Big Ideas About Systems

A slide at ISSS wonders what the big ideas about systems are:

*

Here’s my take:

  • Stocks & flows – a.k.a. states and rates, levels and rates, integration, accumulation, delays – understanding these bathtub dynamics is absolutely central.
  • Feedback -positive and negative feedback, leading to exponential growth and decay and other simple or complex behaviors.
  • Emergence – including the idea that structure determines behavior, the iceberg, and more generally that complex, counter-intuitive patterns can emerge from simple structures.
  • Relationships – ranging from simple connections, to networks, to John Muir’s insight, “When we try to pick out anything by itself, we find it hitched to everything else in the Universe.”
  • Randomness, risk and uncertainty – this does a disservice by condensing a large domain in its own right into an aspect of systems, but it’s certainly critical for understanding the nature of evidence and decision making.
  • Self-reference, e.g., autopoiesis and second-order cybernetics.
  • Evolution – population selection and modification by recombination, mutation and imitation.**
  • Models – recognizing that mental models, diagrams, archetypes and stories can only get you so far – eventually you need simulation and other formal tools.
  • Paradigms – in the sense in which Dana Meadows meant, “The mindset or paradigm out of which the system — its goals, power structure, rules, its culture — arises.”

If pressed for simplification, I’ll take stocks, flows and feedback. If you don’t have those, you don’t have much.

* h/t Angelika Schanda for posting the slide above in the SD Society Facebook group.

** Added following a suggestion by Gustavo Collantes on LinkedIn, which also mentioned learning. That’s an interesting case, because elements of learning are present in ordinary feedback loops, in evolution (imitation), and in self-reference (system redesign).

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