of which to act. The relevance and efficacy of each guiding principle is demonstrated by applying it to the U.S. Federal Aviation Administration complex Next Generation (NextGen) system of systems.
Document Type: Research Article
Publication date: September 1, 2012