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Systems Philosophy

Extracts from: Hitchins, D.K.,
Advanced Systems, Thinking and Management
,
Artech House, Norwood, MA, 2003

                      INDEX

—Developing Systems Philosophy - 20th Century

An Increasingly Mechanistic World

Perceived Limitations in the Traditional Sciences

Life and the Second Law

Information and Entropy

Causality and Teleology

Concept of Open Systems

Summary

Systems Philosophy and Applied Science

So, What defines a System?

Tenets of Systems Philosophy

Understanding Emergence

'Discovering' Emergence

Emergence and Hierarchy

Designing and Creating Emergence

Conclusion

 

Developing Systems Philosophy – 20th Century

An Increasingly Mechanistic World

The Western World as we see it today has been greatly influenced by the Industrial Revolution. The European Renaissance inspired that revolution, partly through the work of René Descartes, the French philosopher of cogito ergo sum fame. His name is enshrined in Cartesian Reductionism, his philosophy of breaking down big things into ever-smaller, and hence more understandable, pieces before assembly or reassembly into something larger. Cartesian Reductionism is alive and well today in almost every walk of life. Every time we list, prioritize, disassemble, disaggregate, decompose, etc., we pay implicit homage to Descartes.

Perceived Limitations in the Traditional Sciences

In the 1930s and before, it was becoming apparent that reductionism and mechanistic views of the world were limited. Initially, the main issue was Life. Life seemed to confound the traditional sciences, physics and chemistry. Organisms could clearly be alive, decaying or dead. Detailed physical or chemical examination, however, observed no difference between those states. DNA, for instance, is precisely the same whether the organism, for which it acts as template, is alive or has been dead for millions of years. Life also represented organization, yet physicists believed implicitly that order should decrease in any closed system over time.

Things other than living organisms were also displaying characteristics that were inconsistent with a simple mechanistic viewpointStability in physics is associated with a rest state of low energy. A bus, for instance, is stable when forces restore its centre of gravity to its lowest point, minimizing potential energy.

Like organisms, mass production systems stabilize at high energy with parts entering, being assembled and finally ejected, to be sold in the market place. As long as the mass of parts entering is roughly equal to the mass of things leaving, and so long as energy was being expended to assemble and move the parts internally, the whole is evidently stable, yet at a high-energy state, not low.

Analogies were presenting themselves between organisms on the one hand and organizations and civilizations on the other. This is the so-called "organismic analogy," which upset some historians, highlighted similarities in behaviour and composition between organisms and large-scale human activity systems. This was not to suggest that civilizations were organisms, but that each constituted a reduction in entropy, each had a life cycle, with growth, stability and finally death; often sudden death; and each appeared to have essential internal structure with organizational parts contributing to the viability of the whole.

It had been the practice to compare the various parts of the human body to supposed mechanical equivalents. The heart was a pump, made of muscle and tissue to be sure, but essentially just like a mechanical pump. The kidneys were filters. The eyes were cameras. The brain was a computer. And so on. Looking at the human body in this way, on a piecemeal basis, it seemed apparent to the observer that there was nothing really inexplicable about life. Man was little different from the robot of science fiction, or the automaton of the ballet. Earlier, it was Descartes himself who introduced the notion of the animal as machine. The animal was complex clockwork.

Later, the idea emerged that man was a heat engine, then a cybernetic machine, then a molecular machine. Such ideas face problems. Ludwig von Bertalanffy identified three:

  1. The origin of the machine. Descartes relied on creation by a blind Watchmaker, but how do machines come about in a universe of undirected physicochemical events? Clocks do not create themselves in Nature.
  2. The problem of regulation. Machines can regulate themselves, of course. The problem concerns regulation and repair after arbitrary disturbance. Can an embryo or a brain be programmed for regulation after disturbances of an indefinite, possibly immense, number?
  3. The continuous exchange of components. Metabolism is a basic characteristic of living things. Life is a machine composed of fuel spending itself continually, yet maintaining itself. This creates a paradox. A machinelike structure of the organism cannot be the ultimate reason for the order of life processes because the machine itself is maintained in an ordered flow of processes. The order, then, must lie in the overall process itself.

Life and the Second Law

The Second Law of Thermodynamics dictates that entropy will increase with time in a closed system. Life appeared to confound the Second Law, the physicists' touchstone. Towards the end of life, when decay set in, it seemed that the Second Law regained lost ground.

At one level, the solution to this issue was evident: organisms could ingest food, and use the ordered substances to maintain and build their structures. In other words, an organism could feed on negative entropy, i.e., food, and so decrease or hold steady its overall entropy. This did not confound the Second Law that, after all, referred to closed systems, since an organism that could ingest was clearly an open system. It was becoming apparent that all systems were open, and that, in consequence, the Second Law may prove difficult to apply rigorously on any scale smaller than that of the Universe itself.

Information and Entropy

Entropy is a measure of disorder. Information theory shows that information reduces uncertainty in the receiver, and hence reduces entropy. Information cannot be readily related to energy, but it can to entropy. If we are trying to choose between 8 options, and we receive information that identifies the best choice, that information has reduced our uncertainty eightfold, or the amount of information is log2 8 = 3 bits (binary digits).

Another form of information is feedback. The primary regulation in organisms is derived from dynamic interactions, generally between two substances, muscles, etc. Increasing blood sugar level is regulated by generation of insulin. Embryonic bud growth is directed by the creation of chemical gradients. And so on. Feedback mechanisms within the body are secondary forms of regulation, such as maintenance of body temperature. Dynamics are at the heart of regulation in organisms, rather than control by feedback.

Causality and Teleology

In the mechanistic world view, the goal of science was analysis, the breaking down of phenomena into ever-smaller parts and the isolation of individual causal factors. Organisms were split into cells, processes into activities, behaviour into reflexes, mass into atoms, etc. Causality was unidirectional. One gene corresponded to one deficiency in the organism. One bacterium caused one disease.

This idea of individual units acting on their own in one-way causality proved insufficient to explain observed phenomena. It became necessary to consider groups of parts mutually interacting. The need for a holistic viewpoint, to consider wholes, to be organismic, for gestalt, emerged. It was proving necessary in many fields of scientific endeavour to consider systems of elements in mutual interaction.

In a similar vein, the mechanistic world view had difficulties with ideas of directed behaviour, or teleology. Analysis down to individual isolated components erases all trace of directed, adaptive, or goal-seeking behaviour, which was therefore viewed as mysterious and beyond the realm of scientific research. Yet the evidence of teleology, of purpose and of goal-seeking behaviour in organisms, was unmistakable.

Organization was also inaccessible to mechanistic science. Organization of people or of organisms is concerned with growth, hierarchy, structure, dominance and submission, control, etc., none of which appeared in traditional physics.

Concept of Open Systems

The concept of the open system emerged in response to many of the shortcomings of the mechanistic viewpoint. An open system exchanges energy, material and information with its environment. In modern biology, the open system is fundamental. The human body is an open system, as are many of its internal organic subsystems. Human activity systems, organizations, and many technological systems are open systems. Some systems may be considered more open than others, but all systems must be open in some degree, otherwise we would not be aware of their existence.

The basis of the open system model is the dynamic interactions of its components. In this it is differentiated from the cybernetic model (q.v.), which is based on feedback. The open system ingests, and removes waste. The open system responds to stimuli. The open system can exhibit growth, can be stable at high energy levels, and can collapse and disintegrate. The open system can maintain and (may be able to) reproduce itself. The theory of open systems is part of General Systems Theory.

Summary

Systems philosophy has emerged as a reaction to the limitations evident in the philosophy of Cartesian reductionism in a mechanistic world. The most evident limitations include the inability to distinguish living from the non-living parts, and to address the ability of life to decrease entropy in apparent contradiction of the Second Law of Thermodynamics.

Observing the behaviour of whole systems, and seeing the parallels between different systems, enabled system philosophers to perceive a reduction in complexity. A "systems view" made complex things and situations simpler to understand, organize and manage.

An "organismic analogy" was observed, in which organizations behaved like organisms, and civilizations were observed to have life cycles analogous to those of organisms. This was not to say that organizations were organisms, but that they behaved in many ways as organisms behaved, and in particular that they were made of many complementary parts mutually cooperating to create the whole system.

The notion of the open system was developed, a system in which there were inflows and outflows, and in which stability occurred at high energy, not low as with physical entities. Many real world systems were recognized as open systems, including socio-technical systems, social systems, industrial process systems, etc.

General Systems Theory described open systems and their behaviour mathematically, and using models. These models in particular influenced the fledgling disciplines of operational analysis, systems thinking and systems engineering. It became practicable to define and identify open systems, and to categorize different open systems according to their shape, structure, purpose, etc., without necessarily identifying their content in any detail.

Instead of looking inside a system, it was possible to identify its emergent properties, capabilities and behaviours. These emerged from the system parts, but also from the interactions between those parts. The notion of emergence became central to systems philosophy, systems science and systems engineering, together with three tenets: holistic, concerned with wholes; synthetic, built up from parts to create a coherent whole; and organismic, built up from complementary parts which interact to support each other and to create emergent properties, capabilities and behaviours.

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Systems Philosophy and Applied Science

Classic science employs Cartesian reductionism, the breaking down of complexes into discrete parts; the parts, it is hoped, will be much easier to understand. The whole can then be explained by putting together the explanations for the parts.

There is a flaw in this reasoning, one that becomes more important as the subject becomes more complex. In breaking down a complex, the interconnections between the parts are themselves broken and lost. This is analogous to a surgeon excising the organs from a patient, examining and understanding how each organ works individually, and then putting them all back together again. The patient is, of course, long dead, and will not magically come alive again. Why not? Well, each of the organs remains healthy within the body by virtue of its interactions with all the other organs. Each and every organ depends on the other organs. Without those interactions, organs degenerate. Moreover, the organs are complementary — they each provide what the others need — and there is therefore, a minimum number and variety of organs for the body to sustain.

This mutual interdependence is the hallmark, not only of the human body, but of all complex systems. An effective national governmental system operates and behaves in just the same manner, for instance.

From a different perspective, it has become apparent that some "things" can exist only as wholes. Naval task force, for instance, would be ineffective if all of the major elements were not simultaneously present and operative, allowing the conduct of warfare on all three fronts: air, surface and subsurface. Effectiveness "emerges" from the dynamic interactions of the various force elements, not just with themselves, but also with some supposed foe. This notion can be generalized; effectiveness is the effect that one system has when interacting purposefully with another. It is, therefore, a function not only of the acting system but also of the system that reacts/is acted upon, and in consequence effectiveness is a dynamic parameter, shifting with time during the course of interactions. This is not a perspective with which reductionists are comfortable.

Although reductionist philosophy has been very successful, then, it misses something. It misses the interactions between the parts of a whole that give that whole unique properties. It is the interactions between our organs that keep us alive. It is the interactions between the neurons in our brain that keep us conscious. Consciousness is sometimes referred to as an emergent property.

The term, emergent property, refers to properties of some whole that are not exclusively attributable to any of its parts. The pungent odour of ammonia when two colourless, odourless gases, nitrogen and hydrogen, combine. The appearance of smooth movement when a series of still pictures of a moving subject are flipped in sequence. The high reliability of a piece of equipment made from many unreliable parts. And so on. Emergence originates in the interactions between the parts. Reductionism obscures those interactions, and therefore denies emergence.

So, What defines a System?

Trickier than you might think. According to Chambers Dictionary, a system is

"anything formed of parts placed together or adjusted into a regular and connected whole; a set of things considered as a connected whole;" and so on.

Chambers is OK as far as it goes, but it overlooks interactions between the parts, and it omits mention of emergence, Then there is a definition by the INCOSE Fellows:

"A system is a construct or collection of different elements that together produce results not obtainable by the elements alone. The elements, or parts, can include people, hardware, software, facilities, policies, and documents; that is, all things required to produce systems-level results. The results include system level qualities, properties, characteristics, functions, behaviour and performance. The value added by the system as a whole, beyond that contributed independently by the parts, is primarily created by the relationship among the parts; that is, how they are interconnected (Rechtin, 2000)."

This is much better — it is getting to the heart of the notion of "system," although it is studiously avoiding using the term 'emergence,' preferring instead to refer to "systems level." It falls down in the last sentence: it is not the relationship among the parts that "adds value" — but rather the interactions between the parts that cause the system to be more — or less — than the sum of its parts. No interactions, no emergence, no "added value."

Relationship between the parts may be necessary, even inevitable, but it is not sufficient. Being related does not make someone "part of the family" — that requires continual interaction. Life is not sustained by the organs being related to each other — they have to interact, too. Apparent movement when flicking through a set of still photographs of a galloping horse derives from interactions between eye/retina, optic nerve and brain — that the parts are related is true, but not causal with respect to the emergent behaviour. .

My own definition has taken many years and gone through many refinement trying always to simplify, but it seems to be there, or thereabouts — finally:

"A system is an open set of complementary, interacting parts, with properties, capabilities and behaviours of the set emerging both from the parts and from their interactions to synthesize a unified whole."

This covers the full ground as follows:

  • open — the system can accept additions and losses, inflows and outflows
  • set — a grouping of things that have something in common
  • complementary — together, making up a whole
  • interacting — acting with each other, i.e., essentially dynamic
  • parts — entities, pieces of a whole, subsystems
  • properties — tangible, usually physical, features such as mass, volume, shape, appearance, etc.,
  • capabilities - upper limits to functional abilities
  • behaviours - reactions to stimuli
  • of the set — of the whole system
  • unified whole — the various parts operate together as one — the whole.

Note: the interactions identified in the definition are not confined to those between the parts. Some of the parts may also interact with entities that are outside the system, and these "external" interactions may also affect whole system properties, capabilities and behaviours.

Tenets of Systems Philosophy

Three tenets of systems philosophy are worthy of serious note: the organismic analogyholism, and synthesis.

  1. The organismic analogy proposes, not that all complex systems are organisms, but rather that, like biological organisms, they behave as unified wholes. Each has a life-cycle, each exhibit growth, stability and death — often sudden, collapsing death.
  2. Holism proposes that everything within a system is connected/related to — and affects — everything else, so there is mutual interdependence. Viewing, or even considering, parts on their own is irrational. Systems, and their problems have to be viewed as a whole. Holism observes the tendency of the natural world to create 'wholes,' and that a whole may be more than the sum of its parts...
  3. Synthesis is the opposite of reduction. Synthesis proposes that the various parts of a complex system cannot exist/survive/operate/behave/even be considered in mutual isolation. A system comes into existence when the complementary parts are brought together. Each then depends for its very existence on interchanges with the other parts. In turn, this implies that open systems are/have to be active/dynamic.

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Understanding Emergence

Enlarging upon ideas, concepts and methods in the author's 2007 book:
Systems Engineering: A 21st Century Systems Methodology
John Wiley & Sons

'Discovering' Emergence

From the start, in the early 1900s, the 'systems movement' has concerned itself with emergence, i.e., with emergent properties, capabilities and behaviours. Scientists observed that the behaviour of some wholes could not be explained by looking at their parts — in separating some wholes into their rationally separable parts, something 'got lost.' For biological wholes, this was pretty obvious: carving up a body into its various organs resulted in loss of life, and reconnecting all the organs failed to restore life.

At a more prosaic level, bringing together elements such as the alkali metal, sodium, and the greenish gas, chlorine — both harmful to human life — resulted in crystalline sodium chloride, common salt, which is essential to human life: the properties of common salt are emergent, since they are not to be found in its rationally separable elemental parts

Not entirely dissimilarly, flicking through a sequence of still photographs of a galloping horse gave the impression of smooth movement. Where does this emergent property of movement come from?

Initially, emergence was seen as somewhat weird, even mystical and magical. Researchers, however, soon determined that emergence came about from interactions between the rationally separable parts of the whole, rather than from the parts per se… So, the outer electron pattern of the sodium chloride molecule, with outer shell electron interactions between sodium and chlorine components, gave it its distinct properties.

And the appearance of smooth motion emerged from the interactions between the still photographs, the continual bleaching/fading of the retina, the encoding of retinal data into some seven representations of each still image, the optic nerve, and the optical cortex, which was able to perceive smooth transitions — provided the stills were sequenced quickly enough — whence 'what the butler saw' and, subsequently, the motion picture industry and today's television with its -typically — 50 Hz frame rate…

With developing understanding of the origins of emergence, it was only a matter of time before scientists began to ask: "Is it possible to select parts, bring them together, and cause them to interact such that specific/requisite emergent properties, capabilities and behaviours can be created?" And at that point, the idea of systems engineering might be said to have emerged. After all, there was a promise of being able to gain 'something for nothing,' which is fundamentally tempting. Even more exciting, some things might be possible through created emergence that might otherwise be impossible...

Emergence and Hierarchy

A classical view of systems is that they form a hierarchy of subsystems within systems, sub-subsystems within subsystems and so on ad infinitum. Looked at from the side, as it were, the hierarchy forms a pyramidal or conical shape. Looked at from 'on top,' hierarchy can be perceived as a large sphere, with smaller interacting spheres within it, inside each of which are even smaller, interacting sub-spheres, and so on.

The graphic offers a notional image of systems within systems within systems. Note that the outer blue system sphere constitutes a hierarchy level and that it will be interacting with other system spheres at that level, not shown. The first level of hierarchy down shows five large contained subsystem spheres, all presumed to be interacting through the contained environment. Each of these five large subsystem spheres has its own emergent properties. Interacting together, they constitute the emergent properties of the outer, containing system sphere. One of the large, contained systems shows three contained sub-subsystem spheres, also presumed to be interacting, and also exhibiting their own emergent properties.

Emergence is interesting from another perspective: the nature of emergent properties may be meaningless using the terms and language appropriate at lower levels of hierarchy. Peter Checkland put it this way.

"The shape of an apple, although the result of processes which operate at the level of the cells, organelles, and organic molecules which comprise apple trees, and although, we hope, eventually explicable in terms of those processes, has no meaning at the lower level of description."

This is an important concept, particularly, for systems engineers to understand. The emergent properties, capabilities and behaviours of some system they seek to create will not be describable in the technological and engineering terms that they will use during the design and creating processes.

Designing and Creating Emergence

So, the essential idea behind systems engineering came to be: it should be possible to:

"Select the right parts, bring them together, cause them to interact in the right way, and to so 'orchestrate' those interactions as to create requisite emergent properties, capabilities and behaviours."

In this way, systems, wholes, might be created that were 'greater than the sum of their parts.' Rather than a largely mechanistic approach that had characterized hard science and engineering, this was founded in an organic metaphor, and would employ the Systems Approach. And, it was implicit that the kinds of system to be created would be open systems, acting and interacting with other open systems, and potentially adapting as a result of those interactions, in much the same way as organic systems are open, active, interactive and mutually adaptive. In other words, 'of and about the dynamic real world,' rather than isolated in some closed, static environment.

It may not be immediately obvious how one might go about creating emergent capabilities in manmade systems. The following diagram, which is based on the systems methodology (q.v.) suggest one approach.

The figure draws upon the systems methodology presented in accompanying pages, and employs the generic reference model (GRM) — a general description of any open, dynamic, interactive system. The systems methodology starts with the Problem Space, left, from which is derived a conceptual remedial solution. A Prime Directive (statement of ultimate purpose) for this conceptual remedy can be elaborated into objectives (subgoals) and a goal, for which it may be possible to conceive strategies that the future system solution might employ to achieve. These suggest in turn Prime Mission Functions (PMFs) — the yellow lozenges — that the future system solution should be able to activate to manifest the corresponding strategies. In a similar vein, the future system should be able to activate PMFs - the grey lozenges — to address threats which it may encounter in its future operational life.

It is in the 'orchestration' of these various PMFs, and their consequential interactions, that properties, capabilities and behaviours emerge in manmade systems. The orchestration — or should it be choreography? — of PMFs is shown diagrammatically in the right of the figure.

To understand how this might work, consider a seemingly-simple example:

  • A young man is sitting on a bench beside a busy urban street, with traffic moving slowly in both directions.
  • He decides to draw some money from the bank, which is some 75 yards up the road on the other side — this is his 'Mission,' and drawing the money is his Goal
  • He stands up, moves diagonally towards the edge of the road, in the general direction of the bank.
  • At the road's edge, he pauses, scans the traffic for a gap and decides to cross the road in two stages.
  • He waits for a gap in the near-side traffic, and walks smoothly and confidently to the centre, so that traffic is now moving in both directions in front and behind him.
  • He now scans the oncoming traffic in front of him, looking for a second gap.
  • He sees a small gap approaching, decides that he can just get through, and sprints forward at right angles to traffic flow, to reach the pavement/sidewalk as quickly as possible.
  • On arrival, he swivels and slows to a casual stroll, continuing toward the bank, trying to look cool and unflustered — despite the shot of adrenalin, increased heart rate, and the flow of dopamine and serotonin that accompany his risky venture.
  • These various 'steps' are the objectives/subgoals, leading to his goal, that form part of his Mission,


To see what is going on here, first view the young man as a prime example of an IDA - Information-Decision-Action - System. This is a ubiquitous class of systems that collect information, make decisions based upon that information and act, all in real time, or near real time. Many sociotechnical systems are IDA Systems, if only because there are people at the foci within such systems. So, an airliner is an IDA system because the crew take in information about their situation, make appropriate decisions and act upon them, taking the whole airliner along with them. Similarly, an army is an IDA system, most particularly where the various forces under command are deployed by a command and control (C2) system, which gathers intelligence and other situational information, makes decisions, formulates a plan of action, and then controls the execution of the plan by deploying forces in co-ordinated actions. Emergency services, enterprises, platoons, Air Traffic Management, and many, many others are IDA Systems.

Going back to the young man, it is important to understand that he does not consciously control many of his actions in the way that we might think. To appreciate the issue, conduct a 'mind experiment.' Imagine that you are seated, and are going to stand up and walk, but that you have to conduct these everyday actions/procedures by conscious control and coordination of each and every muscle in the parts of the body — spine, abdomen, legs, arms, toes, Try it — you will get nowhere — you will not be able even to stand up and maintain balance, and even if you did manage so to do, it would take ages...

Such seemingly simple actions as standing up require a great deal of coordinated activity, sensing and balancing, which we learned as toddlers. The learning became set in our minds as established routines, which can be triggered by 'firing' the appropriate 'neuron template' in the brain. We set up these templates when we were very young, by trial and error, until we could call up the appropriate routine at will, seemingly without conscious thought. In this way, we can respond to situations very quickly, or smoothly and deliberately, according to situation, by calling up the appropriate neuron template. We can call up templates in sequence, and can transition between them, so we can stand and transition to walking virtually in one movement. We may even be able to 'modify' routines in real time, e.g., to stand and walk around an object in one seemingly smooth movement.

Similarly, a concert pianist could not play, say, the Minute Waltz if he/she had to perform by reading and playing each note off the sheet music — it would take too long, and be prone to error. Instead, the pianist learns complete musical phrases which he/she can subsequently 'trigger' in the correct sequence to play the piece at speed. Note, however, that the expert pianist can 'influence' each musical phrase during a real-time performance, to 'interpret' his/her performance.

  • Now, going back to the figure above, we can see at the top of the 'strand' of PMFs that at least one is concerned with sensing situation.
    • This sensed information allows the IDA system (young man, army, airliner, Air Traffic Management, etc.) to assess the current situation, which seems to be often done either by mental simulation, i.e., observing what is going on and anticipating what is going to happen next...
  • Next, the IDA system may choose what action(s) it needs to take to further its intent/and to evade or overcome threats.
    • This is, essentially, the formulation of a plan of action
  • In executing the plan, the IDA system calls upon sets of (sub)routines, standard operating procedures, or learned activity sequences, which can be strung together easily and swiftly, enabling operation in real time or near real time.
  • To pursue a particular mission, it may be necessary to activate a variety of PMFs in series/parallel, such that their interactions may result in emergent properties of the whole.
    • This is orchestration or choreography of actions to create synergies — cooperation, coordination, complementation, etc.
    • To 'optimize' the degree of synergy, it may be possible to 'adjust' the contribution of various PMFs relative to each other
    • So, there may be 4 Cs of synergy and emergence: complementation; cooperation; coordination; and, contribution...

For the young man crossing the road, emergent properties might include agility and teleology. Note that his ability to dodge traffic when crossing the road is unique among animals — no other animal could cross a busy road safely, and in particular, no other animal could behave in such a flexible manner, adapting behaviour to situation and circumstance.

For an army-as-an-IDA System, emergent properties might include flexibility, adaptability, survivability, synergistic concentration of force...etc, The ability to operate in such a flexible, adaptable, responsive manner might make the difference between winning and losing...

The figure shows, further, at top right, the ability to adapt plans in real time as demanded by developing situations. So, the young man, temporarily trapped in the middle of the road, perceives a small gap coming his way, 'calculates' (by simulation?) that he can cross though the small gap — just — and chooses to sprint across the second half of the road. So, he modifies the plan and substitutes one or more routines for those previously envisaged when he had anticipated an easier, more leisurely crossing.

The following figure generalizes the process of 'designing in' emergence. At the top can be seen elements from the decision-making processes: assess situation, strategize & plan. They connect to the execution of the plan. The execution of the plan involves the system in activating and deploying its primary mission functions (PMFs) — not surprisingly since the plan is inevitably about undertaking a mission... according to what mission, and which strategy characterizes that mission, different PMFs will come into play. Each of the PMFs will be comprise of sequences of routines, each routine being comprised in turn of a set of activities. Execution, then, consists of triggering the appropriate actions at the appropriate times, which constitute activating routines. Routines activated in series / parallel constitute PMFs. Several PMFs operating in a cooperative and coordinated manner my result in emergent properties, capabilities and behaviours.

In the figure, the coordination of all of the various activities is referred to as 'orchestration.' The net result of good orchestration is that the various parts of the system cooperate, coordinate, complement and contribute synergistically — and that results both in properly acting and ineracting PMFs and in emergent properties, capabilities and behaviours.

Conclusion

Systems ideas, systems science, systems thinking, systems theory and systems engineering are centred around the notion of emergence — it is this feature that characterizes and distinguishes 'systems' from other disciplines and pursuits of understanding. For instance, the essence of systems engineering may be seen as the bringing together of the right parts to interact in the right way and for those interactions to be so orchestrated as to produce requisite emergent properties, capabilities and behaviours...It is philosophically possible to 'create' emergent properties, capabilities and behaviours to order — indeed, that is, or should be, the driving purpose of systems design and systems engineering.


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