In characterizing systems behaviour, complex-systems scientists use tools from a variety of disciplines, including nonlinear dynamics, information theory, computation theory, evolutionary biology and social network analysis, among others. All of these topics have been studied for some time, but only fairly recently has the study of networks in general become a major topic of research in complex engineering systems. The research reported in this paper is discussing how the visually augmented analysis of complex socio-networks (networks of people and technology engaged in a product/service-system (PSS) life cycle) may be applied in engineering design research. Network thinking of the kind described in this paper could be fundamental for developing new and effective techniques for solving the problems in the engineering design research related to the interpretation of the huge amount of data captured during experiments and observations that are more and more used as a main research method. Case studies that are presented illustrate also the significance of the network based research approach in providing insight into ways of improving the design process for complex engineering systems.