What’s Missing From Your Design Toolkit?
For the last few weeks, my classmates and I have been reading and discussing a set of readings focused on Design Thinking. This has run in parallel with the work in our research class, where we are actively applying the design thinking methodology. In this post I’ll be processing my thoughts on design thinking methodology, where I think it works best, and where I think it might be lacking.
First, some of the main authors and their ideas:
Edward de Bono – Discusses the importance of creativity and gives us a variety of tools to aid in the process of withholding judgement and allowing our brains to go to weird, new places. He argues that “the normal behavior of the brain in perception is to set up routine patterns and to follow these. In order to cut across patterns, we can use deliberate techniques.”
Nigel Cross, Discovering Design Ability – Explores what design is capable of and seeks to establish design as a “discipline in its own right. He also makes the case that design can be taught.
Horst Rittel & Melvin Webber – Asserts that design is meant for big, messy, wicked problems. And, in fact, the formulation of the wicked problem is, itself, the problem.
Tim Brown & Jocelyn Wyatt – Posits that design thinking and design need to be separate words, as they mean different things. They argue that design speaks specifically to the product, whereas design thinking speaks to the system, or the context in which that product will be operating.
Richard Buchanan- Build the idea that design is layered, and operates in the world across four main areas: symbolic and visual communication, material objects, activities and organized services, and then finally complex systems or environments for living, working, playing, and learning.
Herbert A. Simon- Believes that a well defined problem isn’t a real thing. If you think you’ve distilled a discrete problem, then you are missing the context. In the world, there is going to be far too much to measure.
Chris Pacione – Evolution of the Mind: A Case for Design Literacy – Suggests that design is the new math. Essentially, math was once a skill only mathematicians used. But now, it’s integral to our society and to nearly all professions. Design could and should be the next math.
Now, my take on design thinking.
I’m a believer in its power. I am drawn in particular to Pacione’s take on the value of design across a broad array of professions and work types. Design thinking allows us to open up our minds, to see things that no one has seen. Latent problems exist all around us and we have to be actively engaged in uncovering them in order to do so. The methodology of design thinking helps us do just that.
However, all of the tools we’ve been learning and applying in our design research course only give us a way to gather and make sense of qualitative, biased information. We meet people and we ask them questions and we learn how they operate, what motivates them. Essentially, we are learning their perceptions of reality. From there, patterns emerge from what we have learned.
From this point, there is a HUGE jump toward insights. We gather no new data, but somehow designers are able to jump from identifying a pattern to knowing why it’s interesting and matters in the context of the larger story. That’s a huge leap. And the only way a designer gets there is by using his/her intuition. Intuition, by definition, is instinctual. It’s a gut feeling about something. But that intuition comes from somewhere. It’s made up of all of our life experiences, our knowledge base, and what we know to be true about the world. We use our own lens to evaluate patterns in others perceptions and then we arrive at an entirely new ideas.
But what about times when a designer doesn’t have a lot of knowledge about a space? I’d argue this is where quantitative data could come in. We are out in the field learning as much as we can from people, why not integrate quantitative data to paint a more robust picture?
My classmate, Michelle, crystallizes this idea in her recent post by saying “people may believe quantitative data is reductive, dry, lacks personality or nuance. But when I hear those critiques, I think, ‘You’re just looking at the wrong data!’ The right quantitative data for your problem will spark curiosity, will express nuance, will prompt expansive thinking. With practice interpreting or visualizing data, quantitative data can tell a lively and highly specific story, or at least point you in the direction of one.”
I’d ask designers not to shy away from quantitative data, but to lean into it. Use it as another tool. Quantitative research methods might have flaws, but you can learn some things from it that you can’t learn from 15 interviews. Integrating it into the design thinking methodology would make for a more rigorous process and help drive toward much more significant insights.