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Complicated issues have a lot of parts that interact in some predictable, usually linear, fashion. The more elements there are to the issue, the more complicated it becomes but it retains the feature of having some predictability.

Complex systems not only have a lot of parts but they have multiple (and frequently unclear) feedback loops, tipping points, and non-linear impacts. These systems are inherently difficult to predict.

With a complicated system, with enough knowledge, you can usually make a reasonable prediction of what the outcomes are likely to be even if the problem has several root causes. Within limits, you can plan a project from start to finish with predictable adjustments along the way.

With a complex system, it is virtually impossible to predict the final outcome. Changes to complex systems are frequently characterized by having numerous unintended outcomes. It is usually the case that there cannot be enough information to allow a reliable forecast of outcomes. Instead, the process requires robust risk mitigation and incremental adjustments that move you towards the desired outcome.

Structured decision-making is valuable in both cases but especially critical when dealing with complex systems

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