A new look at systems thinking, and how we know what we know
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This is a book for enterprise, business and software architects/analysts, and other business change agents. It is about terms and concepts used when discussing where and how some part of the world, especially but not only a social entity or a business, behaves in a way reasonably called a “system”. It is relevant also to teachers of computing, system and software engineering.
The book is a new look at – and a critical analysis of - the systems thinking field, rather than an endorsement or promotion of it. It applies “critical thinking” to the writings of systems thinkers such as Ackoff, Ashby, Beer, Clemson, Meadows, Midgely and von Foerster. So, be prepared for your favourite guru to be challenged!
Before you can understand and be sympathetic to the direction the analysis leads, you will probably need to take time to read the first three chapters thoroughly. Above all, you must recognize the schism between activity systems thinking and social entity thinking. While both are needed, and they can be pursued in parallel, attempts unify them in a grand general system theory end up being confused and confusing.
The aim is not to help you save the planet or radically transform your business. For both novice and seasoned system thinkers, the aims are to:
· present a concise, accessible and coherent overview of established ideas, with the addition of new insights
· expose issues in current system thinking and practice
· rescue systems thinking from the pseudo-science found today under the headings of “systems thinking”, “complexity science” and “management science”
· to help you avoid “jingle/jangle fallacies”
· to advance system science by promoting a distinction between activity systems and social entities that can help you change either or both.
What does system thinking add to thinking in general? Triumphs of human thinking include the laws of physics, chemistry, biology, psychology and economics. These laws typify, or model, the behavior of entities or phenomena we observe and envisage in the world around us.
What differentiates a system from any old entity, and a system model from any old model? Some overgeneralize as in “a system is a whole composed of interrelated parts” or “a slice of the world that changes state”. A definition that fits everything you can imagine is too vacuous to be of practical use.
Some define a system as a polythetic type from which different thinkers select different properties. This makes systems thinking a catch-all heading for diverse ways of thinking. It obscures the schism between activity systems and social entities in a blizzard of what appears meaningless babble to somebody who understands one rather than the other.
(The final part of the book addresses typification. Given a monothetic type, an individual must have all the properties. E.g. a “triangle” is a polygon with three sides, whose internal angles add up to 180 degrees. Given a polythetic type, an individual need not have all the properties. E.g. a “mother” may be typified as a female, birth giver, child rearer, partner of a father.)
Some borrow particular words from mathematics and physical sciences, but overload them with other meanings, or no clear meaning. The challenge is to avoid scientism (misapplying scientific ideas and practices to matters of human social and political concern), creating debatable analogies between different ideas, and obscuring the original meaning and value of the scientific terms and concepts.
Four particular views of systems thinking were developed in the second half of the 20th century.
· In cybernetics, Ashby's system is a set of state variables, governed by rules that determine how those variables change over time.
· In system dynamics, Forrester's system is a set of stocks (quantitative variables) that each grow and shrink, and cause related stocks to grow and shrink.
· In soft systems methodology, Checkland's system is set of interrelated business activities, performed by actors, that transform inputs into outputs of value to customers.
· In management science, Boulding's system is a population of individual actors, each with their own private memory, who communicate using messages.
The first three all involve creating or using a model that defines an entity's way of behaving as a rule-bound activity system. The rules govern how the entity changes state and/or transforms inputs into outputs. Note that rule-bound behavior can be linear or non-linear, homeostatic or progressive, predictable or chaotic.
Then, what about Boulding's population of individual actors? Suppose the actors are not rule-bound. Instead, they communicate and self-determine how they act, regardless of any given model. This is a different kind of entity. It might be called a “social system”, but to avoid confusion, we shall call it a social entity and distinguish it from any activity system it participates in.
Some systems thinking falls into category of speculative classifications and unproven models of how the world works. Some is dubious psychology, like the "Myers-Briggs Type Indicator", and "Neuro-Linguistic Programming".
Any effort to advance system architecture frameworks and systems thinking approaches, separately or together, has to expose and resolve ambiguities. In doing so, this book pursues several lines of thinking, related to even more general views of human cognition and philosophy. This book:
· relates modern EA and BA techniques to scientific foundations, for example in cybernetics and Lean manufacturing
· resolves half a dozen ambiguities in the terminology of modern EA and BA frameworks
· resolves many more ambiguities in 50 years of systems thinking discussion
· reconciles "self-organization" with activity systems thinking
· challenges pseudo-scientific uses of system theory terms and concepts
· counters the narrative of systems thinking as a kind of socio-cultural movement
· advances a type theory that may be used to settle some philosophical debates.4
In my first year at university, I studied psychology, human biology and the history and philosophy of science (from Descartes to Popper). I went on to complete a degree course in psychology, then started work as a programmer. Over those few years, I was struck by the entanglement of ideas in that mix of disciplines. It has taken me decades to disentangle them as far as I do here; and I hope this will help readers think more clearly about systems thinking,
This book is underpinned by five new or newly presented ideas.
2. Classifying causality into four kinds helps us to characterise what makes social entity thinking different.
3. Representing “change” as a three-dimensional phenomenon helps us to think more clearly about what it means to model and design changes to systems.
4. Separating meta system from system – allowing one actor to play a role in each - helps us to reconcile activity system thinking with “self-organization”, and gives us an alternative to second order cybernetics.
5. Using an "epistemological triangle" to distinguish models from what they model, and relate information to the phenomena it corresponds to, gives us a practical and useful alternative to the classic semiotic triangle.
There is a lot to take in. Some readers find the writing style is dense or terse. But if you stick with it, your patience will be rewarded. Readers have said: “The most important work on EA and applied System Theory today” and “Makes EA more powerful, coherent and usable.”
The book is structured into several parts. Since it serves a wide range of readers, and not every reader will want to read it in a linear fashion, here’s some advice on how to navigate the book.
· If you are new to systems thinking, read the first one or two chapters in each part, then return to what interests you.
· If you are a professional enterprise or business architect, start with “EA as systems thinking”, then return to read what interests you.
· If you are a seasoned systems thinker, skip around as you see fit.
· If you are interested in the evolution of intelligence and communication, psycho-biology, mathematics or philosophy, you should read the final part.
Systems thinking foundations
This part begins by resolving many ambiguities in the terminology used by systems thinkers. It proceeds to outline the classic ideas of social entity thinking and activity systems thinking. It concludes with an extensive analysis of abstraction in system description, and the dynamics of activity systems.
This part distils general principles from Ashby’s cybernetics, which addresses the storage and transmission of information, in memories and messages, to describe and direct the state of things. It discusses the application of cybernetics to management science, by Clemson and Beer.
This part further addresses confusions and ambiguities in discussion of “systems thinking” and “complexity science”. It discusses five big confusions, concerning system, purpose, behavior, holism and change. It goes on to discuss how Meadows tried to generalize from the distinct ideas from activity systems and social entity thinking, and points to ambiguities in “complexity science”.
EA as systems thinking
This part is not so much a “how to” method as an exploration and explanation of where systems thinking ideas are best used in and alongside any EA framework or method you already know, such as TOGAF or BIZBOK. It shows how distinguishing activity systems from social entities leads to a more consistent and coherent view of the whole systems thinking field. It distinguishes agile systems from agile system development. It discusses “self-organization” and a way of approaching “wicked problems”.
The earlier parts of this book are largely about the description of reality that occurs in the modelling of systems. This final part discusses the acquisition, communication and verification of information from a more psycho-biological perspective. It discusses how we know what we know, and describe things by typifying them in memories and messages. Three points of note.
· That the universe exists in a mind-independent way is the presumption of all modern science. It is implicit in the difference between age of the universe, and the age of planets on which life can exist.
· The fact that human (and other animal) experience of the world involves forming descriptions of real-world phenomena (including models of systems) in memories and messages is well explained as a side effect of biological evolution. It is implicit in the "good regulator theorem" of Ashby and Conant.
· There is no presumption in biology that descriptions or models are complete or wholly accurate, only that, often enough, they help the actors who use them to survive and replicate.
With the help of a new epistemological triangle, the final part explores some implications of the ideas above for semiotics, philosophy and mathematics.
Compiling the reference list will be the last step. Many of the works listed below can be found on the internet. This book clarifies, compares, contrasts and positions ideas expressed in these works, and relates them to EA. Some (notably Jackson and Meadows) provide more detail about associated techniques.
“Introduction to Cybernetics” (1957)
“Principles of the self-organizing system” (1962).
Ackoff, R.L. 1971. “Towards a system of system concepts” Management Science, vol. 17, no. 11.
“Re-Creating the Corporation - A Design of Organizations for the 21st Century” (1999)
“On The Mismatch Between Systems And Their Models”. (Ackoff 2003)
And in this article, Ackoff says a few things disputed later
“Language truth and logic” (A J Ayer)
“Diagnosing the system for organisations” (Beer 1985).
(Links to these have proved fragile, but you can probably find them.)
Bertalanffy, L. von. 1968. General System Theory: Foundations, Development, Applications. Revised ed. New York, NY, USA: Braziller.
See also this long history of Bertalanffy’s GST
And related notes: On “General Systemology”, and on its relationship to cybernetics.
Checkland, P. 1999. Systems Thinking, Systems Practice. New York, NY, USA: John Wiley & Sons.
“What is Management Cybernetics? (Barry Clemson and Allena Leonard, 1984)
”Creative Holism” (2003, Michael C Jackson)
“Thinking in Systems: a Primer” (2009, Donella Meadows)
“Luhmann’s theory of autopoietic social systems” (2001, David Seidl, Munich Business Research).
Other authors mentioned include Capra, Checkland, Churchman, Forrester, Midgely, Ostrom, Senge, Snowden and Von Foerster.
Churchman, C. W. 1968. The Systems Approach and its Enemies. New York, NY, USA: Dell Publishing.
Flood, R. L. 1999. Rethinking the Fifth Discipline: Learning Within the Unknowable. London UK: Routledge.
Hitchins, D. 2009. "What are the general principles applicable to systems?" INCOSE Insight, vol. 12, no. 4.
INCOSE. 2012. INCOSE Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, version 3.2.2. San Diego, CA, USA: International Council on Systems Engineering (INCOSE), INCOSE-TP-2003-002-03.2.1.
Lawson, H. 2010. A Journey Through the Systems Landscape. London, UK: College Publications, Kings College.
Ramage, M. and K. Shipp. 2009. Systems Thinkers. Dordrecht, The Netherlands: Springer.
Weinberg, G. M. 1975. An Introduction to General Systems Thinking. New York, NY, USA: Wiley.