Collaborative Systems Thinking: An exploration of the mechanisms enabling team systems thinking

Aerospace systems are among the most complex anthropogenic systems and require large quantities of systems knowledge to design successfully. Within the aerospace industry, an aging workforce places those with the most systems experience near retirement at a time when fewer new programs exist to provide systems experience to the incoming generation of aerospace engineers and leaders. The resulting population will be a set of individuals who by themselves may lack sufficient systems knowledge. It is therefore important to look at teams of aerospace engineers as a new unit of systems knowledge and thinking. By understanding more about how teams engage in collaborative systems thinking (CST), organizations can better determine which types of training and intervention will lead to greater exchanges of systems-level knowledge within teams. Following a broad literature search, the constructs of team traits, technical process, and culture were identified as important for exploring CST. Using the literature and a set of 8 pilot interviews as guidance, 26 case studies (10 full and 16 abbreviated) were conducted to gather empirical data on CST enablers and barriers. These case studies incorporated data from 94 surveys and 65 interviews. From these data, a regression model was developed to identify the five strongest predictors of CST and facilitate validation. Eight additional abbreviated case studies were used to test the model and demonstrate the results are generalizable beyond the initial sample set. To summarize the results, CST teams are differentiable from non-CST teams. Among the most prevalent differentiators is a team’s self-reported balance between individual and consensus decision making. Teams that engage in consensus decision making reported stronger engagement in collaborative systems thinking. Another differentiator is the median number of past program experiences on a team. Teams whose members reported more past similar program experiences also reported more engagement in collaborative systems thinking. Data show the number of past similar programs worked is a better predictor than years of industry experience. The apparent enabling effects of qualitative team traits are also discussed. The conclusions of this document propose ways in which these findings may be used to improve training and team intervention within industry, academia, and government. Thesis Committee Chair: Deborah J. Nightingale Title: Professor of the Practice of Aeronautics and Astronautics and Engineering Systems