HOw design & science are complimentary

Idea Generation

Where do new and innovative research ideas come from? This is a critical junction that determines whether a research agenda will be radical or incremental. What can be learned by comparing the way designers and scientists come up with new ideas?

We will prototype how Design Thinking Paradigms (DTPs) can be used by cross disciplinary research teams during project Ideation. DTPs involve the transfer of principals and behaviors of design to other disciplines with the premise that Design Thinking can be applied to all types of problem solving.

These paradigms have been introduced and have successfully led to changes in innovation practices in engineering, healthcare, and business. Our aim is to identify and test science scenarios that integrate design thinking and to analyze how scientific outcomes might be impacted as a result..

Team Collaboration

The need for building stronger capacity for sharing and integrating deep expertise across disciplines. Translational research requires an interdisciplinary, team-based approach – this is not only limited to combining data and knowledge, but also requires a careful integration of expertise, methodology, practice, culture, and ultimately team cohesion.

In (engineering) design teams, there is the recognition that teamwork should be treated as a socio-technical process, wherein the social interactions amongst team members are one of the strongest predictors of team performance as measured by technical innovation and outcomes.

In science teams, I've often observed that we are very good at putting interdisciplinary teams on paper, but how often do we find that the outcomes are less than realized.

The reasons for this vary, and much of the unique circumstances about team science is articulated at length by the good work of the science of team science academic community. I think design can be part of that solution.

Approaches to Solving Complex Research Problems

What research challenges require radically different ways of thinking? These are challenges that are long standing and where current approaches are not effective.

By definition, when we build off of existing knowledge (conventionality), we are inheriting the biases that come with that understanding. As a way of knowing that relies on this foundation, science can be prone to idea fixation, or relying heavily on certain types of approaches. When should we challenge these biases? How do we overcome them?

One of the features of design practice that I’m really intrigued by is Reframing. This is a fundamental concept in design (more on that in a separate post) and where it has been particularly useful is in tackling complex problems. These are problems where existing solutions have failed because x, y, and z. What’s fascinating to me is that designers have structured ways of approaching the reframing process (see Frame Innovation). We are exploring how this can be used for the toughest challenges in science like drug discovery pipeline.

By the way, and yes, reframing happens in science and in basic science. An elegant example of this is FoldIt.