A Network‐Based Analysis of Team Coordination and Shared Cognition in Systems Engineering

This paper presents a network-based approach for analyzing team coordination and shared cognition in engineering design teams. The research setting is an Integrated Concurrent Engineering ICE laboratory in which teams of approximately 20 engineers are collocated to conduct rapid conceptual design of scientific spacecraft. A design structure matrix DSM of expected interactions is constructed from technical information flow data, and DSM representations of reported interactions are created using survey data from 10 ICE design teams. A comparative analysis of expected and reported interactions is used to calculate a metric of team coordination called socio-technical congruence STC. To examine shared cognition, pairwise shared mental models SMMs are measured using pre- and post-session surveys on system design drivers. Shared knowledge networks SMMs as edges are constructed, and team learning is measured as the change in network structure over time. Analysis reveals statistically significant correlations between team learning and each of three technical attributes system development time, launch mass, and mission concept maturity and between team learning and team coordination. These results indicate that team members learn most from each other when working on difficult or unfamiliar problems and when expected and reported interactions are aligned. The paper concludes that team coordination and the design product in ICE are not necessarily directly related to each other but that both are related to shared cognition. Although this study focuses on conceptual design, it lays the foundation for future work examining the role of team coordination and shared cognition in full-scale system development programs.