Difference between revisions of "Systems Thinking"
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More information on the [[Systems Failure Approach]]
More information on the [[Systems Failure Approach]]
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=== [[Strategic Options Development and Analysis (SODA)]] ===
Revision as of 23:17, 26 December 2017
- 1 Defining Systems Thinking
- 2 Systemic and / or Systematic
- 3 Systems Conceptualisation
- 4 Hard Systems Thinking or Traditional Systems Engineering
- 5 Soft Systems Thinking
- 6 Systems of Power or Coercive Systems
- 7 System Of Systems
- 8 The Intelligent Complex Adaptive System Of Systems (ICASOS) Model
- 9 Systems Thinking and Enterprise Systems Engineering
- 10 Systems Thinking and (Real) Enterprise Architecture
- 11 Systems Concepts and Principles
- 12 Systems Laws
- 13 Systems Thinking and Operational Research
- 14 Systems Methodologies, Methods and Techniques
- 14.1 Traditional Systems Engineering
- 14.2 Integrated DEFinition (IDEF) Methods
- 14.3 General System Theory
- 14.4 The Systems Thinking Iceberg Model (Meadows)
- 14.5 System Dynamics (Forrester)
- 14.6 System Dynamics (Senge)
- 14.7 Management Cybernetics
- 14.8 The Formal System Model
- 14.9 Systems Failure Apporach
- 14.10 Viable System Diagnostics (VSD)
- 14.11 The Viable System Model (VSM)
- 14.12 Strategic Options Development and Analysis (SODA)
- 14.13 Strategic Assumptions Surfacing and Testing (SAST)
- 14.14 The Strategic Choice Approach (SCA)
- 14.15 Critical Systems Heuristics (CSH)
- 14.16 Appreciative Systems
- 14.17 Social Systems
- 14.18 Learning Systems
- 14.19 Critical Systems
- 14.20 Human Activity Systems (HAS)
- 14.21 Socio-Technical Systems (STS)
- 14.22 Soft Systems Methodology (SSM) (Checkland)
- 14.23 Soft Systems Methodology (SSM) (Wilson)
- 14.24 System Of Systems Methdologies (SOSM)
- 14.25 System Of Systems (SOS)
- 14.26 Total Systems Intervention (TSI)
- 14.27 Complex Systems
- 14.28 Autonomous Systems
- 14.29 Adaptive Systems
- 14.30 Cynefin
- 14.31 Socio-Technical Systems (STS)
- 14.32 Organizational Cybernetics
- 14.33 Systemic Enterprise Architecture Management (SEAM)
- 14.34 Interactive Planning
- 15 Systemic Intervention
- 16 Systemic Innovation
- 17 Systems Standards
- 18 Systems Thinking in UK Universities
- 19 Internet-Based Courses on Systems Thinking
- 20 Navigation
Defining Systems Thinking
"Systems Thinking" refers to a discipline of both Theory (ie an academic discipline) and Practice (ie a discipline used by consultants and practitioners) founded on the notion of a "System" - and a philosophy of systemic causation. Wikipedia tautologously (circularly) defines Systems Thinking as the study of systems. Others, in similarly tautologous fashion, define Systems Thinking as an approach to analysis based on applying the notion of a System to construct models of the "systems collection" of concern (and under study). Barry Richmond defines Systems Thinking as both an "art and science" - involved in the deeper (implied better) understanding of some segment of the world. According to the UK Open University's "Systems Thinking and Practice" course:
The essence of systems thinking and practice is in ‘seeing’ the world in a particular way, because how you ‘see’ things affects the way you approach situations or undertake specific tasks.
According to yet others "Systems Thinking" is defined as:
Systems thinking is a management discipline that concerns an understanding of a system by examining the linkages and interactions between the components that comprise the entirety of that defined system.
Systems thinking enables you to grasp and manage situations of complexity and uncertainty in which there are no simple answers. It’s a way of learning your way to effective action by looking at connected wholes rather than separate parts. It is sometimes called practical holism.
Citing Peter Senge, the University of Bristol considers "Systems Thinking" a framework for (systemic) insight:
Systems thinking is a framework for seeing interrelationships rather than things, for seeing patterns rather than static snapshots. It is a set of general principles spanning fields as diverse as physical and social sciences, engineering and management.
Clearly various 'authorities' define "Systems Thinking" in their own ways and adopt a position on a spectrum as to whether any particular concept, practice or method is properly called "Systems Thinking". In the last few decades of the 20th Century there were some fairly acrimonious and divisive debates among the systems thinking community, involving people like Ackoff, Checkland, Jackson and Ormerod about whether any particular concept or practice was included or excluded under some label - like "Applied Systems Thinking" or "Operational Research" or "Soft Systems Thinking". Often the disputes and disagreements were traceable back to fundamental philosophical differences; for example, the subjectivist idealist "System" was only an idea that people impose on reality while for the physicalist, realist the "System" was a real thing independent of peoples' ideas.
STREAMS takes an inclusive, eclectic, pragmatic but principled view and counts as a part of "Systems Thinking" any discipline, practice or method or concept / notion that applies The Concept of "System" to achieve better understanding of something and construct a shared model of the thing. This includes so-called "problem-situation"s.
"STREAMS considers: "Systems Thinking" is any discipline, practice or method or concept / notion that applies The Concept of "System" to achieve better understanding of something and construct a shared (conceptual) model of the thing."
STREAMS takes the view that the philosophical disputes dividing the systems community are the consequence of bad philosophy. For example, the above dispute between the subjectivists and the physicalists is based on a confusion and conflation of a thing (System) with the idea of a thing (System) - itself based on an invalid assumption of a simple monism, or naive dualism - bad philosophy.
STREAMS considers that this definition of Systems Thinking can encompass all the separate traditions identified in the past - and clarify their relationships through the application of the STREAMS Philosophy. Nevertheless, it is convenient to subdivide Systems Thinking along the lines identified by professor Jackson as below.
Systems Thinking can and has been applied in a wide range of fields, or disciplines,including Economics, Biology, Engineering, and "Management" or Organisational Design. In this sense, it transcends any single discipline and is truly Transdisciplinary.
Systemic and / or Systematic
"Systemic" is a term that comes from medicine where it means roughly "applying to the whole - every subsystem - (of the body)". The term "systemic" was adopted by the financial markets and the financial industry generally where it means applying to every asset class or risk category (or, equivalently, every stock or shares traded in the market). Hence systemic risks cannot be avoided (or mitigated) by diversifying an asset portfolio - by definition the risks apply to every asset.
Hence in the more generalised Systems Thinking "systemic" means applying to a collection of systems, subsystems and components. A "systemic perspective" is a view, or analysis that examines all the systems (or subsystems) that need to be considered.
"Systematic", on the other hand, means "according to system" and usually has an implication, when applied to human activities, of being methodical. Probing a little deeper into the notion of "systematic" leads to the ideas that the "system" involved is a system of human activity that includes cognition and to be "systematic" means to apply the relevant best theory, methodology and methods available for the purposes or activity being undertaken.
The two adjectives are related through the underlying notion of a "system" - but mean quite different things, and have different connotations and implications.
The words "system", "systemic" and "systematic" became somewhat clichéd during the latter half of the 20th century and were often mis-used in an attempt to make something sound impressive, important, intelligent and scientific. Care has to be exercised in reading general literature therefore as to whether these words are being used carefully, with precise meanings or being used merely as buzzwords to create the right psychological effect in the unwary reader.
The Open University OpenLearn course "Systems Thinking in Practice" offers this table emphasising the differences between "systematic thinking" and "systemic thinking".
However, in the STREAMS' view they have not got the distinction quite right and it is actually more subtle than they think. For example, they suggest that in "Systematic Thinking" perspective is not important but in "Systemic Thinking" there are multiple perspectives that retain their identity when combined. A better conception though is that in "Systematic Thinking" a 3rd-person perspective - what an impartial, neutral, unbiased, objective observer would think (if such a conceptualisation could be obtained by a partial, biassed, cognitively limited individual) - is privileged (accorded more weight) over any and all 1st-person perspectives - what biased, fallible, 'bounded' individuals think - while in "Systemic Thinking" multiple 1st-person perspectives can be combined to produce an intersubjective perspective that approaches 3rd-person objectivity. The OU are too simplistic about it; the distinction between 'Systemic' and 'Systematic' is not one of distinct, black-and-white categories but one of degrees, many shades of grey (gray) between the black of Systemic and the white of Systematic.
Any method of "Systems Analysis" or attempt to understand some system or system of systems begins with an effort to form a (coherent and relevant) concept of the system or systems that are "of interest". This process we call in STREAMS, System Conceptualisation. How systems are conceived and that conception expressed in models (including all forms of systems diagrams) is profoundly affected by the philosophy adopted by those engaged in the effort - even if their philosophy is not explicit. The STREAMS Philosophy is made explicit - and how it affects the process is described here: System Conceptualisation.
Hard Systems Thinking or Traditional Systems Engineering
"Professional engineers make sense of their world by thinking about it in the following way. A specification is produced which gives a careful description of something which is required, whether a physical object or a complete system. The professional skill of the engineer is then used to meet the specification in the most efficient, economic, and elegant way. ... Engineering thinking is teleological; it asks what is the purpose served the object or system? The engineer works back from the purpose, or objective, and creates an object or system which will achieve that objective. The whole design realization process is driven by the discipline of having to meet a declared objective. (Machol, 1965; Chestnut, 1967; Wymore, 1976). ... 'Systems Analysis'... ...brings together ideas from engineering and ideas from economics and seeks to help a real-world decision-maker faced with carrying out a major project. ... 'Operational Research',... ...grew out of the application of the scientific method not to unchanging Nature but to wartime military operations. ... Traditionally, the approach seeks to apply the empirical method of science to real-world operations. ... It is obvious that the fundamental thinking underlying Systems Engineering, Systems Analysis and Operational Research is very similar. Though they have different names as a result of their different histories, these three approaches to rational intervention in human affairs can readily be shown to represent one approach (Checkland, 1981, 1983).
From Checkland, P., (2001), "Soft Systems Methodology", Chapter 4 in Rosenhead and Mingers.
From a STREAMS perspective, while we think Checkland underestimates the extent to which Engineering is a creative and exploratory discipline between Science and Craft, we agree with him that there is a body of knowledge of the application of mathematical and scientific methods and knowledge to real-world human problems (or problem situations) that goes under various names including those three. In STREAMS we call this body of knowledge "Traditional Systems Engineering".
Since, in the 21st Century, the logical (not geographic) parts of the World in which people live are largely synthetic and constructed (or engineered), Engineering is an important and powerful force shaping the World and people's lives - and Systems Engineering is arguably the most general part of the Engineering discipline. Systems Engineering is therefore considered to comprise both Systems Analysis and Systems Synthesis.
The word "Traditional" prepended to the term "System Engineering" serves to indicate the original body-of-knowledge before its expansion into a new domain of Systems Thinking that encompasses human ideas and perceptions (of problem situations). Traditional Systems Engineering is founded on the same, traditional Positivist philosophy (after August Comte's "The Nature And Importance Of The Positive Philosophy") that underpins Science and Mathematics - and endeavours to take an objective, 3rd-person view and stance. The expansion into "Soft Systems Thinking" incorporates some of the response to the shortcomings of Positivism and some elements of "Social Constructivism" - as applied to social systems and seeks to incorporate 1st-person perspectives (which are often not objective in the traditional sense).
The POSIWID Principle
"POSIWID" is an acronym that stands for "[the] Purpose Of (a) System Is What It Does". The POSIWID principle is a stance that refers to a teleologic perspective on systems. This is problematic for natural systems (which are not designed) as there is no teleology in Nature (if the Principle of Naturalistic Closure is adhered to) - and so the assignment of purpose is a human conception and convention. For example, it may be said that the purpose of the respiratory system in animals is to deliver oxygen into the blood so that it may be used in biochemical reactions. This however, is not intrinsic in the behaviour of the respiratory system; it is the way people choose to understand the nature of respiration, because it is useful to do so. This functional perspective is emphasised by POSIWID; it is a principle that assigns purpose according to function and therefore assists in the understanding of the wider system. For synthetic, engineered, designed systems the assignment of purpose is more straightforward - but even here it is not simple. Design, where understanding is insufficient or deficient is often fallible; the intended purpose of the system may not be what the system actually does. For example tuition fees may be intended as a system to ensure equitable funding of education in a society but may actually function as a disincentive that serves to lower the general level of education in society. The POSIWID principle would assert that intentions (well-meaning or not) should be ignored and the 'true' purpose of the system be identified as what it actually does. POSIWID therefore serves as an antidote to wishful or pollyannaish thinking in systems analysis.
The Hard Systems Approach
The Hard Systems Approach is a process-model for an approach to determining the optimum course of action given clear teleology - ie that the intended outcomes or objectives are clear than the uncertainty lies mainly in the appropriate course for getting to the objectives most efficiently or with least risk. It is the systems expression of what in military thinking is called Ends-Ways-Means Analysis.
More on the Hard Systems Approach coming soon.
Model-Based Systems Engineering (MBSE)
Model-Based Systems Engineering is a modern, developed methodology (a systematic collection of methods) of systems engineering in the tradition of Hard Systems Thinking (or Traditional Systems Engineering) in which formal models of the systems and domains (systems contexts) are used as the communications vehicle between stakeholders instead of the traditional documents. Of course, in any problem situation with any scale and complexity there will not be a single formal model but a significant number of interlinked and interdependent models representing both different systems of interest and different stakeholder perspectives on those systems. In modern practice this collocation of system models is held in an online repository accessible to all the stakeholders and users of the models; and the models themselves are interactive in some sense. The era of documents as the primary means of formal communication in Engineering really ended at the end of the 20th Century.
Model-Based Systems Engineering, as conceived by INCOSE, restricts itself to Hard Systems - which generally means the technologies and technical systems used in an Enterprise. In this form it can be considered as a form of technology-centric Enterprise Architecture generally akin to "ICT Architecture" - but with a wider base of technologies. If however, the MBSE approach is used to address the soft systems in an enterprise as well as the hard systems then it is broadly a methodology of Real Enterprise Architecture.
More on Traditional Systems Engineering coming soon.
Soft Systems Thinking
Systems of Power or Coercive Systems
See also Enterprise Systems Engineering.
The Intelligent Complex Adaptive System Of Systems (ICASOS) Model
The Intelligent, Complex, Adaptive System Of Systems Model is a conceptual model of an arbitrary, generic enterprise comprising people, processes and technologies. It is a system of human activity systems and technical systems, that embodies and expresses human intelligence (and machine intelligence if any is available), adapts to its context or environment (and changes in it) and is inherently complex (with emergent behaviours and outcomes). According to Harmon:
"In this context an enterprise is a system. It is a complex system. It is an intelligent complex adaptive system (ICAS). ... The enterprise is also a system of systems (SOS) and one of several systems within a system. This is true in both a hierarchical and an operational context. Therefore, it could also be viewed as an intelligent complex adaptive system of systems (ICASOS). ... The ICASOS assumption is essential to a more complete understanding of enterprise performance (capability, operation and results) and performance assurance (management). Failure to recognize the enterprise as an intelligent complex adaptive system of systems (ICASOS) can lead to improper scoping and the development of solutions for the wrong problem."
STREAMS considers that enterprises are ICASOSs - and can be effectively modelled as ICASOSs.
More on the Intelligent Complex Adaptive System Of Systems Model coming soon.
Systems Thinking and Enterprise Systems Engineering
Systems Thinking and (Real) Enterprise Architecture
A substantial minority, if not the majority, of the Enterprise Architecture practitioners community consider the discipline to be founded on Systems Thinking. Examples include "Enterprise Architecture and EA Governance: A Stratified Systems Approach"
More on the relationship between Systems Thinking and (Real) Enterprise Architecture coming soon.
The UCL Centre for Systems Engineering identifies the following Principles of Systems Engineering (Management):
- Principles Govern Process
- Seek Alternative Systems Perspectives
- Understand the Enterprise Context
- Integrate Systems Engineering and Project Management
- Invest in the Early Stages of Projects
The relationship to Enterprise Architecture principles is obvious.
"Laws" are a special subcategory of principles that encapsulate a consistently recurrent causal (nomological) relation. That means a "Law" says something like "if X happens then Y invariably follows". However, Laws and Principles are often mislabeled and confused - but it doesn't matter. From a pragmatic perspective the difference between a Law and a Principle is an unimportant philosophical difference between two categories of human assertion. The important thing is how you use the conceptual tools - not the label on the toolbox.
Theorems can be regarded as a form of well-developed model of reality (or some segment of it) based on a set of coherent concepts, principles and nomological relations (or "laws) that can be widely, if not universally applied to understand that segment of reality. They are much more well-developed and empirically grounded and verified than hypotheses - and can be "established" as the best orthodox way of understanding and describing reality. They are also logically coherent (given their underlying concepts and principles) with wider bodies of knowledge. However, as with Laws and Principles they are often confused and conflated with other forms and modes of "human assertion". Again it is the content of the theorem (or law or principle) that matters and not the intellectual taxonomic label attached to it. The collection of theorems (principles, laws) forms the body of the Theory for the field or discipline.
Within STREAMS, 'Theory' - including concepts and principles - is a link in the chain of logical derivation from Philosophy to Practice between Philosophy and Methodology - with Concepts and Principles closer to Philosophy and Theorems and Laws closer to Methodology.
Systems Thinking and Operational Research
Systems Methodologies, Methods and Techniques
Classical Control Systems Theory or "Classical Control Theory" is a branch of Traditional Systems Engineering that uses mathematical techniques to analyse and model the behaviour of systems (often real-world engineered systems) that apply negative (balancing) feedback as a method of control (of the system behaviour). Such systems often use 'analogue techniques' to implement system control, produce desired behaviours and suppress unwanted behaviours. Perhaps the most familiar of such systems are the (non-computer-controlled) suspension systems of cars where they are used to 'shape' the vehicle dynamics - but they can be found in all manner of vehicles and other dynamical systems including traditional analogue 'guidance systems'. Such systems can often be modelled by one or a set of Ordinary Differential Equations. The mathematical description and analysis of control systems can be traced back to the work of the (great) physicist James Clerk Maxwell and his analysis of the centrifugal governor for the control of the speed of steam engines in "On Governors".
More on Classical Control Systems Theory coming soon.
More Information: Traditional Systems Engineering
More Information: Integrated DEFinition (IDEF) Methods
General System Theory can be considered to originate in the work of Kenneth Boulding, Ludwig Van Bertalanffy and the Society for General Systems Research. Their aim was to extract general abstract principles and theories from the various systems concepts that occurred in many different fields in the 1950s and 1960s, including Physics, Biology, Economics and Organisational Management. Hence they dubbed the discipline and theory they initiated the theory of the "General System" - not the specific systems of any discipline or field (like Physics or Economics) - or "General System Theory". This was the founding of what is probably more properly known as "Systems Science" - but is also probably the origin of "Systems Engineering".
... there exist models, principles and laws that apply to generalized systems or their subclasses, irrespective of their particular kind, the nature of their component elements, and the relations of "forces" between them. It seems legitimate to ask for a theory, not of systems of a more or less special kind, but of universal principles applying to systems in general. ... In this way we postulate a new discipline called General System Theory. Its subject matter is the formulation and derivation of those principles which are valid for "systems" in general.
Boulding's Hierarchy of Systems (Types)
Kenneth Boulding, one of the founders of General System Theory, and, it can be argued Systems Thinking, defined the following hierarchy of systems. It should be noted that it is (for the most part) a hierarchy of system types. In principle it is possible to define a similar hierarchy of systems of ontological compoistion - ie a hierarchy based on the "made of" relationship rather than the "type of" relation. From an ontological pluralist perspective it is also somewhat confused - mixing up fundamentally different types of thing (e.g. "frameworks" and "plants"). This is based on the fundamental but extremely common philosophical mistake of conflating the idea of a thing with the thing itself. Hence the bottom-most level of Boulding's hierarchy should not be "frameworks" (the idea of the fundamental particles and field of the universe) but the actual fundamental physical components themselves (as described by the theories of Physics and their ontological commitments).
# Frameworks. The geography and anatomy of the universe : the patterns of electrons around a nucleus, the pattern of atoms in a molecular formula, the arrangement of atoms in a crystal, the anatomy of the gene, the mapping of the earth, etc.
# Clockworks. The solar system or simple machines such as the lever and the pulley, even quite complicated machines like steam engines and dynamos fall mostly under this category.
# Thermostats. Control Mechanisms or Cybernetic Systems : the system will move to the maintenance of any given equilibrium, within limits.
# Cells. Open systems or self-maintaining structures. This is the level at which life begins to differentiate itself from not life.
# Plants. The outstanding characteristics of these systems (studied by the botanists) are first, a division of labor with differentiated and mutually dependent parts (roots, leaves, seeds, etc.), and second, a sharp differentiation between the genotype and the phenotype, associated with the phenomenon of equifinal or "blueprinted" growth.
# Animals. Level characterized by increased mobility, teleological behavior and self-awareness, with the development of specialized 'information receptors (eyes, ears, etc.) leading to an enormous increase in the intake of information.
# Human Beings. In, addition to all, or nearly all, of the characteristics of animal systems man possesses self consciousness, which is something different from mere awareness.
# Social Organizations. The unit of such systems is not perhaps the person but the "role" - that part of the person which is concerned with the organization or situation in question. Social organizations might be defined as a set of roles tied together with channels of communication.
# Trascendental Systems. The ultimates and absolutes and the inescapable unknowables, that also exhibit systematic structure and relationship.
More on General Systems Theory coming soon.
The Systems Thinking Iceberg Model (Meadows)
The Iceberg Model, originally formulated by Donella Meadows is a conceptual tool for systems thinking, an archetypal model of reality and a philosophical conceptual schema. The thrust of the model is that the "above-the-surface" patterns and occurrences of events (the Events Layer) are determined by a number of "below-the-surface" conceptual layers. The first layer, nearest the surface of appearance, is the patterns of recurrent systems behaviours (the Patterns of Behaviour Layer) - and the trends in the evolution of those patterns. Below this layer is the layer of the enduring structures of systems (the System Structures Layer) - the enduring system components and relationships that produce the behaviours. And beneath this there is the layer of assumptions and beliefs (the Mental Model Layer).
It is easy to criticize the Iceberg Model on philosophical grounds as here: The Systems Thinking Icerberg Model#Philosophical Critique. But note there is an implication of Realism (in that surface appearance is different from the underlying reality), implications of synchronic and diachronic causation (the lower layers cause the upper layers in some sense - and cause the evolution of things over time), perhaps an incoherent nod to Social Constructivism (in that beliefs and assumptions somehow cause or compose into 'systems') and a clear resonance with Bhaskar's notions of a stratified reality with enduring (intransitive) "objects of knowledge".
More on the Iceberg Model coming soon.
System Dynamics (Forrester)
"System Dynamics" was one of the earliest and most seminal strands of Systems Thinking and is generally attributed to Jay Forrester. The discipline was originally known as "Industrial Dynamics". The central and most important notion in System Dynamics is that of flows (of various types) into, between and out from the components of the system. In the Concept of the System therefore the "intransitive" (non-moving, unchanging) components of the system effect transformations (perform transformative processes) on the transitive flows through the system - and System Dynamics focuses attention on the flows and hence describes the dynamics of the system - how the state of the system changes over time (and so the name System Dynamics).
"Bloomfield does not regard SD as mere technique, but as a systems philosophy because it embodies a theory about the nature of complex feedback systems. This theory holds that people live in a network of feedback structures, incorporating economic, political and ecological subsystems. The feedback structures determine many of the problems – from famine to overcrowding, and inflation and unemployment to ecological collapse – which have caused considerable public concern in recent times."
[Open University - Mastering Systems Thinking in Practice - OpenLearn Course.]
Hence one of the most fundamental and informative model constructs in System Dynamics is the "stocks and flows" diagram - which traces and maps the stocks of the transitive elements at each system component - or "node" in the system map - and the rate of flow along the links in the system map. This concept is the fundamental of Operations Management - for example any manufacturing plant can be modelled as a system that has a number of inputs, produces a number of outputs and has a number of flows through transformative processes along which the intransitive elements flow with time.
More on System Dynamics coming soon.
System Dynamics (Senge)
The Senge version of "System Dynamics" may be regarded as the Forrester version updated and re-focused on the social systems inside organizations and re-positioned as a methodology for organizational understanding, problems-solving and learning. Forrester style systems models - focusing on flows, including causal flows - are regarded as models that feed into higher-order organizational perception, decision-making and action-taking loops - that generate system behaviours at multiple levels (or orders). In a manner highly reminiscent of Critical Realism's Ontology and Philosophy of Science applied to the social (managerial) systems of organizations, Senge suggests there are three levels of 'explanation' (or intuitive analysis) that managers adopt: explanations in terms of Events, Patterns of Behaviour, and Systemic Structure.
"The systems perspective shows that there are multiple levels of explanation in any complex situation... ... "Event Explanations" - who did what to whom - doom their holders to a reactive stance... ...event explnations are the most common in contemporary culture, and that is exactly why reactive management prevails. ... "Patterns of Behavior" explanations focus on seeing longer-term trends and assessing their implications. ... "Patterns of Behavior" explanations begin to break the grip of short-term reactiveness. ... The third level of explanation, the (systemic) "structural" is the least common and most powerful. ... Though rare, "Structural Explanations", when they are clearly and widely understood, have considerable impact.
More on the Senge version of System Dynamics coming soon.
The Systems Failure Approach (SFA) has much in common with Soft Systems Methodology but is positioned by Fortune and Peters as a formal mechanism of Organizational Learning. In essence the SFA is a technique that examines the causes of project failure - particularly ICT implementation project failures. It does this by considering the project as the subject of a mini-SSM exercise in which the "real-world" project (temporary) organization is compared with and against an idealized reference model of a project - the Formal System Model - to identify the missing or poorly designed elements that were the ultimate cause of the failure. This 'learning' is then (supposed to be) fed-back into the organizational knowledge management to help avoid making the same mistakes again in the next project.
More information on the Systems Failure Approach
Strategic Options Development and Analysis (SODA) is a method for exploring the options for addressing a complex problem situation with complex goals or objectives. It is therefore a decision-making tool - that seeks to determine the optimum course of action for a decision-making group. It features a technique of "causal mapping" to explore the views of the situation's stakeholders in a structured "Means-Ends" format. In many ways this resonates with the 'traditional' Ends-Ways-Means analysis used in military circles to identify, evaluate and select from proposed Courses-of-Action (COAs). However, SODA is better grounded in theory than the pragmatically-developed military strategy-to-tactical technique.
SODA operates on four theoretical perspectives: The Individual, the Negotiated Enterprise, the Consultant and the Technology and Techniques perspective. It constructs "a publicly viewable model amenable to continuous change and analysis". [Ref. Ackerman and Eden] As such it also has clear resonances with the practice of Enterprise Architecture - which also seeks to construct a publicly viewable multi-perspective model that encompasses the same elements.
More on SODA coming soon.
Strategic Assumptions Surfacing and Testing is different from the methods of the more Traditional Systems Engineering methodologies and can be considered more of a "meta-level" method. Whereas in TSE the focus of analytical attention is on the World 1 systems (the real-world physical) and their models, SAST steps up a level and looks at the stakeholders involved in the systems analysis and the development of the model. The intention of the SAST method is to make the differing perceptions and assumptions of the stakeholders explicit. SAST identifies four key principles for examining the relationships between stakeholder groups involved in the analysis:
- Adversarial - considering of opposing viewpoints, assumptions and perceptions.
- Participative - involving and including different stakeholder and analyst groups
- Integrative - aimed at bring differing views and perceptions together in a common synthesis
- Managerial Mind Supporting - aimed at getting a deeper, consensus understanding
More on SAST coming soon.
The Strategic Choice Approach (SCA) is a method or "approach" to managing complexity under uncertainty in support of decision-making. The SCA views non-routine decision-making as profoundly influenced by three types of uncertainty: 1) Uncertainty about Values (UV), 2) Uncertainty about the (working) Environment (UE) and 3) Uncertainty about Related Agendas (UR). It introduces four different modes of decision-making (under uncertainty): 1) Shaping, 2) Choosing, 3) Designing and 4) Comparing that are linked by various cyclic processes. It provides a conceptual toolbox of methods that can be applied in each of the four modes of decision-making.
More on the Strategic Choice Approach coming soon.
Critical Systems Heuristics (CSH) is a method of systems analysis based on philosophical critical theory applied to Systems Thinking. It is a method of structured Boundary Critique based on twelve interrogatives (questions) that mark the intersection of concerns on two critical dimensions: 1) Boundary judgments about a system of interest and 2) sources of influence. CSH helps with three things: 1) sense-making of the problem situation 2) making explicit multiple perspectives and developing common understanding and 3) reflectively analysing and changing the problem situation. This has clear resonances with Enterprise Architecture - which does exactly the same three things but using different modelling conventions from CSH and often less critical in practice.
More on Critical Systems Heuristics coming soon.
The concept of Appreciative Systems was introduced early on in Systems Thinking by Sir Geoffrey Vickers in the 1960s. The essence of his thinking was to regard humans as components in a system whose interactions are driven by communications and perceptions - and judgements. He therefore introduced the notion of a Human Activity System. In many ways Vickers' work was a pre-cursor to Soft Systems Thinking, in particular Soft Systems Methodology and he had a degree of influence over Peter Checkland and its development. The following quotation from "Human Systems Are Different" summarises the core of "Appreciative Systems" thinking:
"I find it surprising that we have no accepted word to describe the activity of attaching meaning to communication or the code by which we do so, a code which is constantly confirmed, developed or changed by use. I have for many years referred to this mental activity as appreciation; and to the code which it uses, as its appreciative system; and to the state of that code at any time as its ”appreciative setting‘. I call it a system because, although tolerant of ambiguity and even inconsistency, it is sensitive to them and tries to reconcile them."
The use of the word "code" here is slightly misleading to modern ears - it is used more in the sense of "moral code" than "computer code";it is about the mental process of extracting human meaning from messages (perceptions, communications) rather than the technical process of extracting a meaningful (meaning-potential-ful) message from a stream of symbols. [Ref. John Searle's distinction between illocutionary information and perlocutionary information.] Vicker's also clearly anticipates the concepts of "social systems" and "cognitive filters" which were to appear in later Systems Thinking and the general Management literature.
It is also somewhat ironic that Vickers' Systems Thinking pracitioner concepts of appreciative systems also prefigure the philosophical theory, published in 1981, of Jurgen Habermas called the "Theory of Communicative Action" with which it clearly resonates.
More on Appreciative Systems coming soon.
Social Systems Science (Ackoff)
More on Social Systems coming soon.
In STREAMS there are multiple "strands" to the topic of "Learning Systems".
- Strand 1 is based on the work of Jean Piaget that considers a child (but it could be any animal or collection of insects or other systems possessing "cognitive powers" and memory) as a system that adapts itself - its own mental processing and range of behaviours - according to the stimuli it receives from the outside world and as its own internal cognitive powers grow.
- Strand 2 is based on the theories of (individual) learning of Kolb and other educationalists.
- Strand 3 is based on the theories of social or organisational learning (and knowledge management) including those of Chris Argyris and Donald Schon, Max Boisot and Nonaka and Takeeuchi.
- Strand 4 is based on the theories of autopoiesis of Maturana and Varela applied to not the short-term notion of "cognition" - but to the longer-term notions of knowledge development and conscious behaviour - including systemic notions from epigentics about how information from the environment is incorporated into the system.
- Strand 5 is based on notions from Innovation Management about exploring the "design-product space" through innovations, product development and successive prototypes.
- Strand 6 is derived from Soft Systems Thinking applied to the management of the corporate knowledge-base.
- Strand 7 is the notion of "Learning Systems" as organized educational materials, interactive software (including Wikis and simulations) and systematic, organised learning experiences.
More on Leaning Systems coming soon.
Soft Systems Methodology (SSM) (Checkland)
Soft Systems Methodology (SSM) was a product of the "action research" community of systems thnkers centred on Lancaster University but its leading exponent is Peter Checkland. The essential aspect of Soft Systems Methodology is that it transfers the systematicity in addressing "problem situations" from the systems processing the materials, energy and information in the problem situation to the methods and groups analysing the problem situation and its systems. SSM is firmly rooted philosophically in Interpretivism - which is a philosophy of academic research that rejects the notion of a "controlled experiment" but commits to the researcher acting in the situation and then interpreting the results, outcomes and consequences of the action as a way to formulate a "proto-theory". This approach - characteristic of "action research" - is though to be more appropriate to social systems - such as organizations - where the practicalities of constructing and running experiements - including costs and effort and possibility of control - make traditional, positivist experiments impossible. Consequently the perceptions and interpretations of groups of stakeholders and "researchers" in the "problem situation" play a central role in the methodology. SSM is fully committed to the principle of knowledge fallibility and that different stakeholder and researcher groups will have different perceptions and interpretations of the same problem situation. It offers a systematic socio-cultural, social-constructivist set of methods whereby different perceptions and interpretations can be assembled, negotiated and reconciled into a consensus multi-aspect model of the "as-is" problem situation. This model can then be compared with the situation idealised (made ideal, with problem resolved) in a "to-be" model that may be used normatively to identify and implement the necessary change actions on the roadmap from real-world "as-is" to "to-be" situations.
The resonances with Enterprise Architecture methodology are clear - and in this sense SSM is a "pre-cursor" form of Enterprise Architecture.
More on Soft Systems Methodology coming soon.
Soft Systems Methodology (SSM) (Wilson)
The Wilson version of SSM has much in common with that of Checkland, with whom Brian Wilson collaborated for many years at Lancaster University. While there are some minor methodological differences the fundamental theory and conceptual basis of the two versions are the same. Arguably the Wilson version is more practical and less philosophic. Again arguably it is more realistic - ie closer to Philosophical Realism - and less social constructivist - further from Philosophical Interpretivism and Epistemic Relativism - than Checkland's and so lays greater emphasis on the SSM 'stream of logic-based analysis' (as opposed to the 'stream of cultural analysis'). Within STREAMS this makes the Wilson version both easier to apply and more 'accurate' and less a "conflation of opinion" than the Checkland version as is closer to our base STREAMS Philosophy. This is not to deny the reality of different perceptions of any problem situation and the important role that culture and the exchange of different views plays in any soft systems approach. The definitive works on the Wilson version of SSM are his "Systems Concepts, Methodologies and Applications" and "Soft Systems Methodology: Conceptual Model Building and Its Contribution".
More on the Wilson version of SSM coming soon.
The System of Systems Methodologies is more of a "meta-methodology" that spans the other systems methodologies. It provides a logic and a means of analysis to choose between the application of the other systems methodologies -including them in combination. As such it is a methodology that assumes a "multimethodology" perspective. In essence it does this by defining a two-dimensional taxonomic landscape of "problem situations"; the dimensions are 1) the nature of the systems in the problem situation and 2) the participants in the systems-based analysis. The continuum of systems types is said to run from the simple to the complex while the paticipants run through broad categories of "Unitary", "Pluralist", and "Coercive" - each with defined characteristics of the participants in terms of their worldviews, interests and objectives and their level of consensus. Combining the two dimensions gives rise to six paradigm cases - i.e. Simple-Unitary through to Complex-Coercive and these "problem contexts" are identified with the systems methodologies that are thought to work best in those contexts. Jackson and Flood also plot the common organisational metaphors used in thinking about such problem situations.
More on the System of Systems Methodologies coming soon.
Adaptive Systems are, by definition, systems that adapt; systems that change (themselves) in response to changes in their environment or context. Two forms of adaptation may be distinguished: 1) homeostatic adaptation and 2) evolutionary adaptation.
In homeostatic adaptation, which may be regarded as 1st order adaptation, the dynamic state of the system's components change but the overall structure of the system does not. An example of such as system might be an organism that increases is rate of perspiration in response to a rise in temperature of the environment in order to maintain its body temperature. An organisational example might be a production line where the speed of the line is increased in order to produce more units in order to meet increased demand from the market (environment). In homeostatic adaptation the structure of the system does not change - and there may be limits to how much or bow far the system can adapt in this manner.
In contrast, in evolutionary adaptation the structure of the system itself changes - and therefore so does the dynamics. Biological evolution is the obvious example, but organisational examples might include the introduction of a new machine (in a production line) or a new process or new methods of achieving the same ends, or indeed new organisational structures that do the same processes more efficiently. Automation and robotics are thus significant sources of adaption and adaptation is closely connected to innovation. Adaptation will usually involve a change in the inputs and outputs of the system - crossing the system boundary and therefore a change in the relationship of the system with its context (which may include similar systems in cooperation or competition with the adapting system).
Systemic Innovation represents the overlap and convergence of Systems Thinking and Innovation Management.
'System' is defined as a set of components that interact with each other. Any particular component may be a component in many systems - concurrently; and any system may be a subsystem of many larger systems. This view of organisational, social and technological reality as a complex system-of-systems is the 'Systemic Perspective'. A characteristic of real systems, consequent of the interactions that are definitive of systems, is that removing or significantly changing a component is that the dynamics of the systems of which it is a part are affected. This means that, depending on the strength of coupling between the systems in the complex, it is not possible to compartmentalise change; change in one system, subsystem or component necessitates change in others.
Innovations range in scope and scale from incremental micro-innovations through to large-scale, radical innovations. Often innovations come in clusters of "related change" where one innovation drives a sequence of coupled innovations in related areas. Systemic Innovation therefore describes a set of interconnected innovations, where each is dependent on the other, with innovation both in the parts of the system and in the ways that they interact. Systemic innovation is macro-scale innovation in the framework of the Systemic Perspective.
Systemic innovation is often required for the full value of radical innovations to be realised. For example, for the shift of automotive technology to electric power to is (as of 2018) transforming the nature of transport, and a a whole raft of complementary innovations in terms of products and services (charging stations, electrical power generation and distribution, car control systems including self-driving cars, 'smart roads', road traffic management and so on) and regulations were necessary and inevitable.
The notion of "Systemic Innovation" has clear resonance with holistic Real Enterprise Architecture - where holistic and coherent systems models are produced for many systems that encompass the Business Architecture - organisations, processes, finances, services, products, markets/industries, capabilities etc. - the Information Architecture - data and models, stores and flows, databases and subject-matters etc. - and the Technology Architecture - production technologies and ICT, hardware and software, etc. and plan coordinated change (ie innovation) across the architecture areas. 'Systemic Innovation' may be synonymous with 'Real Enterprise Architecture' - if the latter is conceived as applying to a much, much wider range of technologies than just ICT.
Systems Thinking in UK Universities
The [UK] Open University has a [Systems Thinking In Practice] programme which provides qualifications to M.Sc. level. The programme has resulted in a number of Systems Thinking books. It also provides Systems Thinking modules and input into a number of Open University courses including their Master's programme in Technology Management and also provides an open access introduction to Systems Thinking and an OpenLearn (free, open access course): Mastering Systems Thinking in Practice which provides a digital badge.
Cranfield University runs a short intensive course on Systems Thinking In Practice targeted at people engaged in the [UK] Defence Industry.
University College London (UCL) - a leading college in the University of London - hosts the UCL Centre for Systems Engineering that runs Masters and (PhD) Research programmes in Systems Engineering for professional engineering managers and similar engaged in academic research. It also runs a number of short courses on Systems Engineering including a one-day workshop on applying systems thinking entitled Systems Thinking and run by the UCL Centre for Systems Engineering.
The Centre for Systems Studies is run in the context Hull University's Business School. It is an international centre of excellence for research on systems thinking and practice.
Lancaster University has an active Systems / Soft Operational Research Group in its Department of Management Science which runs undergraduate, Masters and Doctoral programmes in Management Science and Operational Research. It claims to be
"One of the best-known and longest established centres for operational research and systems thinking in Europe, going back to the 1960s."
Internet-Based Courses on Systems Thinking
FutureLearn: Systems Thinking and Complexity
Johns Hopkins University (US) Systems Thinking in Public Health
CETAD (Lancaster University): Systems Thinking
Open University (UK): Introducing Systems Thinking
Open University (UK): Systems Thinking And Practice
Open University (UK): Mastering Systems Thinking in Practice
Open University (UK): Systems Engineering: Challenging Complexity
Open University (UK): Systems Modelling
Open University (UK): Managing Complexity: A Systems Approach
Open University (UK): Systems Diragramming