Using Systems Practice to Unravel Complexity (Hands on)

The previous post dealt with some of the more conceptual aspects of managing complexity through a group process. Week four of the SP UK course, which this blog is addressing after week 5, deals with the more hands-on aspects of creating different types of systems diagrams or systems maps, what they can do and why to use them. The course describes a systems diagram as simply a special arrangement of words, symbols and lines of one sort or another that expresses someone’s thinking about what has happened or about how certain things are or about how they might be. It is meant to help to express one’s thinking about some situation or some system.

Writing and speech are the usual means of expressing thinking, systems thinking adds systems mapping or systems diagraming providing a more visual mode. The SP UK course sees all three as means to basically the same thing with the capacity to convert one to the other, highlighting different aspects.

Text (or speech) can run linearly along a line of print in a single dimension. So branching of complex ideas requires navigating complex grammar but such arrangements of words are hard to take in and hold in the mind. One reads or hears one phrase at a time, followed by the next in an algorithmic step-like fashion, requiring holding the overall structure of a description in one’s head making important interconnections difficult to pick out and to express. This often necessitates that text contains lists, sub-sections, and tables in some hierarchical format. The NCP Wiki follows such a format as does this blog, while the NCP Kumu Map does not (being closer to an influence map).

Diagrams can be very different from text or speech, expanding in dimensions on a visual basis making working with complex connections easier. It is arguably easier to comprehend the ideas of other people, especially in a group setting, by displaying the ideas in a diagram and then discussing them, than it is with either only speech or writing. It is scanned more easily by a group of eyes when projected on to a screen, messaging information to the eye based on its shape even before fully decoding the details.

Drawing a diagram can serve as a simple representation of a situation to help sort things out for one’s own use or a diagram can be a draft statement, as a basis for explaining what you think to other people. A diagram can also be created by several people working together, displaying differing viewpoints, allowing new common perspectives to emerge, conflicts to be discussed and expert knowledge of different members to be harnessed.

Another advantage a diagram has over especially text is that the phrases or flow of information in a diagram can be followed in different sequences triggering new insights, suggesting creative viewpoints and making holistic interpretations. One can choose to start following a path within a diagram from anywhere to anywhere it may lead. As one finds out more about a situation and understands more, one can add things at the fringes of the diagram or in between existing components of the diagram.

Drawing a diagram though, can according to the course, often require two different, difficult but still related tasks. First is getting the thinking straight and knowing what it is you want to express. The second is choosing an appropriate way of representing those thoughts

The SP UK course asserts that a diagram is never finished nor completed, but merely accepted as being the most useful representation so far, again echoing George Box. In truth, putting in too much should be also be avoided. It is far too easy, for myself included, to put everything into a diagram, losing the fundamental point of saying something clearly and economically.

A diagram is a compromise between breadth of scope, depth of information and clarity of presentation all of which should be kept in balance according to the SP UK course. One should try to focus on the purpose, what it is trying to achieve, by adding a title that sets out what the diagram is all about. The layout of a diagram is as important as the composition of a picture, using as a picture does different colors and sizes to differentiate between kinds of things.

Here is the somewhat summarized course instructor's set of diagraming best practices, and as admitted by him, not necessarily exhaustive. Diagrams can take several endeavors to help one’s thinking and understanding in learning about a situation, expect new insights and expect to redraw to incorporate those new insights. A diagram is not just words and lines but space as well. Cramped diagrams are always unclear, spread out. Use recognizable diagram types, especially if unfamiliar. Each diagram should have a title describing the type of diagram it is and its purpose. Use a key to explain different sorts of lines or label the arrows, if the meaning of lines and arrows is not fairly self-evident. However, diagramming is not an exact science but a craft skill with a distinctly personal element, developed through practice. Clarify your own purpose in drawing a diagram. What aspects of the issues you are considering are you trying to represent? This is essential when you are to choose an appropriate type of diagram within which to work, though this is sometimes a challenge having started the exploration before knowing the destiny.

Below are various types of systems diagrams or systems maps. Systems Maps seems a more general term, essentially a snapshot of the system and its environment at a given point in time. The main use of systems maps is helping one to decide how to structure a situation and to communicate to others your perspective of that system. A map may convey no more information than a list of components but because it can be easier to grasp it can have more impact. The different types of systems diagrams or maps listed below seem to move along a continuum of increasing complexity and information robustness. A distinction can also be made between focusing on issues of structure, with spray diagrams, systems maps and influence diagrams which sometimes include 'agents' or stakeholders but little or no detail on their precise 'agency' and focusing on issues of agency, multiple cause diagrams, causal loop diagram and stock and flow diagrams, illustrating the agency (the process) of change. Various causes of a certain event or situation are represented, and relationships between variables in a given situation are investigated. The definitions are taken from the SP UK course and other sources. Different uses, among many, of systems mapping, include Kumu Systems Mapping, An Introduction to System Mapping by FSG and Systems Mapping Disruptive Design.

Spray Diagrams are used to represent the structure of an argument, encapsulating relationships between the ideas of others or for note-taking. A simple fast technique for getting ideas down without being concerned about details of the structure.

Rich Picture Systems Diagrams, explore and express situations through diagrams to create a preliminary mental model, helping to open discussion and to come to a broad, shared understanding of a situation.

Influence Diagrams serve to represents the main structural features of a situation and important relationships existing among them. Influence diagrams can be developed from a systems map by adding arrows or as the starting point for a multiple cause diagram by determining a clearer definition of the type of influence.

Multiple Cause Diagrams explore why a given event happened or why a certain class of events tends to occur or why something went wrong or keeps recurring so that steps can be taken to prevent its recurrence. While not intended to predict behavior, it may be able to develop a list of factors to be aware of when considering comparable future circumstances. A multiple cause diagram, focusing on actual causes over a period of time showing the causes themselves and how they are interlinked, goes a step further than an influence diagram which describes the capacity of structural components to exert weak and strong influences at any one time.

Before going further, there is a need to confess that any critiques, implied or not, concerning the course's approach to complexity, especially dynamic complexity were not warranted. The course is intentionally designed not to deal with a level of dynamic complexity, especially as envisioned by the recently completed Complexity Explorer course. The SP UK course, therefore, does not include either Causal Loop Diagrams (CLDs) or Stock and Flow Models (SFMs) as both of these are seen as being tools more for Systems Dynamics.

Causal Loop Diagrams consist of four basic elements: variables (Kumu elements), links between them (Kumu connections), with signs showing how they are interconnected, and loops with signs showing what type of behavior the system produces, representing problems or issues from a causal perspective, making one more aware of structural forces producing puzzling behavior. The difference with multiple cause diagrams, as far as I can discern, is that causal loop diagrams involve reinforcing and balancing feedback loops which arguably would make the system persistent over time.

Stock and Flow Diagrams are also used in system dynamics modeling. Dynamic behavior is thought to arise due to the Principle of Accumulation, more precisely, this principle states that all dynamic behavior in the world occurs when flows accumulate in stocks.

These two aspects of addressing the complexity of situations and systems could be seen as different sides of the matter. There could also be seen to be a chicken and egg relationship in developing an understanding with a better understanding of one enhanced by the other, which comes first though is another question. An unaddressed question is what dynamic tools are out there to assist in this endeavor? The two are Kumu and Insight Maker though there are many others.

Using Systems Practice to Unravel Complexity (Conceptually)

This section of the SP UK course focuses on the diversity of activities considered to constitute ‘managing’ in working with others involved in a complex situation. More specifically, managing undertaken by a systems practitioner of both the complex situation being investigated and the relationships between those involved in that complex situation including the systems practitioner. The course asserts that systems thinking can simplify complexity by taking multiple partial views but admits that this needs some explanation. The process being undertaken by this blog could be deemed asynchronous co-learning because again, it is not meant as a substitute for actually taking the course.

An unfolding network of conversation and relationships. ‘Managing’ involves maintaining a network of asynchronous relationships in the context of an ever-changing flux of events and ideas. As any manager engages in one conversation, others are engaged in different conversations. As individuals participate in different conversations a coherent network of conversations results (adapted from Winter, 2002, p. 67 and p. 83).

Many complex situations involve many different people with different perspectives. Understanding multiple perspectives involves first recognizing and acknowledging one's own worldview then reflecting on the relationships one has with the other participants and with the complex situation itself. Although this is hard to do for other people as we cannot truly experience or know their perspective on the world as they see it there are tools and techniques which can help you ‘imagine’ what those other perspectives might be. We can use systems tools and approaches to bring out other people's perspectives in ways that respects and represents their views. This, however, entails its own challenges.

The course advises besides being clear and explicit about one’s own point of view and considering different perspectives, using techniques such as systems mapping or as termed by the course systems diagramming as a means of mediating the different perspectives.

A particular type of systems diagram then is used to get participants to structure and capture their own thinking about a given situation and that diagram with any accompanying or recordings is then a set of perspectives for grounding a systems investigation.

Involving others through a diagram, according to the SP UK course, can take two main forms, co-creation of a collective diagram and using a diagram as the focus for a mediated discussion of the situation that the diagram represents. While agreeing with both techniques being powerful in helping those involved to gain a shared understanding of a situation by drawing out the different perspectives, they don’t seem truly separate but more intertwined. Co-creation is arguably always the better option as people own what they create but a systems practitioner with more experience may also have to meditate at certain times to allow co-creation to continue.

This, according to the course, depends on the relationships involved and whether one is taking the role of a ‘manager’ who is part of the situation or of a ‘researcher’ who is an observer of the situation or better to my mind both. Furthermore, it shouldn't be thought, in my view, that there is only one manager or one researcher. All participants can take on these roles to some extent.

The course advises that as a ‘researcher’, “One needs to understand and acknowledge the limitations and constraints that a particular diagram brings to your study and to build in processes that ensure a reasonable degree of robustness to the information gathered and how it is analyzed and reported”.

Contribution to a group process includes proposing new ideas, seeking clarification, providing information, summarizing what has been said, providing support for other people’s ideas, and being open to other people’s arguments. Impeding a group's effectiveness could include attacking other people’s suggestions, being perhaps very defensive about their own suggestions, talking at the same time as someone else and talking aimlessly without adding to the discussion.

If several people work together to produce a single diagram as their perspective on a system then they have to find some way of coming to an agreement, which takes one of two paths. Either they aim to achieve functional, but superficial, conformity, which was my primary concern with Systems Practice US and other forms of democracy by app or algorithmic programming, or they take the time to aim for a deeper consensus.

Sometimes behavior and action can be changed as a result of thinking being changed without any need for explicit, written action points. Often though it may require developing a negotiated set of actions for moving on to say implementation, as in connecting ideas together for strategic application to begin overcoming what Jeffrey Pfeffer and Robert I. Sutton called the Knowing-Doing Gap.

The course cites C. W. Churchman (1971) who identified nine conditions for assessing the adequacy of any purposeful system's design. He argued that these conditions must be fulfilled for a system to demonstrate purposefulness. These nine conditions were later reordered into three groups of three conditions each, with the addition of each group having a particular corresponding category of social role – client, decision-maker, and planner. Churchman seems to have never named the groups themselves.

Werner Ulrich (1983) later added two allied categories "role-specific concerns" and "key problems” with each of the associated social roles. Ulrich also identified each group with a term reflecting a primary source of influence - motivation, control, or expertise for the social roles of client, decision-maker, and planner (or ‘designer’) respectively. The course sets the groups of Churchman & Ulrich’s purposeful system's design roles, conditions, and influences in Table 1 provided by the SP UK course here.

Although purpose in relation to such a system’s approach is addressed, the focus of the section is more on ‘involvement’ in a purposeful system's design which is being interpreted as the influences a social role has and what influences that social role, along with other associated categories.

The decision was made to create a systems diagram or systems map, as featured the previous week of the course (but to be dealt with in the next post) based on Churchman & Ulrich’s purposeful system's design chart, using the Kumu mapping system. The emerging objective came to be moving from an apparently complicated, management-oriented but constrained configuration to a more complex and while still contained more unbounded configuration requiring greater collaboration.

This presumes though others are not only familiar with systems diagrams or maps but also familiar with the Kumu mapping program. If several people are all contributing to the development of a diagram then it’s likely their knowledge of the particular diagramming technique, their disposition towards it, and expectations of what will come from it will be different.

This is in addition to asking others to have changed their basic vantage point of thinking primarily longitudinally or by reductionistic and algorithmic means instead of expanding their perspective by thinking latitudinally or more holistically in their own understanding of the situation, as discussed in previous posts, and being able to apply different systems thinking methodologies.

For this reason, a Kumu presentation, intended to explain to anyone unfamiliar with Kumu navigation, was created (finally, after lengthy but lackluster good intentions), as well as a Kumu presentation on the alternative systems maps, of Churchman & Ulrich’s purposeful system's design, conveying the information in more of a story format. The intention is to break down the complexity into smaller chunks. This still adds a good deal of data though beyond the complex issues themselves with which others must contend.

When the purposeful system's design is placed graphically on a page, the three groups can be seen as separate, with a particular source for which there is one for each group, in the center. The three conditions for a particular group are placed then around with each one connected to the source, each other, and a corresponding category. It is these categories that are most apparent to the world. This worded explanation is arguably not as intuitive as the picture should be.

This section of the course dealt in large part with abstract, conceptual ideas of managing complexity and creating purposeful system design but it addressed these issues through the hands-on approach of diagramming, at least conceptually if not practically. This is the main difference between the SP UK course and the SP US course with the later putting far greater emphasis on hands-on group diagramming. Different types of diagrams will be the focus of the next post.

Systems of Complexity, Complexity of Systems Part 2

The differences between the various perspectives on systems and complexity considered in the previous post reflect an epistemological approach contrasted with a more ontological one. The SP UK course argues that there are reasons for being cautious in talking about the ontology or the categorization of systems in terms of the language we might use and how that might influence our perceptions. The SP UK course seeks to define and distinguish systems of interest within complex situations as epistemological devices rather than actual ontological things.

There are differences between thinking that systems are ‘out there’, a position reinforced by the naming of ‘recognized’ systems in everyday language; and of seeing those systems as mental constructs useful for helping to explain how complex situations work. These can be configured as explanatory systems, as in ‘it’s the system for making the trains run on time’ with the level of the description being an additional distinction in defining the system.

If, however, as the SP UK course seems to admit, such an explanatory system exists anywhere then, it is in the mind of the individual(s) who conceives of it, being simply a particular way of thinking about selected aspects of the world and how their interrelationships are useful in relation to an individual’s concerns.

This brings to mind Chris Argyris' Ladder of Inference, as well as his theories of action, single and double-loop learning and organizational learning in, "Teaching Smart People How To Learn” considered previously by New Community Paradigms, especially in addressing meta-issues.

Throughout the history of Western thought and practice of science and philosophy, the question whether to focus on parts or the whole has given rise to two different approaches. Emphasizing the parts has been referred to as mechanistic, reductionist or atomistic while emphasizing the whole has been termed holistic, organismic or ecological.

Two distinctive attributes, according to the SP UK course, can be derived from the word system, systemic and systematic. Systemic thinking or thinking in terms of wholes may be contrasted with what the course terms systematic thinking, which is linear, step-by-step thinking. Personally, I would replace systematic with complicated as NCP has used the term systematic in a different manner in the past.

The SP UK course provides a list of some of what it considers some of the characteristics distinguishing systemic thinking with systematic thinking: whole vs parts, abstract (based on perspective of participants) vs concrete, individual perspectives vs non-perspective, greater than sum of parts vs reductionistic, holistic organization vs building blocks, nested systems vs foundation of parts understood, contextual vs analytical, and concern with process vs concerned with entities and properties. One argument by the SP UK course is that systemic thinking is geared towards systems of interest.

As Fritjof Capra (1996) noted: “In twentieth-century science, the holistic perspective has become known as ‘systemic’ and the way of thinking it implies ‘systems thinking’.” Capra also claimed systems thinking as being ‘contextual’ thinking'; as in explaining things in their context which means explaining them in relation to their environment, it is also seen then as being environmental thinking by the SP UK course.

Similarly, it is possible to recognize differences between systemic practice or action and systematic practice or action. With systematic practice the decision-maker claims to be objective and remains ‘outside’ the system, the system is seen as distinct from the environment, perception and action are based on belief in ‘real world’, ethics and values are not addressed as a central theme and traditions of understanding are not questioned although method of analysis may be evaluated.

Whereas with systemic practice the role and the action of the decision-maker is very much part of an interacting ecology of systems, interaction of practitioner and system of interest within a context (environment) is the main focus, perception and action based on experience of the world, especially those that connect entities and meaning generated by viewing events in their contexts, ethics are perceived as being multi-leveled as are the levels of systems themselves and the attempt is made to stand back and explore the traditions of understanding in which the practitioner is immersed.

This leads to important distinctions between the two ways in which the term ‘system’ is used depending on traditions and practices. Some more commonly recognized designations or levels of systems based on Kenneth Boulding’s hierarchy of systems or of complexity, in these instances of more dynamic complexity involving rational-technical levels, including:

• Mechanistic, from static structural frameworks, such as bridges and crystals to simple self-maintaining open systems that such as living cells to lower organisms such as plants that have separate organs but little control over their own development. 

• Animals that have a brain to guide behavior and an ability to learn. 

• A personal level involving humans who exhibit language, self-consciousness, and conscious acquisition of knowledge. 

• An environmental level involving socio-cultural systems whose members have different tasks but shared values, and which have a lot of internal communication. 

• As well as a seemingly added level of spirituality involving transcendental systems such as the idea of God or inescapable unknowables. 

This is not the only way of describing hierarchies as it depends on the purpose of the categorization and the purpose we might ascribe to each (sub) system description. Boulding’s descriptions can then be recognized more as real world systems than as explanatory systems.

The Systems Practice UK course goes on to differentiate between simple purposive systems and complex purposeful systems which begin to integrate type 1 complexity with more diverse social, cultural, psychological complexity with the assumed intention of navigating both with systems of interest. This, however, arguably adds another source of complexity to those considerations for those without adequate familiarity with systems thinking necessitating a requirement to demonstrate the value-added benefit of taking additional effort and ostensibly enhancing the involved complexity.

Systems Practice UK then seeks to use the appropriate language or means of communicating data to define and distinguish systems of interest within complex situations as epistemological devices rather than actual ontological things out there. Casti's (1994) classifying characteristics exhibited by simple and complex systems can be seen as actual ontological things but the SP UK course seems to revise this to address situations regarded as simple ‘purposive systems’ and situations regarded as complex ‘purposeful systems’ again reflecting a view of systems as conceptual epistemological devices.

Simple purposive systems, or what I would term complicated systems, exhibit predictable behavior as with a fixed interest bank account. Have few interactions and feedback or feedforward loops as with a simple barter economy of few goods and services. Power is concentrated among a few decision makers through centralized decision-making. It is possible to look at components, which because of weak interactions are decomposable without losing properties of the whole.

Complex purposeful systems can generate counterintuitive, seemingly acausal (non-linear) behavior that is full of surprises such as lowering taxes and interest rates leading to higher unemployment. It can involve a large array of variables with numerous interactions, lags, feedback loops and feed-forward loops, creating the possibility that new, self-organizing behaviors will emerge. The numerous components generate the actual system behavior. They are irreducible, so neglecting any part of the process or severing any of the connections linking its components invariably destroys essential aspects of the system's behavior or structure resulting in dynamic changes in the system and the environment. Decision-making is decentralized as a result, power, therefore, becomes more diffuse.

This view once adopted, however, has implications for systems thinking and systems practice. Exploring these implications will assist in deciding what course of action works best for any particular practitioner.

The instructor’s perspective is that it is usually more appropriate to approach the task systemically when managing or intervening in complex situations. Systemic thinking provides the context for systematic thinking and action. Both systematic thinking and systemic thinking have their place. It is not that systemic is good, systematic is bad. They are not in opposition in the hands of an aware practitioner and can be complementary in dealing with complex situations. An ideal, aware, systems practitioner then is one who is able to distinguish between systemic and systematic thinking and is able to embody these distinctions in practice. This would have implications for the initial starting conditions for any form of purposeful action as to whether to start out systemically or systematically.

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.

Systems Practice Entwining Complexity with Rationality and Emotion

As was said in the previous post on the ongoing Systems Practice course, difficulties and messes are broad terms and the distinction between them is not clear-cut and categorical. Rather they are on opposing ends of a continuum, with many, if not most, problems lying somewhere in between.

The attributes that distinguish messes from difficulties concern their scale and the uncertainty associated with them and whether these aspects were bounded or unbounded. To describe a situation as messy implies that in some important respects it is unbounded rather than if just a difficulty which then would be bounded. In addition, there is also the issue of complexity including elements of rational and emotional aspects of complexity that need to be considered.

• Difficulties, being well-defined and more limited situations, mainly involve hard complexity. Given a particular view of the matter, what is the best that can be done?

• Messes, on the other hand, are ill-defined; they include large measures of both hard and soft complexity. Of course, this may not be obvious at first and some or all of those involved may fail to recognise the soft complexity: they may initially resent alternative viewpoints, perhaps seeing them as misguided or even wilful attempts to confuse the ‘real’ issue.

According to the current course, complexity is not just a matter of there being many different factors and interactions to bear in mind in a multitude of combinations and permutations of possible decisions and events.

Complexity is also generated by the very different constructions that can be placed on those factors, decisions and events. It is not only a matter of technical or computational issues with which engineers and operational researchers deal or of the uncertainty, even irreducible uncertainty, that must be allowed for, evaluated and selected.

‘Hard complexity’ is defined by the course as generating difficult computational problems as illustrated by the game of chess, the enormous range of possible move and counter-move sequences to be considered and assessed by each of two players. This next portion of the course's definition needs to be quoted.

It is, unquestionably, complicated. Nevertheless, the nature of the game, the moves of the pieces, the fundamental purposes of the players – all these are unproblematic.

NCP has differentiated between complexity and complicated in a number of different venues. One aspect has been to see the connections of complexity as intrinsic and of complicated as intricate. The word ‘unproblematic’ in this context seems somewhat similar to the term ‘trivial’ in more formal mathematics or at least as Richard Feynman saw it. Chess, arguably, could be seen as a hard or complicated algorithm, whether unproblematic or not, from a single-sided, checkmate in 12 moves perspective but with the counteracting feedback of another player seems to me to make it unpredictably complex.

‘Soft complexity’ doesn't arise from the ‘facts’ It arises from the variety of very different (mental) constructions, and how they can be related to alternative explanations for behavior or events. Soft complexity can also feature a high degree of emotional involvement.

The course goes on to quote John Casti (1994), a mathematical modeler and writer on complex systems who links complexity to a more vernacular understanding:

… when we speak of something being complex, what we are doing is making use of everyday language to express a feeling or impression that we dignify with the label complex.

The course sets hard and soft complexity on a graph putting the computational difficulty on the x-axis and the emotional involvement on the y axis. Messes then are situations involving high degrees of both.

Complexity, particularly soft complexity, the course asserts, as far as I can interpret it, then arises from the different perspectives and how they can be interpreted, and equally, perhaps more importantly, the degree of emotional involvement people have in the situation, especially if one has a technical or engineering background making it difficult to come to terms with it.

The current course then does not attempt to address complexity at the level of complexity science as the scientific study of complex systems. It only endeavors to note distinctions between complex situations and complex systems. More about the implications, including the more philosophical, will be covered in a future post. This post will consider more personal connections with past interactions with systems practice approaches.

Despite a hypothesis that systems thinking could serve as scaffolding for deliberative and participatory systems of democracy most past system thinking projects have been solitary explorations or solitary experiments done in parallel but not actually connected with other independent efforts.

The current course raises a number of issues relevant to the interactions with a previous Systems Practice-oriented course, as team leader, of a group of ten which attempted at least by virtual modeling to address homelessness in Portland, Oregon. This was a follow-on to a previous financial modeling course as part of someone else's still ongoing, real world, on the ground effort to address homelessness in Portland, Oregon. It was among the first experiences with a group approach to systems thinking.

My personal reason for the choice was to continue that effort believing that we need to collaborate on larger scales to develop systematic means of addressing systemic wicked problems of which homelessness is one. The systems practice group approach both significantly informed the manner in which I contributed over time inducing me to substantially change my approach in ways during that course that I would not have if I had worked solely on my own.

Systems practice may though be a weaker approach in my view for those with less exposure to systems thinking because it can overly emphasize coming to a consensus. One of the primary issues of systems thinking is the tendency of people to only look at causal factors in immediate or near-immediate approximation whether by time, distance or causal relationship.

I believe that there should have been a stronger foundation in systems thinking provided at the beginning of the course and introducing Kumu at the very start could have helped with that. The challenge was crossing over to a more holistic, systems thinking perspective through a systems practice group process.

Questions of ‘interpersonal relationships’ (i.e. personal evaluations, likes and dislikes) as a contributing factor in the situation didn't really come up as the course was online. It should be noted though that NCP sees face to face interaction as an essential factor in community governance.

The other people on the team saw the situation differently from each other, they also saw many of the Systems Practice terms differently but then sometimes those terms weren't clearly expressed. It is unclear how we saw each other but interactions were done in a positive manner.

The inclusion of ‘political concerns’ were a contributing factor in the way that we all saw the situation but were related more to means than ends. All of the political concerns attributed to the people involved were considered ‘legitimate' by the group. There was likely a pro-liberal selection bias due to the course being sponsored by Acumen. There were no homeless, or homeless advocates involved or even anybody from Portland and the direct involvement of the original social entrepreneur was lost because of conflicting schedules, though she did remain available in an advisory capacity.

The most important consideration that was not adequately represented in terms of hard information and demonstrable facts, in what is now being defined as a messy situation, was the local residential reaction to the proposed system of homeless intervention, the role of residents in deciding the fate of the proposed homeless camp food truck programs. This arose from multiple causes, and was behind some of the disagreements over focus and priorities. My usual systems approach resulted going both further back by causal degrees than my teammates and with what they felt comfortable.

The discussion of what is now being termed soft complexity helped in distinguishing difficulties from messes though we didn’t name them that. We went beyond thinking about difficulties and messes only terms of hard complexity. Others contributed to the notion of trust in our system maps to a much greater extent than I did.

But the more soft complexity there is in a situation, the messier it is likely to be. Working out what to do with a mess is no longer a matter of thinking the situation through, but of rethinking or reframing it as well.