A conditional value-at-risk approach to risk management in system-of-systems architectures

The development of a system-of-systems (SoS) is challenging due to the complex dynamics attributed to the interdependencies between systems and the inherent technical and programmatic uncertainties. The sheer number of decision variables that need to be considered in SoS development prompts the need for effective analytical support frameworks. Current frameworks and guidelines in addressing SoS challenges lack analytical means of objective SoS level decision-making. Research in this paper adopts computational decision methods rooted in financial risk management that allow SoS practitioners the means to identify optimal `portfolios' of systems based on dimensions of capability, cost and operational risk. Many risk management processes are in place for individual systems, but these tools and techniques are not always compatible for SoS. Our research leverages a Conditional Value-at-Risk (CVaR) perspective to managing risks that can incorporate simulation/observed data in the decision-making process. We demonstrate the method using a simple SoSE problem.