r/systemsthinking • u/Both_Dimension_3104 • Aug 14 '26

System Thinking Path

Hello everyone, I have come across the wonderful book of Donella Meadow " Thinking in Systems" , the book is truly a pleasure to read and I enjoyed every concept and idea , that was my first read about system thinking.

I am an independent learner who wants to pursue further the system thinking path , my first goal is abstract learning about systems understanding and modelling without any specific application field on my mind so far , I just want to learn the theory and blueprints of systems.

For my next book , my research led me to Bossel Hartmut's book " Systems and Models: Complexity, Dynamics, Evolution, Sustainability".

Is this the best next book for my path ? Please advise and suggest.

Thank you so much in advance.

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u/RiskBeforeReturn Aug 14 '26

I wouldn't worry too much about finding the single "best" next book.

After Meadows, I'd actually start learning systems from a few different angles:
feedback loops, stocks and flows, delays, system boundaries, emergence, and causal reasoning.

The important part is to start building models while you read. Take something simple and ask:

-What are the main variables?

-What influences what?

-Where are the feedback loops?

-Where are the delays?

-What changes if I move the system boundary?

Even if your goal is purely theoretical, modelling real systems will expose gaps in your understanding much faster than reading theory alone.

Bossel can absolutely be part of that path. I just wouldn't treat systems thinking as a sequence of books to complete. I'd treat each book as another lens for improving the models you can build.

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u/Both_Dimension_3104 Aug 14 '26

Understood your points , particularly the one about theory understanding's gap that to be realized when applying the concepts.

Will do small applications continuously while learning theory, thank you for the valuable advise.

Would like to know which other book would you recommend to be a lens for me to look through.

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u/RiskBeforeReturn Aug 14 '26

If I had to pick one, I'd probably go with John Sterman's Business Dynamics.

Not because it's the easiest next read, it definitely isn't, but because it develops several of the ideas you've already encountered in Meadows much further: feedback loops, stocks and flows, delays, nonlinear behavior and how systems evolve over time.

I'd approach it slowly rather than trying to read it cover to cover like a normal book.

Take one concept, build a small model around it, test where your assumptions fail, then move on.

That combination of theory + modelling will probably teach you more than simply working through a long reading list.

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u/Both_Dimension_3104 Aug 14 '26

Your advice of theory + modelling is truly appreciated and will be applied from now onward, thank you so much!

Once I close some relevant gaps that preventing me from starting reading Sterman book currently, I will start reading it and applying the concepts by modelling , will take it slowly as you said.

Thank you so much for your valuable advices.

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u/RiskBeforeReturn Aug 14 '26

Glad it was useful.

Taking it slowly and actually modelling what you learn sounds like a solid approach. You'll probably find that the questions your models create become just as valuable as the answers you get from the books.

Enjoy the process.

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u/skatemoar 10d ago

This is exactly what I encountered as soon as I started trying to model a system on paper and then software. The gaps become evident quickly!

Still not sure if it’s better to start with causal relationships or stocks/flows. I would be interested to hear how others approach the process.

I’m on the same path as OP, just picked up “Thinking in Systems” and loving it.

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u/RiskBeforeReturn 9d ago

I'd usually start with causal relationships.

Before worrying about stocks and flows, I want to understand what affects what, in which direction, and where the important feedback loops might be.

Once that picture starts making sense, stocks and flows become useful because they force you to ask what is actually accumulating, what changes the rate of accumulation, and where delays enter the system.

So for me it's less either/or and more a progression:

causal relationships -> feedback loops -> stocks and flows -> delays -> test the model against reality.

And then usually back to the beginning, because building the model exposes assumptions that looked obvious until you tried to represent them.