Fresh ideas about design
I doubt that architecture and quantum physics have ever been considered in the same sentence, but I’ll argue that they are different perspectives on the same problem.
In the early 1900s, physicists worked to explain how sub-atomic particles behaved. The standard (Newtonian) worldview had for centuries described how everything worked, until suddenly it didn’t, at least at the sub-atomic level. As they struggled to make the old theories describe these new conditions, physicists began to suspect that their fundamental conception was wrong. Where Newtonian physics conceived the universe as a machine-like assembly of parts that could be described individually, they began to think that the universe was in fact one whole, inter-related, complex entity. Everything was connected to everything else. It’s called Complexity, and quantum physics is how it’s described.
Design thinking can be understood by considering the difference between Newtonian physics and Quantum physics. Through the eyes of Newtonian physics, the universe is a vast machine, and if you could break the problem into parts, you would understand the whole. In quantum physics, the universe is seen as a single complex, connected whole, impossible to describe independently. Traditional thinking seeks to isolate the elements [problem] and resolve the individual issue piecemeal. In contrast, design thinking conceives the problem as an aspect or condition within a larger context.
Divergent thinking is the ability to offer different, unique or variant ideas within an overall theme. Convergent thinking is the ability to find the “correct” solution to a given problem by narrowing the issue and then “doing the math.” Design thinking uses both, employing divergent thinking as a way to ensure that many possible ideas are explored in the first instance, and convergent thinking to assess and narrow these down to a final approach. Design thinking encourages divergence to generate many solutions (possible or impossible) and then uses convergence to test and implement the best solution.
Design thinking is especially useful in addressing ill-defined or tricky problems—what Horst Rittel referred to as ”wicked problems.” With ill-defined (wicked) problems, both the problem and the solution are unclear at the outset of the problem-solving exercise. Ill-defined problems often contain higher-order or obscure relationships. “Tame” or well-defined problems are ones where the problem is clear, and the solution is available through the application of some specific, technical knowledge. For wicked problems, the general thrust of the problem may be clear, but considerable time, effort and a variety of perspectives are needed to understand the issue. In design thinking, problem definition and problem shaping comprise the critical first step. At Strada, we call this Placemapping.
Design thinking benefits from cross-disciplinary insight, from varied perspectives starting with problem definition. Constant and relentless questioning drives this phase, always asking “Why?” Asking why is not to critique an idea, but rather to help understand the pros and cons of each idea, clarifying the boundaries of a potential solution set. Most importantly, defining the problem via design thinking requires the suspension of judgment in defining the problem statement.
Although design is often used to describe a result, in its most powerful form design is a verb, not a noun. Design is a protocol for solving problems and exploring opportunities. In the last few years, this approach to problem solving has become the buzz word in business circles, a new way of thinking about problems (beyond the built environment), because problems continue to get more complicated, inter-related and ill defined. The old approaches were not delivering adequate results. Like physics in the early 20th century, society is looking for ways to describe and resolve the more complex, interdependent and unclear problems.
Because the process involves complex cognitive mechanisms, the design solution(s) often engages elements in multiple cognitive domains—visual, mathematical, auditory or tactile—requiring the use of multiple, inter-related communication/presentation methods. As the problem is explored, an understanding of the possible results requires representation by using different media such as precedents and 3D modeling as well as statistical models and graphs, to develop an understanding of the obscure or ill-defined elements of the complex solution set.
As it turns out, the people who say design isn’t rocket science are right. It’s harder.
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