Exploring The Ashby Space: | Harish’s Notebook – My notes… Lean, Cybernetics, Quality & Data Science.

Today’s post is a follow-up to an earlier post, Solving a Lean Problem versus a Six Sigma Problem: In today’s post, I am looking at “The Ashby Space.” The post is based on the works of Ross Ashby, …

Source: Exploring The Ashby Space: | Harish’s Notebook – My notes… Lean, Cybernetics, Quality & Data Science.

The Cybernetic View of Quality Control: | Harish’s Notebook – My notes… Lean, Cybernetics, Quality & Data Science.

My last post was a review of Mark Graban’s wonderful book, Measures of Success. After reading Graban’s book, I started rereading Walter Shewhart’s books, Statistical Method from the Viewpoint of Qu…

Source: The Cybernetic View of Quality Control: | Harish’s Notebook – My notes… Lean, Cybernetics, Quality & Data Science.

Law of Requisite Hierarchy – Aulin, 1978

 

Source: Law of Requisite Hierarchy

Law of Requisite Hierarchy

The weaker the average regulatory ability and the larger the average uncertainty of available regulators, the more requisite hierarchy is needed in the organization of regulation and control for the same result of regulation

[Node to be completed]

The statement of the Law of Requisite Hierarchy by Arvid Aulin, is followed by:

“. . . . [In other words], the lack of regulatory ability can be compensated to a certain extent by greater hierarchy in organization.”

(Cybernetic Laws of Social Progress, p. 115)

 

paper (pdf) 1978 http://pespmc1.vub.ac.be/books/Aulin-LawofRequisiteHierarchy.pdf

 

A Study of “Organizational Closure” and Autopoiesis:

Harish's avatarHarish's Notebook - My notes... Lean, Cybernetics, Quality & Data Science.

autopoiesis

In today’s post, I am looking at the phrase “Organizational Closure” and the concept of autopoiesis. But before that, I would like to start with another phrase “Information Tight”. Both of these phrases are of great importance in the field of Cybernetics. I first came across the phrase “Information Tight” in Ross Ashby’s book, “An Introduction to Cybernetics”. Ross Ashby was one of the pioneers of Cybernetics. Ashby said: [1]Cybernetics might, in fact, be defined as the study of systems that are open to energy but closed to information and control— systems that are “information‐tight”.

This statement can be confusing at first, when you look at it from the perspective of Thermodynamics. Ashby is defining “information tight” as being closed to information and control. The Cybernetician, Bernard Scott views this as: [2]…an organism does not receive “information” as something transmitted to it, rather, as a circularly…

View original post 2,314 more words

Systems Dynamics Society conference: online Summer School July 14-17 | System Dynamics Colloquium July 19 Main Conference July 20-22 | Workshops July 23-24

https://www.systemdynamics.org/about

https://www.systemdynamics.org/program-overview

Critical Back-Casting | Integration and Implementation Insights – Gerald Midgely

 

Source: Critical Back-Casting | Integration and Implementation Insights

 

Critical Back-Casting

Community member post by Gerald Midgley

gerald-midgley
Gerald Midgley (biography)

How can we design new services or strategies when the participation of marginalized stakeholders is vital to ethicality? How can we liberate people’s creativity so we can move from incremental improvements to more fundamental change?

To answer these questions, I have brought together insights from Russ Ackoff and Werner Ulrich to develop a new method that I call Critical Back-Casting.

Russ Ackoff, writing in the 1980s, is critical of organizations that focus on incremental improvements without ever asking whether they are doing the right thing in the first place. Thus, they are at risk of continually ‘improving’ the wrong thing, when they would be better off going for a more radical redesign. Ackoff makes two far-reaching prescriptions to tackle this problem. The first is participative co-creation: all parts of an organization should be involved in the redesign. This way, you can get whole-of-organization buy in for radical change, rather than the imposition of a top-down strategic plan. The second prescription is idealized design, and this represents a radical break from business-as-usual strategic planning.

Idealized design involves everybody in the organization working collectively to redesign it. However, rather than ask ‘how can we improve what we are doing?’, people are encouraged instead to imagine that their organization has ceased to exist, and they are on a task force to produce a design of something entirely new that will really meet the needs of citizens or customers. The task force only has to respect three constraints:

  1. Technological feasibility – they can propose new technology, but it has to be possible to develop it (so no science fiction!).
  2. Viability – when up and running, the system or service must be sustainable (initial investment costs can be disregarded though, as ideas always run ahead of investments).
  3. Adaptability – the system or services must be capable of learning and adaptation into the future as things change.

The idea is to liberate people from the constraints of current assumptions and to stimulate creative thinking. While one might assume that different stakeholders will have very different visions of the ideal system or service, and will come into conflict, Ackoff says that this is not the case: there is invariably an overwhelming agreement on the ideal, with only relatively minor disagreements to resolve, and the consensus on the majority of issues generates sufficient trust for people to have confidence that remaining disagreements can be constructively addressed. My own experience suggests that Ackoff is right, and once the ideal design is generated, an action agenda can be created with practical steps toward implementation.

In modern management-speak, this approach is called ‘back-casting’ (starting with where you ideally want to be and then working backwards to the present day), and it is contrasted with ‘forecasting’, where people take what we have today as given and try to anticipate what will happen next. Ackoff’s books describe numerous examples of back-casting in practice, mostly in large multi-national industries, but also for city planning and other public sector change initiatives.

However, when I first read Ackoff’s work, I had some reservations. He talks about involving everyone in the organization, but in community contexts, participation usually needs to be much wider than formally constituted organizations, and this means facing up to the problem of marginalization. If marginalized stakeholders who are supposed to benefit from a service are not centrally involved in its design, the result can be something that is based on a simplified professional model of the typical service user, rather than accounting for the lived, diverse experiences of real people.

A way to address this is to draw on 12 questions, originally designed by Werner Ulrich (1994) in the context of empowering citizens to challenge professionally imposed designs. These questions can support both marginalized stakeholders and professionals in thinking through critical issues of governance and inclusion as they produce their ideal service or system design. My version of these questions, modified for use in back-casting, can be found below. I have used the word ‘service’, but it could equally well be ‘system’, ‘partnership’ or any other term that refers to a purposeful initiative. Because Werner Ulrich says that his questions stimulate critical thinking, I call their use with idealized design (and the three constraints listed earlier), Critical Back-Casting.

Here are the questions:

(1) Who or what should benefit from the service, and how?

(2) What should be the purposes of the service; i.e. what goals should it aim for in order to deliver to the beneficiaries?

(3) What should be the service’s key measures of success?

(4) Who should be seen as the key decision makers; i.e. have the authority to change who should benefit, what the purposes should be and how success should be measured?

(5) What components (resources, people, policies, etc.) should be under the authority of the decision makers?

(6) What is essential for delivery of the benefits and purposes, but should not be under the authority of the decision makers?

(7) Who, either in addition to or instead of the decision makers, should be involved in delivering the benefits and goals?

(8) What should count as expertise; i.e. who should be considered an expert and what should be their roles?

(9) What are the key factors that will guarantee (or increase the likelihood of) success?

(10) Who or what could be affected by the activities of the service; should the affected be represented in decision making, and (if so) how?

(11) To what extent should the affected be able to retain independence; i.e., opt out or neutralise the effects on them, and/or take actions of their own choosing?

(12) Upon what core values and assumptions should the service be based?

I have used Critical Back-Casting in approximately 20 projects, with various participants (e.g., homeless children, older people, children in residential care, people with mental health problems and many service providing stakeholders). Midgley (2000) provides a couple of detailed examples. Below, I offer several general reflections based on this experience.

Facilitation:

  • A facilitator is needed to make this work.
  • Once a facilitator has used the questions in several projects, they become internalized sufficiently to inform more free-form facilitation exercises, without the need to go through them systematically.

The questions:

  • For every question, 6-10 follow-up questions need to be asked to tease out details specific to the context.
  • The questions work equally well with professionals, ordinary citizens and people with marginalized identities who have had no previous experience of planning and management. Indeed, more frequently than not, ‘ordinary’ citizens and marginalized stakeholders find it easier to generate ideal designs than professionals, because the latter tend to be more disempowered by limitations built into their current organizations.

The process:

  • Expectations need to be managed. Ideally, the method is used in a real planning initiative where stakeholders can be confident that their ideas will inform action. If this is not the case (e.g., if the exercise is only going to inform recommendations for action that may or may not be implemented), then participants need to know this.
  • Power relations matter. If the participants don’t feel they can talk freely and openly in front of one another, the process will fail.
  • When free and open communication is not possible, an antidote is to run separate groups with different categories of stakeholder. However, when people see the far-ranging consensus that is produced, they usually want a follow-up workshop to bring the groups together, and this possibility needs to be planned into the process.
  • There are always moments in the flow of the discussion when it feels natural and necessary to deviate from the questions to look at what the structures for governance should be. This usually happens once people have realized that the meaningful engagement of stakeholders is necessary, and they want to look at how this can be accomplished.

Implementation:

  • Supporting people with action planning after the idealized design is essential.
  • Full implementation is more likely in the context of the design of new services rather than the reform of existing ones. This is not to say that the insights from back-casting are completely irrelevant to reform projects – they can provide a vision to work towards. However this has to be done more incrementally than might be ideal because the very survival of the organization is usually dependent on the continuous delivery of services. Nevertheless, full implementation in reform projects is possible when the organization or initiative is in dire trouble and radical change is the only realistic option for survival.
  • Finally, as long as people can talk freely, workshops using this approach are tremendously exciting (sometimes euphoric) because they almost always generate far-reaching insights. This is therefore a really useful approach for providing a foundation upon which to build further collaboration into the future.

Do you have related methods or experiences to share?

References:

Ackoff, R. L., Magidson, J., and Addison, H. J. (2006). Idealized Design: Creating an Organization’s Future. Wharton School Publishing: Upper Saddle River, NJ, USA.

Midgley, G. (2000). Systemic Intervention: Philosophy, Methodology, and Practice. Kluwer/Plenum: New York, USA.

Ulrich, W. (1994). Critical Heuristics of Social Planning: A New Approach to Practical Philosophy. Wiley: Chichester, UK.

Biography: Gerald Midgley is Professor of Systems Thinking in the Centre for Systems Studies, Business School, University of Hull, UK. He also holds Adjunct Professorships at the University of Queensland, Australia; the University of Canterbury, New Zealand; Mälardalen University, Sweden; and Victoria University of Wellington, New Zealand. He publishes on systems thinking, operational research and stakeholder engagement and has been involved in a wide variety of public sector, community development, third sector, evaluation, technology foresight and resource management projects. He is a member of the Co-Creative Capacity Pursuit funded by the National Socio-Environmental Synthesis Center (SESYNC).

This blog post is one of a series developed in preparation for the second meeting in January 2017 of the Co-Creative Capacity Pursuit. This pursuit is part of the theme Building Resources for Complex, Action-Oriented Team Science funded by the National Socio-Environmental Synthesis Center (SESYNC).

Source and comments: Critical Back-Casting | Integration and Implementation Insights

 

#55 Becoming a Model Thinker with Scott Page — The Knowledge Project with Shane Parrish — Overcast

 

Source: #55 Becoming a Model Thinker with Scott Page — The Knowledge Project with Shane Parrish — Overcast

 

The Knowledge Project with Shane Parrish

#55 Becoming a Model Thinker with Scott Page

April 2, 2019
0:571:22:36


2016/11/07 David Gelenter, “Consciousness, Computers, and the Tides of Mind”, Econtalk (MP3 audio)

daviding's avatarMedia Queue --> Coevolving Innovations

The most destructive analogy in the last 100 years, says @DavidGelernter with @econtalker : “Post-Turing thinkers decided that brains were organic computers, that computation was a perfect model of what minds do, that minds can be built out of software, and that mind relates to brain as software relates to computer”. Interview states position that consciousness won’t be found in a computer.

The cited source is visible on a page on Google Books:

In his famous 1950 paper about artificial intelligence, Alan Turing mentions consciousness, in passing, as a phenomenon associated with minds, in some ways mysterious. But he treats it as irrelevant. If you define the purpose of mind as rational thought, then consciousness certainly seems irrelevant. And for Turing, rational thought was indeed the purpose of mind.

Turing’s favorite word in this connection is “intelligence”: he saw the goal of technology not as an artificial mind (with…

View original post 648 more words

12 Rules Portland: Technology, Temperament & Free Speech — The Jordan B. Peterson Podcast — Overcast

The first hour or so of this is probably the best and most systems thinking summary of a bunch of the Peterson stuff I’ve come across.

 

Source: 12 Rules Portland: Technology, Temperament & Free Speech — The Jordan B. Peterson Podcast — Overcast

 

The Jordan B. Peterson Podcast

12 Rules Portland: Technology, Temperament & Free Speech

April 7, 2019
0:182:04:03

Bittorio revisited: structural coupling in the Game of Life

cxdig's avatarComplexity Digest

The notion of structural coupling plays a central role in Maturana and Varela’s biology of cognition framework and strongly influenced Varela’s subsequent enactive elaboration of this framework. Building upon previous work using a glider in the Game of Life (GoL) cellular automaton as a toy model of a minimal autopoietic system with which to concretely explore these theoretical frameworks, this article presents an analysis of structural coupling between a glider and its environment. Specifically, for sufficiently small GoL universes, we completely characterize the nonautonomous dynamics of both a glider and its environment in terms of interaction graphs, derive the set of possible glider lives determined by the mutual constraints between these interaction graphs, and show how such lives are embedded in the state transition graph of the entire GoL universe.

 

Bittorio revisited: structural coupling in the Game of Life
Randall D Beer

Adaptive Behavior

Source: journals.sagepub.com

View original post

Improvisation Blog: Recursive Pedagogy, Systems thinking and Personal Learning Environments

Mark Johnson’s blog is consistently excellent and thought-provoking and I particularly like this one, especially his definition of systems thinking:

To think of ‘systems’ is a thought that accepts that the world is produced by thought.

Source: Improvisation Blog: Recursive Pedagogy, Systems thinking and Personal Learning Environments

Monday, 29 July 2019

Recursive Pedagogy, Systems thinking and Personal Learning Environments

Most of us are learning most of what we know, what we can do, what we use on an everyday basis, what we talk about to friends and colleagues, online. Not sat in lectures, gaining certificates, or sitting exams. Those things (the formal stuff) can provide ‘passports’ for doing new things, gaining trust in professional colleagues, getting a new job. But it is not where the learning is really happening any more. The extent to which this is a dramatic change in the way society organises its internal conversations is remarkably underestimated. Instead, institutions have sought to establish the realm of ‘online learning’ as a kind of niche – commodifying it, declaring scarcity around it, creating a market. This isn’t true of just educational institutions of course. Social media corporations saw a different kind of marketing opportunity: to harness the desire to learn online into a kind of game which would continually manipulate and disorient individuals in the hope that they might buy stuff they didn’t want, or vote for people who weren’t good for them. But the basic fact remains: most of us are learning most of what we know online.
That means machines are shaping us. One senses that our sense of self is increasingly constituted by machines. I wonder if the slightly paranoid reactionaries who worry about the power of digital ‘platforms’ are really anxious about an assault on what they see as ‘agency’ and ‘self’ by corporations. But are we so sure about the nature of self or agency in the first place? Are we being naive to suppose autonomous agents acting in an environment of machines? Wasn’t the constitution of self always trans-personal? Wasn’t it always trans-personal-mechanical? The deeper soul-searching that needs to be done is a search for the individual in world of machines. Some might say this is Latour’s project – but seeing ‘agency’ everywhere is not helpful (what does it mean, exactly?). Rather more, we should look to Gilbert Simondon, Luhmann, Kittler, and a few others. There’s also a biological side to the argument which situates ‘self’ and consciousness with cells and evolutionary history, not brains. That too is important. It’s a perspective which also carries a warning: that the assertion of agency, autonomy and self against the machine is an error in thinking which produces in its wake bad decision, ecological catastrophe and the kind of corporate madness which our platform reactionaries complain about in the first place!

Having said this, we then need to think about ‘personal’ learning in a context where the ‘personal’ is constituted by its mechanical and social environment. Machine learning gives us an insight into a way of thinking about ‘personal’ learning. Deep down, it means ‘system awareness’: to see ourselves as part of a system which constitutes us being aware of a system. It’s recursive.

Some people object to the word ‘system’, thinking that it (again) denies ‘agency’. Ask them to define what they mean by agency, and we end up confused. So its useful to be a bit clearer about ‘system’. Here’s my definition:

To think of ‘systems’ is a thought that accepts that the world is produced by thought.

This is why I’m a cybernetician. I think this is critically important. To deny that thought produces the world is to set thought against those things which constitute it. When thought is set against that which constitutes it, it becomes destructive of those things it denies: the planet, society, love.

So what of learning? What of learning online? What of personal learning?

It’s about seeing our learning as a recursive process too. To study something is to study the machines through which we learn something. It may be that the machine learning revolution will make this more apparent, for the machines increasingly operate in the same kind of way that our consciousness operates in learning the stuff that is taught by the machines. It’s about closing the reflexive loop.

So what about all that stuff about certificates, trust, passports, etc? It seems likely to me that closing the reflexive loop will produce new ways of codifying what we know: a kind of meta-codification of knowledge and skill. Against this, the institutional stamp of authority will look as old-fashioned as the wax seal.

The Future Will Be Formulated Using Category Theory

I think that… I understand this not at all! Do you?

 

Source: The Future Will Be Formulated Using Category Theory

The Future Will Be Formulated Using Category Theory

Category Theory

A new approach to defining and designing systems is coming.

Introduction

The human ecosystem is made of open and closed systems. While the earth is a closed system for matter but an open system for energy, the human body is considered an open system. There is a growing belief that the current understanding of science cannot wholly explain human life, mind, and consciousness, nor can it explain the nature and origin of life, matter, the environment, the universe, and reality. Perhaps there is a need for a new ontological model of reality to look into the mysteries of the universe beyond the human ecosystem in cyberspace, aquaspace, geospace, and space (CAGS).

The universe is understood to be made of mathematics. Mathematics is primarily about rules and patterns, and science is about discovering and documenting rules and patterns that occur in nature. So, as we begin to study the universe beyond CAGS, we must focus on discovering and documenting rules and patterns and their relationships in open and closed systems that occur in nature, matter, and the universe. That brings us to an important question: how will understanding mathematical laws that govern us beyond the human ecosystem help us understand open systems better? To begin with, it will help us by giving us a reference model for understanding the interconnectedness and interdependencies of the human ecosystem.

Category theory provides a structural framework for mathematics and is on its way to becoming a language for consciousness for the entire universe. As the Stanford Encyclopedia of Philosophy states: “Roughly, [category theory] is a general mathematical theory of structures and of systems of structures… At a minimum, it is a powerful language, or conceptual framework, allowing us to see the universal components of a family of structures of a given kind, and how the structures of different kinds are interrelated. Category theory is both an interesting object of philosophical study, and a potentially powerful formal tool for philosophical investigations of concepts such as space, system, and even truth.”

Category theory is already becoming a key driver for current mathematics and academic computer science and is beginning to be applied to mathematical physics. Now, it is believed that Quantum physics, the study of the universe on an atomic scale, gives us a reference model to understand the human ecosystem in the discrete individual unit. As category theory becomes the language of mathematics for the articulation of the laws of physics, there is a hope that it will help us in defining and designing the open systems in the human ecosystem that can assist us on our journey towards understanding the origin of our universe and our place within it.

Understanding Category Theory

Based on the Mathematical Universe Hypothesis, the emerging reality is that we live in a relational reality. What does that mean? It means that the properties of the biosphere around us stem not from properties of its ultimate building blocks, but from the relations among these building blocks. While the position of category theory as a foundational language in applied mathematics and mathematical modeling is still in its infancy and a rather unexplored path, it is crucial to understand how it can help us understand the complex problems facing humanity.

The systems and structures we look at in the universe are self-organized at several different levels. Moreover, we live in a relational reality where self-organization is an obvious principle which is embedded in our description of the universe. This means that the properties of the world around us stem not from properties of its ultimate building blocks or individual units, but from the relations among these building blocks and units. That brings us to an important question: Is category theory a tool to understand the relationships? Moreover, how does category theory explain the relational reality of the contested commons of cyberspace, aquaspace, geospace, and space (CAGS)?

Category theory has already shown promise by providing an abstract framework for modeling processes to apply to science, engineering, and the contested commons of the human ecosystem. It is vital to explore how can we further apply category theory to the problems we are trying to solve today (security issues to surveillance issues, environmental issues to economics issues, automation issue to social issues and more).? How will category theory help us understand the complex issues facing the future of humanity?

Category Theory Applications

From assisting us in understanding how patterns of innovation rise to how patterns of destruction develop, category theory has the potential to be a powerful language or conceptual framework on which we can formulate our collective future. By keeping category theory as a reference model, we are more able to see the common components of a family of structures of any given kind that will finally help us understand how constructive and destructive structures and behavior are interrelated and integrated. Now, processes are universal, but we don’t look at our human ecosystem in the form of processes. Should we? Since in nature, a causal law takes the form that, similarly to actions by an individual, specific processes tie causes and effects together, we most certainly should.

Prof. (Dr.) John Carlos Baez expands on this notion in Risk Roundup: “In any system, we are dealing with on Earth, it is always very fundamentally an open system — its constantly being affected in unpredictable ways by the outside world and it is also affecting the outside world in unpredictable ways.”

If an individual being is seen as a single unit, what defines and determines our behavior and relationships? While the concept of reductionism (which essentially states that the whole is composed of simpler parts yielding discreteness and that the study of the whole can be reduced to the study of its parts) has become an integral part of the human ecosystem, can we continue to rely on the reductionist approach? It is time we understand the cause and effect of individual human behavior, and its impact on the collective human species since the nature of reality in the human ecosystem is inherently and inevitably dual. Since particle-like and wave-like behaviors are inextricably connected, they must be inherent in any design and development of open systems.

Since, category theory is expected to be a language for consciousness for the entire universe and will give us evidence to the more profound puzzle as to how to formulate the processes and patterns in the human-made ecosystem, will it help us dig deeper into why the order of the universe is dependent on interconnected and interrelated processes? Moreover, how are the systems and states undergoing open and closed processes that alter them in nature?

Justifiably category theory is rapidly becoming important today in understanding the current and future problems facing humanity. It is time decision-makers across nations begin to understand the promise of category theory and apply it to define and design systems at all levels keeping in mind the interconnected relationships between discrete individual units to build our collective future.

What Next?

Like particles in quantum mechanics, an individual unit, be it biological or non-biological, has an essential presence in spaces found in the universe (both natural and human-made). So, as we try to define and design open systems for the coming tomorrow, it is critical to understand and evaluate the essential laws of category theory to strengthen the human ecosystem in which we exist. It seems the future will need to be built using category theory.

NEVER MISS ANY OF DR. PANDYA’S POSTS

Join here for a regular update on Risk Group Insights.

Follow me on Twitter or LinkedIn. Check out my website.

Jayshree Pandya (née Bhatt), Ph.D., the founder and chief executive officer of Risk Group LLC is working passionately to define a new security centric operating system

Source: The Future Will Be Formulated Using Category Theory

The Inherent Instability of Disordered Systems – Bar-Yam, Lynch, Bar-Yam (2018)

Thanks to the General Intellect Unit podcast: http://generalintellectunit.net/e/032-the-inherent-instabiliyt-of-disordered-systems/

pdf: https://arxiv.org/pdf/1812.00450.pdf

Source: [1812.00450] The Inherent Instability of Disordered Systems

The Inherent Instability of Disordered Systems

The Multiscale Law of Requisite Variety is a scientific law relating, at each scale, the variation in an environment to the variation in internal state that is necessary for effective response by a system. While this law has been used to describe the effectiveness of systems in self-regulation, the consequences for failure have not been formalized. Here we use this law to consider the internal dynamics of an unstructured system, and its response to a structured environment. We find that, due to its inability to respond, a completely unstructured system is inherently unstable to the formation of structure. And in general, any system without structure above a certain scale is unable to withstand structure arising above that scale. To describe complicated internal dynamics, we develop a characterization of multiscale changes in a system. This characterization is motivated by Shannon information theoretic ideas of noise, but considers structured information. We then relate our findings to political anarchism showing that society requires some organizing processes, even if there is no traditional government or hierarchies. We also formulate our findings as an inverse second law of thermodynamics; while closed systems collapse into disorder, systems open to a structured environment spontaneously generate order.

Comments: 15 pages, 5 figures
Subjects: Physics and Society (physics.soc-ph); Disordered Systems and Neural Networks (cond-mat.dis-nn); Statistical Mechanics (cond-mat.stat-mech); Adaptation and Self-Organizing Systems (nlin.AO)
Report number: New England Complex Systems Institute 2018-12-01
Cite as: arXiv:1812.00450 [physics.soc-ph]
(or arXiv:1812.00450v1 [physics.soc-ph] for this version)

Submission history

From: Yaneer Bar-Yam [view email]
[v1] Sun, 2 Dec 2018 19:21:34 UTC (26 KB)

System and SE Definitions from INCOSE

 

Source: System and SE Definitions

Overview

The INCOSE Fellows’ Initiative on System and Systems Engineering Definitions was established in 2016, to review current INCOSE definitions of SYSTEM and SYSTEMS ENGINEERING, and to recommend any changes necessary to align the definitions to current practice and to the aspirations of INCOSE’s 2025 Vision.

This website presents the final output from the initiative in on-line form, as a set of linked web pages.
The formal published document version of the new definitions will be launched by INCOSE at the International Symposium in Summer 2019.

The final definitions take into account the extensive comments received during the review of the previous draft in September 2018. The review was open to all INCOSE members, and attracted over 350 individual comments and suggestions.

The three key recommendations – for definitions of systems engineeringengineered system, and a general definition of system – are presented here, with a very brief contextual explanation. Other pages provide more explanation of these definitions, and also define other specific system types and categories that are important for the systems engineering community.

Read on here, and explore the new definitions, or download the SE Definition full paper here.

The Three Essential Definitions

Systems Engineering definition

Systems Engineering is a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods.

We use the terms “engineering” and “engineered” in their widest sense: “the action of working artfully to bring something about”. “Engineered systems” may be composed of any or all of people, products, services, information, processes, and natural elements.

Engineered System Definition

An engineered system is a system designed or adapted to interact with an anticipated operational environment to achieve one or more intended purposes while complying with applicable constraints.

Thus, an “engineered system” is a system – not necessarily a technological one – which has been or will be “systems engineered” for a purpose.

Most general “System” definition

system is an arrangement of parts or elements that together exhibit behaviour or meaning that the individual constituents do not.

Systems can be either physical or conceptual, or a combination of both.

Systems in the physical universe are composed of matter and energy, may embody information encoded in matter-energy carriers, and exhibit observable behaviour.

Conceptual systems are abstract systems of pure information, and do not directly exhibit behaviour, but exhibit “meaning”. In both cases, the system’s properties (as a whole) result, or emerge from:

  • the parts or elements and their individual properties; AND
  • the relationships and interactions between and among the parts, the system and its environment.

Source: System and SE Definitions

Systems Changers – the Point People

 

Source: Systems Changers – Homepage

 

From climate change to poverty to healthcare, the large, complex social, environmental and economic problems we face today are too big for any one organisation to tackle alone. They require us to work together in new ways to address the root causes of problems and to create new outcomes that can change entire systems.

The failure of many of the systems that underpin modern life is increasingly difficult to avoid, so it’s not surprising that interest in ‘systems innovation’ is growing fast. At the Point People, we’ve seen pioneers emerging in this field from different sectors, leading very different kinds of organisations and speaking very different professional languages.

We had a hunch that these frontrunners could tell a compelling story about what systemic innovation looks and feels like in practice. So we put them in front of a camera and asked them a handful of questions.

The Systems
Compass

This project was made possible thanks to the generous support of Green Templeton College, the University of Oxford

Systems Changers

Although we spoke with people from very different backgrounds, common insights emerged that crossed these professional boundaries. These fall into six themes:

First
The craft of collaboration is vital to systemic change. This is easy to say, much harder to do in practice. The interviews highlight key ways in which deep collaboration can occur, as well as some of the significant barriers to achieving true partnership.

Second
Narrative is crucial. Narratives help people understand how the systems they live in are socially constructed. They help us become aware of how we prop up failing systems, and how we can build new ones.

Third
Theory and practice need to be understood as a double helix, inextricably linked. Our interviewees used different language to make this point – from appreciative enquiry to agile development – but behind this lies a shared, deeply held commitment to learning and iteration.

Forth
Systems change involves liminal spaces. Innovators need to be able to move in and out of the systems they are trying to change. Even when they are outside of the status quo, they are able to maintain a dialogue with it. If designed well, these liminal spaces can hold unstable groups of people together in the collective pursuit of change.

Fifth
Systems change looks more like a movement than like change led from either ‘top down’ or ‘bottom up’. Successful systems changers need to understand how to orchestrate multiple points of intervention, and align diverse interests with a common goal.

Sixth
Systemic leaders are unafraid of the unknown – in fact, they embrace uncertainty. They are able to identify points of intervention and act in the face of complexity. They combine a desire to understand systems with a realisation that they will always have to take action without perfect knowledge.

Just as there were important points of agreement, the interviews also highlighted important tensions and questions:

  • Is it is possible to design for systems change at all?
  • Is systems change revolutionary or an evolution? .
  • Is systems change an elitist discourse that excludes more than it enables?
  • Do organisations and institutions play a key role in achieving systems change; or are they obstacles, part of the old system that gets in the way?

Source: Systems Changers – Homepage