Data-enabled design. A situated design approach that uses data as creative material when designing for intelligent ecosystems


An increasing amount of interactive products and services, that people interact with on a daily basis, collect data about how they are being used. This enables these products to gain a detailed and nuanced understanding of their user(s) and the context they are situated in, based on which they can adapt their behaviour and interaction. Next to this, the increased connectivity of these products and services makes that they become part of larger ecosystems in which multiple users, products and services interact. We refer to this new generation of intelligent and connected products as intelligent ecosystems.
Our research investigates how data, that is a crucial part of intelligent ecosystems, can be utilized when designing for them.

This dissertation starts by presenting a user-experience oriented perspective and an experimental prototype-centric perspective. These perspectives are used as the main building blocks for the data-enabled design methodology that we set out to develop. After that, we present three design case studies that explore how data can be employed to design for intelligent ecosystems, in the context of baby feeding, baby health and personal health. These case studies, that were executed at Philips Design, are used to iteratively advance the data-enabled design methodology and our understanding of intelligent ecosystems.
Where well-known approaches, that use data in design assign a more evaluative and directive role to data, data-enabled design argues for more explorative and creative situated design explorations. To guide design researchers and practitioners in the setup and execution of the methodology we present a framework for data-enabled design. This framework presents a situated design approach, provides clear handles on the role data plays in situated design explorations, and explains how different explorations can be orchestrated in the design process to design for intelligent ecosystems.



Doctorate type


Year of completion


Case study type

Impact case study

Institution details

Industrial Design department

Industrial Design