Vehicles are becoming more and more connected, and in combination with various services, they generate large amounts of data, which is mainly used in development processes for testing purposes in Ford. However, sensor data has more potentials for product development, and one valuable potential is to contribute to product innovation in the early design stage, which can be seen from existing studies on data-enabled design. However, the large amount and complexity of data make it hard for the Ford Research and innovation (R&A) team to approach data, nevertheless apply data in the design process. In addition, there are no available methods and tools that fit in with Ford’s data availability and workflow to guide them to apply data for product development, which can make the R&A team feel clueless in their practice. Based on the challenge, I framed the initial research question of this project as: How to facilitate the Ford R&A team to apply user data to enhance creativity in their ideation process? Then, I conducted research, product development, and evaluation to deliver the final design intervention. Afterwards, the concept “A toolbox for creative problem solving with data “was developed and tested. Based on the evaluation of the toolbox, I designed a guidebook containing a three-step method as a guide to applying the toolbox. The second-round evaluation shows that the final design intervention is believed to provide innovative methods and tools for the R&A team to generate insights from data combinations for the problem framing process and cultivate creative thinking during the session. Moreover, the three-step method for combining data fills the method gap for the implementation of data-enabled design in organizational practice. In conclusion, the final design intervention sufficiently fulfils the design goal and contributes to the method study on data-enabled design.
Master Thesis: TU Delft repository