Five Notes on Systems Theory

Five Notes on Systems Theory This prĂŠcis chronicles five short notes on the General System Theory; the nature of a system; open and closed systems; leverage points; and the learning organization.

Olivier Serrat 10/07/2019

1 The Skeleton of Science In his Metaphysics (n.d.), Aristotle (384–322 BC)—the Father of Western Philosophy—sagely recognized that "… many things have a plurality of parts and are not merely a complete aggregate but instead some kind of a whole beyond its parts …". Oppositely, from the time of Descartes (1596–1650) through The Age of Enlightenment and well into the 20th century, the scientific method progressed under two related assumptions: a system could be broken down into individual components so that each might be analyzed as an independent entity, and the components could be added in linear fashion to describe the totality of the system. For sure, reductionism can make large, complicated problems less intimidating and more amenable to solutions; by systematic observation, measurement, and experimentation and the formulation, testing, and modification of hypotheses, the scientific method has broken much ground and delivered immense knowledge; even so, one always risks losing the interconnectedness of situations in their fullest expressions. "Independently of each other, similar problems and solutions have developed in widely different fields", von Bertalanffy (1969) remarked in the face of ever-increasing specialization and the splitting of science into innumerable disciplines and subdisciplines (p. 31).1 Positing that focusing on complexity and interdependence promotes understanding of the dynamic behavior of systems, von Bertalanffy (1969) then proposed the General System Theory for application in the natural and social sciences.2 Today, the applications of systems theory include computing, ecology, engineering, family psychotherapy, the learning organization (Senge, 2006), and management. In the latter instance, given that the first consideration of an organization (e.g., a business or a city) is to survive (Leonard, 2009), systems analysis—developed independently of systems theory—now helps decision-makers identify, reconstruct, optimize, and control organizations in light of multiple objectives, constraints, and resources. In such instances, systems analysis helps specify possible courses of action and their benefits, costs, and risks. Ideas related to systems theory are also used in the emerging sciences of complexity, such as Complexity Leadership Theory; in the study of self-organization and heterogeneous networks of interacting actors; and in associated domains such as artificial intelligence, artificial life, chaotic dynamics, computer modeling and simulation, far-from-equilibrium thermodynamics, and neural networks.

There can be no doubt that systems thinking complements reductionism and that the world and our lives would be poorer without it. But, try as one might, systems thinking is not the be-all and end-all of approaches to problem solving: (a) systems thinking encourages binary (or black-andwhite) solutions, even though real-life is about paradox (or gray areas), and so may prevent creative types from contributing because such personalities are entirely intuitive; (b) systems thinking underrates the inestimable value of experiencing, something that happens in social organizations but not in natural systems; (c) systems thinking may be more suited to 1

This intuits that von Bertalanffy (1969) did not formulate the General System Theory to fill a gap in knowledge but, rather, to put paid to the proliferation of gaps as "… the physicist, the biologist, the psychologist, and the social scientist are, so to speak, encapsulated in their private universes, and it is difficult to get word from one cocoon to the other" (p. 30).

2 To put it simply, a system is a set of regularly interacting or interdependent elements (or components, entities, factors, members, parts, units, etc.) that work together to form an integrated whole. (Hence, the term "systemic" refers to something that spreads throughout and so affects a system entirely.) Every system is confined by spatial and temporal boundaries, influenced by its environment (unless it is closed), described by structure and purpose, and expressed by functioning that—in complex systems—can involve the acquisition of qualitatively new properties through emergence and lead to continual evolution.

2 circumstances of apparent complexity (that some might instead term complicated)—where the interaction of components seems complex at first glance but demonstrates relatively simpler order below the surface—and may have limitations in instances of truly complex systems, such as social systems; and (d) systems thinking needs to be followed by "systems doing" since one must by then deal with real people instead of models. Perhaps because of this, systems thinking in business life is yet to demonstrate unalloyed success in the formulation of, say, policy, strategy, or investments or—put plainly—performance that is unequivocally superior to that of other approaches to thinking about the world, which systems thinking seems intrinsically wont to crowd out.

More Than the Sum of Its Parts? Or Other?

First articulated by Aristotle, then, systems thinking is now summed up by the catchphrase that the whole is more (or greater) than the sum of its parts; usually, this is taken to mean that the whole is "better" than one might expect from the totally of the individual parts because the way they combine adds a different quality, or synergy, such as what one might expect from successful teamwork; more pertinently, perhaps, the notion should impart that the whole is "other" than the sum of the parts (and of course the individual effect of each part), "other" being taken to denote the system that comes about from the cohesion (or "togetherness") of the parts in a given environment.

That said, there is more to the attributes of a system than mere cohesion (or "togetherness") of the parts within an environment, as von Bertalanffy (1969), Senge (2006), and Meadows (2008), among others, have explained. To be given full expression so it might truly be "more than the sum of its parts" and function in this or that way, several other factors must both be at play and maintain integrity across the elements: the main factors—indeed, characteristics—have to do with resilience, self-organization, and hierarchy (and the balance among them) (Meadows, 2008, pp. 75–85).

Effectiveness, the measure of a system's ability to perform the functions necessary to achieve its goal, may be the ultimate attestation that a system is "more than the sum of its parts."

Effectiveness was described by Hitchins (2007) as a combination of performance (meaning, how well a function is carried out), availability (that is, how often the function can be deployed when needed), and survivability (namely, how likely is it that the system will be able to use the function fully). Hitchins (2007) offered an engineering perspective on systems and, unsurprisingly, other perspectives exist: from the perspective of organizations, Senge (2006) explained that a system can (or rather should) also learn, thereby improving its effectiveness over time. We live in a world of organizations and Senge (2006), for one, offered both a convincing rationale why such (socio-technical) systems should be both more and other than the sum of their parts and how they might achieve that.

Open and Closed Systems At the heart of the General System Theory, von Bertalanffy (1969) contrasted two types of systems, viz., open systems and closed systems. Open systems are systems that allow interactions between their internal elements and the environment.3 "An open system is defined as a system in exchange of matter with its environment, presenting import and export, buildingup and breaking-down of its material components" (von Bertalanffy, 1969, p. 140). To wit, 3

Interactions can take the form of energy, information, or material transfers into or out of a system's boundaries.

3 "Every living organism is essentially an open system. It maintains itself in a continuous inflow and outflow, a building up and breaking down of components, never being, so long as it is alive, in a state of chemical and thermodynamic equilibrium but maintained in a so-called steady state which is distinct from the latter. This is the very essence of that fundamental phenomenon of life which is called metabolism, the chemical processes within living cells" (von Bertalanffy, 1969, p.

39).

Elaborating, von Bertalanffy (1969) wrote that an open system is a complex of interacting elements that interact with their environments, can acquire qualitatively new properties through emergence, and are thus in continual evolution by means of feedback.4 In the social sciences, for instance, an open system is a process that exchanges, say, capital, information, material, or people with its environment. The key characteristics of an open system pertain to: • Importation of Energy. An open system takes energy—in various kinds of inputs—from the environment; without inputs of energy, no open system can survive.

• Throughput. An open system converts inputs into various kinds of outputs; the transformation process is known as throughput.

• Outputs. An open system exports outputs to the environment; the manner in which it does so determines its viability and existence.

• System as Cycles of Events. The pattern of an open system's activities—inputs, throughput, outputs—has a cyclical character; outputs that are exported to the environment provide inputs toward the repetition of other cycles.

• Negative Entropy. To endure, open systems must slow the entropic process; this can be achieved by importing more energy from the environment than what a system expends. (A law of nature, entropy dictates that all organized forms eventually degrade or run down.)

• Feedback Mechanism. With feedback, an open system receives information from the environment; with negative feedback, a system can correct deviations from a more optimal (or desired) course of actions.

• Steady State. When maintaining negative entropy, the importation of energy from the environment can hold a degree of constancy in energy exchange, and so that the open system achieves steady state; however, this steady state is not a true equilibrium since energy import and export is a continuous process and a new equilibrium is soon formed.

• Differentiation. An open system moves to differentiation and elaboration; old patterns are changed by new specialized functions.

• Integration and Coordination. As differentiation proceeds, an open system must somehow integrate and coordinate related parts.

• Equifinality. Equifinality, the property of allowing or having the same effect or result from different events, means that an open system can reach a given end-state by many potential means. (Accountlearning.com, n.d.)

The methodology and mathematical modeling technique of system dynamics, which owes to Forrester's work in the mid-1950s, is an approach to understanding the nonlinear behavior of complex systems over time using stocks, flows, internal feedback loops, table functions, and time delays. The main idea of systems dynamics was borrowed from control engineering (or control systems engineering) to model the dynamics of business and social systems and highlight the impacts of different feedback loops in the systems. Developed independently from 4

In precisely opposite fashion, closed systems are isolated from their environment. "In any closed system, the final state is unequivocally determined by the initial conditions" (von Bertalanffy, 1969, p. 40). Equilibrium thermodynamics, to mention but one, is a field of study that applies to closed systems.

4 the General System Theory, which deals with the concept and principles of open systems in general, the basics are nevertheless similar. To note, the General System Theory's conception of open systems and—more to the point—closed systems (generally) resonates with the system dynamics concept of an endogenous isolating boundary (e.g., rate, stock, time, etc.), with the important caveat that the closed-boundary concept of systems dynamics implies that the system behavior of interest is not imposed from the outside but created from within, the object being to study dynamics and model impacts. (In systems dynamics, a system's boundaries demarcate limits to the system's internal components and processes; internal to its boundaries, the system has some degree of integrity, meaning the parts work together with integrity to give the system a degree of autonomy; beyond the boundaries, the system loses its autonomy.)

Leverage in Systems In the context of systems analysis, Meadows (1997) explained that "[leverage points] are places within a complex system (a corporation, an economy, a living body, a city, an ecosystem) where a small shift in one thing can produce big changes in everything" (p. 1). [That said, in an online version of the same article, Meadows (n.d.) cautioned that "Th[e] idea [of leverage points] is not unique to systems analysis—it's embedded in legend. The silver bullet, the trimtab, the miracle cure, the secret passage, the magic password, the single hero who turns the tide of history."

(Meadows (n.d.)] In increasing order of effectiveness, Meadows (1997) identified the places to intervene in a system to be: 9. Constants, parameters, numbers (e.g., standards, subsidies, taxes) 8. Regulating negative feedback loops 7. Driving positive feedback loops 6. Material flows and nodes of material intersection 5. Information flows 4. The rules of the system (e.g., constraints, incentives, punishments) 3. The distribution of power over the rules of the system 2. The goals of the system 1. The mindset or paradigm out of which the system—its goals, power structure, rules, its culture—arises The nine places to intervene in a system are commonsensical, not to say obvious. But, "Counterintuitive. That's Forrester's word to describe complex systems. Leverage points are not intuitive. Or if they are, we intuitively use them backward, systematically worsening whatever problems we are trying to solve", Meadows (n.d.) added. Why places to intervene in a system should be counterintuitive demands explanation that neither Meadows (1997) nor (presumably) Forrester provided. Counterintuitive may be the wrong word: instead, Meadows and Forrester might have explained that, particularly in hierarchies but more likely than not everywhere, it is the distribution of power over the rules of the system, meaning, the pigeonholing of responsibilities and associated lack of incentives, that more often than not dissuades personnel from volunteering fixes. From this perspective, begging to differ also with Repenning and Sterman (2001), it is not that "The ability to identify and learn about new improvement methods no longer presents a significant barrier to most managers [and that] … [i]nstead, successfully implementing these innovations presents the biggest challenge" (Repenning & Sterman, 2001, p. 65, emphasis in original). How to multiply the outcome of efforts without a corresponding increase in the consumption of resources ought to be what each and every organization seeks: and yet, all too often, organizations are comfortable with policies, strategies, structures, systems, and business processes that keep them in the middle of the road. "Give me a lever long enough and a fulcrum on which to place it, and I shall move the world," Archimedes (287– 212 BC) is alleged to have said: notwithstanding, the principle of leverage is rarely applied in

5 organizations because not enough attention is paid to the fulcrum, the point on which a lever rests (or is supported) and on which it pivots. In organizations, lest we forget, the fulcrum is people and organizations that hope to leverage for change had better understand people and their organizational cultures.

The Disciplines of the Learning Organization In the first appendix of The Fifth Discipline, which presents the five component technologies of the learning organization as learning disciplines, Senge (2006) remarked that each discipline can be pondered at three distinct levels: (a) essences (viz. the state of being of those with high levels of mastery in the discipline); (b) principles (viz. guiding ideas and insights); and (c) practices (viz. what you do) (p. 383). Because we all go through distinct stages of learning, Senge (2006) averred that it is helpful to approach the learning disciplines by developing new cognitive capacities (Stage 1), experimenting with new action rules (Stage 2), and enacting new values and assumptions (Stage 3). The three levels of the five "pyramids" used to depict the practices, principles, and essences are compiled in the table below.

Table: The Learning Disciplines Learning Discipline Systems Thinking

Essence

Principle

• Holism • Interconnectedness

• Structure Influences Behavior • Policy Resistance • Leverage • Vision • Creative Tension vs. Emotional Tension • Subconscious • Espoused Theory vs. Theory-in-Use • Ladder of Inference • Balance Inquiry and Advocacy • Shared Vision as "Hologram" • Commitment vs.

Compliance

Personal Mastery

• Being • Generativeness • Connectedness

Mental Models

• Love of Truth • Openness

Shared Vision

• Commonality of Purpose • Partnership

Team Learning

• Collective Intelligence • Alignment

• Dia Logos • Integrate Dialogue and Discussion • Defensive Routines

Practice • Systems Archetypes • Simulation • Clarifying Personal Vision • Holding Creative Tension (Focusing on the Result, Seeing Current Reality) • Making Choices • Distinguishing "Data" from Abstractions Based on Data • Testing Assumptions • "Left-Hand" Column • Visioning Process (Sharing Personal Visions, Listening to Others, Allowing Freedom of Choice) • Acknowledging Current Reality • Suspending Assumptions • Acting as Colleagues • Surfacing Own Defensiveness • Practicing

Note. Compiled from Senge (2006).

Presenting the five disciplines as learning disciplines at the end of The Fifth Discipline seems a strange afterthought but underscores the idealistic pragmatism of Senge (2006), which moved him to both explore and promote ideas that many would consider utopian (or as a minimum abstract), and to mediate these with a clear architecture so they might be worked on. An accent on learning runs through Senge (2006): of course, "survival learning" in situations of rapid change is not good enough; but, even "adaptive learning" must be joined by "generative

6 learning" to enhance the capacity to create. For Senge (2006), real learning gets to the heart of what it is to be human.

The architecture of the five disciplines—that the literature never seems to discuss—is ingenious: summarizing perforce, the construct and its interrelationships are about promoting enrollment, commitment, and compliance toward shared meaning (shared vision), engaging oneself in the world (personal mastery), reflecting on assumptions and biases (mental models), fructifying the ability to cooperate (team learning), and discerning the ''big picture'' (systems thinking). So, the answer to the question of how do Senge's (2006) five learning disciplines aid in creating a learning organization is superficially straightforward: one should follow Senge's (2006) good advice.

Except, of course, that building a learning organization is not as easy as Senge's (2006) construct has us make out. Senge's (2006) advice was aimed at practicing and aspiring managers and leaders: but, did it foster praxis, meaning, informed and committed action on the part of those The Fifth Discipline was addressed at? The harsh reality is that—at a glance—very few organizations have come close to the combination of characteristics that Senge (2006) identified with the learning organization. First, this is because wholehearted cultivation of learning is not likely to happen (or could at best only ever be a tangential concern) in a capitalist system that hangs for dear life on financial imperatives. Second, the people that Senge (2006) addressed rarely have the disposition, the theoretical tools, the like-minded colleagues, or even the time with which to follow through: in most organizations, the move in perpetual beta from product to process and then back again is psychologically and socially demanding (if the systems in place allow it at all). Third, Senge (2006) underestimated the political dimensions of organizational life, especially with regard to shared vision.

Considering why few organizations adopt systems thinking, Ackoff (n.d.) identified one general reason and one specific reason: the general reason is that—from kindergarten all the way through university and so in organizations too—mistakes are treated as bad things. "Therefore, organizations and individuals that never admit to a mistake never learn anything. Organizations and individuals that always transfer responsibility for their mistakes to others also avoid learning" (Ackoff, n.d., p. 2).5 The specific reason, that Senge's (2006) success as a bestselling book should imaginably have remedied in time, is that very few managers have any knowledge or understanding of systems thinking.

In backhanded reference of the "Success to the Successful" system archetype,6 there is every chance that if people were required to give an example of a contemporary learning organization they would (from an American perspective) choose such corporate "winners" as Amazon Web Services, Salesforce, Cisco, Ingersoll Rand, and T-Mobile.7 But, the trouble with self-fulfilling prophesies is that they obscure real accomplishments elsewhere, which some would argue 5

Ackoff (n.d.) made an important distinction between errors of commission and errors of omission, and argued that the latter are more serious (p. 2).

6 In systems thinking, an archetype is a recurring pattern of behavior (or "common story") that throws light on the structures that drive systems (Kim & Anderson, 1998). Senge (2006) described 10 archetypes: (a) balancing process with delay, (b) limits to growth, (c) shifting the burden, (d) shifting the burden to the intervenor, (e) eroding goals, (f) escalation, (g) success to the successful, (h) the tragedy of the commons, (i) fixes that fail, and (j) growth and underinvestment (pp. 389–400).

7 I would choose Pixar Animation Studios for its approaches to overcoming the forces that stand in the way of inspiration.

7 need not necessarily be at the corporate level. Senge (2006) may have been the victim of perfectionism: it does not have to be—systematically—all or nothing. If we were to celebrate learning offices (and departments) we might have more reasons to believe in the ideal of the learning organization for the reason that we would find more expressions of it, however imperfect. "The maxim 'Nothing avails but perfection' may be spelt shorter: 'Paralysis'," said Winston Churchill.

References Accountlearning.com. (n.d.). Retrieved from https://accountlearning.com/ Ackoff, R. (n.d.). Why few organizations adopt systems thinking. Retrieved from https://ackoffcenter.blogs.com/ackoff_center_weblog/files/Why_few_aopt_ST.pdf Von Bertalanffy, L. (1969). General system theory: foundations, development, applications. New York, NY: George Braziller, Inc. Hitchins, D. (2007). Systems engineering: A 21st century systems methodology. Hoboken, NJ: John Wiley and Sons.

Kim, D., & Anderson, V. (1998). Systems archetype basics: From story to structure. Waltham, MA: Pegasus Communications, Inc. Leonard, A. (2009). The viable systems model and its application to complex organizations.

Systemic Practice and Action Research, 22, 223–233.

Meadows, D. (1997). Leverage points: places to intervene in a system. The Sustainability Institute, 19.

Meadows, D. (n.d.). Leverage points: places to intervene in a system. Retrieved from http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/ Meadows, D. (2008). Thinking in systems: A primer. White River Junction, VT: Chelsea Green Pub. Senge, P. (2006). The fifth discipline: The art and practice of the learning organization (2nd ed.).

New York, NY: Currency/Doubleday.

Repenning, N. P., & Sterman, J. D. (2001). Nobody ever gets credit for fixing problems that never happened: Creating and sustaining process improvement. California Management Review, 43(4), 64–88.