A Value-Centric Approach for Quantitative Risk Management

Risk management in the aerospace industry typically derives from a multi-step framework called Continuous Risk Management (CRM). In this process, identified risks are analyzed for their potential impact to the program. A plan for mitigating the impact of the risk is formulated, and developments related to the risk are tracked over time. While risk assessment methods vary, the most common is a qualitative, subjective assessment of the likelihood of the risk occurring and the severity of the resulting consequence. While useful for ranking risks, these likelihood and impact assessments typically lack quantitative rigor. Furthermore, disagreements often occur regarding likelihood and consequence assessments when a given risk has a continuum of likelihood and probability. For example, a given risk might have a high probability of a low consequence impact while also having a low probability of a high consequence impact. These types of risks are poorly handled by the subjective risk assessment process, but could be modeled quite well using probability distributions. Similarly, disagreements can also occur when considering the potential impacts to cost, schedule and/or technical performance. By employing a system value model, the relative importance of these impacts can be translated into a more intuitive and revealing form. In order to more accurately assess these risks, Orbital has developed a quantitative value-centric risk scenario modeling approach for potential use on future programs. Rather than replacing the traditional risk management process, this new approach has been integrated with an existing risk management system. The authors have designed and implemented a novel procedure for assessing the value-impact of top risks. Assessment of each risk involves the efforts of at least three members of the engineering team: the risk owner, to provide the information necessary to model the risk scenario; the risk manager, to elicit the necessary information; and the risk modeler, to create the appropriate scenario models to evaluate the potential impact on the overall system value. Rather than replace the traditional process, this approach translates the potentially-subjective cost, schedule, and technical performance impacts into a quantitative estimate of each risk’s impact on the system value. The goal of this revised approach is to better inform risk-related decisions by considering them in a quantitative value framework. This approach can be similarly applied when evaluating potential opportunities (also termed “upside risks”).