System Dynamics

To do system innovation we have to work with the relationships between the parts and that starts by creating some kind of model for those linkages or connections. An ideal modeling method for this is system dynamics. Over the past several decades system dynamics has proven to be a very effective and useful tool for mapping out the relationships and basic dynamics within complex organizations.

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[omerfadem]

I was taking a course called "System Dynamics and Control" when I was a mechanical engineering student. At that time I realized that this is how human brain deals with complexity. There is no way to know everything. Instead we experience things and take feedback from them then we adapt ourselves to the conditions. For example we assume that we are intelligent enough to pass an exam without studying it. When we fail the exam we realize that this is the wrong way to approach and we change the strategy. Understanding complex systems help us to understand ourselves. Thanks for the videos.

[sparky]

I like the idea of complex systems because it gives a scientific explanation for a lot of ideas in philosophy and eastern religions.

Like for example the idea of letting go of the desire to control and plan everything around you because this approach often ends up giving you exactly the opposite of what you want. We cannot hope of being in control of a complex system. The best we can do is learn to live in harmony with it.

[flyingguitarist]

Have you heard about Agent-based modelling?
Coz it ABM covers the limitations of systems dynamics model i.e systems dynamics is aggregrated and homogenoues with no Time-Location constraints, missing the details. ABM covers the big picture as well as the details.

[jessedampare]

The highlight of my days are when you upload videos of systems innovation.

[jonlaban]

Gold rushes always collapse...

There is currently a gold rush in Virginia USA building data centres 😘

[SantaBJ]

My only real problem with systems dynamics theory (at least as presented here, and commonly elsewhere) is in some of its basic assertions, such as how systems tend toward equilibrium. This is just plain wrong outside of a very specific and very rare type of dynamic systeme: A closed, iterative system. That kind of system is hard to find in reality. Truth is, system interfaces (the interfaces between distinct systems) disequilibriate, and most systems change continuously (usually within a metastable framework). Entrainment through shared, predictable behaviours and standard processes gets around this by, in essence, embedding the interfaced systems within a shared system. This is part of why this error persists in the theory, because hidden (or ignored) entrainment makes embedded systems appear discrete.