by: Julia HeuritschPosted on:

Synergetics – Dictionary

This dictionary introduces the most important (physical) concepts to understand self-organisation and transformation processes.

Chaos

Contrary to how we use the term chaos in our daily language, chaos in physics does not denote complete disorder, but actually requires some state of order! “Chaos is a self-organising process”, which results from the non-linear interactions of many different elements[1: p.304]. Non-linearity results from the system’s complexity – it’s plurality of parts and large number of possible dynamics amongst them.

Chaos theory is more commonly known as the “butterfly effect”; a stroke of a butterfly’s wing may cause a tornado on the other side of the globe. This illustration emphasises one of the most important characteristics of chaos: a minor change in the root cause (wing flap), may lead to a major impact (tornado). Therefore, we observe a non-linear relationship between input and output.

Contrary to our linear understanding of causality of our mechanistic image of the world – a certain input causes certain output – a property of chaos is that the output is not that easily predictable. Chaotic processes are only contingently predictable, because small deviations in a process may lead to large differences in the further course of events. Contrary to our intuition, however, chaotic processes are generally deterministic, which means that they are – at least theoretically – fully explainable. Except, of course, if quantum mechanical randomness is at play (strong emergence). Chaos arises from the non-linear interactions happening in complex systems. Our brains, social interactions and organisations are all examples of such “chaotic” systems.

A video on chaotic attractors

Because chaotic processes are generally deterministic, they are computable (which doesn’t necessarily equal unlimited predictability!). Representing these numbers as a graph, one gets so-called attractors. The behaviour of the system is very likely to be represented by the attractor. An example for an attractor is the climate; 7°C max daytime temperature may be theoretically possible to experience on a middle-European summer day, however is not very likely to happen (this possibility lies outside the attractor). And if it did happen, the weather will likely normalise again in the days after (the weather will be attracted back to the climate). Generally speaking, if any system behaviour were possible and equally likely, one would only see noise instead of an attractor, i.e. a random distribution of data points.

We may then conclude that the behaviour of complex systems leads to chaotic order, so-called self-organisation. Therefore, by means of chaos theory, synergetics (the meta-theory of transformation processes) can model complex systems and their self-organisation.

Complex Systems

Until today, there is no measure for complexity, which can “be applied meaningfully and in a strictly scientific sense. Thus, with a complex system we therefore refer to a system, which consists of many different interacting parts, whose dynamics generally lead to unpredictable behaviour”[1: p.77].

Contrary to our linear understanding of causality of our mechanistic image of the world – a certain input causes certain output – complex systems are characterised by so-called non-linear interactions. Non-linear dynamics lead to small changes of a cause to have potentially a huge impact on the effect (“butterfly effect”; chaos theory). This means that the predictability w.r.t. a specific outcome, given a particular input, is limited.

Hence, trying to control complex system, such as a human or an organisation, will lead to disillusion. One first needs to accept the self-organised character of such systems, in order to have any constructive influences on them.

What complexity means to an organisation is summarised beautifully by Christiane Schirsmann[2: p.521], based on Dörner & Funke[3: p.2]:

  • There are a plurality of elements/ influencing factors and some may be unknown (intransparency). Consequently, mono-causal explanations are no longer sufficient, because they cannot map the system’s complexity accurately. A systemic perspective with reference to patterns and structure seems to be more appropriate (synergetics!).
  • The participating influencing elements/ factors are generally related and influence each other. This results into a “limit w.r.t. control of the complex system”[4: p.96].
  • The internal system dynamics and the complexity of its evolution over time is not predictable limitlessly and in detail. A “line-of-sight sailing”[5] may be recommendable.
  • There may be a plurality of possible aims, which makes decisions generally more difficult.

From these consequences of the complexity of social systems, such as an organisation, follows evidently that predictability, security and control are more an illusion than something to rationality seek for as a goal in itself. What remains: The acceptance that a complex system is inherently self-organised and that we *can* foster healthy structures by utilising the generic principles of self-organisation.

Emergence

Within complex systems (such as an organisation), one distinguishes between micro and macro level. The former refers to the system’s individual parts, such as the employees and the latter refers to system properties, such as the organisational culture. Macro phenomena emerge from the dynamics of micro phenomena and, in turn, influence them.

Watch this illustrative video on emergence

This emergence implies the “development of novel properties (or qualities) of a system”[1: p.79], which cannot simply be explained solely on the basis of the properties of the individual parts that make up the system. What is regarded as “novel properties” depends on the point of view. Taking an organisation as an example, the organisational culture would be a “novel” phenomenon, emerging from the interactions of many humans.

There are 2 forms: weak and strong emergence.

If a phenomenon can – at least theoretically – be explained reductively, we are dealing with the so-called weak emergence. We may also call it quasi emergence, since the emergent character of the macro phenomenon disappears, when one takes a closer (educated) look at the properties and interactions of the micro parts of the system. Practically, such a reductive explanation often requires a certain level of (scientific) knowledge and potentially technological innovations (e.g. finding out more about the building blocks of the universe is the main purpose of CERN). When phenomena seem to be strongly emergent at first glance, it could be that more research leads to an explanation of the dynamics of the individual parts and therefore the phenomenon in question is actually weakly emergent. This is why for a scientist (or anybody who wants to understand a phenomenon’s true origins) it is highly recommendable to assume weak emergence, and to have a closer look below the surface.

By contrast, if one assumes that a phenomenon is strongly emergent, one would forgo any possibility to explain up front. The respective phenomenon can only be described on the abstract level (step 4 in the figure of this episode of how social phenomena emerge) without referring to its true causes. At the current state of knowledge, we have to assume that only quantum fluctuations bear the potential of bringing true chance and thereby genuinely non-explainable factors into the game.

Emergence plays a key role in self-organisation, whose fundamental principles are the topic of the series on synergetics.

Self-Organisation

Organisational self-organisation refers to decision making processes and related structures (organisation models), as well as methods, which developed beyond any formal-hierarchical management or outside the “books”. Self-organisation, therefore, premises employee empowerment with respect to their content-related, as well as formal competences. Employees need to be able and encouraged to participate in decisions.  

The term self-organisation originates from the natural sciences. In particular, synergetics is the currently most developed interdisciplinary theory of self-organisation. In synergetics parlance, self-organisation refers to the spontaneous (i.e. not centrally controlled) formation of order in complex systems[1]. Complex systems are characterised by consisting of a plurality of interacting parts. Due to the large number of parts and plurality of possible dynamics amongst them, these interactions are non-linear. This bears the potential of reflexive processes (circular causality), for example, feedback loops. On a macroscopic-phenomenological level, self-organisation causes qualitatively novel properties (emergence), which the individual parts of the system do not inherently possess. Order (e.g. patterns, cells, waves, brain, social systems, such as an organisation) comes into being.

However, self-organisation doesn’t only happen within physical phenomena, such as water waves or planetary motions, but also within learning and development processes of humans and social structures. In practice, we experience this self-organised character by noticing that we humans (bio-psychological-social systems) and, all the more, social systems are far too complex as to be controlled centrally or by top-down management. Moreover, predictability of evolvement of such systems is limited by nature (chaos theory).

The acceptance, that all complex systems are inherently self-organised, does not mean, however, that we are doomed to fall prey to total chaos (as we use the term in our daily language). On the one hand, this acceptance is not an excuse for a laissez-faire mentality, co-drifting or chaotic daily life structures. On the other hand, self-organisation does not equal highly developed self-determination or a good self-management. Self-organisation is automatically not a normative term: “The theoretical understanding of the processes of spontaneous structure formation is not associated with an explicit goal of action or a particular set of values.”[1: p.65]. Thus, self-organisation does not prescribe what is good or bad*; it just happens, even without consciousness or governance.

However, if we understand, how self-organisation happens, we can learn what we can change and what we can’t, and how we can utilize its principles to foster a constructive self-organisation. Therefore, only when we accept that complex systems are inherently self-organised and understand its underlying “mechanisms”, then we have the tools to bring about genuine and constructive transformations.

Hence, in order to foster healthy systems – such as healthy minds and empowering organisational cultures – promoting, facilitating and fostering a constructive self-organisation is essential. (Self-) reflection and the consideration of the 8 generic principles of self-organisation are key to this life-long endeavour.  

* Unlike institutional norms.

Synergetics

Synergetics is the most developed interdisciplinary science of the formation and self-organization of patterns and structures. It was originally founded by the physicist Hermann Haken.

Synergetics uses formalisations from physics to describe the principles involved in the formation of order transitions (such as change & transformations). Essentially, there are 3 factors, which determine any system:

  • Control parameters:
    These describe the influence of the surroundings on the respective system. Control parameters are external circumstances, such as the magnitude of the energy influx, the stock price, the economic situation, the size of the organisation. Control parameters are the relatively most difficult influenceable factors of the system.
  • Order parameters:
    These are the predominant/ leading parts of the system. Examples are a dominant figure, the purpose of the organisation, the organisational culture or its structure. Order parameters embody macroscopic qualities, which emerge from microscopic qualities. The organisational culture, for example, can’t be installed externally by some consultant just like that; instead it is the result of the interaction between employees, which, in turn, originates from their values and those of the organisation. Order parameters can be more easily influenced than control parameters. However, they are relatively more stable than the so-called enslaved parts of the system.
  • Enslaved parts:
    While order parameters emerge from the interaction of the parts of the system, they, in turn, enslave the system’s parts (principle of enslavement). Hence, we are dealing with a so-called circular causality. Examples of circular are positive/ negative feedback loops. “Enslavement” may sound quite brutal, but has a different connotation in physics (macroscopic properties of a system influencing microscopic ones) and shouldn’t be taking literally. Often we have the choice whether we’d like to be “tag-alongs” or whether we choose to act, for example, against organisational norms. Nevertheless, we should not underestimate the implicit and subtle impact of order parameters, such as an organisational culture or behavioural norms in our society. The enslaved parts of the system are the relatively most dynamic (most influenceable) factors of the system. 

Because these basic principles can be applied to any physical, biological, psychological, as well as social and organisational process, synergetics maybe be considered as a meta-theory of transformation- and innovation processes. It’s key achievement is its ability to explain and model the emergence, properties and behaviour of extremely complex phenomena on the basis of just a few basic principles.

References
[1] Haken, H. & Schiepek, G. (2006, [2010]): “Synergetik in der Psychologie – Selbstorganisation verstehen und gestalten”, Hogrefe; Quotes are translated from German by me
[2] Schiersmann, C. (2020): “Das integrative Heidelberger Prozessmodell für Beratung – Umgang mit Komplexität und Unsicherheit” in “Selbstorganisation – ein Paradigma für die Humanwissenschaften”; Viol, K, Schöller, H. & Aichhorn, W. (Hrsg.), 2020, Springer: https://link.springer.com/chapter/10.1007%2F978-3-658-29906-4_3
[3] Dörner, D. & Funke, J. (2017). “Complex Problem Solving: What It Is and What It Is Not.” Frontiers in Psychology, 8, e1153.
[4] Servatius, H.G. (1991): “Vom strategischen Management zur evolutionären” Führung. Stuttgart: Poeschel.
[5] Hinz, O. (2017): “Segeln auf Sicht: Das Führungshandbuch für ungewisse Zeiten.” Wiesbaden: Springer Gabler.

Navigate through the episodes of the special theme The Science of Human Behaviour here:

Table of Contents

  1. Introduction to The Science of Human Behaviour
  2. Motivation: Research shows that there are 5 different types of motivation. Especially the aggregate forms – autonomous vs. controlled motivation – have a different impact on our well-being.
  3. Decision Making: Rational Choice Theory explains how we make our 35000 daily decisions and how social phenomena arise from our individual behaviour.
  4. Self-Organisation & Transformation: Synergetics – the meta-theory of order transitions – connects the natural sciences with the social sciences and explain what we can change and what we cannot.

Written by Julia Heuritsch | Last edited: 30th September 2022

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