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REFLECTIONS ON THE FRACTALORGANISATION BY PATRICKHOVERSTADT

by John Coghlan

INTRODUCTION

Accessible

I recently said to a friend: “Stafford Beer’s Viable System Model is brilliant. It is certainly superior to bureaucracy. Why hasn’t it been adopted more widely?” My friendreplied, “The model is just too complex for many managers to understand. “

Solution

Enter Patrick Hoverstadt, with his book, The Fractal Organisation: Creating SustainableOrganisation with the Viable System Model (John Wiley and Sons Inc, Hoboken, NJ, USA2008). The book shows:

1. how to use the Viable System Model to improve organisations2. management tools to improve such things as change management and

innovation.3. organisational pathologies to remedy

I. A HUGE PROBLEM

Hoverstadt points out that the old bureaucratic, energy-flow, command-and-controlorganisations have short lives, while their projects have a very high failure rate.Most studies show that in the US and Britain:

• 90% of strategic plans fail• 85% of US companies fail within 40 years; half of British firms, within 12.5 years• Organisational change management projects fail 70% to 80% of the time.

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• Monitoring within firms very often fails, while leading to corporate game playing such as failing to report certain things to be able to attain goals.

II FAILURE, COMPLEXITY AND EMERGENCE

II.1 The old world has gone

Why are command-and-control, hierarchical, top-down-managed bureaucracies, that once served us, failing us? For one thing, the world of Weber, Taylor and Henry Ford is gone: the world is awash with complexity. With this, comes a phenomena married to complexity, emergence and unpredictability. There are also inherent weaknesses to the old bureaucracies which make it impossible for them to deal with these complexities.

II.2 Complexity and Emergence

What are the reasons for the failure? Why did bureaucratic management work well, but now, it is working poorly? Hoverstadt blames, for one, complexity and emergence.

II.3 Now and Then

Society is vastly more complex than in the time of Weber, Taylor and Ford, three who, a century ago, brought us a theory of bureaucracy and of mass production. Hoverstadt states that when Henry Ford first used Taylor’s Scientific Management a century ago, 95% of employees could not at first do their boss’s job. Now the ratio has reversed. When Henry Ford began to manufacture his model T, the market was happy with one model in one style in in one colour. Now, as people become vastly more educated than when Ford started out, markets have evolved vastly beyond this in complexity. Weber’s ideas on bureaucracy have, too, worked well, up to a point. But now, given a hyper-complex and hyper-connected world, many bureaucracies are failing to accomplish what they should.

II.4 Kondratieff, Schumpeter and Complexity

Allied with what Hoverstadt states, according to some futurists, knowledge in society now doubles every two years. With the Internet, research becomes vastly easier. One can obtain copies of scholarly articles in moments, while write replies to the author in as much time.

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Kondratieff, though, the Soviet economist who discovered that capitalist economies run on fifty-year boom-bust cycles, may still apply. With each fifty-year business cycle (Kondratieff Cycle), new technologies enter to buoy up downturns. Technological innovation, based upon scientific discovery, seems to shadow these cycles:

1. Watson’s condensation chamber (1770s) led to a post Napoleonic upturn in European economies with the steam engine and the steam boat.

2. Faraday’s and Oerstedt’s experiments (1820s) on electro-magnetism, led to Morse’s telegraph, leading to building large scale telegraph networks

3. Their ideas later led to Clerk-Maxwell’s theories on electro-magnetic fields (1865), then to Herz’s experiment proving that Clerk-Maxwell’s electro-magnetic waves exist (1887), leading to large scale telecommunications networks, with radio, television and microwave stations.

4. Max Plank's Quantum Theory of 1900, led to such discoveries as the transistor and the laser, leading to the “high tech” business cycle.

5. Watson and Crick's model of DNA of 1953, has led to the latest economic cycle, the biotech cycle. This cycle is taking up the slack from the falling high tech cycle.

II.5 New Cycles, vastly more complexity

Each new techno-business cycle brings us technologies tens of times more complex. Compare the thousands of parts of the car with the millions in a laptop (active, though non-moving parts, the semi-conductor junctions) – then think of the complexity of genetic engineering.

(Please note that some inventions spurring an upward jump in an economic cycle, are not tied in with paradigms, such as accidental discoveries. On was in the early 1850s, in which Henry Bessemer found that air blown upon melting iron helps to burn out impurities as well as fuses any carbon in iron ore to the iron, to produce high quality steel at a faster rate than before.)

II. 6 Complexity and management

This growing complexity calls upon workers and managers to have much higher education (that is, command much more information and complexity), while dealing with much more complex means of production and management. So in brief, whereas products and production must have far greater complexity, so workers and managers, far greater education (inner complexity). This has led to the great complexity that bureaucracies fail to deal with.

II.7 Folding Cinnamon rolls: Determining the Indeterminable Out of great complexity, comes emergence. What is emergence? Let’s look at a cinnamon roll. A cinnamon roll has layers of cinnamon in it, giving each slice the characteristic whirl in the centre. Ivar Eckland points out in his book Au hazard : la chance, la science et le monde (Seuil, Paris, 2000), that if you fold cinnamon-roll dough

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several times, it may be a deterministic process. But then again, if someone tries to divine later how you folded the dough, it could have been done in hundreds of ways. This is a grey area with determinism, with chains of causes too complex as to be knowable. “Emergence” emerged from the study of such systems.

II.8 Knowing limits to knowing

When we know that we can’t know something, we are dealing with an epistemological horizon: a horizon like that of a black hole. One can see such thinking in such things as Heisenberg’s Uncertainty Principle and Godel’s Theorem. Three hundred years ago, Francis Bacon wrote that his scientific method would find out all there is to know in twenty years. We now know that there are things unknowable. One hundred years ago, we did not know that there were some things we could not know. And so with emergence in organisations, in markets and in technology. Organisations must have ways to deal with the emergent: events they cannot clearly predict. Bureaucracies though, tend to be poor at this. Their strength is in controlling only predictable outcomes in very stable environments.

III BUREAUCRACY’S WOES

III.1 Complexity’s problems

Hovercraft speaks of the problem of complexity leading, in bureaucracy, to:

1. poor risk management2. poor change management3. poor communication4. poor adaptability

As well, I believe, bureaucracy leads to an inflexibility of mind, incapacity to deal with adaption needed when faced with emerging trends.

III.2 Modern Times syndrome

One problem that Hoverstadt did not bring up: command-and-control bureaucracyInstils obedience; not questioning; following, not creating; rigidity, not problem-solving. In the film, Modern Times Charlie Chaplain’s job is to tighten a screw on mountings passing on an assembly line. When he leaves to go to lunch, he still automatically turns screws in mountings. When he arrives at the cafeteria, he has lost his mind, continually tightening imaginary large screws in mountings.

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Comical, but revealing: how many times have you met people in bureaucracies saying, to good solutions or to good suggestions, ‘’But we’ve always done it this way.’’ Given Charlie-Chaplain like mindsets, how can employees deal with risk, change, adaptability or even participate in it? How can they adapt to emergence rapidly? How can they innovate? How can they deal with risks fast and effectively? How indeed, when they work in an atmosphere of fearing to “rock the boat.” How indeed, in a strongly command-and-control environment, a production line environment, where clichés abound as in Ionesco’s, The Bald Soprano.

III.3 Poor Risk Management

Given the deeply complex environment of today, risks are a part of emergence within the environment. For Hoverstadt, poor risk management at the head of the list of causes for early corporate failures. Here he cites Machiavelli, who stated that we too often see a threat when it is too late, rather than being able to divine it well before hand. Hoverstadt also speaks of Clausewitz, who spoke up for decentralization of military units. During the Napoleonic occupation of Spain, Napoleon insisted on fighting Wellington’s expeditionary force from Paris. The Emperor would send orders based upon old intelligence. Meanwhile the British military gave Wellington free-reign to decide as he saw fit. The French, with outdated intelligence, and outdated decisions, continually lost to Wellington’s much smaller forces.The moral: lower units must not only be able to see risks, but to act on them quickly, as well. So each unit of an organisation must keep tabs on those their work affects, and those who could affect their work: stakeholders. Hoverstadt thinks that it would be good to keep daily or weekly databases on these, but not in a corporate headquarters, but in a unit office.

III.4 Too Many Filters, Too much time

One element that I have seen is that bureaucracies filter out important weak signals, with too many layers of hierarchy filtering out too much information and wasting too much time doing so. By the time high authority gets the message, figures out a response, then sends the orders on how to deal with the signal, through many layers of hierarchy, it is too late to deal with whatever the signal is saying: Wellington has won the battle. By the time the message of pain travels the long distance to the dinosaur’s brain, mice have eaten away part of his tail. By the time he reacts, the mice have fled. This is why huge bureaucracies deal with strategic threats, strategic opportunities and innovation, poorly.

III.5 Little Participation, Less Change

In change management, employees in bureaucracies have little say over the changes

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made, so lack commitment to the changes. Certain units cannot adapt to the changes at the rate top management has prescribed. Different parts of an enterprise have different degrees of adaptability: when certain units try to adapt beyond what they can do, then the change fails. Writes Hoverstadt, employees usually subvert change after thechange begins to fail, not before.

III.6 Poor Communications

Hoverstadt shows also that poor communications Have been a culprit leading to early deaths of the command-and-control, top-down, hierarchical bureaucracies. Flexibility comes, in part, from good, fast communications. For one, given their inflexibility, bureaucracies handle risk management and change management poorly.

III.7 Inhibiting dialogue

Strict command and control bureaucracy also inhibits dialogue betweenStakeholders. What Hoverstadt proposes, based upon Stafford Beer’s work, is an organic, non-mechanical system, is based upon continual dialogue between any unit and any other its activities may affect, or be affected by. This opening of communications is one of its secrets to adapting within and without, to be able to survive.

IV THE SOLUTION: THE SYSTEMS ORGANISATION

But what kind of organisation could be better than bureaucracy? The post-World-War II era has brought us the systems or cybernetic organisation and management. Cybernetics, from the Greek word kubernetes, a steersman (kuberman = rudder), is the science of steering organisations to attain their goals. Purpose-oriented networks of relations between people or things, states, variety, flows of information – all of these deal with the elements on which the Viable System Model is based.

Bureaucracy is based upon mechanical models: top-down flows of energy, with an experienced elite and those who follow. Systems-based organisations are based upon biological models: flows of information within a networked context.

IV.1 Solution: The Systems Organisation

To understand the Viable System Model, first get to know systems, variety and self-controlling networks, which generate variety.

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Patrick Hoverstadt suggests the Viable System Model as a way to raise the longevity of organisations and projects. The Viable System Model is based upon systems science. Systems science and the cybernetic organisation deals with the inter-relationships of the units to the whole organisation, the relationships forming networks between people or things working toward a result. To understand the Viable System Model, let us take a look at systems in general. A systems organisation is based upon:

1. The interrelationship of the parts (units) of an organisation, and thatthese should be aligned to support the identity and viability of the organisation.(While for a bureaucratic organisation, the top-down hierarchical command is all important, in a systems organisation, inter-relationship is most important.

2. An organic rather than a top-down structure: the organic paradigm, as AlfredNorth Whitehead described in his book, Science and the Modern World (Cambridge University Press, 2011, originally published in 1926), that in which one part is a microcosm of the whole of a system. (We will see below how this fits in with the idea of fractal).

IV.2 Systems as bathtubs

A system can be as simple as a bathtub. One of the Club of Rome’s founders, Dr. Donella Meadows, in her excellent book, Thinking in Systems, A Primer, (White River Junction Publishers, Hanover, New Hampshire, 2008) described systems as a bathtub. The state of the system was how high the water was in the tub. The plug and the tap were regulators to change the state of the system. They were valves to add water and to reduce water. The water can be many levels, the states of this system. The variety of this system tells you how many different states the system can have, that is, levels the bathwater can take. The purpose of the system is to regulate bathwater levels.

IV.3 Variety as levels of bathwater

Yet in an organisation, variety is certainly more complex than bathwater levels. But it is the same idea: when five people can do a task five ways, then we are dealing with 25 as the variety. Variety measures the complexity of the organisation. So systems regulate variety, and so regulate complexity, toward a certain goal. And the goal is what the system does or produces. It could be ensuring the right level of bathwater, or producing high-quality passenger aircraft.

IV.4 Variety Rules

Variety has rules. Ross Ashby, a psychiatrist and cybernetician, wrote the first two rules on variety in systems, while an associate, an engineer and cybernetician, Roger Conant, cited the third:

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1. only variety can absorb variety2. the system controlling a sub-system must have more

variety than the sub-system it governs

Another rule, stated by another cybernetician, Roger Conant, states that the governing part of a system must be a model, in miniature, of the system it is modelling. This will be important when imagining the fractal organization.

IV.5 Networks with an End

Russell Ackoff, architect and cybernetician, defines systems as networks of relations between entities working together to produce a result. So the Viable System model is akin to Donella Meadow's bath-tub system, with people either increasing or decreasing the complexity - read variety, in networks of relations. When a certain unit needs to produce more widgets in the interests of the organisation, that unit increases its potential for variety, taking measures to expand, or otherwise increase production. When the need for production of a certain widget decreases, the unit takes measures to decrease its variety, by, say, sending employees to another unit, passing on machines to other units or whatever. When the products turn out to have lower quality than the client wants, then the producing units increase their complexity by studying processes and constraints. When the market demands a better, more complex widget, then production must increase its variety, producing the new, more complex item.

V THE VIABLE SYSTEM MODEL

V.1 Fractals

What is a fractal? At the end of the 19th century, mathematicians began to have an interest in what later was to be called ‘’fractal geometry.’’ In the early 20th century, starting with the mathematician Poincaré and others, mathematicians and physicists began to question if there were limits to knowledge. At the end of the Second World War, mathematicians, engineers and others began to become interested in complex systems. In the seventies, Stafford Beer, a consultant, made up an organisational structure based on that of the most complex information handling system: the nervous system. Out of all this has come Hoverstadt’s fractal, Viable System Model organisation.

V.2 Scales and Fractals

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Networks can either be symmetrical, with each node having the same number of connections. Or they can be a-symmetrical. The a-symmetrical networks that grow into structures that contain similar structures that contain similar structures and so on – scale-free networks, are the networks that organisms and that organisations are built upon.

What’s a fractal organisation? The fractal organization is built upon self-similar units contained in like units, contained in like units and so on. And so the fractal organization of Patrick Hoverstadt’s book is one with similar units, contained within similar units and so on.

Stafford Beer’s Viable System Model deals with a paradigm, or model, that is information (systems) based. It is based upon the most complex information handling system we know of: the human brain and nervous system. It is also a scale free model, a fractal.

V.3 History of Fractals

Fractals have over a hundred year history. In the late 19th century, mathematicians were fascinated with the very nature of coherence in mathematical theory, and the idea that there were singularities, geometric objects, for example, contradicting mathematical principle. One was the search for geometrical figures that were continuous but undifferentiable at every point, which is what fractals are. Benoit Mandelbrod, a mathematician working for IBM, formally set up fractal geometry in the seventies, which is when Stafford Beer, a management consultant and cybernetician, developed the Viable System Model.

V.4 Re-iteration, Self-Similarity

Fractal geometry is the geometry of self-similarity and re-iteration: it deals with forms, let’s say a triangle, containing smaller triangles containing themselves even smaller triangles, and so on. Just so the fractal organisation has the same set of managerial structures within like managerial structures within like managerial structures.

V.5 Paradigm Leap: Viable Systems

The new, cybernetic organisation is a change in organisational models. Peter Drucker, the eminent management writer, has written about this change. It took Stafford Beer to describe it in detail. And now, Patrick Hoverstadt is describing this for the public.

V.6 Kuhn On Paradigms

Before describing the Viable System Model, first, a word on models, or, as Thomas Kuhn called them, paradigms. Thomas Kuhn wrote the book, The Structure of Scientific Revolutions (University of Chicago Press, 1962). His theory is that science advanced in leaps, each leap starting with new scientific models of something – a paradigm.

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V.7 Organisational paradigm change

Peter Drucker stated that organisations are moving from a paradigm based on energy flow, to one based upon information flow, from being based upon mechanical models to being based on biological models. He also stated that the new organisation was based upon biological models (see Bertalanffy, Ludwig von, General Systems Theory Foundations, Development, Applications, George Braziller Inc., New York, USA, 1968).

V.8 Morphology of an information organisation

What would an information organisation look like? Stafford Beer (TheBrain of the Firm, John Wiley and Sons, Chinchester, 1972), developed an organisationbased upon flows of information – within the nervous system. Beer points out five levelsof the nervous system, from the tactile-kinesthetic nerves producing sensation andmuscular action to the neo-cortex, contemplating the future. These correspond to fivesystems of the viable organisation.

Hoverstadt calls them:

1. Operations2. Coordination3. Delivery Management and Monitoring4. Development5. Policy

Note that the first three deal with what Beer called the here-and-now, while the last two deal with the there-and-then. Note that the first three systems deal with what Beer called the ‘’Here and now’’, while the last two deal with the ‘’There and then.’’ That is, the first three levels deal with the concrete mostly, while the last two deal mainly with abstraction, for example, looking forward into the future

V.9 The Organic Paradigm and Adaption

The information organisation that this model describes, allows, states Hoverstadt, toadapt to environments and to emerging problems and opportunities must faster andmore effectively than can bureaucracies. In 1926, in his book, Science and the ModernWorld, (Whitehead, A.N. (1997) [1920]. Science and the Modern World. Lowell Lectures. Simon and Schuster, New York) Alfred North Whitehead wrote of a change in paradigm in world view from that of the mechanical to that of the organic. In organic systems, the parts were microcosms of the system itself. Hoverstadt's describes the fractal VSM organisation is both an information system and an organic system.

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VI. VSM AND BETTER ACCOUNTING, MONITORING AND SIGNALLING

Vi.1 The VSM and Stakeholders

How does one ensure that firms and projects can survive longer and succeed? Hoverstadt states that one big failure of the traditional, bureaucratic firm is in monitoring stakeholders. Stakeholders are not only clients, but anyone outside or inside the firm that could be hurt or helped by a decision in the firm. An example of stakeholders are those living in areas a plant may pollute, or those within the firm – for example, who may immediately need a tool or whatever to complete their work. So a study of stakeholders is a study of networks of relationships.

VI.2 Stakeholder accountability and the VSM

Hoverstadt touches on stakeholder accountability, dealing with it more fully in a paperhe wrote, Complexity, Governance and Risk. In bureaucratic organisations, informationis often caught in silos: the left hand knoweth not what the right hand doeth. I have mentioned, too, that often levels of hierarchy cut off vital information about emergence. So many bureaucratic organisations fail with social accountability, the stuff of scandals. If a firm deals with an African supplier using child-slave labour, the consumer will find out. The Web has made the world that much more transparent. The Viable Systems model, without silos, ensuring better information flows, so that stakeholders within can more clearly see problems and opportunities of stakeholders without.

VI.3 TALE OF NETWORKS

Look at flows of information within with a bureaucratic hierarchy, then within a network-based organization – a systems organization (remember that systems are networks of interrelationships). Take a large government bureaucracy with nine layers of hierarchy: from bottom to top, information must pass through eight junctions. Organizations based upon systems models – that is, upon networks of relationships, offer workers only three or four degrees of separation: half the number of junctions to pass through to get a point across. Think of what this means to an organization’s units’ ability to communicate with one another, to the ability of an organization to adapt and change, to respond fast to challenges or opportunities.

VI.4 Monitoring for performance in bureaucracies and in the VSM organisation

With a bureaucracy, there is top down monitoring. But with a Fractal VSM organisation,

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each unit monitors the relationships it has with stakeholders, inside and outside the organisation. Hoverstadt sets down several rules for monitoring toavoid corporate game playing. Basically the monitoring is done closer to the source ofinformation, and the measures on which the performance is judged are agreed to by allparties. Autonomy, auto-control and such concepts recur often in systems thinking.

VII Networks of signals: Threats, Opportunities, Innovations, Changes

VII.1 Bureaucratic Pitfalls

Much of the problem with bureaucracy is in reading signals and in communications. Bureaucracies are prone to three signalling pathologies:

1. Peter Drucker said that by going through a level of hierarchy, a signal loses half its information; and so by the time those at the top of the bureaucratic structure read signals, they may very well have missed important information about emerging trends.

2. The number of layers of hierarchy that a signal must pass through ensures that it sometimes travels too slowly for the organisation’s good, ensuring that top brass only react to a signal too late.

3. And not only news of threats may trickle too slowly up the bureaucratic vine; good ideas for innovations may to, or may be completely be filtered out of the lines of command and control.

4. Systems organizations are scale-free networks of relationships leading to specific results. Given seven billion people in the world, it takes only six intermediary people to connect anyone on the globe. That is networking. Now consider the Canadian federal government bureaucracy. It has at least nine layers of hierarchy, with only 260,000 employees. (confer: http://www.tbs-sct.gc.ca/res/stats/ssen-ane-eng.asp) Without going through the mathematics, it appears that there are twice the number of degrees of separation in the hierarchy than in the network.

5. The point here is that bureaucracies are poor at handling information. The systems-based organisation, such as the Viable System Model, is based upon networks of signalling between stake holders, rather than keeping information in silos, or filtering it out, or reacting too slowly to it.

VII.2 Strategic risk:

The most pressing problem in ensuring that an organisation survives, states Hoverstadt, is to find strategic risks far before they become strategic problems, as Machiavelli once pointed out. In the fractal organisation, each unit would keep tabs on stakeholders within its domain, and those dealing especially with strategic risk could monitor these

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daily. Where bureaucracies deal with top-down flows of information and slow and very incomplete bottom-up flows of information, the systems organisation such as the Viable System Model organisation concentrates on modulating relationships much more between stakeholders, be they within the organisation or without.

VII.3 Reading Signals

How does one know if a tiny signal from, say, the market, is a strategic risk, opportunityor whatever will lead to an emergent trend? Beer proposed a solution: using Bayesian statistics: these don’t measure the probability of an event alone, but rather, given the probability of one condition, what the possibility of a specific phenomenon happening given that condition. Bayes’ statistics separate the emergent signals, ones that are unexpected in a certain context, from the static of meaningless, weak signals.

VII.4. VSM and Communications

These are reasons for believing that the VSM handles communications better than bureaucracies. Possibly, the most important, is the proximity of one person or unit to everyone else – one need go through far fewer junctions to contact another, than in a bureaucracy.

VI.5 Change Management

Bureaucracy, as we have seen, has great difficulties with change management. With change management, managers often move ahead when they succeed with a change, but lag when a change does not succeed. As well, managers vary in their motivation to carry out the plans and, as said, various units have different capacities to change and to change in certain areas. It is such things that usually ensure a lack of harmony in the changes, and this leads to failure in change.

VII.6 Mosaic management

For change management, a huge problem as we have seen, Hoverstadt prescribes Mosaic Change Management. This method comes from a biological paradigm. Peter Drucker said that we are changing the paradigms of organisations from mechanical systems to biological systems (see Ludwig von Bertalanffy, cited above). Interesting that mosaic change management comes from a phenomena making biological evolution possible. If a certain organ or whatever radically changed in an animal or plant, it would call for radical changes all over their bodies. As well, were a species to radically mutate, then they would have a hard time finding a niche in their ecosystem. But not so if they evolved in very small steps, and leaving vestigial elements of their bodies behind as a

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backup allowing for the same old organs to do the same work, while the new systems are slowly taking up this slack.

VII.7 The VSM and Mosaic Change Management

In Mosaic Change Management, each unit adapts to change at its own rate but works with other units, regulating their interactions, and to keep vestigial elements to ensure that there is enough variety within the unit to continue the work they are doing, Mosaic change management within the Viable System Model resolves several problems that change management regularly faces:

• The lack of commitment of workers and lower-level managers, when planning is highly centralized

• Trying to change a section too fast, as the change requires more variety to do so, so in changing at its own rate of change, managers avoid failures

• More networking between stakeholders, no silos to deal with, in whichimportant information has to rise up the bureaucracy then down, to get to astakeholder affected by changes in one’s section.

• More autonomy to tailor changes, but also to ensure coordination withstakeholders, and to ensure that these changes to the changes do notcompromise the whole program

VII.8 Interactive Management

Another fascinating change management method Hoverstadt brings up is Russell Ackoff’s Interactive Management. Ackoff bases the method upon these bases:

1. Participation: everyone must participate in the discussion about the change, in all units of the organisation, so all units form planning boards

2. Each group must arrive at a consensus as to the qualities of the ideal situation they are striving for and the ideal properties of the design that they wish to aim for.

3. Each group works on ways to deal with obstacles blocking the road to the ideal design.

Ackoff believes that to solve a problem, you must take into consideration these things:

1. That the solution to the problem lies in an area outside the problem area, that is, with a metasystem.

2. That to solve a problem, one has to redesign part of a larger system.

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3. That one should start not with the problem area, but with the whole organization to see how the workings of the whole organization may bring about the problem.

In brief, the method deals with wholes as interactive systems, not with just parts as separate things

VII.9 Team Syntegrity

Stafford Beer himself developed this method. The idea is that the ideal discussion group is made up of five to twelve people, and that the organisation call these small groups together to decide on changes and methods. Then people from each gr1oup pass on to people of another group to discuss the changes and methods.

The idea comes from Buckminster Fuller’s idea of syntegration. In Fuller’s architecture, syntegration is the art of balancing compressional and tensional forces. Doing so, using cables and solid beams forming triangular units, allowed for building domes far larger than those which could be made based upon tensional forces alone.

Fuller believed that this study of balancing forces could be used to model all systems. He believed that all systems could be modelled as polyhedra. The complex polyhedral that he constructed were based upon either triangular faces or pentagonal faces.

Beer used the ideas of the mathematician Bavelas to study the centrality of communications in a system. If one were to describe communications as a polyhedral with people as nodes and struts as contacts, then how could one ensure that everyone was equidistant from everyone else? The answer: to build an isohedron, made of small groups of pentagons as faces, and, in all, having 30 nodes. This forms the basis for discussion in Beer’s Syntegration. Groups of five people work on one question, come to some agreement, then link together into larger groups (isohedrons) of thirty, each of six groups of five working on the same problem. This is a reiterative process moving to larger and larger groups, until all stakeholders have thoroughly discussed just that one question.

Professor Malik, of the Malik Institute for administration, of St. Gallen University, in Switzerland, stated that using this method increased organizational effectiveness eighty times, while speeding up decision making a hundred times.

VII.10 Strategic Opportunity: Innovation

To adapt to the environment, be it customers or competition or new technologies,organisations must innovate. Each unit, in fact, should be able to innovate, Hoverstadtstates, assessing themselves and reporting on such things as the viability andcontribution of an innovation. As mentioned above, he proposes using Bayesianstatistics to measure the viability of an innovation project as it unfolds..

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VII.11 Unleashing innovation

Bureaucracy’s command-and-control over the units, and layers of hierarchy, both militate against innovation. Those wishing to innovate usually wait an interminable time for approval from higher authority, and the innovation idea must go through several channels, greatly reducing the information higher management can have about the proposed innovation. If time doesn’t kill the innovation, filtering through the hierarchy will.

Hoverstadt proposes that units of the organization put forward innovations:

1. Proving that there is a good possibility they’d work2. Showing how much and who these would help the organization 3. Continually working with stakeholders to ensure that the innovation helps

without hurting4. Works with Bayes theorem to study emergent trends in the innovation.

Now autopoesis (from the Greek, ‘’self-creation’’) studies things emerging spontaneously from given conditions. Given conversations, relationships, study, new information and so on, new ideas emerge. This is the autopoesis of ideas. (cf. works by Drs. Umberto Maturana and Francisco Varela and their idea of autopoesis.)

VIII. On performance and complexity

I have covered some of Hoverstadt’s explanations of the VSM and its superiority over bureaucracy. I have covered the main concepts, as well as certain management methods which Hoverstadt speaks of. Hoverstadt speaks of other concepts, such as performance measurement, coherence, governance and so on, which I will not touch here, save to say that the book has a wealth of ideas that, I believe, few business books can touch.

Performance measures have often led to unintended results. Police not reporting many crimes so as to show that the crime rate is down, or vice versa. Hoverstadt mentions three rules for measuring performance . One is that the performers and observers should get together to set these measures up.

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VIII.1 Dynamic Performance Management

The author also mentions Dynamic Performance Management. Workers work better when personal goals align with organisational goals. Workers work better if they try to surpass what they have shown themselves capable of. Workers work better if they receive more coaching – that is, more, and more regular, feedback. These are some of the pillars of this system.

VIII.2 Complexity drivers

What elements raise the variety (the complexity) an organisation must deal with? Hoverstadt names four:

• Geography• Time• Client s• Technology

All contribute to the complexity (and so, the variety), of the organisation. Primaryactivities, says Hoverstadt, must be broken down into these areas. Roughly, they deal with where, when, who and how.

VIII.3 Cutting Variety:

The right variety is something the system must have: Hoverstadt points out and example of cutting variety to be able to cut waste and ineffectiveness in a firm. Here, he writes on how assembly lines may actually increase complexity and variety in a process, rather than diminish them. He points out how cellular manufacturing - small multidisciplinary teams, sometimes can vastly reduce the complexity in manufacturing done on an assembly line.

VIII. 4 Dialogue over Dogma

The Enlightenment has been a movement of dialogue over dogma. And so with thesystems-based (cybernetic) organisation, such as that which Beer designed. Hoverstadtcovers innovation, change management and risk management. In all three, dialoguebetween all stakeholders plays a far greater role than in top-down bureaucracy. Since all units work on these elements of management, or at least all can contribute, they have much more commitment to the outcome. Since all can adapt their activities, coordinating these adaptions with other stakeholders, units can work in harmony with other units with innovation, change and managing risks. As an organic-system and not mechanical system, the Viable System Model allows for rapid change, innovation and

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avoiding risks emerging fast, things bureaucracies have great difficulty at doing (See above, VI.3 Tale of Networks).

IX. PATHOLOGIES

Not only does the book deal with the VSM. At the end of each chapter lies a sectiondescribing corporate pathologies in the area covered by that chapter. I give here four examples:

1. the open feedback loop2. the bean counter3. the one building castles in the sky4. silos decisions

IX.1 Open Feedback Loop

For example, the feedback loop is not closed: that is, the people who need the positive or negative feedback to either improve or augment their work, do not get the information the feedback they need.

IX.2 Bean counters and Castle Builders

In another archetype, the bean counters, accountants can argue that the company is doing well concentrating on what they are doing. However, they may totally fail to foresee a coming opportunity or danger. Indeed, Russell Ackoff spoke about errors of omission. What happens when one decides NOT to do something? How did that decision help or hurt the organisation? On the opposite end lies another archetypal pathology, castles in the sky: the visionaries who rob the present to produce the future.

IX.3 Silo Decisions

Silo decisions is another: when one is working on strategy, people from many disciplines should participate in the dialogue. Better decisions come from greater participation of people from many disciplines. It goes back to the study on the submarine, the USS Scorpion, lost off the Azores in the late sixties. An interdisciplinary team, each giving their estimate as to where the sub could have gone to the bottom, tracked it, to within meters of where it was found. Silo decisions can go wrong by 1) not taking into account the effect the decisions have on others outside the silo and b) not taking into account points of view with presuppositions different from those within the silo.

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Most of the methods that Hoverstadt writes about are based on either proximity of the stakeholders, such as in monitoring, or autopoesis and self-control.

X THE FUTURE

At the end of the book, Hoverstadt shows how VSM analysis helped three organisations in three domains to solve problems: manufacturing, information technology and medical care. Another organisation showing good results from using the VSM model on studying organisational problems is Malik Solutions, in St. Gallen, Switzerland. Certainly, several case studies have attested to how the VSM is an excellent diagnostic tool for an organisation.

I have gone over certain elements of the book, yet also have added certain ideas showing the depth of Hoverstadt’s thought, the depth of Beer’s thought and systems methods Beer speaks about using with the VSM. Yes, there are ways to overcome the crisis of short lives in enterprises.

I have focussed on the larger questions of the Viable System Model itself: it’s nature, it’s advantages and so on. Hoverstadt covers certain questions such as cohesion, governance and so on within the organization, questions that I have scarcely dealt with. My point was to look at VSM in its entirety, not so much the parts.

On the future of the VSM, neural research is finding out fascinating new things about how neurons and regions within the brain, network. It would be fascinating to see cyberneticians with interests such as Beer’s, to move ahead, refining the VSM based on this new research.

The book exudes information, explains ideas simply and offers the reader anintroduction to a systems-based structure of an organisation. The book presents a verycomplex subject to managers, directors and CEOs. Given the death rate oforganisations, change management projects and other projects, thebook has much to say about making an organisation much better able to sustain itself –be viable. “Sustainable” has become a catchword, This book shows the way. .