Data-enabled Design

Data-enabled design (DED) is a relatively young approach, developed from needs to innovate based on reliable, deep contextual insights and to design adaptive systems that can address end-user needs in a personalized way. One key aspect of the approach is that data serves the design process in an active form, that it can be collected flexibly from the context and from real end-users through appropriate creative means. In this sense, data-enabled design aims to innovate on what we can know from a context and how this knowledge and insight can benefit the design process effectively.

In Data-enabled Design, designers and design researchers use data as a creative design material. The goal of data-enabled design projects is to design complex products and services that are embedded in so-called “intelligent ecosystems”, i.e., dynamic compositions of interrelated products, services and people. These systems are meant to understand users within their context by collecting and processing data and adapting their function and experience accordingly.

Two explorations

The data-enabled design process supports two kinds of explorations: a research-oriented contextual exploration and a solution-oriented informed exploration. We call them explorations as they are a collection of design activities composed of the six steps of the data-enabled design loop. While the loop might seem structured and linear, in reality, design teams applying DED carry out activities based on the kind of explorations that are appropriate in a given phase of the design process. For instance, different users might be involved in different user tests, or the same users might go through multiple explorations during one user test. These explorations might happen in parallel when the designers wish to explore multiple elements of the system at the same time. In this way, contextual and informed explorations can sometimes happen simultaneously. Below, we describe the characteristics of the two kinds of explorations in more detail.

The goal of a contextual exploration is to gain an understanding of the everyday con- text that the team is designing for, focused on understanding values and motivations of users in their context. These contextual explorations have a focus on collecting research data, which is data that informs the design research team about the intri- cacies of the context, and which provide room for identifying design opportunities. During contextual explorations, participants provide data and receive basic feedback in return. One of the outcomes of these explorations is a data strategy that informs the design research team on what data (not) to collect from the context.

The second kind of exploration, the informed exploration, has a stronger focus on design and on bringing interventions into the context. A new group of participants might be recruited for this kind of exploration, to make sure that assumptions from the contextual explorations can be evaluated against a fresh pool of participants and their contexts. These informed explorations have a stronger focus on so-called solution data. Solution data is data that plays a role in facilitating interactions between users and the system, e.g., by being presented to them for reflection and feedback or by triggering system interactions.

Find more information on the concepts page.