Estimating change propagation risk using TRLs and system architecture

Abstract

Risk estimation is a key activity for product development and technology integration programs. There are a number of decision support tools that help project managers identify and mitigate risks in a project, however few explicitly consider the effects of architecture on risk. We propose a novel risk estimation framework that includes considerations of the system architecture. By starting with traditional project management literature, we define risk as a combination of likelihood and impact. We use Technology Readiness Levels as our measure for likelihood, and given that change propagates through interfaces, we used metrics that relate to connectivity to estimate impact. To analyze the connectivity, we model systems using networks of nodes and edges and calculate centrality metrics. This framework is applied to an industry example and we visualize the data in different formats to aid in analysis. The insights gained from this analysis are discussed, and we conclude that the risk estimation framework provides estimates that are in line with the experience of engineers at the company.