The Naïve Dream of Systemic Maps

Unseen Risks in Complex Environments

Causal Loop Diagrams

When seeking improvement, merely optimizing the parts of the system is not enough. This tautology was popularized in the 1990s. Management teams were asked to think systemically: consider the whole and the interactions between its parts, especially in terms of cause and effect. For example: Albert is angry at Bohr, which makes Bohr angry at Albert, which makes Albert even angrier at Bohr, which makes Bohr even… — in an endless causal loop.

When Cause and Effect Won’t Walk Hand in Hand

Creating systemic maps of all parts is a terrific idea. Unfortunately, however, the complexities of our reality might soon render it useless. Here, new parts are constantly being born, and old ones are dying as we speak. New interactions are established between the parts, and others suddenly disappear. In addition to this constant state of change, the number of parts and interactions is vastly greater than any human, or even a computer system, can keep track of. And frosting on the cake: other “wholes” are penetrating, and thus changing, our “whole” in a coevolution process.

There Are Better Ways

You may already know that the recent twenty years has given us a body of new methods for working in such complex environments. These methods affirm, for instance, diversity rather than specialization, guiding principles rather than strict rules, parallel contradictory theories rather than premature alignment, and direction rather than goals. In fact, these are all based on the lesson we may learn from this very article: Doing the same thing twice might give us two different outcomes. Or as a Albert perhaps would have phrased it: “Insanity is doing the same thing over and over and always expecting identical results.”



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Staffan Nöteberg

🌱 Twenty Years of Agile Coaching and Leadership • Monotasking and Pomodoro books (700.000 copies sold)