This is the third article in this blog about systemic… It may be time to look a little more at the definition of a “system”, as heard by systemicists.

Here, we will briefly discuss what is meant by “system”, as well as the properties of systems.

Emergence of the notion and definition

If the idea of a system has existed for a long time (certainly we can go back to antiquity), this article focuses on its definition in the General Theory of Systems.

This time (unlike cybernetics), the story does not begin with mathematicians in search of understanding and modeling, or with “psychia workers” (psychoanalysts, psychiatrists, socio-psychologists, etc.). For once, it is a real applied scientist who is in maneuvers (hop, that’s done :P): Ludwig von Bertalanffy.

Without going back to his entire life – which is in any case available in the link above – I will look at a “detail” of it: under what circumstances does von Bertalanffy set out to pose this General Theory of Systems, in 68, with a few other friends?

It seems that – for his part – this is a reaction to the rise of Reductionism. Even if he participated in some work of this approach, surely the reductionists went too far to his taste in simplifying problems.

To summarize very briefly and roughly reductionism, the idea is as follows: “So store everything you can’t explain either in the box “it doesn’t exist [really]”, or in the box “It’s like that”.

I had warned that the summary would be rude, however it is more the result of von Bertalanffy’s reaction that interests me, than its cause – except that it makes it possible to understand the words “between the lines” of the definition. And to return to the definition of a system:

A system is a set, a complex of interacting elements, which are open and interacting with their environment.

A system is the subject of progressive transformations that can be called growth, development, senescence and death.

Small disclaimer: this is not the exact translation of von Bertalanffy’s words; however, it is a consensual summary.

Once this definition is set, I want to highlight two important things:

    • A system is open to its environment. This is one of its inalienable characteristics: trying to study the behavior of a system and consider it as a closed and isolated whole leads to nonsense or misinterpretations. And if you don’t understand something, it’s better to assume it as “I don’t understand it and it can be complex”, rather than advocating the non-existence or invariability of this thing.
    • A system is dynamic and alive. It is not satisfied with a sum of elements that move, it transforms over time. Studying a system twice with a few years of interval can be like studying two different systems. It seems obvious… That said, how many of us have never said: “Ah, but they, I know them! I know how they work!”? (Clearly, I see myself saying it, and having said it a number of times…).

Here is the definition… Now, let’s move on to the properties of the systems – since it is thanks to them that we can build support strategies…

Some properties of the systems

I’m not going to start enumerating all the properties of a system… Just 6 of them that catch my attention.

The total

From this property come two characteristics of the systems:

  • The first is that a system is not limited to the sum of its parts. Because all the elements interact, they modify and contribute to the definition of the system.
  • In addition, because a system is a set of related elements, any change in one of the elements leads to a change in all the parts of the system and the system itself.

Emergence and adaptation

As a system is open, it remains in adaptation to changes resulting from internal and external disturbances. Not everything can be anticipated, especially when it comes to external disruptions; changes generated by information external to the system may force either:

  • The use of pre-existing operating rules (regulation) to maintain its autonomy,
  • the emergence of new operating rules, interactions, which will affect the system if those available are not sufficient to maintain the autonomy of the system.

Equifinality and multipurpose

These two concepts invalidate any use of looking for “root causes” in situations:

  • Different changes can lead to the same end, especially if the system is particularly well regulated. This is the principle of equifinality. If we start from the end to explain an event, we are highly likely to identify a bad “starting” situation, through our beliefs, biases, history that will tingle our “backspace”. Thus, work on “root causes” often speaks more about the experience of the stakeholders than about the situation studied.
  • The same change can produce different purposes. Simply because the change, within a system, will also interact with changes external to the system, or to other changes within it. It can be intuited that a solution that worked at a given time will no longer work a little later.

Homeostasis

Subject already discussed in this article, homeostasis is to be linked with the equifinality property of systems. As long as there is no emergence of new rules for the system’s operation, it will tend to return to its “normal” state. A system is constantly changing – because it is alive – while maintaining itself autonomously around its own purpose.

Interactivity

All elements of the system interact with others, directly or indirectly. And the system is interacting with its environment, which means that all the elements of a system interact directly or indirectly with the system’s ecosystem.

This means that it is useless to think of “isolating” a problem to deal with it, since this problem is related to all the elements, and impacts all the elements. A given problem can, moreover, be identified as such for one or more elements of the system, and considered conversely as a benefit for others. The latter can, moreover, through the feedback mechanism, maintain the said problem, in order to continue to benefit from the positive benefits that this problem creates for them.

Circular causality

By all the previous properties, we can understand that the Cartesian principle “cause -> consequence” is wrong. Each change of an element generates reactions from all the elements of the system, which will return to the first and lead it to react to it, and so on.

The cause ends up becoming the consequence of itself.