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Designing Quality into Project Organizations through Computational Organizational Simulation

TitleDesigning Quality into Project Organizations through Computational Organizational Simulation
Publication TypeWorking Paper
Year of Publication1998
AuthorsThomsen, J, Kunz, J, Levitt, RE
Date Published03/1998
Publication Languageeng
KeywordsCenter for Integrated Facility Engineering, CIFE, Computational Organizational Design and Analysis, Contingency Theory, External Validation, Intervention Study, Stanford University, Total Quality Management
AbstractThis paper shifts the focus of quality management from measuring and controlling the quality of work processes to the next level upstream-measuring and controlling the quality of the organizations that execute work processes. Starting from an organizational information-processing perspective, we have developed the Virtual Team Alliance (VTA), a complex, coherent computational model of project participants' information-processing behavior that include variables (e.g., activity flexibility and goal incongruency) that are substantively critical to performance of projects. Project participants are endowed with fragments of canonical information-processing micro-behavior (e.g., attention allocation, information processing, communication, and decision-making), and then assembled into networks of actors and tasks to represent project organizations. Through simulation of project participants' micro-level behavior, our computational model generates useful and measurable emergent quantitative performance predictions regarding the efficiency and quality of a project's configuration of work processes and organizational structure. The model produces two measures of efficiency-project duration and cost-and three measures of work process quality-problem-solving quality, coordination quality, and decision-making quality. In addition to providing a project manager with measures to support specific and detailed organizational design decisions involving trade-offs between cost, duration, and work process quality, our model predicts organizational risks that might adversely affect project performance. Users can identify and test feasible, detailed, and useful interventions to mitigate organizational risks contingently. We prospectively applied our model early in the development process of an industrial project team within the aerospace industry. Our model forecasted backlogs arising from extra coordination and rework and the resulting problems that might occur without organizational change. Based on simulations and analysis of our model, we made specific recommendations to the project manager for improving work process performance. After considering our recommendations, the cooperating manager intervened in the engineering process to reduce some of the organizational risks that we predicted might adversely affect project performance. In our subsequent observations of the project, the potential organizational risks that our model had initially identified as being likely to affect project performance adversely were avoided by the manager's intervention.
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