Accelerating digital innovation for growth, impact, and transformation of large established organizations.

Close this search box.

Lead DIGIT Lab Academics: Professor Saeema Ahmed-Kristensen and Dr Boyeun Lee

Despite the possibilities enabled with data in the new product development (NPD) process, researchers and practitioners lack a clear method or process to understand how data can drive new services or products.

To gain an understanding of the current state of the art, a systematic literature review was undertaken. We have reviewed 140+ articles to identify how data and machine learning are used within new product service development process. Through descriptive and thematic analysis, we have developed an evidence-based data-driven design framework encompassing seven data-driven design activities. The review highlights the type of data (the source) and the data-driven design activities undertaken in order to plan business strategies, understand user needs, identify product service requirements, generate concept ideas, customise products, maintain systems, and support design decisions. The framework was validated with 50 + industry practitioners through a set of workshops.

Related publications

  • B. Lee and S. Ahmed-Kristensen. (Under review) The framework of Data-Driven Design within New Product Service Development Process: A Systematic Literature Review. Computers in Industry.
  • B. Lee, S. Ahmed-Kristensen. 2023. Four Patterns of Data-Driven Design Activities in New Product Development. In Proceedings of the Design Society: 2023 International Conference on Engineering Design (ICED ’23). July 24–28, 2023, Bordeaux, France. 10 pages. DOI
Share the Post:

Related Posts