Decomposing Complex Problems Using Influential Attribute Network Graphs
Garret Fitzpatrick, Ian Monk · INCOSE International Symposium · 2018
Abstract The deployment of new technologies and processes within established value chains requires a thorough understanding of the complex interactions between the existing system's behavior, structure, and the economic driving factors behind them. Recognizing these interactions and their effects within the system is a critical first step in defining the right problem to solve. Influential Attributes Network (IAN) graphs can be used as pictorial depictions of system relationships and have proven to be a valuable tool for communicating to stakeholders the critical factors that are driving often ambiguous problems. For large, complex projects these graphs help to break problems into smaller, more manageable pieces and focus technology development teams on the highest impact areas. IAN graphs also help to examine how potential solutions can address original requirements and communicate traceability from system architecture decisions back to underlying economic conditions. Ultimately, this tool helps the architect reduce ambiguity, employ creativity, and manage complexity.