Complicated versus Complex
Some problems or systems are complicated; others are complex. Understanding the difference is the first step towards engaging with problems.
The difference lies mainly in the relationship between causes and their effects: are these relationships clear and easily described, or are they murky and difficult to understand?
Complicated issues show clear links between causes and effects. The links may not be obvious at first, but with rigorous analysis they become clear. When a piece of machinery stops working, for example, we take it apart, find a broken piece and either fix or replace it. More generally, when we suspect that two events in a complicated system are causally related, we can be confident that if we just study it in the right way, applying enough intelligence and skill, the relationship will become clear. Then that understanding, and the correct way to solve the problem, can be documented for next time.
But when things get complex, rigorous analysis may not be enough. Usually, it takes a lot of time and careful, imaginative observation as well. We need to look for patterns -- which sometimes means waiting for them to emerge -- then apply insight and intelligence to the task of teasing out the relationships between cause and effect. This process takes time and usually requires repeated iterations, as well as an ability to understand and be sensitive to nuance. Simply following the right analytical steps isn’t going to do the job.
A lot of big IT project failures are rooted in organisations’ inability to understand this difference. If the tools you are applying are good for complicated environments but yours is complex, you won’t succeed. In fact, the surprising thing is just how surprised people are when projects in a complex environment fail – because the tools and methodologies they are using were suited to complication, not complexity.
