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4.18 AVERAGE
4.18 AVERAGE
Not quite what I expected but not entirely disappointed either. For the record, I did study dynamical systems from a purely mathematical standpoint in undergrad and beyond. So I am familiar with the more complex aspects of the models she mentions in the book, which is to say, I found the material a little too high-level. I understand this is meant to be a primer, so I am not dinging for it.
The first few chapters are easier to get through than the middle chapters where there the author's attempt to oversimplify complex situations and behaviors cause the material to lose some of it's efficacy. Also, you can probably skim this book's later chapters by just reading the last paragraph in each section - it could have been half the length.
Here are the main points:
Overall, a good summary of Systems Theory with great advice on how to navigate their complex ins-and-outs.
The first few chapters are easier to get through than the middle chapters where there the author's attempt to oversimplify complex situations and behaviors cause the material to lose some of it's efficacy. Also, you can probably skim this book's later chapters by just reading the last paragraph in each section - it could have been half the length.
Here are the main points:
- A system is an interconnected set of elements that achieves something.
- Systems consist of elements, interconnections, and a function or purpose.
- Understanding a system's purpose requires observing its behavior.
- Stocks are accumulations of material or information at a given time.
- Flows cause stocks to change over time.
- Feedback loops influence system behavior.
- Systems can be deceptive when focusing on individual events.
- Nonlinearities can change the strengths of feedback loops.
- Boundaries are artificially created and may limit understanding.
- Delays are pervasive in systems and affect response times.
- There are various points of intervention in a system.
- Guidelines for living in a world of systems include understanding, challenging mental models, sharing information, using language carefully, focusing on what is important, implementing feedback policies, considering the well-being of the whole system, listening to the wisdom of the system, taking responsibility, maintaining a learning mindset, embracing complexity, expanding time horizons, challenging disciplinary boundaries, broadening the circle of caring, and upholding the goal of goodness.
Overall, a good summary of Systems Theory with great advice on how to navigate their complex ins-and-outs.
Thinking in Systems gives you a useful new perspective for thinking about complex structures, whether you are an engineer, an economist or just want to understand the world a bit better.
This was a great intro to systems thinking - mostly high level analysis of systems and how to influence systems. I feel like it barely scratched the surface of this field, but it still packed a lot into a relatively short text.
Overall pretty interesting if not a bit dry and preachy at times though I suppose that’s to be expected.
Some interesting insight into how systems work and how people work as well. People are generally predisposed to pessimism and this book addresses the regular reinforcements that should occur to take this into account. The author states that people believe someone saying they can’t do something over someone telling them they can. I think that’s a pretty interesting and fair observation.
My most memorable takeaways are that the GNP doesn’t matter alone without taking into account things that are hard to measure. Excluding health, happiness, and quality of life from systems discussions negatively impacts the system. Rivers flood more than lakes. Learn how to express yourself with the right terms for your audience and subject (inuit populations have 53 words to describe snow).
Overall a recommend giving it a read. Cool graphs too.
Some interesting insight into how systems work and how people work as well. People are generally predisposed to pessimism and this book addresses the regular reinforcements that should occur to take this into account. The author states that people believe someone saying they can’t do something over someone telling them they can. I think that’s a pretty interesting and fair observation.
My most memorable takeaways are that the GNP doesn’t matter alone without taking into account things that are hard to measure. Excluding health, happiness, and quality of life from systems discussions negatively impacts the system. Rivers flood more than lakes. Learn how to express yourself with the right terms for your audience and subject (inuit populations have 53 words to describe snow).
Overall a recommend giving it a read. Cool graphs too.
Solid and enjoyable baseline intro to systems thinking. Primarily for economics and environmental systems. Has a nice list of system pathologies to look out for.
inspiring
fast-paced
The best book to start a journey into the perplexity of everything.
Thinking in systems is a fascinating, if somewhat dated book. Meadows was a pioneering contributor to systems thinking, a member of the Limits to Growth membership, who's life and career was cut tragically short by cerebral meningitis. Thinking in Systems is assembled from notes and lecturers, and represents a consistent whole anchored by the material in the essay Leverage Points: Places to Intervene in a System
Systems are modelled by stocks, flows, and sinks. Stocks are quantities that we care about, hopefully measurable, often not. Flows increase or decrease stocks, and can be fixed or vary based on natural, human, controlled, or uncontrolled processes. Sinks are much like stocks, but are assumed to be set to an infinity, an approximation that makes calculation easier. The basic dynamics of systems are feedback loops, delays, and oscillations. Negative feedback loops make the level of a stock trend towards a finite value. Positive feedback does the opposite, increasing the amount of a stock higher and higher until some countervailing feedback loop appears. And finally, due to innate delays, systems tend to oscillate rather than settling at a single configuration.
Where this gets tricky is first in mathematical modelling, because assigning limits to systems and making sure that the models match the real world is more of an art than a science ("All models are wrong, but some are useful" --George Box). And second, in convincing others of the somewhat counter-intuitive results of systems thinking. The one that jumped out to me was a simple inventory management model which entered into wildly uncontrolled oscillations as the decision to re-order became more responsive to inventory levels. Desired behave was achieved by basing re-order decisions on bi-weekly moving averages.
Meadows usefully provides the math at the end of the book. I feel like a contemporary update would include computer resources for experimentation and examples updated from the immediate post-Cold War where this book was written, but this is a useful book.
Systems are modelled by stocks, flows, and sinks. Stocks are quantities that we care about, hopefully measurable, often not. Flows increase or decrease stocks, and can be fixed or vary based on natural, human, controlled, or uncontrolled processes. Sinks are much like stocks, but are assumed to be set to an infinity, an approximation that makes calculation easier. The basic dynamics of systems are feedback loops, delays, and oscillations. Negative feedback loops make the level of a stock trend towards a finite value. Positive feedback does the opposite, increasing the amount of a stock higher and higher until some countervailing feedback loop appears. And finally, due to innate delays, systems tend to oscillate rather than settling at a single configuration.
Where this gets tricky is first in mathematical modelling, because assigning limits to systems and making sure that the models match the real world is more of an art than a science ("All models are wrong, but some are useful" --George Box). And second, in convincing others of the somewhat counter-intuitive results of systems thinking. The one that jumped out to me was a simple inventory management model which entered into wildly uncontrolled oscillations as the decision to re-order became more responsive to inventory levels. Desired behave was achieved by basing re-order decisions on bi-weekly moving averages.
Meadows usefully provides the math at the end of the book. I feel like a contemporary update would include computer resources for experimentation and examples updated from the immediate post-Cold War where this book was written, but this is a useful book.
challenging
informative
reflective
medium-paced
My much-appreciated Goodreads friend Philippe introduced me to systems thinking 10 years ago. That really was a world that suddenly opened up: for the first time I saw that in addition to the approach that wis based on reductionist science and technology, largely traceable to Francis Bacon and René Descartes, there was a completely different approach that, in my opinion, did much more justice to the complexity of the reality in which we live. At Philippe's suggestion, I read a number of books that introduced me to systems theory in all its facets. Because let's be clear: in that world too, complexity is the order of the day, with numerous approaches that have both great merits and clear shortcomings.
In this book Donella Meadows (1941-2001) offers an introduction. According to the editor, it is based on a manuscript from 1993 that was never published, and of which the concrete examples are sometimes slightly outdated. That does not alter the fact that I am still quite impressed by the 'house of systems thinking' and by Meadows' own hands-on approach. This book can really be called a handbook, with case studies in which the author illustrates the basic aspects of systems thinking. To my taste, these case studies come a bit too much from the economic or technological angle, but that may be because this was Meadows' specialization. I will have to ask him explicitly again, but that may also explain why my friend Philippe did not appreciate her approach, that – according to him – too much exudes the MIT spirit.
I must concede I still have a problem with the word 'system', because in my intuitive dictionary that still suggests too much of a mechanistic worldview, whilst mechanistic thinking is absolutely contradictory to systems thinking. For the same reason also structuralism absolutely clashes with systems thinking (although it seems that there are certain directions within systems thinking -they are not discussed here - that lean very close to this). And, to add injury to insult, also holism is not really a suitable approach, because in most directions of holism the whole takes precedence over the parts, while in true systems thinking the complex, sometimes chaotic interaction between parts and the whole always is primeval. (As said, the world of systems thinking itself is quite a complex world). So, for want of a better word, we will have to make do with that word ‘system’.
Finally, an aspect that Meadows rightly points out repeatedly: a system essentially is a temporal phenomenon; you have to observe it over time, and you can only work with it if you fully respect that factor of time (some consequences of interventions only emerge after some time). As a historian, I am of course happy to hear that. And it made me wonder whether we might be better off replacing the term ‘system’ with the term ‘process’, but maybe now I’m just complicating matters. Anyway, as you can notice, Meadows’ book not only offers a nice introduction, but it also immediately sets a whole thought process in motion. If that is not ‘systemic’, then I don’t know what is.
informative
medium-paced
informative
fast-paced