"We cannot solve our problems with the same thinking we used when we created them."
- Albert Einstein
We're all familiar with the idea of using the right tool for the job. When your job is to understand a Complex Adaptive System, we believe that Complexity Science is that tool. Here's why:
Complex Adaptive Systems usually involve living organisms. They feature many connected and interdependent elements that have the capacity to change, and the ability to learn from experience.
Linear scientific methods would seek to fully understand each individual element of the system, and the cause and effect relationship between the elements. If you're trying to understand a more mechanical, non-living system, these methods work nicely. For example, if you want to understand how and why a clock works, go with the linear scientific method.
Non-linear scientific methods also seek to understand the individual elements of a system, but in addition, they examine patterns of relationships, how they are sustained, how they self-organize, and how outcomes emerge. If you're trying to understand how and why societies, financial markets, or biological systems function, we prefer the non-linear approach.