Everything is as simple or complex as you want it to be

Illustration by Ollie Hirst for this article.

Everything is as simple or complex as you want it to be.

As creators, our role is to not only look at the top, face level of what it is we build (or what inspires us) but also the many different layers of complexity contained within the thing.

That is: when we perceive the world around us we can do so with as much or as little attention to—and consideration for—detail as we want. This intention in how we perceive things influences what we can do with the information we have available on us.

Simple concepts are more efficient for communication purposes, they're easier to parse or break apart, and generally more likely to be what the general population thinks about. But simple things are also easily misunderstood and poor representations of the whole. Nothing is ever as simple as we first perceive them to be.

People, projects, devices with screens, the things we see on a screen, products we buy, apps we use, everything in the world around us are designed to be either immensely complex or plainly simple. How complex something appears to us depends mostly on how it's presented, but also how we choose to look at it. The more you look into and think about something, the more complex it becomes.

At the most simplistic level things are singular: a problem is... well, a problem. A computer is a computer. These simple generalizations are helpful for us to understand the complexity of the thing and to communicate about it.

This is an over simplification and yet it's also how we tend to view projects in our careers. You have a problem and some concept of a solution to remedy it. Simple.

If you ask a child to explain how they did something, their response usually follows this framing; first there was this, then this. Two ends of the same line. This is also how we tend to choose to view strangers on the internet, products we don't like, and politicians.

But if we really look at any of these things we start to see additional layers to it. The computer is made up of many complicated parts. The path to a project solution is rarely straight, it's often much more complex. When it comes to design problems there are constraints—technological, financial, time, energy, and others—as well as additional considerations such as unforeseen situations or pre-existing concepts not previously considered, a competitive market, access to information and insights, and so on. You may even find that what you thought as being a straight-forward problem was jut one small piece of a larger issue.

Those outside the realm of design tend to see design as simple, but those within the space understand just how complex the work can be. This is true of all careers.

When we look at something closely it becomes evident that any one problem consists of many smaller problems. When we look closer, our perspective shifts to see things in slightly more complex lens. We begin to see that there is more than just a linear path to what it is we're evaluating, there are tentacles to the complexity. We end up with something that looks more like this a tree, with roots branching out from a trunk. We can choose to look closely at the project now and see it for what it is: a mess of objectives, constraints, resources, and energy.

The problem of "how to build a computer” is made up of thousands of smaller problems: how to machine the case, how to wire circuitry and fit it into a small container, how to provide power and ensure the power source is reliable and can last for many years, how to layout keys onto the casing and the mechanics of the keys themselves. On and on the complexity goes, only ever as deep as what we're willing to look at. There are problems with thermodynamics, machine physics, and the elasticity of the materials used in the thing.

What often makes the initial problem a problem to begin with is that it entails many smaller problems. In the absence of these complexities the problem wouldn't be a problem because the solution would be straight-forward. Most things are not as simple as we anticipate them to be. People, projects, and products certainly fall into this category of being more complex than what we often see at-a-glance.

These smaller components—problems, constraints, and information—are connected in a way that influences the others as well. They're less of a branching off a central problem and more akin to a web of complexity.

Looking at a problem in terms of many smaller problems is a good way to zoom into the complexity, but there's more to the situation than looking closer at it! Not only do we need to zoom-in on all the smaller elements of something, we need to also zoom-out to see what additional problems are influence the one we've set out to solve. We end up in a space that looks something like a solar system of problems and solutions.

Where will the thing be used, in what environment? How often will it be used or abused? What are the constraints and resources available to the thing that will exist outside of it? What is the history of things like this? Suddenly what we thought of as being simple is far more elaborate, and far more reliant on things outside our initial consideration.

This is why whenever you're stuck on a problem it's easier to come up with a solution by stepping back from it—both literally and figuratively. Often the thing that has us stuck is just outside where we're looking.

Problems and concepts are rarely linear lines to solutions, nor are problems ever siloed on their own. What's more likely is that any given thing is itself a complexity to a larger ecosystem.

To really be a truly critical thinker is to consider the larger and smaller complexities of any given thing, and the interplay between them.

To be an effective product designer, engineer, product manager, data scientist, or any other function within the product development lifecycle, we must be capable of navigating the spectrum of complexity in the world around us. Doing so gives us insights into the things we build, and enable us to use the layers of complexity to our advantage. We can simplify concepts in order to communicate them with outside markets, or we can draw on the complexity of a concept in order to ensure the work we're doing is going to be long-lasting or highly effective.

In standard design practices this process of looking in and out at the problem landscape is the very first step to creating solutions. It's a divergence of perspective and thinking in order to ensure you aren't overlooking critical information that could influence how you pursue solving the problem.

Before we can seriously attempt to solve a problem, we must first understand everything around it. The more time you have to consider the landscape, the better equipped you will be for solving the problem. As Don Norman wrote in his seminal book on modern design, The Design of Everyday Things:

In design, the secret to success is to understand what the real problem is... complexity is essential, it is confusion that is undesirable.

The world around us is only ever as simple or complex as we want it to be. We control this narrative by how long and how intently we look at something. Asking questions like: "What does this consist of? What is it made of? How do the parts work together?” as well as: "What is the larger ecosystem this is part of? What outward forces play a part in how this thing comes together?” add to our ability to perceive the complexities of something.

And when we understand the whole parts of something, we're better equipped to change it. To add to it, modify it, remove it, or improve it.

In the absence of understanding the complexities we're merely setup to talk about the thing. Sometimes communication is all we need, but if we're to build or design something truly meaningful we need to look a bit closer than what's on the surface—or in the message—of any thing.