A human systems complexity model : how elite engineers acquire, create, and diffuse knowledge

For knowledge workers, lifelong learning, obsolescence, and innovation are intertwined as well as being highly influenced by social and economic systems. This is especially true for engineers in the semiconductor industry, which has been marked by a geometric rate of change. Using a complexity science lens, this case study describes elite semiconductor manufacturing engineers’ experiences as knowledge users and creators. The study represents a) the complex environment in which the engineers practice their profession as individuals and a system, b) the triggers that compel learning and examination of the status quo, and c) ways in which the system of elite engineers use information and share new knowledge. Seventeen elite engineers voices are included in this study which uses structured interviews about workplace learning projects and scores from the Change Style Indicator instrument. Thematic coding, descriptive statistics, and existing models examine the interactions and interdependencies within the system of elite engineers. In addition to Lewin’s Force Field Analysis and Mink’s Open Organizations models, a model for examining human systems from a complexity science perspective provides a lens through which to interpret the data. The Human Systems Complexity Model honors the non-linearity of complex systems. The conceptual model is represented by a conic geometric shape with three conic sections that offer glimpses into the sensemaking processes of the social system. Each conic section has a theme, 1) interconnectedness of process and matter, 2) triggers for questioning the status quo, and 3) emergence of knowledge. The discussion includes emergent themes that point to future directions for inquiry. The themes are relevant to professionals in the fields of human resources, technical training, library science (knowledge management), management, and engineering.