Decision contexts can be complicated or complex

The Cynefin framework classifies decision contexts into four types: obvious, chaotic, complex (Complexity), complicated.

In The Checklist Manifesto, Atul Gawande cites research that breaks down problems into three categories: simple, complicated, and complex:

Simple problems […] are ones like baking a cake from a mix. There is a recipe. Sometimes there are a few basic techniques to learn. But once these are mastered, following the recipe brings a high likelihood of success.

Complicated problems are ones like sending a rocket to the moon. They can sometimes be broken down into a series of simple problems. But there is no straightforward recipe. Success frequently requires multiple people, often multiple teams, and specialized expertise. Unanticipated difficulties are frequent. Timing and coordination become serious concerns.

Complex problems are ones like raising a child. Once you learn how to send a rocket to the moon, you can repeat the process with other rockets and perfect it. One rocket is like another rocket. But not so with raising a child […].Every child is unique. Although raising one child may provide experience, it does not guarantee success with the next child. Expertise is valuable but most certainly not sufficient. Indeed, the next child may require an entirely different approach from the previous one. And this brings up another feature of complex problems: their outcomes remain highly uncertain. Yet we all know that it is possible to raise a child well. It’s complex, that’s all.

In the book It’s Not Complicated, Rick Nason explains how if you manage complex things as if they are merely complicated, you will likely fail.

Complicated problems can be hard to solve, but they are addressable with rules and recipes, like the algorithms that place ads on your Twitter feed. They also can be resolved with systems and processes, like the hierarchical structure that most companies use to command and control employees.

The solutions to complicated problems don’t work as well with complex problems, however. Complex problems involve too many unknowns and too many interrelated factors to reduce to rules and processes. A technological disruption like blockchain is a complex problem. A competitor with an innovative business model — an Uber or an Airbnb — is a complex problem. There’s no algorithm that will tell you how to respond.