A quasi-experimental evaluation of engineering design methodologies and the effect on the creativity of system architectures for complex technical systems

System engineering firms have an increasing competitive need to produce more creative system architectures. One of the drivers for this need was the 1994 Federal Acquisition Streamlining Act (FASA). As a result, federal contractors relied more on writing proposals that included unique, value-added solutions to meet performance objectives. Many experts proclaimed the effectiveness of methods and techniques to produce creative technical solutions. However, it was not conclusive whether the creators of those techniques had more empirical than anecdotal evidence to support any claims of effectiveness. To address this lack of evidence, the current research evaluated creativity enhancing methods and techniques as applied to the systems engineering design process. The empirical evidence suggested that engineering design methods could increase the creativity of system architectures for complex technical systems. This research had two goals. First, to construct engineering design methods and appropriate training in those methods to increase the creativity of system architecture artifacts based on two categories of creativity enhancing techniques. Second, to determine which of the two systems engineering design methods resulted in greater creativity for system architectures.;The research used a quasi-experimental design to determine if there was a significant difference in the effect of the two training interventions on the creativity of system architectures. The quasi-experimental methodology compensated for lack of controls on all real world factors that could influence validity. As such, many known and unknown factors contributed to this rare and time-sensitive data gathering opportunity.;Interventions included the Systematic Engineering Design Method (SEDM) and the Intuitive Engineering Design Method (IEDM). The SEDM employed requirements-driven ideas, analytical decision-making, and criteria-based idea selection. The IEDM intervention used expressive techniques designed to increase the number of ideas generated, stimulate free-flowing dialogue, and remove the inhibitions in selecting the most creative ideas. The investigator combined a variety of creativity enhancing techniques to develop these engineering design methods, which evaluated the effect on the creativity of systems architectures.;The overarching question was which engineering design method had a greater effect on the creativity of systems architectures. Creativity was a function of novelty, utility, and wholeness of the system architectures as evaluated by a panel of judges. To be a judge, each person had 10 years of professional experience in system engineering and is knowledgeable about systems architectures in complex technical systems. The four judges met these criteria.;The interventions applied to four training occasions lasting 10-weeks each and continuing over a 12-month period. Each occasion consisted of three to five teams with four to six participants. The total number of participants was 49. An expert panel of four judges determined the dependent variable using a bipolar semantic scale to evaluate the system architectures produced by the teams. Each team used one of the two system design methodologies. The approach used to evaluate the creativity of the system architectures was the Consensual Technique for Creative Assessment. The investigator used other instruments to measure factors that potentially influenced the validity of the experiment.;The research showed that the Systematic Engineering Design Method (SEDM) produced designs that judges evaluated as having more creativity than those designs produced by teams using the Intuitive Engineering Design Method (IEDM). The research tested the causal relationship between the two types of engineering design methods. The results showed that a SEDM was better at producing novelty and utility in complex system architectures than was the IEDM when systems engineering professionals produced them and domain experts evaluated them. Because of the attrition of participants over the period of the experiment, the statistical results might overstate the degree of statistical confidence provided in the findings.