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Developing products with set-based design: How to set up an idea portfolio and a team organization to establish design feasibility

  • Anja Schulze (a1)
Abstract

Prior research has identified set-based design as a method that accounts for the high level of uncertainty that is associated with the design of innovative products or systems. Rather than precisely specifying a system architecture in the early design stages, set-based design builds on designing a system and its architecture in an evolutionary way. The literature on set-based design has studied how a system's design evolves by moving from a number of optional design ideas to the final system through gradually eliminating unfeasible design ideas and continually developing design ideas for which engineers increasingly establish feasibility. However, little is known about how firms set up the design process and the organization to successfully create new products with set-based design. Our research contributes to closing this gap. First, we study how firms determine the number (i.e., portfolio) of design ideas to pursue, an important step of the early design process. Second, we study how firms organize for set-based design by assigning teams to develop design ideas and eventually design a system's architecture. Our research uses an exploratory case study approach, investigating five cases in three different firms. First, we find that the early design process is characterized by the absence of formal idea evaluation and selection. Instead, firms start to pursue all initially created design ideas, evaluating and selecting them in an evolutionary manner as the design project progresses. Second, we identify two organizational approaches associated with set-based design: assign one team to pursue all ideas or assign one team per design idea.

Copyright
Corresponding author
Reprint requests to: Anja Schulze, Department of Business Administration, University of Zurich, Plattenstrasse 14, Zürich 8032, Switzerland. E-mail: anja.schulze@uzh.ch
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AI EDAM
  • ISSN: 0890-0604
  • EISSN: 1469-1760
  • URL: /core/journals/ai-edam
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