Having worked in automated systems analysis and optimization across several fields, I think Meadows' thinking is very instructive. Some of her notions which stand out in particular to me:
* The importance of the effect of feedback loops in complex system. When unexpected or counterintuitive behavior occurs, a hidden or misunderstood reinforcement feedback loop is often at root.
* The requirement that systems that seek to automate or optimize complex interactive systems be constantly-adaptive because the system itself will interact with the observation/analysis/optimization acts. This can seem like crazy voodoo at first, but it is undeniable when you start to experience it in action.
* Understanding of cost externalities vs benefit rewards for system actors and how they relate to system sources/sinks (or "stocks and flows"). This drives so much of our economy, as well as the subsystems which feed it and she has some illuminating thoughts and analyses on addressing these issues broadly.
This all of course goes well beyond the more basic material on oversimplification vs complexity in simulation or interventions, limits of rationality in system-actors, nonlinearity vs linear thinking, boundary conditions/non-boundary conditions, etc.
For those intrigued by Systems Thinking but want to explore it in context of startups (or business in general), consider reading Scaling Lean by Ash Maurya [1]. The whole Customer Factory [2] is based on a causal loop diagram of McClure's Pirate Metrics (AARRR); Ash also incorporates a lot of Theory of Constraints into the book. Highly recommended.
Systems Thinking was also part of Intel's culture under Andrew Grove (at least at the leadership level, from what I can tell). You can see evidence of that in his super-acclaimed book, High Output Management [3], especially the first couple of chapters (though he doesn't refer to it directly). Rich Jolly, another executive @ Intel, actually has a PhD in Systems Science and also wrote a book, Systems Thinking for Business [4], although it's definitely a bit more advanced and more theoretical than the others listed here.
And, I whole-heartedly agree - Meadows' book is simply an AMAZING treatise of Systems Thinking. It's a great place to start regardless of your background (the beauty of ST is that it is applicable to a broad range of fields and disciplines).
As an aside, does anyone know of any good/free/open source tools for drawing causal loop diagrams, or better yet, running simulations?
System Dynamics remains a woefully underused theoretical system for modeling complex systems and understanding the feedback loops involved and the way the structure of the system influences the outcome. I know of no one that explains it more clearly than Donella Meadows (RIP).
Isn't it 50% New Age pseudoscience though? I mean, how would you respond to that criticism? Particularly at the level of detail that might be taught in schools, I wonder about its falsifiability.
I say this as someone who is prepared to consider the idea of systems thinking as a "second tier" cognitive strategy, as advanced by Wilber etc. I can't imagine that idea getting mainstream traction.
The world is changing, as it's becoming evident that everything is more and more interconnected, and while studying History can help you figure some of these connections out, I believe that System Thinking gives a better insight about broader domains. After all, it's engineering applied to a broad field - not just maths, computers, and biology, but it's about finding out the connections that make our society/behaviors the way they are.
It's like psychology. Some people nowadays still don't consider it a science, although it applies similar principles to human/animal behavior, but it's a science, isn't it?
I believe it's a good way to discover new patterns to build more sustainable societies, as psychology is a good way to improve human life and relations among humans.
Sure, some "systems thinking" falls under the woo-umbrella. But I'd hardly call the hard systems sciences New Age pseudoscience. System Dynamics, Agent-Based Modeling, etc all have methods and evaluative feedback loops in terms of measuring whether they are predictive or not. If you system dynamics model predicts a 10-year S-curve and you see 20 years of exponential growth, you probably don't have the model correct.
If you stop at the level of "everything is connected" - it can lead to all sorts of woo-ey conclusions - much like a light understanding of quantum physics can (some of which I happen to agree with, but aren't yet falsifiable) - but SD was developed at MIT by engineers...
I'm not sure how to respond to it being 50% new age pseudoscience, because I'm having trouble even putting my finger on that as a criticism. Are there more specific criticisms? A lot of systems thinking comes down to basic rationalism and causality, doing things like checking assumptions and conclusions through critical thinking. Maybe that part of it isn't rooted in empiricism, but that's not a bad thing at all. The rationalism vs empiricism debate goes back centuries.
This has really influenced my thinking as a strategist and architect, particularly around when to introduce and remove process in teams. In particular, trying to figure out how to engineer reinforcing loops so that your teams and groups experience virtuous cycles of productivity.
I haven't read "Thinking in Systems," but I'm wondering if it's similar in spirit to Mindstorms, which advocated teaching in terms of thinking in microworlds, or systems.
We've built a platform that helps people diagram, explore, and share the complex systems Donella talks about. Her work has been a major influence on Kumu and we even have a quote of hers on the manifesto.
My guess (I didn't downvote) is you would have fewer downvotes if you a) addressed the comment readers in general rather than the poster of the article in specific, and b) explained "what we're doing at Kumu" that is relevant to either the article or the audience.
Your linked manifesto shows that you care about similar issues to Donella Meadows and the OP, but doesn't shed any light on what Kumu is or why the audience would be interested in it.
I had to browse to your front page to discover that you appear to make a diagramming tool for causal loop diagrams along other things, which is relevant and potentially useful to people interested in systems thinking. I've bookmarked it and will try it out sometime!
Your follow-up comment protesting the downvotes was a lot more informative than the comment being downvoted :)
Self-promotion / employment solicitation is generally strongly frowned on. I'm finding your comment relevant and have moderated accordingly. Providing a bit more by way of detail on what you're doing and what specifically you're focusing on would be helpful -- the website's a tad vague on that.
It's also almost always an error to comment on downvotes themselves on your own comments or posts.
Strongly disagree: people here are OK with capitalism in general, and with promoting things we have worked hard to create, as long as it's appropriate for the conversation.
There's pitching an idea or work that you've done, which seems to work, even where it goes against the HN hivemind (see especially @idlewords / Maciej Czeglowski), where good citizenship's been established.
I thought there was a general guideline against submitting employment posts, though I can't find that in the HN guidelines or FAQ. Either it's mentioned elsewhere, has changed, or my weed's too good.
As for the response -- I'm commenting on what I've observed over years. Some forms of more direct promotion seem to provoke the negatives. Sometimes I agree, sometimes not.
It's pretty much always been ok to promote yourself here when you've worked hard on something, and the promotion is relevant. What no one wants are spammers, but it's super easy to tell the difference in most cases. You look at that guy's posting history, he's not just pushing his site.
The interested reader may also like this slideshare overview of Thinking in Systems ch. 1-3: http://www.slideshare.net/sandhyajohnson/thinking-in-systems...
Another of her well-known works is Leverage Points, which is also great and goes into more detail on some of that which is summarized in OP's linked article. http://donellameadows.org/archives/leverage-points-places-to... , https://en.wikipedia.org/wiki/Twelve_leverage_points
Having worked in automated systems analysis and optimization across several fields, I think Meadows' thinking is very instructive. Some of her notions which stand out in particular to me:
* The importance of the effect of feedback loops in complex system. When unexpected or counterintuitive behavior occurs, a hidden or misunderstood reinforcement feedback loop is often at root.
* The requirement that systems that seek to automate or optimize complex interactive systems be constantly-adaptive because the system itself will interact with the observation/analysis/optimization acts. This can seem like crazy voodoo at first, but it is undeniable when you start to experience it in action.
* Understanding of cost externalities vs benefit rewards for system actors and how they relate to system sources/sinks (or "stocks and flows"). This drives so much of our economy, as well as the subsystems which feed it and she has some illuminating thoughts and analyses on addressing these issues broadly.
This all of course goes well beyond the more basic material on oversimplification vs complexity in simulation or interventions, limits of rationality in system-actors, nonlinearity vs linear thinking, boundary conditions/non-boundary conditions, etc.