A Complex Systems Perspective of Risk Mitigation and Modeling in Development and Acquisition Programs

Abstract

The current methodologies used in risk assessment are heavily subjective and inaccurate in various life cycle phases of complex engineered systems. The increase in complexity has caused a paradigm shift from root cause analysis to the search of a set of concurrent causes for each event and the relevant complexity content of the system. Many of the system's life cycle risks are currently assessed subjectively by imprecise methodologies such as color-coded risk matrix, and subsequently they suffer from unforeseen failures as well as cost and schedule overruns. This research project proposes a novel approach to major improvement of risk assessment by creating a set of appropriate complexity measures (informed by historical case studies) as pre-indicators of emergence of risks at different stages of a systems development process, and also a framework that enables the decision-makers on assessing the actual risk level at each phase of the development based on requirements, design decisions, and alternatives. The goal of this research is to capture the complexity of the system with some innovative metrics, thus allowing for better decision-making in architecture and design selections.