Take a photo of a barcode or cover
A review by morgan_blackledge
An Introductory Guide to Systems Thinking by David Kerr
5.0
An Introductory Guide to Systems Thinking by David Kerr
Once in a while you learn a method, or an idea or a construct (e.g. statistics, or experimental design, or a Game of Thrones fan theory - https://shar.es/174Bjp - ) and it radically transforms your world view.
The experience is like having someone flip on a magic light switch, and suddenly you can see a new layer of information that was previously invisible.
Sort of like on CSI when they use one of those black light wands, and all of the "genetic information" on the sheets of the hotel room glows like radioactive maple syrup.
Once they turn the light wand off. The information is no longer "visible". But you know it's there, and (in this particular example) it's creepy AF.
I don't know about y'all. But CSI has ruined me for sleeping in cheep hotel rooms.
Getting back to the point. Once you encounter and assimilate one of these powerful theoretical constructs (let's call them thinking tools), suddenly you begin to see a whole new layer of information, organization or even a whole new dimension of analysis.
Once you see the other dimension, even after the "switch goes back off," you still know the dimension is there, and suddenly the world is a slightly (or significantly) richer, more meaningful, more organized experience.
Learning Systems Theory is one of these "magic light switch" experiences.
You start to encounter and learn the simple, intuitive component constructs of systems theory and after a critical mass of exposure and assimilation, a switch flips and suddenly, you're walking around in an augmented reality.
It's like a Robocop POV style flowchart digital overlay is now informing your interpretation of life's (formerly baffling) events.
It's like stumbling around in a maze, and suddenly you're wearing Google Glass*, and out of the corner of your eye, you see a Pac Man style overhead blueprint with a "you are here" dot and a clear path to the exit.
*That is, util the battery runs out or until you rip those dorky things off your face before anyone sees you, just sayin'.
It's like reading a book review and having the reviewer bombard you with metaphor after metaphor until you're literally screaming "ok, I get it already, God, move on dude!"
By now I assume you get the picture. Systems Theory is one of those "thinking tools" that enables you to make progress where you were once spinning your wheels (and maybe didn't even know it).
If you want a quick video primer on Systems Theory, check out Complexity Lab's YouTube channel, goto the play lists, and prepare to have your brain tickled (in a very good way).
The thing about systems theory is it's very visual and all about dynamical processes. So it is rather more easily explained via animated illustrations with voiceover.
I know there are a million of these PSA style animated, infotainment vids kicking around and wasting your life in 6 minute intervals, but Complexity Lab's stuff is exceptionally well done and the content is perfectly adaptable to the form.
Trust me:
https://m.youtube.com/channel/UCutCcajxhR33k9UR-DdLsAQ?noapp=1
One of the awesomely awesome things about Systems Theory is that it gives you a set of pretty simple tools that enables you to map and/or model the dynamical behavior of systems from the macro (2nd tier) perspective.
Sort of like a blueprint, which gives you just enough, information to build the house.
Systems Theory makes complex shit simple. This book keeps it simple. It's a minimally sufficient primer. It takes about an hour and change to read. But sort of like chess. Learning the rules is fairly easy. Learning how to play well takes practice.
You can think of this book as the "rule manual" for systems thinking. By that criteria, the book is a total success.
The Definitions of a System:
So how exactly does Systems Theory define what a system is.
According to the author, David Kerr:
A system can be defined as: “an interconnected set of elements that is coherently organized in a way that achieves something.”
"systems thinking is really a way of understanding the world that emphasises the relationships among a system’s parts rather than the parts themselves."
The traditional (reductive) approach to complex situations and problems is to deconstruct the subject of study to it's basic constant parts and try to understand each of them in isolation.
This has obviously been a very successful approach to understanding our world. Pretty much the entirety of scientific achievement has come via reductionist methods. But reductionism's use value has a limit.
Sometimes, breaking a system in to parts just breaks the system and obfuscates its real function, purpose, behavior etc.
Peter Senge says in his book, The Fifth Discipline: “dividing an elephant in half does not produce two elephants.”
When it comes to systems, particularly complex, nonlinear, dynamical systems with (for all intents and purposes) unpredictable emergent properties, we have to be able to analyze the system as a whole, over time in order to properly understand it.
In order to do this, we need a method of generalized abstraction that enables us to effectively chart, map and/or model what ever system were studying. Systems Theory is exactly that.
The following are some of the key concepts of systems theory according to David Kerr.
Elements:
"A key principle of systems is that they are comprised of “elements” or components."
"A car for example has an ignition system, fuel system and braking system. These components can work alongside each other, or they can be contained or embedded within each other."
As with reductionist approaches, it's still critical to identify the constituent elements of a system. But that's just the beginning of mapping a system.
Interconnections and Interrelationships:
"The elements that comprise a system are interconnected and are interrelated. These elements can affect the other elements within the system in a variety of ways."
Emergence:
"A key principle of systems thinking is the idea that 'the whole is greater than the sum of its parts'."
Emergence occurs when elements of a system come together and interact in such a way as to engender something (a function or behavior etc.) to manifest that is not present in the elements alone.
Life is the obvious example. Put the right chemistry together, and under the right conditions, life emerges.
System Purpose:
"What is emergent from a system is not necessarily the same as what is intended."
“the purpose of a system is what it does.”
Not necessarily what it claims to do.
"the purpose of a system has nothing to do with rhetoric and everything to do with behavior."
Here here!
Complexity:
"Detail Complexity -There is detail complexity if there are lots of different elements."
"Dynamic Complexity -There is dynamic complexity if there are a large number of connections between the elements themselves where each element can have a number of different states."
Stocks:
"A ‘stock’ in a system is, quite simply, a reservoir or store of resources of some kind. Examples of stock could include the water in a reservoir, the number of trees in a forest or the amount of cash an organisation has in the bank."
Inflows and Outflows:
"An inflow is a flow of information, energy or resource flowing into the stock, whereas an outflow is the information, energy or resources flowing out of the stock. Importantly, the rate of inflow and outflow will have an overall impact on the size of the stock".
Feedback:
"‘Feedback’ exists when changes in a stock affect the flows into or out of the same stock. For example, putting money into a saving account will attract interest, which subsequently increases the amount of money in the account. Hence, systems can change in response to feedback."
Balancing Feedback:
"Balancing feedback exists when the flow coming back into the system brings the system back into balance. For example, if I forget to eat, my body will tell me that I need to take on board fuel in the form of food."
Another term for this is homeostasis.
Dynamic Systems:
"Most complex systems are ‘dynamic’ -that is they have multiple parts or elements of the system that are changing, whilst the system itself remains distinctive, recognisable and retains its overall nature."
Open and Self-organizing Systems:
"Self-organising systems all exchange energy with their environments in this way, and are therefore all characterised as ‘open systems’".
Self-correction:
"The behaviour of the system may also be impacted by external interventions or external ‘perturbations’. In these circumstances the dynamic system may be able to react to the external intervention and correct itself accordingly.
Balance:
"Finding balance within complex systems such as organizations is not always easy. Whether we notice them or not, limits are always present. Sadly, the world appears to have a surfeit of managers who deliver results at great expense to those around them. A surprising number of them appear to achieve seniority by focusing on short-term delivery, before moving on and leaving others to deal with their mess."
Time Delays:
"As we’ve already mentioned, with complex systems such as organisations there are likely to be several components and several feedback loops operating all at once and from lots of different directions. When we introduce time delays into one or more of these feedback loops, systems start to become even more interesting. Time delays are likely to exist in all kinds of systems".
Resilience and Learning
"A formal definition of resilience is: the property of a material that enables it to resume its original shape or position after being bent, stretched, or compressed”.
"Lao Tsu understood this when he wrote the Tao te Ching over 2,500 years ago… Just as a sapless tree will split and decay, So an inflexible force will meet defeat; The hard and mighty lie beneath the ground While the tender and weak dance on the breeze above."
Model Construction:
"in order for us to figure out where we should best apply our interventions, we need to ‘map’ our understanding of the system we are concerned with. Here, there are a few important principles to consider, and a few questions we need to ask ourselves. First of all, what level of the system are you going to map? How sure are you that you are mapping at the right level, or will you need to map the system at several levels? Where are we drawing the boundaries of the system? Do we need to make the boundary of the system under consideration wider? How detailed should our feedback loops be? Do we need to plot every feedback loop and stock? And so on."
Stafford Beer, who said: “A model is neither true nor false; it is more –or less –useful.”
I'm well aware of how insufficient these constructs are out of context. But I hope This review will have at least inspired you to invest to hour and a half necessary to read this powerful little book (and maybe watch a vid or two at Completely Lab's YouTube channel).
Great (game changing) book.
Five Stars*****
Once in a while you learn a method, or an idea or a construct (e.g. statistics, or experimental design, or a Game of Thrones fan theory - https://shar.es/174Bjp - ) and it radically transforms your world view.
The experience is like having someone flip on a magic light switch, and suddenly you can see a new layer of information that was previously invisible.
Sort of like on CSI when they use one of those black light wands, and all of the "genetic information" on the sheets of the hotel room glows like radioactive maple syrup.
Once they turn the light wand off. The information is no longer "visible". But you know it's there, and (in this particular example) it's creepy AF.
I don't know about y'all. But CSI has ruined me for sleeping in cheep hotel rooms.
Getting back to the point. Once you encounter and assimilate one of these powerful theoretical constructs (let's call them thinking tools), suddenly you begin to see a whole new layer of information, organization or even a whole new dimension of analysis.
Once you see the other dimension, even after the "switch goes back off," you still know the dimension is there, and suddenly the world is a slightly (or significantly) richer, more meaningful, more organized experience.
Learning Systems Theory is one of these "magic light switch" experiences.
You start to encounter and learn the simple, intuitive component constructs of systems theory and after a critical mass of exposure and assimilation, a switch flips and suddenly, you're walking around in an augmented reality.
It's like a Robocop POV style flowchart digital overlay is now informing your interpretation of life's (formerly baffling) events.
It's like stumbling around in a maze, and suddenly you're wearing Google Glass*, and out of the corner of your eye, you see a Pac Man style overhead blueprint with a "you are here" dot and a clear path to the exit.
*That is, util the battery runs out or until you rip those dorky things off your face before anyone sees you, just sayin'.
It's like reading a book review and having the reviewer bombard you with metaphor after metaphor until you're literally screaming "ok, I get it already, God, move on dude!"
By now I assume you get the picture. Systems Theory is one of those "thinking tools" that enables you to make progress where you were once spinning your wheels (and maybe didn't even know it).
If you want a quick video primer on Systems Theory, check out Complexity Lab's YouTube channel, goto the play lists, and prepare to have your brain tickled (in a very good way).
The thing about systems theory is it's very visual and all about dynamical processes. So it is rather more easily explained via animated illustrations with voiceover.
I know there are a million of these PSA style animated, infotainment vids kicking around and wasting your life in 6 minute intervals, but Complexity Lab's stuff is exceptionally well done and the content is perfectly adaptable to the form.
Trust me:
https://m.youtube.com/channel/UCutCcajxhR33k9UR-DdLsAQ?noapp=1
One of the awesomely awesome things about Systems Theory is that it gives you a set of pretty simple tools that enables you to map and/or model the dynamical behavior of systems from the macro (2nd tier) perspective.
Sort of like a blueprint, which gives you just enough, information to build the house.
Systems Theory makes complex shit simple. This book keeps it simple. It's a minimally sufficient primer. It takes about an hour and change to read. But sort of like chess. Learning the rules is fairly easy. Learning how to play well takes practice.
You can think of this book as the "rule manual" for systems thinking. By that criteria, the book is a total success.
The Definitions of a System:
So how exactly does Systems Theory define what a system is.
According to the author, David Kerr:
A system can be defined as: “an interconnected set of elements that is coherently organized in a way that achieves something.”
"systems thinking is really a way of understanding the world that emphasises the relationships among a system’s parts rather than the parts themselves."
The traditional (reductive) approach to complex situations and problems is to deconstruct the subject of study to it's basic constant parts and try to understand each of them in isolation.
This has obviously been a very successful approach to understanding our world. Pretty much the entirety of scientific achievement has come via reductionist methods. But reductionism's use value has a limit.
Sometimes, breaking a system in to parts just breaks the system and obfuscates its real function, purpose, behavior etc.
Peter Senge says in his book, The Fifth Discipline: “dividing an elephant in half does not produce two elephants.”
When it comes to systems, particularly complex, nonlinear, dynamical systems with (for all intents and purposes) unpredictable emergent properties, we have to be able to analyze the system as a whole, over time in order to properly understand it.
In order to do this, we need a method of generalized abstraction that enables us to effectively chart, map and/or model what ever system were studying. Systems Theory is exactly that.
The following are some of the key concepts of systems theory according to David Kerr.
Elements:
"A key principle of systems is that they are comprised of “elements” or components."
"A car for example has an ignition system, fuel system and braking system. These components can work alongside each other, or they can be contained or embedded within each other."
As with reductionist approaches, it's still critical to identify the constituent elements of a system. But that's just the beginning of mapping a system.
Interconnections and Interrelationships:
"The elements that comprise a system are interconnected and are interrelated. These elements can affect the other elements within the system in a variety of ways."
Emergence:
"A key principle of systems thinking is the idea that 'the whole is greater than the sum of its parts'."
Emergence occurs when elements of a system come together and interact in such a way as to engender something (a function or behavior etc.) to manifest that is not present in the elements alone.
Life is the obvious example. Put the right chemistry together, and under the right conditions, life emerges.
System Purpose:
"What is emergent from a system is not necessarily the same as what is intended."
“the purpose of a system is what it does.”
Not necessarily what it claims to do.
"the purpose of a system has nothing to do with rhetoric and everything to do with behavior."
Here here!
Complexity:
"Detail Complexity -There is detail complexity if there are lots of different elements."
"Dynamic Complexity -There is dynamic complexity if there are a large number of connections between the elements themselves where each element can have a number of different states."
Stocks:
"A ‘stock’ in a system is, quite simply, a reservoir or store of resources of some kind. Examples of stock could include the water in a reservoir, the number of trees in a forest or the amount of cash an organisation has in the bank."
Inflows and Outflows:
"An inflow is a flow of information, energy or resource flowing into the stock, whereas an outflow is the information, energy or resources flowing out of the stock. Importantly, the rate of inflow and outflow will have an overall impact on the size of the stock".
Feedback:
"‘Feedback’ exists when changes in a stock affect the flows into or out of the same stock. For example, putting money into a saving account will attract interest, which subsequently increases the amount of money in the account. Hence, systems can change in response to feedback."
Balancing Feedback:
"Balancing feedback exists when the flow coming back into the system brings the system back into balance. For example, if I forget to eat, my body will tell me that I need to take on board fuel in the form of food."
Another term for this is homeostasis.
Dynamic Systems:
"Most complex systems are ‘dynamic’ -that is they have multiple parts or elements of the system that are changing, whilst the system itself remains distinctive, recognisable and retains its overall nature."
Open and Self-organizing Systems:
"Self-organising systems all exchange energy with their environments in this way, and are therefore all characterised as ‘open systems’".
Self-correction:
"The behaviour of the system may also be impacted by external interventions or external ‘perturbations’. In these circumstances the dynamic system may be able to react to the external intervention and correct itself accordingly.
Balance:
"Finding balance within complex systems such as organizations is not always easy. Whether we notice them or not, limits are always present. Sadly, the world appears to have a surfeit of managers who deliver results at great expense to those around them. A surprising number of them appear to achieve seniority by focusing on short-term delivery, before moving on and leaving others to deal with their mess."
Time Delays:
"As we’ve already mentioned, with complex systems such as organisations there are likely to be several components and several feedback loops operating all at once and from lots of different directions. When we introduce time delays into one or more of these feedback loops, systems start to become even more interesting. Time delays are likely to exist in all kinds of systems".
Resilience and Learning
"A formal definition of resilience is: the property of a material that enables it to resume its original shape or position after being bent, stretched, or compressed”.
"Lao Tsu understood this when he wrote the Tao te Ching over 2,500 years ago… Just as a sapless tree will split and decay, So an inflexible force will meet defeat; The hard and mighty lie beneath the ground While the tender and weak dance on the breeze above."
Model Construction:
"in order for us to figure out where we should best apply our interventions, we need to ‘map’ our understanding of the system we are concerned with. Here, there are a few important principles to consider, and a few questions we need to ask ourselves. First of all, what level of the system are you going to map? How sure are you that you are mapping at the right level, or will you need to map the system at several levels? Where are we drawing the boundaries of the system? Do we need to make the boundary of the system under consideration wider? How detailed should our feedback loops be? Do we need to plot every feedback loop and stock? And so on."
Stafford Beer, who said: “A model is neither true nor false; it is more –or less –useful.”
I'm well aware of how insufficient these constructs are out of context. But I hope This review will have at least inspired you to invest to hour and a half necessary to read this powerful little book (and maybe watch a vid or two at Completely Lab's YouTube channel).
Great (game changing) book.
Five Stars*****