Data Driven Styling: Augmenting Intuition in The Product Design Process Using Holistic Styling Analysis (HSA)

[+] Author and Article Information
Charlie Ranscombe

Centre for Design Innovation, Department of Interior Architecture and Industrial Design, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

Philip Kinsella

Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

Janneke Blijlevens

School of Economics, Finance and Marketing, Royal Melbourne Institute of Technology, Building 80, Level 10, Room 29, 445 Swanston Street, Melbourne, VIC 3000, Australia

1Corresponding author.

ASME doi:10.1115/1.4037249 History: Received January 22, 2017; Revised June 07, 2017


Styling or product appearance is well known for holding great influence on its differentiation, branding, and overall success in the market. However, the styling process is difficult due to the intuitive and subjective way in which designers evaluate designs. In particular, negotiating iterations between designers and engineers is challenging since engineers have objective, data driven approaches to rationalize decisions whereas designers rely on instinct and intuition. While the literature shows sustained interest in this issue, and provides methods to analyze appearance objectively, many approaches rely on abstracted or simplified versions of a product's appearance as the basis for analyses, ignoring the holistic nature of product appearance. This article contributes by proposing an improvement employing digital shape comparison tools applied to 3D geometry of products, and generating data on differentiation in product shape–that is, the Holistic Styling Analysis (HSA). The HSA provides objective assessment of difference in appearance to form the basis for designers to rationalize styling to other stakeholders during the design process. The HSA is tested through an automotive industry case study. Results show the method adds objectivity to decision-making by providing objective reference measures for differentiation in the styling of previous and competing products. Such measures can be used to inform styling goals, and to identify intended degrees of difference in key features while highlighting areas to maintain consistency. As such, we contribute by providing a means for styling designers to use data to drive their activities in the same manner as other stakeholders.

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