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The use of analytics in the design of sociotechnical products

Published online by Cambridge University Press:  27 August 2014

David Van Horn  and
Kemper Lewis
David Van Horn
Affiliation:
Department of Mechanical and Aerospace Engineering, University at Buffalo–SUNY, Buffalo, New York, USA
Kemper Lewis*
Affiliation:
Department of Mechanical and Aerospace Engineering, University at Buffalo–SUNY, Buffalo, New York, USA
*
Reprint requests to: Kemper Lewis, Department of Mechanical and Aerospace Engineering, University at Buffalo–SUNY, Buffalo, NY 14260, USA. E-mail: kelewis@buffalo.edu
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Abstract

The use of analytics has been emerging as a way to better understand the complex dynamics and resulting trends that occur when social and technical systems intersect. For instance, web analytics studies the intersection between society and the Internet to better understand use patterns and preferences. Business analytics studies the interfaces between human capital and technical systems in the context of corporate management and industrial production. Engineering design is ripe with such sociotechnical systems where consumers and engineered systems intersect producing a complex sociotechnical system marked by difficult to predict behavior and trends. In this paper, the paradigm of design analytics is further developed and used to study a diverse sociotechnical product. The product is a refrigerator that is hypothetically equipped with sensors and feedback mechanisms, and a simulator models the interactions of a population of 1000 users. Analyzing this sociotechnical product using design analytics demonstrates the ability to extract valuable insights at the juncture of people and technology. Insights into the leading behaviors of different populations are presented, and it is shown that design analytics and the associated tools can provide a platform for designers to develop better performing products that meet both explicit and implicit customer needs.

Keywords

Design AnalyticsProduct Use InformationSociotechnical Product
Type
Regular Articles
Information
AI EDAM , Volume 29 , Issue 1 , February 2015 , pp. 65 - 81
Copyright
Copyright © Cambridge University Press 2014 

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