Jeff Sussna on Twitter: “Anyone know of a good group exercise that demonstrates emergent order in complex systems?

A great exchange on twitter that largely revealed that all the people who replied to Jeff have been using the same ‘triangle’ exercise (including me) – and some variants, and some other comments…

The “enemies” of the systems approach


Here is a link to the abstracts of the individual chapters of C. West Churchman’s ‘The systems approach and its enemies’, which was Churchman’s last book of his great trilogy. Churchman’s work is the focal point of CSL4D. I used the abstracts to produce a concept map (see below), which I will describe in this post. I believe it could serve as a useful introduction to Churchman’s work.

Systems     Social systems are all systems with humans in them. The human environment is full of systems: organizations, business, projects, governments, nations, the world, shopping systems, transport systems, security systems, financial systems etc. All of these systems have been designed. The systems idea implies that systems have components (subsystems) and boundaries. Systems are not closed, they are mostly conceived as semi-open, which implies that their boundaries are subject to debate. In soft systems lingo we speak of the “boundary critique.”

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System Dynamics: a core Systems Engineering Capability (part 2 – modeling physical factors) – Kim Warren

System Dynamics: a core Systems Engineering Capability (part 2 – modeling physical factors)

Kim Warren

Strategy writer | Strategy+Business modelling |Online strategy course + software

9 articles

This is the 2nd of three articles explaining how time-based, quantified simulation with System Dynamics (SD) is an ideal support for model-based systems engineering (MBSE) and is therefore a skill that every systems engineer should possess. Part 1,, used a small SD model to show how the method works, and its benefits. This 2nd part of the series explains how SD can model physical systems – construction projects, supply-chains, ageing assets and so on – and also include non-physical elements, such as workloads and costs. Part 3, at, builds the simple example from part-1 into a model of a larger business initiative and explains the wider opportunities for SEs to exploit SD business models.

(A conventional paper covering all three parts and offering more detail and examples is at

Modeling systems of physical factors

Since SD’s foundations lie in engineering control theory, the method has naturally been applied to a very wide range of physical-system challenges. Project management SD models are mostly built around stocks of work-to-be-done (as shown in the small part-1 model) and work-completed (Lyneis and Ford 2007). However, such models usually include changes that occur to quantities of relevant physical items or materials themselves – units produced, tons of material consumed and so on.

Other application domains are more centred on the dynamic behaviour of physical factors themselves. Supply chains are of course made up of interconnected stocks of items and materials, between which goods and materials flow. SD models of supply chains capture their high-level dynamics – how aggregate quantities rather than individual entities move and change over time – but can add connections to non-physical factors, such as workloads and the financial value of those materials.

Models can also account for often-powerful intangible factors and their impact on the management of supply chains. Fear of stock-outs, for example, may cause over-ordering, with potentially damaging and costly implications for inventory levels and flows (Sterman, 2000: chapter 17). Figure 1 shows a business holding inventory in order to meet customer-orders and replenishing that inventory with orders placed on a supplier and received after a delivery delay. The figure shows changes occurring to orders and inventory in response to a change in customers’ order-rate, given a particular policy for setting the order quantity to place on a supplier. The model at demonstrates the complexities of designing an ordering policy that best-meets changing customer orders while minimising the costs incurred by holding inventory.

Figure 1: Changing orders and inventory levels in a simple supply chain

Asset management is another domain in which SD models of physical factors have been applied. Such models can track populations of different types of equipment through a typical life-cycle – after a short bedding-in period, units have a long reliable life, before degenerating and becoming quite unreliable. The commitment of staffing and expenditure to maintenance, refurbishment and replacement of assets is a complex challenge that must balance system-performance aims (notably reliability) against the considerable costs of sustaining the network of physical assets. (See a demonstration model of such a challenge at

A key SD contribution – connecting systems of physical and non-physical factors

Physical factors feature in many SD models of environmental challenges, such as the management of water resources, natural resources (crops, fish, livestock …), and climate-change impacts (Ford, 2011). The special contribution of such models is the ability to capture interactions between physical and non-physical factors in a faithful simulation of an entire situation or episode – the asset-management model includes financial factors for example.

A much larger model requiring integration of physical, non-physical and financial factors concerns a large-scale engineering project to rejuvenate water quality and wild-life in a moribund lake, explained at *. The project required integrated modeling of the hydraulics and water quality, power-generation, physical construction, and the financial business case. Achieving this integrated simulation depended on capturing the knowledge of experts from several disciplines in a shared mental model, enabling all parties to see the relationships between their own part of the system and the whole. The resulting model enabled all parties to see, clearly and immediately, the impact of alternative assumptions and options for the project.

Suggested next steps

Continue to the part-3 article at, to see how the simple model from the part-1 article can be built into a model of a larger business initiative. Part 3 also explains the wider opportunities for SEs to exploit SD business models.

This case is courtesy of Copernicos Groep.

Ford, A., 2011. System dynamics models of environment, energy and climate change. In Extreme Environmental Events. Springer, New York, NY.

Lyneis, J.M. and Ford, D.N., 2007. System dynamics applied to project management: a survey, assessment, and directions for future research. System Dynamics Review, 23, pp. 157-189.

Sterman, J., 2000. Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill, New York.

The Mother of Modern Management:

A nice overview of the contribution of Lillian Gilbreth.
Just barely, perhaps, systems, but worth considering.

See also:
Lillian Gilbreth: The Forgotten Mother of Modern Management

The Tale of Taylor and Gilbreth

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


Today (May 8, 2016) is Mother’s day.  In today’s post I will be writing about somebody who has been called “the mother of modern management”, and “America’s First Lady of Engineering”, in addition to several additional similar titles.

She was known as “Mother” for several things – “Mother of the Year” (1957), “Mother of Industrial Psychology” (1954), “Mother of Modern Management” and “the greatest woman engineer in the world” (1954). (Source: Digging History)

Many of her concepts and ideas lend really well to the Toyota Production System. I will be looking at Lillian Moller Gilbreth, the wife of Frank Gilbreth. The Gilbreths were famous for the time and motion studies, and were most likely the first successful management consultant couple. Lillian did not study Engineering at school. She had a Bachelor’s and Master’s Degree in Literature, and a Doctoral degree in Psychology. Frank Gilbreth did not attend college, although…

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Forum for the Future | Systems change field building convening

Source: Forum for the Future | Systems change field building convening


In June 2018, we co-convened an event on Wasan Island, Canada, bringing together practitioners, academics, funders to explore together how we might work together to build the field of systems change.

In the context of growing use of the term “systems change” and increasing interest in systemic approaches to address some of the world’s most complex challenges, we co-convened a retreat in June 2018 bringing together practitioners, academics, funders to explore together how we might work together to build the field of systems change.

Pathways to building the field

In the run-up to the retreat, we asked people attending and unable to attend to offer their definitions of systems change, and of field-building. In June we spent three days on Wasan Island, Canada, with a group of 25 people exploring pathways to building the field. These pathways are interlocking, mutually supportive routes from where we are today to a desired future. They form a nested hierarchy, with the “Stewardship” pathway supporting the other four, which together contribute to cultivating systems change practice in service of our collective purpose.

Download our full write-up of the retreat here:

Systems change: a field building convening

Improvisation Blog: Stafford Beer’s Critical Holism in Education – Mark Johnson

Source: Improvisation Blog: Stafford Beer’s Critical Holism in Education

Thursday, 15 November 2018

Stafford Beer’s Critical Holism in Education

I gave a presentation about how Stafford Beer’s work relates to education to a small group of people from the education faculty at Cambridge last week. I wanted to avoid presenting Beer’s work as a kind of fait-accompli, where the Viable System Model (VSM), or Syntegration is the answer (I think this kind of evangelism is very off-putting). But his work is mind-blowing, and if he didn’t “have the answer”, he certainly had an important way of asking questions in a very practical way which is sorely missing from anything in the educational discourse today.

The problems – the reasons why the VSM or Syntegration isn’t the answer – or indeed, any other cybernetic theory cannot provide a full answer – are that fundamental problems of time, meaning, emergence, non-ergodicity and coherence haven’t been resolved in any of the systems sciences. This is why, for example, the question of agency in cybernetic descriptions is such a problematic question: “where’s the person? They’re in the recursions”, which leads to a slight air of dissatisfaction. We can work to improve this situation – but this will only happen with a critical engagement with cybernetics.

This is not to take anything away from Beer. He nailed what he was doing and what cybernetics is really about: “Cybernetics is about holism”. Yes. There are of course many many definitions of cybernetics, which describe it as “ways of thinking”, or “ways of thinking about ways of thinking”, “the art and science of defensible metaphors” (!), or “the science of effective organisation” – it all gets rather philosophical, giving a newcomer the feeling that they’ve arrived in some kind of cult. But, in the end, what unite them all is that they all deal with wholes. They all run counter to reductionism.

Holism has a bad name. It is rather closely associated with cults, with theories of everything. But this isn’t what Beer meant. He was after (and indeed possessed) a science of holism (notwithstanding the problems raised above). If it is wholes we have to grapple with, and not parts, then we need to know how wholes work – and they are not simple things, but once opened out, they reveal a structure. It is this structure which can be studied and experimented with.

The structure unfolds because whatever whole is considered contains things which cannot be decided. Beer calls these “undecidables”. I have recently preferred simply to talk about uncertainty. The point is that this uncertainty has to be dealt with, and by definition, it cannot be dealt with within the “whole”. So any whole requires a metasystem – something which sits outside the whole and mops up the uncertainty. It does it, often, by imposing categories for dealing with the uncertainty. It’s the metasystem where the reductionism goes on!

Beer knew that there were good and bad ways in which the relationship between a whole and a metasystem could work. If education is seen to be a “whole”, then the metasystem has to mop up things like uncertainties over teacher and student “performance”: it invents categories and metrics to measure teaching and learning. It even ties some of these metrics to the pay or job security of teachers. More recently it deploys technologies to reinforce these metrics. What happens? “explosive complexification”.

Why do these uncertainties arise in the first place? What is it about the whole which invites pathological metasystemic regulation? There’s a simple answer to this. It is the hierarchical structures of organisation which education adopts. These structures themselves are very poor at mopping up their own uncertainty: hierarchies attenuate complexity from their bottom to their top, and from the environment to each individual. The only mechanism they have for managing uncertainty is authoritarianism, and this eventually leads to collapse.

What is required are forms of organisation which manage their uncertainty effectively. In education, the most effective way any individual – whether teacher or learner – can manage their uncertainty is to talk to others: “What do you think?” The best form of educational organisation is one which creates the conditions for conversation. Here, Beer’s holism suggests that the way to do this is to disrupt the metasystems of each individual. This is really what he attempted with his Syntegration technique. It’s what Von Foerster articulated when he spoke about education’s role in learning to ask “legitimate questions”, or questions to which nobody knows the answer:

  1. “Education is neither a right nor a privilege: it is a necessity.”
  1. “Education is learning to ask legitimate questions.”

A society who has made these two discoveries will ultimately be able to discover the third and most utopian one:

  1. “A is better off when B is better off.” (Von Foerster, Understanding Understanding, p209)

Understanding how Von Foerster gets from 2 to 3 is core to appreciating the power of Beer’s Critical Holism.

What can Social Systems Theory bring to the VSM? | strategic structures – Ivo Velitchkov


Source: What can Social Systems Theory bring to the VSM? | strategic structures


What can Social Systems Theory bring to the VSM?

In 2015, when the Metaphorum was in Hull, I tried to kick off a discussion about potential contributions from cognitive science, and particularly from the Enactive school. I shared some insights and hinted at other possibilities. This year the Metaphorum conference was in Germany for the first time. It was organised by Mark Lambertz and hosted by Sipgate in Düsseldorf. I saw in the fact that the Metaphorum was in Germany a good opportunity to suggest another combination, this time with the Social Systems Theory of Niklas Luhmann.

These are the slides from my talk and here you can also watch them with all animations.

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