Portland State University. Department of Engineering and Technology Management
Antonie M. Jetter
Term of Graduation
Date of Publication
Doctor of Philosophy (Ph.D.) in Technology Management
Engineering and Technology Management
1 online resource (xi, 206 pages)
Scenario planning is used extensively in strategic planning because it helps leaders broaden their perspectives and make better decisions by presenting possible futures in story form. Some of the benefits of using scenarios include breaking away from groupthink, creating better products, acceleration of organization learning and reducing bias. Product development teams, particularly for digital products, are gaining more autonomy in organizations and tend to manage risk by undergoing very short development iterations on their products while leaning on their consumers for feedback -- a process known as agile development. This method tends to limit the perspective of the team and foster groupthink, two side effects which could potentially be addressed using scenarios. However, the time-consuming and expensive processes used to create scenarios are inaccessible to agile product development teams, and even teams that use scenarios for strategic direction typically use them at the beginning of product development and do not keep them up to date over time, eventually making them irrelevant to decision making. This research explores automating the bottlenecks of the scenario process so they can be incorporated into autonomous agile teams by creating and rigorously tests an artifact that combines Natural Language Processing (NLP) to understand data, Interactive Machine Learning (IML) to combine automation with human expertise, Fuzzy Cognitive Maps (FCM) for quantitative scenario modeling, and Horizon Scanning (HS) to keep models up to date; a system I call Scenario Acceleration through Automated Modelling (SAAM). Using Design Science Research (DSR), I demonstrate how these technologies can be used together to speed up the scenario creation process while keeping people in the loop, and how they can be kept up to date over time. This research lays the foundation for product development teams to use scenarios in agile processes, with the goal of creating better products and avoiding disruption.
This work makes several contributions: Firstly, it furthers the body of knowledge on scenario development by showing how to create scenarios with automation and how scenarios could be used by agile teams. Secondly, it demonstrates a novel method of creating FCM with NLP and human collaboration, and how to use Horizon Scanning to keep models up to date over time. Finally, I leave an artifact that can be used by other teams who want to continue this vein of research, or for product teams that want to utilize this method.
© 2022 Christopher W.H. Davis
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Davis, Christopher W.H., "Scenario Acceleration Through Automated Modelling: A Method and System for Creating Traceable Quantitative Future Scenarios Based on FCM System Modeling and Natural Language Processing" (2022). Dissertations and Theses. Paper 6007.