Systems of Complexity, Complexity of Systems Part 1

This blog post will start with a reminder that this series on Systems Practice UK (SP UK) is not a substitute for the course. It is only the sharing of a learning experience. It presents a unique but also a likely biased perspective. It focuses on certain elements of the course and the order of presentation has been altered. This Systems Practice course is also being contrasted with a previously completed Systems Practice (SP US) course and past systems thinking based posts and resources. This specific post, which is the first of two, will take a closer look at the relationship between systems thinking and systems of complexity.

The SP UK course calls for distinguishing between complex situations and complex systems though it never actually does this explicitly. It somewhat covertly, in my view, goes through some persuasive philosophical maneuvering to get to that and other points.

What seems apparent is that for the SP UK course complex systems, what I'll denote as increasingly structurally complex systems, particularly those arising from what is termed classical or type 1 complexity can be defined as a property observed about something out in the ‘real world’ or a physical system. As defined by Schoderbeck et al. (1985) this can range from living organisms to individual families and governments, which arise from the interaction of:

• The number of elements comprising the system, for example, the number of chips on a circuit board

• The attributes of the specified elements of the system, for example, the degree of proficiency of musicians in an orchestra

• The number of interactions among the specified elements of the system, for example, the number of neuronal connections in the brain

• The degree of organization inherent in the system, for example, the social arrangements in a beehive or an ants’ nest.

These classifications though do not convey the extent to which complex systems can evolve to feature emergent or chaotic properties as did recent posts on dynamic complexity. Despite there being increasing levels of numerical networking and agent independency related to complexity there isn't any attempt to categorize complexity as organized or disorganized as Weaver did.

Systems theorists have confronted some of the same questions as complexity theorists did during the 1990s. None of these questions have definitive answers though for systems or for that matter complexity. Do systems exist ‘out there’ in the so-called ‘real world’? Do systems have certain properties, some of which can be described or classified as either complex or simple? Are systems distinguished by an observer in a context? Is systemicity, the quality of being a system, a choice made by an observer when they perceive complexity in a ‘real world’ situation? These questions are related to systems out there in what the course denotes as the “real world”.

The SP UK course addresses this by asserting that this type 1 complexity classification was subsequently regarded as insufficient by other system thinkers and practitioners because it excluded any complexity arising from culture and from human behavior and the complexity arising from the properties of the observer. This raises then two sources of complexity, one external and one more internal.

Russell Ackoff (Creating the Corporate Future 1981, pp. 26–33) asserted that for a set of elements to be usefully viewed as a system, it was necessary that the behavior of each element of the set should have an effect on the behavior of the whole set and that their effects on the whole set should be interdependent. Each subgroup, regardless how they are formed, should have the same effect on the behavior of the whole and none should be completely independent. The phrase “usefully viewed as a system” is pertinent here in my view.

“A system is a collection of entities that are seen by someone and interacting together to do something”. (Morris, 2009).

The ongoing SP UK course asserts that a system is an assembly of components (elements) connected together in an organized way. The components are affected by being in the system and the behavior of the system is changed if they leave it. The word assembly implies that the components are organized. This organized assembly of components does something. This assembly as a whole has been identified by someone who is interested in it. This means then that there are stakeholders with an interest in the system involved either directly or indirectly. Even though still dealing with type 1 complexity, a brief definition of a system of interest then is a set of components interconnected for a purpose.

While the popular naming of recognized systems may be convenient and useful where the situation is merely complicated or purpose is largely uncontroversial it can obscure the fact that a situation is actually very complex with different people having very different perspectives on its purpose or having only partial views of aspects of the wider system. Formulating a system of interest then requires considering engagement with complexity from different perspectives. Usually, such systems are based on widely shared perceptions, well at least in part at the core. Multiple perspectives come into play at the edges.

A subsequent question can then be asked, “What can one learn about a situation one experiences as complex by engaging with the situation using a process of inquiry that formulates systems of interest?” which seems to be a basis for differentiating between complex situations and complex systems.

Underlying this transition to an interest-based systems perspective are questions of the validity or truthfulness of one's approach, both from the limitations of modeling which George Box reminds us is always wrong (but hopefully useful) to mathematical constraints on absolute knowledge.

The word ‘system’ in the context of a system of interest is used to make five points about thinking in terms of systems according to the SP UK course.

First, something cannot usefully be called a ‘system’ unless a systems practitioner has a stake or interest in it. Second, the intangible elements, e.g., norms and assumptions, are essential factors in understanding how a system of interest works. Third, the boundary of a system needs not correspond with recognized departmental, institutional or other ‘physical’ boundaries. Explanatory systems are instead identified in relation to the observer’s interests. Four, one often has to extend the boundary (take a helicopter view) in order to achieve a coherent understanding of a complex situation. Finally, five, a system at one level of analysis can be viewed instead as a sub-system in its environment at a higher level of analysis.
There are additional ways of identifying systems of interest beyond that of ascribing a purpose to a system through a textual description using active verbs rather than passive nouns. One is to draw what is known as a systems map of a situation, another way of representing a system of interest.

Displaying the raw, external complexity of the complex situation on an overhead projector slide and then superimposing different instances of ‘systems of interest’ as corresponding internal complexity, as an overlay on it draws attention to different aspects of the way the particular ‘system of interest’ works and the way the ‘system of interest’ can be perceived by other people who are interested in it.

Systems or situations of concern will consist of key components of that issue which can be delineated though not necessarily as a list, longitudinally but instead latitudinally as boxes scattered randomly on the page to determine thoughts having something in common concerning the same issue. One can then draw a boundary or perhaps two or three boundaries around them, omitting those with no strong connection with any of the other components. This is similar to a process used by the SP US course but which occurred in more of a group setting.

Putting a boundary around this organized assembly of components distinguishes it from its context or environment. One is instinctively able to select things that have something ‘in common’ an admittedly, deliberately vague phrase, before being given any specific rules or guidelines for commonly used criteria for drawing boundaries. A boundary may also separate aspects which are seen as vital from those of secondary importance that may still exert an influence. Applying this criterion requires thinking hard about purpose in drawing the boundary. Further boundaries can separate those aspects of the issue which are under the control of, or are strongly influenced by, separate people or groups. This guideline can help one to become clear about areas where one has the power to make changes and those which you have to accept things as they are. There can also be times when a strong mutual influence between some aspects of the problem exists, but not with others. Separating these two with a boundary helps to reveal that solutions to the problem that has to take account of such strong mutual influences. Boundaries can also be drawn round aspects of the time regarding an issue between short-term problems and those having longer and more pervasive effects, revealing the limitations of solutions that address only the former.

Although such criteria can be helpful, they can restrict ideas if used too rigidly, often making it more helpful to draw the boundaries first and reflect afterward. This process needs to be able to generate new views. The logically, associated terms system, environment and boundary in distinguishing between system and environment requires one to acknowledge though that an issue is not self-contained, that it can only be partially disentangled from its broader context.

The next post will consider some of these issues from a broader context.