Reality is Messy

Reality is Messy

Models are abstractions of reality. They’re helpful but flawed. They help us simplify the complexity of reality, but fall short because they are designed to save space. They’re built on a finite set of parameters, while reality has an infinite set of risks.

Here’s an example: Engineers might have built a dozen models, but no one considered the margin of error this truck driver experienced.

Reality is messy.

Of course, we can’t test whether something fits through trial and error every time we build something new. It’s simply too expensive. So we create models of reality.

Similarly, Figma or Maze prototypes are also models; abstractions of reality. We create them to test our ideas and reduce the cost of making mistakes.

But prototypes fail because we forget that reality is a lot messier than our simulated environments. Lab results might show that 10 out of 10 people were able to find our new feature. Success! But what happens when a sleep-deprived mom with a crying baby in the background needs to find that same feature?

Reality is messy. 

Benjamin Yoskovitz nails this sentiment perfectly:

Customers are people. They lead lives. They have kids, they eat too much, they don’t sleep well, they phone in sick, they get bored, they watch too much reality TV. If you’re building for some kind of idealized, economically rational buyer, you’ll fail.

When we create prototypes and stop considering the messy reality people find themselves in, our ideas inevitably connect with reality, like a truck and a low bridge.

Like George Box says, “All models are wrong, but some are useful.” The most useful ones are those that are more mindful of reality. 

• • •

Photo by David Martin