Managing data-driven design: A survey of the literature and future directions
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Johnson, Julie; Hurst, Ada; Safayeni, Frank
Series: ICED
Institution: University of Waterloo
Section: Design Methods
Page(s): 2525-2534
DOI number: https://doi.org/10.1017/pds.2023.253
ISBN: -
ISSN: -
Abstract
Data-driven design is expected to change design processes and organizations in significant ways. What actions should design managers take to ensure the best possible outcomes in this new data-driven design environment? This paper employs an interdisciplinary literature survey to distill key impacts that data-driven design may have on designers, design teams, organizations and product users. Findings reveal that designers may need a broader set of skills to be successful. For data-driven design to be most effective, design managers will be challenged with many integration tasks, including the integration of AI-based tools into design teams, the closer integration of interdisciplinary teams, the integration of qualitative design thinking methods with new data-driven design paradigms, and the integration of data and algorithms into traditional human-centred design practice, in an effort to overcome cognitive limitations and augment human skill. This paper identifies gaps in the literature at the intersection of data-driven design and design management, design thinking, and systems thinking.
Keywords: data-driven design, AI-driven design, Design management, Artificial intelligence, Design practice