Complex, or merely complicated?
If you are a UX professional, odds are you probably use the words ‘complex’ and ‘complicated’ interchangeably. I certainly did, thinking of one as a synonym for the other. Using complex to define complicated, and vice versa. The problem is when we address a complex problem as a complicated one, we are setting up ourselves and our projects for failure.
Understanding when issues are complicated or complex is an imperative for UX designers. Complicated issues differ from complex ones. Not seeing the distinction, we will use the wrong tools and wrong thinking. For hammers, everything is a nail, remember?
Here is how these things are different. A complicated issue is one in which you can separate the components in a systematic and logical manner. There are clear dependencies that rely on a set of fixed rules or algorithms. Complicated things are typically linear and predictable. Though often hard to see, something complicated has enough structure to allow us to deal with it in a repeatable manner. These structures have a controllable cause and effect that is repetitive. We tend to have grounded confidence in anticipating the next.
I consider making an electric car an example of something that is complicated (amirite, Elon?). However difficult to do, it is doable, repeatable and with known results. While it will always remain a complicated thing, we can design more efficiencies. Expertise, data, AI and technology all help to deliver this. Every effort bringing more control and more visibility to what rules to bend and which ones to leave alone.
For a complex problem, efficiencies and control simply do not apply. We base any AI on known data sets. Technology works on existing patterns. We built our best practices on what we can repeat and can govern. None of it can deal with or adapt to unknown or ever-changing patterns. That is what a complex issue brings; constant volatility and evolving inter-dependencies.
While something complex will have patterns, these will not repeat themselves predictably. Nor interact in predictable ways. There’s no firm count on the parts and there are no fixed rules or algorithms to provide order. Tiny changes can bring tremendous shifts to various parts of unique structures that make up the system. We may not always understand cause and effect.
While complicated issues are solvable, complex challenges are not. That makes a complex thing a lot more different than a complicated thing. And clarifies why we cannot address complexity successfully when we do not change how we design for it.
We can only manage complexity because we cannot solve it.
Where I propose UX-ers to start is first to understand and appreciate the differences between complexity thinking and complicated thinking. The two ways of thinking involve different mindsets. Hold different assumptions and different tolerances of ambiguity. Involve unique attributes and skills that require different governance techniques.
That asks us to shift our expectation and intent. We can only manage complexity because we cannot solve it. This is an experimentation-first effort, while anticipating outcomes we cannot fully predict. We adjust to a try-learn-adapt process that needs tolerance towards failure, margins and milestones. Where we allow for capacity and leeway for people to bring different points of view (the more the better). Where we design by principles as opposed to by rules, because there are no rules in complex problems.
While complexity thinking may feel confronting, it is actually not difficult to do. I find it intuitive and straightforward. For me, it happens when I repeatedly re-frame the questions with fresh eyes. It is practicing my ability to rethink as the game keeps changing. When I do complexity thinking, I assume nothing to be certain. In fact, my effort is in seeing things as always being uncertain. While staying invested in allowing others to change my mind.
That’s what makes something as simple as asking whether an issue is complicated or complex immediately valuable. With evidence that it is merely something complicated, we can apply our best practices, leverage from past experiences, base more decisions on predictability, and have technology deliver efficient results. Whenever we identify a complex problem, we can rapidly facilitate the needed shift in approach and thinking. Build diversity in the design effort. Root it in a shared understanding of a vision. Whet our appetite for ambiguity, and devise experiments that reveal something about the complex issue.
