One of the key aspects of managing a complex system is the switch from fail-safe design to safe-fail experimentation. The nature of a complex system means that we cannot know in advance what will happen, so we cant design for a desired outcome. Instead parallel and possible contradictory experiments allow us to test the evolutionary possibilities of the system. If an experiment starts to produce beneficial results then we amplify it, if negative (and here safe-fail comes in) we dampen it, or even attempt its destruction. Now most people, other than obscurantist post-Popperniarian positivists (you know you are) get this. But the question then follows, how do you select the experiments? What are the criteria of justification under conditions of uncertainty?
My normal answer is two provide two criteria for an experiment to be run.
Now in both these cases we need to be aware that we will be running parallel experiments in the expectation of substantial failure. That is however more desirable than a one time bet, in which we attempt to forecast outcomes where the future is unknowable, or where we suffer analysis paralysis not able to make any decision without guarantees of success.
Neither is it about gut feel and inspirational leadership. It is a structured approach based on low risk discovery. There is a science to managing uncertainty and theories of coherence are central to the develop of that science and its practice.
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