We are, each of us, a system. We are, each of us, systems in multitudes

We are, each of us, a system. We are, each of us, systems in multitudes. We are both at the same time. We are ourselves, as systems, of the same nature as those systems manifested within the world to both our senses and mind continuing the discussion from the previous post and Still Learning to Understand Systems. Separated, from all that we are not without, and from what we are within, as well as between other systems by boundaries that are placed there by us.

The most determinative means, it seems to me, but with the least amount of information of assigning a boundary to a system is to give it a label. Buckminster Fuller’s definition of a system as “the first subdivision of universe into a conceivable entity” provides an important initial context without particularities.  

Russell Ackoff, whose focus on systems was in addressing practical, real-world messes, the kind raised by uncertainty and complexity, said that any particular or specific system could be characterized by three essential conditions which I could also see as being able to assist in establishing the boundary of a system as defined by Fuller.

First, each simple element in a system has an effect on the behavior of the whole system. If it doesn’t have such an effect then it’s not part of the system and belongs outside the boundary. Second, within a system each element is affected by at least one other element in that system, and that none of the elements has an independent effect on the whole. Every element then has an effect on some other element or elements in the system and only has such an effect on the whole in conjunction with some other element or elements.  Third, it is not possible to develop totally independent subsystems from a subgrouping of a system’s elements. Any subsystems within a system that can be made totally independent belong on the outside of the system. It will likely take some experimenting to determine which elements fulfill all three categories. This still leaves a potentially large portion of elements that can be placed on either side of a boundary depending upon how it or they are defined but it is then a matter of consensus or coercion, both of which, again in my view, can be detrimental to understanding a system.

Fuller’s definition, however, is not merely an esoteric abstraction but can provide an immediate, visual illustration of the boundaries of a three-tier hierarchy anchored in geometry. 

The simplest possible three-dimensional configuration or minimum set of relations representing a stable structure (which can also be fractalized) within the “real world” is a tetrahedron, a four-sided, triangular-faced pyramid having four vertices, four faces, and six edges subdividing the world into all that is outside the system’s structure (environment), the structure of the system itself (system), and the system’s interior (bounded elements and connections) having profound, practical implications for all system designers. 

Fuller’s definition of a system bears a particularly significant illustration of the aspect of verticality or nestability, the means of forming a hierarchy, series, or sequence wherein each member, element, or set is contained in and contains the next. From a systems thinking view of the world, this concept of hierarchy finds expression, in the natural world, as a stratified organization of increasing levels of complexity, which can be expressed as a sequence corresponding to levels of emergence distinguishing one level from the next by novel qualitative properties. 

Starting with elementary particles, atoms, and molecules to become various forms of matter, to leap from inorganic to simple organic life-forms,  to evolve into complex organisms, and in aggregate evolve into whole ecosystems, leaping again to consciousness to include humans and subsequently human society. Each level represents a cluster of interacting sub-components, consisting of elements of the previous level. 

Each level can be distinguished by the relative strength of the respective interactions by which it is constrained. Each level being stronger within and weaker between other levels. It is the constrained internal bonds that allow for the individual integrity of a level to stand out against the background of its environment and provide for a definition of boundary conditions.

This is very different from a strictly reductionist based top-down complicated systems of command and control hierarchy, discussed in the last post, that feature little in the way of nested verticality. It again means that from a systems thinking perspective one needs to optimize on at least three levels, the system under consideration, its environment, and its internal components, as a coherent, harmonious integration of relevant aspects for any constructive, systemic intervention.  The familiar and conventional organizational or governance structures of our typical commerce, political, or social affairs organizations are simply inadequate, in not being internally rich enough, to address the demands of an increasingly complex world. 

Many examples of business and governance management perpetuate a model that imposes structures with grossly insufficient variety such as conventional concepts of leadership that violate the law of requisite variety by popularly entrusting power in a single person. Consider the complex interactions that increasingly characterize today’s society, concerning the typical, still-prevailing, hierarchical, command-and-control structure, and I would add afflicted by ”complicatedness”. Such low-variety models ultimately only impoverish the system that is supposedly “under control.”

Another cybernetic term due to Ross Ashby is ”Ultrastability”, the cybernetic concept of regulation relating to the ability of a system to restore homeostatic equilibrium after unexpected perturbations even when a trajectory for doing so has not been specially pre-specified or built-in. A more complex, dynamic form of adaptation is manifested in the typical homeostatic mechanism by which a fixed decision rule is applied to trigger an appropriate corrective action whenever equilibrium is disturbed.

In more interesting cases, read as more complex cases, such as brain-like systems, societies, or ecosystem, a sufficient amount of variety can be “built” into a system so that its internal reconfiguration can be made to match unpredictable changes in its environment even if a specific decision rule is not already embedded in its structure. The general rule then becomes “keep changing internal configurations,” or basically rewire the internal variety of the system in the search for a subset that matches new demands in real-time. The internal variety of a system, even if very high and ultrastable is, however, still finite as an entirely new environmental context condition may require new options that the system cannot generate.  

This gives rise to Ashby’s Law of Requisite Variety which states that “Only variety can absorb variety.” Effective regulation then can only be achieved when the regulating system contains at a minimum, the same amount of variety as the system being regulated. The requirement for requisite variety is applicable regardless of the type of system whether automated devices, technology processes, ecosystems, or social systems.

One means of enhancing requisite variety is redundancy. The term redundancy, commonly understood as unnecessary, in information theory refers to protecting information integrity from deterioration due to the effects of background noise by increasing information content or channel capacity. 

At a state of maximum disorder or entropy, when no distinctions can be made or no information is discernible and activity ceases redundancy will be at zero. Redundancy then allows for more potential “possibilities.” If the rate of change of a system’s redundancy remains positive then it is self-organizing according to Heinz Von Foerster. This would logically seem to extend further to ”Redundancy of Potential Command”.

Internal complexity brought about by requisite variety allows for the emergence and re-emergence of different configurations in response to changing events. The important implication being that “’ living,’ self-organizing systems, including social systems of all types, depending on their internal complexity and inherent redundancy for resilience and long-term viability”.

Distributing and determining by function and relevant knowledge rather than by authority assigned by rank and seniority the processes of decision-making across a network-like organizational structure is termed ”Heterarchy” The potential for so-called “command” is thus distributed, or made redundant, over a large number of components and its location shifts constantly within the network. It is not permanently localized and no fixed vertical hierarchy of authority is discernible. 

Fuller’s definition of a system can be said to transverse across the chasm between the solely conceptual and the countless entities with distinct and independent existence within our universe, laying between that which is conceivable but which is not an entity within our universe and that which may perhaps be an entity, but that is not conceivable. In total, what we call our reality. It brings systems, conceptually defined, to a state of reality within which Norbert Wiener’s Cybernetics can be and by necessity needs to be applied.  

The seemingly, abstract, remote, and perhaps even, esoteric concepts of variety, ultrastability, redundancy of potential command, synergy, and self-organization are all related or are constrained together describing and arguably determining the characteristics of regulating mechanisms that underlie external behavior of complex systems. The practical implications of which are far-reaching and significant not only in that they shape the conduct of human affairs but they could be crucial in resolving the many sustainability-related challenges we are facing. The challenge of all interventions in any socio-ecosystemic domain would be then to keep an open, dynamic stance, working in tandem with the self-organizing properties of the system, rather than inadvertently destroying them. 

Finding Our Way Through Complexity and Uncertainty

The last post looked at Michael Ben-Eli’s paper, ”Understanding Systems”, a part of Sustainability Laboratory’s online course on Systems Thinking and Systems Modeling. This should have been said then, the Understanding Systems paper needs to be read, even more so than this blog post series. This is only my interpretation, far more likely subject to error, jumbled with alternative and added thoughts to tie it to New Community Paradigms. The paper by Ben-Eli has far more insights from Stafford Beer, Ross Ashby, and others not included here.

The previous post was able to fully define the concept of ”system”, based on the insights in ”Understanding Systems”, solely through mutually supporting abstract concepts without referring to anything physical. There wasn't any need for the particularity of specific instances. ”Organization” could be seen as a concept without the need for reference to a specific organization or particular type. Self-organization arose from the further internal interactions of mutually supporting concepts. There was an inference, with the mention of patterns, to our more immediate sensory world but that world is a veil behind which the concept of patterns lay.

That conceptual reality, however, is not the one that we have to survive, strive, and succeed in. Even if the interactions within such conceptual reality are constrained seamlessly, weaving together effortlessly, they are hidden from our own hard-knock reality by a veil of complexity, uncertainty, and randomness and must be divined from the clues made apparent when we look for them.

The key to piercing the veil, so as to glimpse at a system’s internal workings, is to see the same logic found in the circuitry in man-made, automatic, error-control mechanisms as being analogous to the homeostatic logic found in physiological structures that work to maintain specific physiological values such as body temperature, body fluid composition, blood pressure, blood sugar level, etc., by triggering an appropriate corrective action when deviations occur from a norm. 

Cybernetics focuses specifically on understanding the often obscured dynamics of a systems’ internal structures and the mechanisms that maintain its dynamic organization invariant.  The term “cybernetics” denotes the role of feedback mechanisms in processes of regulation and control. The number of possible distinctions related to a system’s internal states in cybernetics is termed “variety”. 

Norbert Wiener, the first pioneer in the field, and his colleagues established I am going to say the immutable connection between the observable behavior of a system or its output and the internal structure of a system in a 1943 paper, Behavior Purpose, and Teleology. 

First, by clarifying the question of purposive behavior by tying a system’s behavior to its specific internal structure which helped to remove the need for “vitalism,” or as in the last post ”vital force”, to explain the special qualities of living systems. Second, by making it clear that to modify a system’s behavior change must be made to the system’s core structure rather than being directed at the behavior of the system. 

Wiener defined cybernetics as “the science of control and communication in the animal and the machine,” highlighting two key ideas. One is establishing the validity of the theory for both man-made devices and living systems. Two, classifying  “control” and “communication” as one, signifying the role of information in processes of control and regulation. 

What then are the structures and mechanisms of a system by which it mediates its operation, viability, performance, and by which it determines how the system can regulate itself? How it can self-organize and how it can adapt and evolve?

Regulatory processes mediate between the factors interacting for particular outcomes or behaviors binding a system together to preserve (constrain) its singular identity. ”Control” then is not meant to be considered as a restricting concept.

Regulation in the cybernetic model is expressed in the context of a system’s capacity to maintain equilibrium states in the face of disturbances from an environment with which it interacts. Regulation can then be regarded as the manifestation of a system’s adaptive capacity.

Cybernetics extents the concept of regulation to evolutionary processes, by which a system can actually transform into a new entity with a higher regulation potency. Amplifying potential variety by processes such as coalition formation, highlighting the importance of cooperation in evolution as has been demonstrated by anthropologists looking at the work of Elinor Ostrom.

The number of different states that a system in the real world can assume or its potential internal variety can be considered a measurement of complexity. Complexity then can be thought of as the number of possible distinctions by which information can be known or that can be determined about a given system, independent of its size. A human cell can be more complex than a large distribution warehouse.

The number of possible states or a variety of a system increases both rapidly and exponentially when the numbers of elements it contains get larger along with the number of interactions or connections between them, as well as the possibility for each interaction to assume more than a single value.

A quantity of variety, however, also produces a measure of uncertainty. Uncertainty or randomness relates to our perception of order or information about the different states of a system although contrariwise to the way order relates to the more deterministic regularities in a system’s behavior produced by a sequence of a system’s changing states which are detectable. 

The concepts of information and uncertainty are closely related having similar mathematical expressions but opposite signs. If uncertainty is at a maximum then all events in a given universe can occur with equal probability which means that no information is available and variety is at zero. Uncertainty then is a measure of disorder in a system or the level of entropy. 

The process of conveying an amount of information concerning one state out of the variety of all the possible states of a system removes some uncertainty but never all of it, some of it is irreducible as Donella Meadows has pointed out. Too much information can be as bad as too little, making distinguishing relevant information from background noise impossible.

The behavior of whole systems, presumably those of sufficient complexity to require multiple subcomponents to achieve a high degree of internal variety, cannot be predicted from the behavior of the system’s parts alone due to the emergence of new, often unexpected properties. This perspective of an entire or whole system is termed synergy in Cybernetics. This ought to be assumed in all cases of social systems design and addressed as they will find inevitable expression in social interactions. 

The concept of variety, along with the concepts of organization, entropy, and order, and I would add synergy, are at the nexus of our ideas involving physics, information theory, and the philosophy of science. Such regularities that can be found within a system are produced by constraints imposed on that system’s potential variety or its internal structure as discussed in the last post. This the Understanding Systems paper asserts is profound.

The far more prevalent traditional reductionist analytical process, according to Ludwig von Bertalanffy, as cited by the Understanding Systems paper, sees interactions between elements being non-existent, or negligible in that they can supposedly be ignored for the purpose of analysis. According to a strictly reductionist perspective, understanding the world should be possible from constructing a picture of it by simply adding up detailed descriptions of its parts.  There is no need but to precisely measure what is immediately before us and sum it up. Ignoring the internal state of systems is to our peril as we are assailed with a world of complexity, uncertainty, and randomness by which the reductionist perspective can be seen as myopic.

The gross deficiencies of currently prevailing top-down hierarchical command and control structures, including an inability to effectively address complexity, have been highlighted by many including Dee Hock, founder and CEO emeritus of VISA International, who advocated instead for a creative combination of “order” and “chaos” or what he termed “chaordic”. A more versatile and dynamic, but also more complex form of organization that allows for the ability to innovate and experiment. 

Switching from a mechanistic, reductionistic perspective of the world to a system view of the world opens one up hopefully but also understandably hesitantly to a variable, dynamic and interdependent reality, which demonstrates not only the need for a transformative shift in values, attitude, and actions in the world but also to pathways able to achieve them. 

Personally, I doubt that this would actually force acknowledgment of such a reality, as Ben-Eli asserts. We, humans, are far more resilient in our mental models than that, persuasion is still required. As he says elsewhere, individual observers can either keep or change their frame of reference. Even if they do change, they will likely have to come together with others in some manner to change their collective conclusions to change the system. Regardless, the implications of switching are still profound.

NCP Inquiries into Systems Practice - 10th post of 3rd Project

This is the tenth blog post in a series on the Jerusalem Vision Project, which is the third Systems Practice project undertaken through the Acumen course using the Omidyar Group’s approach to pragmatically applying Systems Thinking. 

The project took my rudimentary knowledge of Systems Thinking as a basis for obtaining a better understanding of Systems Practice and applied it to a complex challenge - Israeli/Palestinian relationships in the City of Jerusalem of which I admittedly knew relatively nothing.

This specific blog post is going to again review this endeavor, not of achieving better relations between Palestinians and Jews in the City of Jerusalem but in the utilization of Systems Practice to address such complex challenges. These points have been made before but across disparate posts making their assertion somewhat disjointed.

These continuing endeavors seem to have worked well in attaining a better understanding of the Systems Practice methodology having initially made a late start in properly applying the methodology the first time with an inquiry into food trucks for homeless camps but still having concerns about the process afterward nonetheless. The second time, looking at plastic pollution of the ocean in Bangkok, Thailand, gaining a better understanding and a somewhat more successful application but still having questions that remained or continued to be needed to be tested to confirm certain aspects in terms of how Systems Practice could be utilized in developing new community paradigms.

The difference then between this Systems Practice project and the previous two projects is first, a better understanding of how a Systems Practice approach works and second, instead of focusing on each project step by step this project waited until completion to get a better overall view of the process. Both to determine how the Systems Practice process unfolded and to assess how Systems Practice might be integrated with Direct Democracy and Systems Thinking.

However, endeavoring to absorb the entire process after its completion raised a number of complications particularly when attempting to communicate the worthwhileness of the effort with anyone who has had little to no experience with Systems Thinking or Systems Practice. It is not a difficult challenge to get those interested in Systems Thinking or Systems Practice to take a look at another example of the methodology to either agree with or disagree and critique. You can simply ask them, the community is especially helpful.

It is more of a challenge to get those neck deep in dealing with real-world messes to consider Systems Thinking and Systems Practice as viable approaches to finding solutions. This takes us back to the first paragraph. Any contribution I made to specific projects was not based on my first-hand knowledge of the particular challenge under consideration but my relatively better understanding of applying Systems Thinking and increasingly, a Systems Practice approach to these challenges, in cooperation with others who had committed to trying to apply the approach with their enrollment in the course.

The Jerusalem Vision Project had its own particular challenges being based on both more complicated and conflictual issues, in addition to its complex nature. Complicated and conflictual because of political and historical reasons but also somewhat internally conflictual, though collegiately so, because of distinctions between different mental models used by the project participants. The complex nature of the challenge though may not be as readily apparent because of the confusion arising from the complications and inherent conflict.

While I feel confident that those with whom I went through the three Systems Practice projects found it beneficial, this is harder to convey to those who weren't brought to such efforts for their own reasons. All the harder as both Systems Thinking and Systems Practice can be conceptually abstract when people are often anxious for so-called concrete solutions.

Systems Thinking provides a logical construction in finding solutions but is not always explicitly empirically evident. Further complicating the matter is that Systems Thinking, though it has certain foundational aspects, can be categorized by different approaches and underlying philosophies that seemingly conflict. Conceptual conflicts by Systems Thinkers, seeking a solution to be imposed, that may sometimes be made too readily the crux of the matter rather than the detrimental impacts of the challenges themselves.

This can obscure the viability of System Thinking’s fundamental principles but it isn't the primary hurdle to convincing the uninitiated to make the commitment to a Systems Thinking or more specifically a Systems Practice approach which can be substantial.

The primary hurdle is an essential change to a mental model that is linear, analytical, reductionistic to one that incorporates a perspective that is also non-linear, holistic, synthetic. The basis and need for the change and resulting implications can be easily underappreciated while the siren call to grasp at an immediate concrete solution can be addictive. The basis for this distinction and requirement for convergence is explained, more succinctly than I can, by this video from Complexity Labs.

The Acumen/Omidyar Systems Practice approach overcomes this hurdle by having its implementation be dependent upon the convergence but not explicitly so. It follows the logic of some Systems Thinkers that like Fight Club, Systems Thinking shouldn't be talked about. It does lead those who habitually follow a path by reductionistic, analytical, linear thinking so often used by command and control top-down management to the alternative of thinking defined by synthesis, holism and non-linearity without making the transition too obvious.

The Omidyar Group’s approach to Systems Practice though does not only steer most participants, whose primary experience has been following that habitual path to an alternative one but also navigating those supposedly versed in Systems Thinking away from too quickly determining a final path to a solution to whatever complex challenge is being faced. This was my error with the first Systems Practice project, to immediately begin mapping towards a solution.

While the course does present the case for synthesis and Systems Thinking in a general sense early on by examples, it instead takes participants through a number of steps that unless used and tested can seem contrary to how we usually approach such challenges even when using Systems Thinking as individuals. While their purpose may be explained with each step taken, their cumulative effect cannot be fully appreciated until more fully implemented. Until that occurs participants are encouraged by the course to have trust in the process.

What the Omidyar approach does is take the internal, and usually implicit mental maps of each of the individual participants regarding the system in which the mess or complex situation occurs and asks them to hold it in abeyance then work to first create a common goal through the Guiding Star, Near Star and Framing Question. More importantly, though, is a process of disaggregating those individual maps by collecting the factors making them up without any of the connecting relationships unique to each.

This collective set of factors is then jointly categorized as being either enabling or inhibiting and then rearranged into new collections defined by common traits or themes. This process helps not only to open up pathways to the internal mental maps of individual’s that may have been previously closed but also sets the basis for finding a set of new and collectively determined relationships. This arguably has a far stronger basis for democratic deliberations. At no point in the process so far has a systems map or map of any type been started. This took some personal adjustment.

The next steps in the Systems Practice process, upstream and downstream relationship configuration and S.A.T. (structural, attitudinal, transactional) Analysis were touched upon for the third time in recent posts. Despite having my own ideas on S.A.T analysis and its implications, I have come to appreciate its viability in contributing to the process, having been able to anchor it to basic Systems Thinking concepts such as the Systems Thinking Iceberg model and integrating it into basic Causal Loop Diagrams.

However, it needs to be admitted openly that Systems Practice does not provide a panacea. Surely no surprise on its own but it is important to be clear on why. The first goes back to the beginning of this post. I may have made an abstract, conceptual argument for the viability of Systems Practice but in the meantime, I completely abandoned the challenge it was supposed to address - Palestinian/Jewish relations in the City of Jerusalem.

The individual embedded in the system of concern, be they Palestinian or Jew, needs to be convinced of the viability of the process. That has not been accomplished except perhaps for a few individuals. To be even more honest, none of the projects undertaken so far came up with a final answer to their challenge. These were, to be fair time restricted, limited, basically academic projects taken on by groups of strangers globally separated by different time zones. In those cases were doing more was sought out, the complications and often stochastic nature of the real world hampered such efforts. On a broader and long term basis the challenge though is one of implementation and the problem is a Knowing-Doing Gap discussed in previous posts.

Despite these limitations, I have become convinced that Systems Practice can make a valuable contribution to creating new community paradigms. I recognize though that my rationale as presented will have little potential to influence those living with complex, wicked challenges without at least addressing those challenges more directly. I will attempt that in the next post.

The Systems Thinking Iceberg Model helps with Understanding Systems Practice S.A.T. Analysis

So far we have dealt with Guiding Stars, Near Stars and Framing Questions as well as dealing with factors as either enabling or inhibiting in upstream/downstream patterns into different Themes of the system being explored. During this Jerusalem Vision project, a S.A.T. analysis, unique to Systems Practice was again conducted. Factors involved in cause/effect or upstream/downstream relationships can, according to the Systems Practice course be categorized as Structural, Transactional or Attitudinal.

It is a way of looking at a system so as to avoid focusing on only what is obvious and allowing for a deeper understanding of the system overall. By rigorously looking at all the cause and effect relationships, within a system, according to this set of categories, one has a better chance of illuminating the most important causal drivers in the system. This will be only a cursory explanation though, for a more complete one it will be necessary to take the course.

The course provides examples of the three categories of S.A.T. - Structural, Attitudinal or Transactional rather than definitions. The three, as presented by the course, can be seen as being distinct from each other.

There is though arguably an interrelationship between them that can be explored. This is based on a hypothesis that the Structural components or factors of a system help to determine Transactional factor patterns upon which both together Attitudinal factor perspectives are based which in turn support, oppose or acquiesce to those Structural components, which in turn, influence Transactional patterns.

This proposed interrelationship between the S.A.T. categories also suggests correspondence with another Systems Thinking meta-model, the Systems Thinking Iceberg Model. I explored the potential for these ideas with the Kumu project Implications 101 of Systems Iceberg and Systems Practice S.A.T. (Forked).

The Kumu project is based on fundamental Systems Thinking principles in the construction of Causal Loop Diagrams. More specifically, on five examples, of a more general and abstract nature, developed by Gene Bellinger for use in his still-developing interactive learning platform And! It's All Connected. Gene conducted the Systems Thinking Certification course I took. The ”Forked” in the title means that I had permission to make a duplicate of his work and modify it for my own purposes. As I told the And! It's All Connected Facebook group, ”Without a firm foundation through Gene's original maps, I would not have the same degree of confidence”.

Using Gene’s work as a basis, I first extended upon his ideas by adding new loops and then created new perspective (view) on the issues using S.A.T. categorizations. Gene, it should be noted created an advanced Kumu view to define his design. Mine created for the S.A.T. analysis was far more simple but it did, it can be asserted, support and expand upon the ideas below.

According to the course, the Structural category of S.A.T. includes the physical, whether natural such as air quality or drought or the built environment, say housing stock or the transportation system but it also includes the non-physical such as the social environment in which people live; including political, social and economic institutions.

Different types of institutional infrastructure could be considered either physical or non-physical e.g., legal system, economic policy, labor unions, church associations. In many cases, there will be a combination of both physical and non-physical aspects. The physical court building in which the non-physical legal system is practiced. The examples provided by the course could be considered as formal structures, some significant. Systems can give rise to factors that can serve as the structural components within that system helping to define it despite a lack of formal recognition.

The structural category of S.A.T. can be related to the structural level in the Iceberg Model. Structures are built and or are maintained by individuals that they are established by, working transactionally in concert but they are something more than individuals and are capable of persisting beyond individuals.

There is a structural component arising from the interaction of factors and forces which if changed could potentially change the system but to be adequately effective would likely need to be seen as a structural replacement.

Factors, at the Structural level of either the S.A.T. model or Iceberg model, can be considered as stocks both physical, whether natural or built environment and non-physical following Donella Meadows’ definitions.

The Principle of Accumulation states that all dynamic behavior in the world occurs when flows accumulate in stocks. Stocks can be increased or decreased but not instantaneously, 

“a stock takes time to change, because flows take time to flow”.

”A stock, then, is the present memory of the history of changing flows within a system”. 

Donella Meadows

Transactional factors of the S.A.T. can be seen as combining into the events and patterns of the Systems Thinking Iceberg Model. Events become patterns when they are repeated in a systematic enough manner that allows them to be forecasted or their cumulative effect influences the larger system. Transactional factors are set within the Structural framework(s) of a system and are constrained by it.

Transactional is the process of interactions but for me has a slightly different definition from that used by the Systems Practice course. The course seems to limit the definition to key people or the leaders at all levels as they deal with important social, political and economic issues whether they be essential negotiations, violence, problem-solving, influence, or leadership. Examples of key Transactional factors provided by the course include lobbying by human rights activists, the influence of a community elder, mediation by a member of Parliament, or extreme political rhetoric by a religious leader. I don’t see a reason to limit the definition to Grass-tops and not include Grass-root efforts even if they must often occur at a more aggregated level to make a noticeable impact.

What is implied but not made explicit, or at least I will assert that it should be, is that transactional factors involve at least a two-sided interaction though not always apparent. That the interaction must be iterated to become a pattern and that will invariably occur within, through or be supported by some Structural factor or factors.

Those Transactional factors unsupported by Structural factors will be far less sustainable than those that are and far less likely to reach a persistent pattern. It should be noted that an iterated persistent pattern does not mean repeated exact copies, patterns of transactional factors can be modified and systems can evolve.

A Transactional example of extreme political rhetoric could be effective not because it directly changed the structure of a system but because it influenced Attitudinal concerns of the populous which in turn brought changes to the Structural factors of the system though that would have to be through Transactional factors.

Transactional factors do not accumulate as stocks but can define the inflows into and outflows out of stocks. Transactions cannot be a stock. Subsequent transactions may reinforce a pattern of transactions but they replace the previous transaction. Transactions can only influence flows into or out of a stock.

Attitudinal factors are akin to the Mental Model level of the Iceberg, encompassing the attitudes, beliefs, morals, expectations, and values, which are often subconscious or unconscious. They are set by means by which people adapt or acquiesce to the patterns of transactions which if unchecked or unquestioned then allow those established structures to continue functioning through the same continuing pattern of transactions.

The category Attitudinal within S.A.T. relates to widely held beliefs, values, norms, and intergroup relations that affect how large groups of people think and behave e.g., ethnic tensions, social capital, fears, group trauma, religious beliefs, and attitudes like trust in government or a belief in “rugged individualism” and can be non-physical stocks. However, these invariably arise from the Structural and Transactional factors and can be in turn applied to them as well.

If Attitudinal shifts cannot bring changes to Structural factors through a shift in Transactional patterns or vice-versa then that Structural factor may make the system, to use a term used before, entrenched requiring far greater leverage from factors that may not exist as of yet. This can be true even if the Structural factor is not formal or even apparent.

There is a difference between individual social beliefs or what the course calls Attitudinal and what might be termed structural norms of institutions which are not human. All belief is human and although individually based can be aggregated. The later structural norms are not as dependent upon individuals in regard to short, mid-term or sometimes even long-term existence of the system. This is part of the reason why many institutional systems can become entrenched.

"Dana" Meadows Helps Set Course for Systems Practice Guiding Star

The last three blog posts were a detour from the current look at the Systems Practice Jerusalem Vision project to review underlying Systems Thinking principles through Donella Meadows’ book “Thinking in Systems, A Primer”.  Addressing the two new levels of inquiry that we are asking others to adopt to address wicked problems, the first being the controversial events that describe but don't really define such problems.

Arguably, for many for whom the course is a one-off to address some specific issue, this may not be important but if Systems Practice were to be adopted as a standard means of addressing a host of issues over the long term then a better understanding of Systems Thinking becomes basically essential in my view.

Meadow tells us that all systems are composed of elements, connections and, most importantly, a purpose or function. The fulfillment of that purpose or function is a goal of that system, perhaps subsidiary, perhaps primary. Both she and, especially Stafford Beer advise us that the Purpose Of A System Is What It Does.

With each System Practice course project, we decide that a system, with which we are involved, should have different goals and therefore different purposes and functions. We don't actually know fully the goals, purposes or functions of the system in its current configuration, except perhaps for some that may be espoused, but we are first going to decide what is it, what new state, that we are trying to attain. The Systems Practice course does this by establishing a Guiding Star. 

In each of the Systems Practice projects we did not have a common vision when first thrown together. It slowly came together beginning with either the creation of a Complexity Spectrum or online brainstorming or both to determine whether we were dealing with a complicated (clock) problem or a complex (cloud) one. 

At first, our ideas were often directed at finding silver bullet solutions to the problem rather than developing a better understanding of the system under question. Reacting to the current situation rather than proactively planning to navigate to a desired future states by a Guiding Star. 

The concept of developing a Guiding Star was previously considered in New Community Paradigms with setting superordinate goals as part of the series Exploring with the Dialogue, Deliberation and Systemic Transformation Community to Discover New Possibilities. 

The formal description for that effort was, "What superordinate goal could replicate across the collective set of value systems, and act as a 'guiding star' for systemic transformation?”, which our facilitator paraphrased as, "What everyone wants, but no one entity can do themselves." 

The Guiding Star, according to the Acumen Systems Practice course, is an aspirational state or desired future.

A mistake in the first Systems Practice course, by me, was skimping over the Guiding Star, as well as the Near Star and Framing Question, which were created in large part by the group I was leading. I had a working systems map by that time and thought that I already had the needed insights. My approach saw our role as providing answers for consumption by a community, dismissing any concern for democratic deliberation or diversity.

Our collective vision of what that purpose or goal should be still needed to be developed. It was, and I had some input, but it was the conglomeration of about nine different perspectives. For the group dealing with food trucks for homeless campsites the Guiding Star was:

"A societal structure in which, when a person’s community support system fails, he receives appropriate, sufficient and timely support to prevent him from falling into homelessness through a community system that produces minimally decent shelter, sustenance and healthcare for those who become homeless working to integrate them fully back into the community."

During the Thailand Plastic Pollution project it was as decided by those defining the project:

"We are trying to move the City of Bangkok and the entire country of Thailand from both being blighted by and blighting oceans with plastic pollution to being plastic pollution-free." 

Our course catalyst for the project, Yeu advised us that:

"Guiding stars are best described as a vivid future state that provides a direction rather than measured goals. In that respect, do every member of your team share a common understanding of the difference between a system state that is healthier than a previous state? In your case, a less plastic-polluted state than another? Counting plastic items is not a good idea. So what is?”

The point is that there is more to being healthy than merely not being sick. He recommended, which I have also, the use of the "Systems Thinking Iceberg" Another potentially useful resource "Donella Meadows 12 places to leverage systems", emphasizes paradigm shifts in the beliefs and perceptions of stakeholders. It became the basis for the blog post "Dana" Meadows Helps Find Purpose and the Plastic in a System of Plastic Pollution.”

Based on these insights, I advised the Jerusalem Vision team that the Guiding Star should not be a blueprint of an ideal system. It is more giving reason for you wanting to create the ideal system or what it will be to drive you to want to create it, what you hope to achieve to drive you forward through times of hardship and struggle. Being an ideal, it isn't merely delivering the basics but it also won’t attain a level of finality either.

Our Guiding Star for Jerusalem Vision became: 

• "We are trying to move towards a social system that always strives to achieve win-win solutions for all involved."

• "We aspire to a Jerusalem where every resident has equal access to health services, education, employment opportunities, cultural services and regardless of race, culture, gender, socioeconomic background, or other human difference by fostering mutual trust and respect between all of Jerusalem’s inhabitants." 

• "We aspire to a Jerusalem where all communities have a basic trust in the system and bear a mutual respect for the rights of all other communities in Jerusalem and uphold the value of mutual collaboration." 

• "We aspire to achieve a social reality in Jerusalem where all communities feel secure in their identity while respecting the identities of other communities." 

The Near Star is a more near-term goal of a 5-10 year timeframe, a desired but provisional outcome towards the Guiding Star.

The Near Star, I suggested to the team, is not the most basic or least viable result or one that meets minimum requirements of the system that we have in mind. The Near Star, at least in my view, should be the system that we need to put in place to begin to move towards the Guiding Star, not a lesser version of the Guiding Star. While still being expansive enough that it isn't a clockwork objective.

Our first Near Star for Thailand Plastic Pollution was: 

“Bangkok City actors are able to work effectively toward reducing plastic pollution.”

The term “city actors" sounded too institutional or government oriented. It could include community actors but too often from the perspective of those in power. The more community-based term “stakeholders” with the definition being an entity that can affect or is affected by the wicked problem was used contingent with it being as inclusive as possible which would mean expanding outreach and increasing the complexity of overall interactions.

"Stakeholders, who can affect and are affected by plastic pollution in Thailand are able to work effectively toward the elimination of plastic waste." 

Our officially submitted Near Star for Jerusalem Vision is:

"Creating contexts and environments where members of different communities learn and work together encouraging the growth of mutual respect between them as individuals."

Unofficially, for the Jerusalem Vision project we decided that instead of looking at the Near Star as a stepping stone (milestone) toward the larger target (Guiding Star) we would embrace it as a "sandbox" where we could test our understanding of the system to see if we understood it enough to take even more daring steps to influence it.

The NCP Fantasy Systems Thinking Team - Forrester and Meadows

The last two posts attempted to span the distance between the practice of using graphic means and different methods to communicate the relationship of aspects, conceptual or real, of a situation or system, and understanding the complexity arising from those aspects themselves. The former, mapping is being used to assist in the navigating of the territory of the later with both being important. There is a higher level of mental organization still possible, the creation of an overlaying architecture to a systems approach. This arguably moves from a conceptual level to a more philosophical level.

The course provides in chapter 6 a sampling of the background of five notable figures in the systems thinking pantheon, each with a different approach or philosophy about systems thinking, Jay Forrester, Stafford Beer, Sir Geoffrey Vickers, Peter Checkland, and Russell Ackoff.

It was decided to come up with NCP's own Fantasy Systems Thinking Team. The first two selections have one the same as from the course and one new, Jay Forrester and Donella Meadows.

The NCP Wiki incorporates Systems Thinking as a primary component or wiki section, distinguishing between systems thinking approaches, which include systems dynamics programs and systems thinking applications for change-making efforts, featuring the Donella Meadows Project.

Though the course selected the man it did not select his methodology stopping short of incorporating Systems Dynamics. As reported in the blog post, Systems Thinking - Sailing through Wicked Problems on Complex Seas, the most adept advocate for Systems Dynamics is its creator, J. W. Forrester, Professor Emeritus Systems Dynamics at MIT who upended the conventional thinking in management and redefined what growth means through articles such as, System Dynamics: the Foundation Under Systems Thinking and Learning through System Dynamics as Preparation for the 21st Century. Professor Forrester was deemed The Prophet of Unintended Consequences.

Donella Meadows, primary author of Limits to Growth, was a protege of Forrester. She is also a favorite systems thinker given her own wiki-page in the NCP wiki. Even though both Forrester and Meadows were from the systems dynamics school of systems, Meadows from an organic, environmental background can be seen as often being more accessible than Forrester coming from an engineering background though both are just as disciplined.

As reported in the blog post, Advancing Racial Equity Through Collective Impact and Systems Thinking, systems thinking is seen as a means of addressing complexity. We want pragmatic solutions without wasting too much time on theory, looking for something concrete to build upon. This, however, brings about a counterintuitive trap raised by Forrester, who demonstrates how problems can arise when these principles are ignored.

Policy improvements in the short run often degrade a system in the long run while policies producing long-run improvements often initially degrade the system at the start. Though the short run is more visible and more compelling, calling for immediate attention, its impact is not really more concrete, rather becoming more what I have called entrenched, or in Forrester's words:

“However, sequences of actions all aimed at short-run improvement can eventually burden a system with long-run depressants so severe that even heroic short-run measures no longer suffice. Many problems being faced today are the cumulative result of short-run measures taken in prior decades.”

The post asserts that an ability to adopt different perspectives is important to relational mapping and to systems thinking in general. It can also be important to a system of both deliberative and participatory democracy. Essential in questions of equity, particularly those questions asked in terms of community economic and empowerment equity requiring answers of the larger community.

According to Forrester, in navigating between our concrete wants and our complex realities, our own individual mental models are fuzzy, incomplete, and imprecisely formed, continually changing with time, even in conversations. Even with only a single subject each participant in a conversation can employ a different mental model with different fundamental assumptions never brought into the open and different goals left unstated. Our thinking is not as concrete as we would like to think.

The George Box rule, stated before, still applies, all models (including computer) are wrong, but some are useful or on Forrester advice, it's not having a computer but how the computer is used to create the model that's essential.

“With respect to models, the key is not to computerize a model, but, instead, to have a model structure and decision-making policies that properly represent the system under consideration.”

“A good computer model is distinguished from a poor one by the degree to which it captures the essence of a system that it represents.”

As Forrester asserts, though a community system is complex, which means the data coming out of it is complex, this does not necessarily mean the answer is more data.

“The problem is not shortage of data but rather inability to perceive the consequences of information we already possess. The system dynamics approach starts with concepts and information on which people are already acting.”

Forrester demonstrates the paradox of complex systems in our society in that, “Generally, behavior is different from what people have assumed” and how System Dynamics models can help us understand how difficulties within actual social systems arise, and why so many past efforts to improve social systems have failed.

"The country has slipped into short-term policies for managing cities that have become part of the system that is generating even greater troubles."

"Rather than face the rising population problem squarely, governments try to relieve the immediate pressures by more policemen, financial aid, busing to suburban schools, and subsidized health facilities. As a consequence, increasing population reduces the quality of life for everyone."

With simple systems, causes are close, whether arising from different parts of the system and in time to where or when the symptoms occur. This can easily mislead us into believing our actions to alleviate the symptoms to be concrete in nature.

The Donella Meadows Project (formerly Institute) has been introduced previously in this Systems Practice series in Approaching a Systems Practice, Yet Again as an example of an US-based systems thinking enterprise along with the Waters Foundation and the Institute for Systemic Leadership and in discussions regarding uncertainty related to messes, particularly irreducible uncertainty, as suggested by Donella Meadows in More Thinking on Mastering Systems Practice, Dealing with Messes. The uncertainty that is inherent in the situation itself, most notably, complex stochastic output.

Meadows definition of “A system is an interconnected set of elements that is coherently organized in a way that achieves something…. a system must consist of three kinds of things: elements, interconnections and a function or purpose.”

She expanded upon these simple foundational steps to establishing open, positive interactions to bring about change through Dancing with Systems. More importantly, she identified points of leverage within systems in endeavoring to bring about the desired transformation. In a post on the US Systems Practice versus Systems Thinking it was suggested using Donella Meadows' Twelve Leverage Points at least as a systems thinking based background resource.

In the ABCD Conflict Consensus Debate and Systems Thinking posts, ABCD or Asset Based Community Development was seen as fitting the Meadows’ definition of a system. It is a system, a complex, human-based system, that must exist within, and by its purpose interact with the complicated, procedure-based institutional systems. It is a system though that focuses nearly entirely on the "territory" of community relations rather than more abstract issues of mapping. Institutions are also seen as being composed of multiple systems, with an espoused system often conflicting with the actual in-use system, or systems of administration contrasted with systems of organizational culture. The use of systems thinking is an endeavor to bridge these supposedly conflicting perspectives.

As discussed in Sailing Complex and Wicked Seas with Icebergs (Systems Thinking), there is always the question of what specific system are we defining? Are we all talking about the same system, in terms of scope, abstraction, complexity, understanding and potential action?

New Community Paradigms is seeking empowerment of community members from the bottom up through deliberative democracy, scaffolded by systems thinking, and other means. One means of understanding the world, featured before is the Systems Thinking Iceberg Model. With the systems thinking iceberg model, we are not only speaking of combining different methodologies or perspectives but more importantly in terms of combining different mindsets. The use of Kumu mapping, as part of a systems thinking approach, is an attempt to take the deepest levels of the systems thinking iceberg model as well as the most effective interventions of Donella Meadows' Leverage Points with the intention of applying them to real world problems.

Systems Practice versus Thinking pt 2

The last post returned to the Systems Practice course begun earlier this year and defined certain of its operational terms, such as factors, forces, and themes as pieces in the creation of a system puzzle or map. This post will continue explaining the systems practice process of putting those pieces together contrasted more generally with systems thinking and with Kumu mapping. The question that will remain on hold, for now, is how does this apply to alleviating homelessness? This must be addressed first to effectively apply the methodology. 

In Kumu mapping, factors are elements. It is the Kumu connections forming relationships between elements that represent forces.  Similar to gravity as a force only occurring when two or more bodies are in relation to each other. A theme, or collection of commonly related forces, is not quite yet a Causal Loop. To be a loop, those forces and themes need to be organized into a persistent feedback configuration. Until then these themes organized into connected forces are what I call causal influence pathways. One such pathway or theme could then be "cost of living” which might consist of a number of different enabling and inhibiting forces among them  "community bonding" as the interaction of which served as a means of stabilization that lessened the negative impacts that occurred when the cost of living increased because households within a community decided to share resources.

An interim step particular to Systems Practice before finalizing the creation of feedback loops is S.A.T. or Structural, Attitudinal, Transactional analysis. The purpose of SAT  is again to assist in being holistic in the analysis by avoiding focusing solely on those things best known to one's own particular background such as an economist tending toward only economic forces or a social worker focusing only on social forces.

SAT classification is supposed to help make sure that your group is taking a holistic approach when identifying factors and building loops by identifying causes and effects, as well as later in the course when the focus is on leverage points for building a strategy on how to more readily change the system. Once, however, these loops are woven into a systems map there is no longer a need for the formal labeling of SAT and it can fall away as a separate artifact.

There isn't any formal connection between SAT and  Kumu mapping. SAT according to Rob the course's instructor, can be thought of as scaffolding and the Kumu map as the building. The scaffolding helps one in constructing the building but then as said falls away when you are done. I have the same metaphor in mind when applying systems thinking to participatory democracy. It is a means not an end in of itself.

A common systems thinking tool that I believe could be related to SAT analysis and be useful in helping those not familiar with the methodology is the Systems Thinking Iceberg Model. It could be introduced again early in the course and definitely prior to SAT. The Iceberg Model as a meta-perspective of the system does not fall away as does SAT but maintains direct correspondence with the Systems Practice components aligning factors to events, aligning loops and themes to patterns, both SAT and the Iceberg has a structural component, and finally the attitudinal aspect of Systems Practice corresponding to the Systems Iceberg mental model level. 

Another subsequent step that systems practice takes, as part of a dynamic and holistic analysis in identifying feedback loops through putting the pieces together is an Upstream-Downstream analysis. Following any factor or element in the direction of its connecting arrows to another factor, which denotes cause, defines downstream relationships and any arrows connecting into any factor from another factor, denoting effect, defines upstream relationships is the basis for Upstream-Downstream analysis.

The Upstream-Downstream analysis becomes the "seeds" or relevant puzzle pieces in the process of loop building by identifying a few important connections to start the process of identifying persistent patterns. Moving from an Upstream-Downstream analysis to actually building feedback loops though is not a one to one transition. The loops, once created, take on an importance of their own moving beyond what was captured in the Upstream-Downstream analysis. By the time one gets to the Upstream-Downstream analysis, and then subsequently to creating the feedback loops, any distinctions one might assume between enablers and inhibitors tends to break down. 

The course's concepts of upstream/downstream or cause/effects are then arguably dependent on which element was the starting point.  Because a feedback loop (A —> B —> C —> A, etc.)  of forces or dynamics are circular upstream-downstream analysis is artificial because if you travel far enough along a closed loop, any upstream factor will also be downstream.  Start at B then A is upstream and C is downstream. "Happiness" could be seen as a driver and as an enabler for “Wealth,” which could then become an enabler in turn seen to drive “Happiness”.

Overly simple loops though, those with just two factors such as, “Wealth" > “Happiness” —> “Wealth" indicate a need to zoom in and ask what is it about wealth that leads to increased happiness? Is this always the case? Does wealth sometimes lead instead to depression and unhappiness? If so, why? What other factors explain why these patterns vary?

In assembling loops, factors need to be worded as nouns that can be scaled up or down. The "level of corruption" is a more appropriate factor label than is a "high level of corruption". There isn't  a correlation though between how specifically worded a factor is or how elaborate a loop is for the potential of that loop to produce insights into how to engage a system.  The most powerful loops of three to four factors having both profound meaning and being simply worded can be termed “elegant,”

From a non-technical, more social perspective, similar to one provided during Systems Thinking Certification, factors could be thought of as characters in a novel interacting with other characters with arrows showing causal connections and forming sub-plots through loops. Taken together, these subplots will form a plot and eventually a rich story or novel through a dynamic system map. 

All of this leads to reassembling or stitching together or I would suggest quilting together a systems map. First though is determining what was then referred to as the Deep Structure of the system from the myriad of enabling and inhibiting themes and forces that ended up becoming loops. This will be revealed in the next post.

As one of our teammates said, an advantage of drawing Kumu maps is finding dependencies and loops where they were not necessarily obvious. This is the main outcome of connecting many different feedback loops into a systems map. It is according to Rob the interconnection among the loops that surface dependencies and more importantly, areas of possible leverage for making longer-term systems change. 

A further question arose, in creating a Kumu map, as for whether the more granular we can get the more likely we are to find unseen things. Rob used examples from the financial crisis to come up with factors such as debt, rich people hoarding money so it's not available to the economy, bad institutional practices by bankers and others. However, going deeper into technical details like derivate pricing likely would not help in coming up with a useful solution. He asserted, if however, we identify that the prevailing market economy doctrine is not based on scientific fact but has rather become something more like a religious paradigm, we then add a substantial insight into the whole picture. That is a tremendously large step though to take a group through unless they are already inclined, perhaps in some cases too inclined, to such a view.

This brings me to yet another suggested systems thinking based resource and that is Donella Meadows' Twelve Leverage Points as at least a background resource. 

As I have said before, using the development of the concept of time in navigation as a metaphor, I see Kumu mapping as a means of longitudinal thinking in relation to the more common linear or latitudinal thinking that together help in making a global complex perspective more possible.

I started, as I usually do, directly mapping relationships after creating a few experimental maps to test out some ideas, identifying factors from there and developing loops directly and building the map from there. Again, I have to admit that a result of my approach was that it allowed narrowing the focus to an overly limited path. Others, using the Systems Practice approach, with limited or no systems thinking background, provided important insights, like being able to look at the picture on the puzzle box blown up but perhaps not having the necessary pieces themselves.

The course's instructor Rob had spoken of the difficulties of mapping in a fifth-week video.  I could see his point if I had followed the Systems Practice procedure from the beginning as it was very different from my usual approach. 

One of the primary issues that systems thinking seeks to address though is the tendency of people to only look at factors in immediate or near immediate approximation. What then may be an enabling force in one loop may become an inhibiting force in another related loop. In this aspect, systems practice may be a bit weaker for those with less experience in systems thinking.

Instead of considering enabling and inhibiting forces, I focused on adds to or moves in the same direction and detracts from or moves in the opposite direction of Causal Loop Diagram building, letting the system tell me what was enabling or inhibiting over an extended number of degrees across the system. This becomes all the more important when transitioning from abstract mapping to applying the lessons learned to the real world wicked challenge. Because I do not want to see this process be a “one-off” in community empowerment, I will add, even recognizing it is far more involved, one other suggested systems thinking resource to be included and that is systems thinking archetypes. 

This completes the critique of the system's practice process from a first time, limited understanding perspective. It is undoubtedly necessary to take the course oneself to verify what has been suggested but we can get some further idea of its utility. How then did we map out the specific challenge of addressing homelessness?