1. Understanding Systems Thinking & Learning

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A new age—the Systems Age—has clearly begun. Today’s technological changes and innovations focus mainly on systems, particularly electronic ones, and on systems linking and interface (e.g., GATT, Mercosur, the Internet). The systems around us have multiplied and enlarged, often to overwhelming numbers and proportions. Corporations span the globe; communications satellites ring the skies. As distance is redefined, systems collide in countless ways, defying our comprehension of change and the adequacy our usual problem-solving methods. We find ourselves in a small world of enormous complexity, a new world that demands we see it from a new perspective—a systems perspective—with a mindset attuned to processes, patterns, and relationships. Systems thinking is tailor-made to meet this demand and to help us manage our organizations in the Systems Age.

DISCOVERING THE SYSTEMS THINKING MINDSET

To begin with, we must understand that any mindset consists of mental models, or concepts, that influence our interpretation of situations and predispose us to certain responses. These models, which are replete with beliefs and assumptions, thus strongly determine the way we understand the world and act in it. The irony is, they become so ingrained in us, as tendencies and predispositions, that we seldom pay attention to them. Even when something in our experience calls them into question—an “unsolvable” problem, perhaps, or an “unmanagable” interpersonal conflict—we miss the call. Those problems and conflicts, patched up for the time being, never really get resolved, and we wonder why success eludes us.

Often, not until a crisis hits, driving us deep into ourselves, do we realize we’ve been acting on unfounded beliefs or outmoded assumptions, and finally shift our mindset. But we don’t always catch the obvious lesson: that we need to put ourselves in touch with our mental models, hold them up to the light and look for biases and unsupported “facts,” those things which cause us to misunderstand the world; in short, that we must take an active role in shaping our mindsets, opting for mental models which better “capture” the world we need to understand. It is at this point where the systems thinking mindset comes in.

Mindset and Worldview

The beauty of this mindset is that its mental models are based on natural laws, principles of interrelationship, and interdependence found in all living systems. They give us a new view of ourselves and our many systems, from the tiniest cell to the entire earth; and as our organizations are included in that great range, they help us define organizational problems as systems problems, so we can respond in more productive ways. The systems thinking mindset is a new orientation to life. In many ways it also operates as a worldview—an overall perspective on, and understanding of, the world.

To develop this mindset, we must first look to three fundamental principles of living systems: that of openness, interrelationship, and interdependence.

The Principle of Openness

Any system falls into one of two basic categories: open or closed. An open system accepts inputs from its environment, acts on the inputs to create outputs, and releases the outputs to its environment. In contrast, a closed system is isolated and hermetic; an experimental, sterile chemistry lab would be an example. Virtually every system in which we operate is an open system, although some are more open than others—a key to success, as we shall see later in this guidebook.

By viewing the systems around us as open ones, we become more aware of their interactions with their environment. This awareness is crucial, for if we are to manage change, make decisions, and solve problems within systems, our considerations must include that environment as well as the systems components that support the objective of the whole. This is the nature of systems, and we have to work with it.

The Principles of Interrelationship and Interdependence

When one component of a system changes, it affects many other systems components and may even alter the entire system. Likewise, when a system itself changes, it has a necessary effect on the other systems in its environment. Why? Because there are points of relationship and interdependence that extend through and across systems and link them in various ways.

Just think of an ecosystem like a salt marsh. Its inhabitants—biological systems such as birds, insects, mollusks, grasses, algae—depend on the conditions of that marsh; but the conditions also depend on them. If the grasses begin to die off, for example, the birds will be more vulnerable to intruders and have no place to nest; their absence will cause condition breakdown for other inhabitants, who will likely overpopulate; moreover, the lack of grasses will mean more erosion. If poor conditions continue, eventually the marsh will be little more than a drainage hole.

Why might the grasses begin to die? Because of a change in the marsh’s environment, in other systems. Maybe an increase in storms has resulted in a closed breechway, causing water deoxygenation (a causal chain running from weather to coastal to marshland systems); or perhaps or a rise in beach traffic has lead to more exhaust pollutants (a confluence of chemical, technological and biological systems). And the loss of the marsh will affect the entire coastal area, itself a system full of systems and interrelated with, and interdependent on, its environmental systems.

The above is, of course, a worst-case scenario, yet we see similar scenarios all the time, and not only in ecological systems. We see them in the failure of businesses, communities, and even nations; these too are living systems, part of the natural order of life. We also see them in ourselves, for we are biological entities, each body a configuration of physical and mental systems. Our overall well-being is inextricably bound up in the well-being of those systems, with patterns of interdependence linking them to one another and their environment. Just how strong these links are becomes clearer all the time. We now know, for instance, that mental stress can compromise the immune system and that an optimistic attitude can help the body heal faster. Because neither stress nor optimism can be looked at under a microscope, this relationship strikes some people as odd, even dubious; but to someone with a systems thinking mindset, it makes complete sense—is simply the laws of living systems at work.

Putting the Principles to Work

Once we get a mental handle on the principles of openness, interrelationship, and interdependence, it is only natural for us to wonder how we can get a practical handle on putting them to work in our organizations and other living systems. The fact is, many of us have already begun to do it. Collaborative, team, and systems-oriented efforts are becoming more and more common in organizations and communities. Also, there are fields of thought such as Gestalt Therapy, Complexity Theory, and Chaos Theory, and technological areas like operations research, telecommunications, and information systems, that deal with the interrelationship of processes and patterns—the art of systems thinking in its broadest sense. Among its practitioners are such diverse people as Fritjoff Capra, Jay Forester, Peter Senge, Russ Ackoff, Meg Wheatley, Eric Trist, and Ludwig von Bertalanffy, all of whom recognize that systems behave in accordance with these principles, and that what we see changing on one systems level will affect other levels in various, ongoing patterns of cause and effect.

To become practitioners of that art ourselves, we need to start looking at societal and organizational problems as systems problems and seek systems-integrated solutions. Rather than identify a problem as one isolated occurrence, we must learn to identify and solve patterns of problems. We also must try to detect patterns of relationship and interdependence between systems, looking for “leverage points”—areas of influence that, if acted upon, can lead to lasting beneficial changes throughout those systems.

Our systems thinking mindset thus requires mental models that help us discover more than just “partial systems” solutions—what we tend to get in today’s systems-focused efforts. As yet there is only one body of thought that provides us with those mental models, offering us a way to reach fully integrated solutions to our systems problems. And it is not Gestalt Therapy or Chaos Theory. It is General Systems Theory, a lost art based on a natural perspective of the world and its many systems. Perhaps because its originators were primarily biologists, this theory looks not to artificial constructs or paradigms for its understanding of the world, but to life itself, acknowledging that living systems are the natural order of life. Let’s take a closer look.

GENERAL SYSTEMS THEORY

In the 1920s, biologist Ludwig von Bertalanffy and others proposed the idea of a general theory of systems that would embrace all levels of science, from the study of a single cell to the study of society and the planet as a whole. They were seeking these generalizations in order to create a recognizable standard of scientific principles that could then be applied to virtually any body of work. Out of this study came the scientific application called General Systems Theory.

Geoffrey Vickers, in 1970, explained the theory more in layman’s terms:

The words general systems theory imply that some things can usefully be said about systems in general, despite the immense diversity of their specific forms. One of these things should be a scheme of classification.

Every science begins by classifying its subject matter, if only descriptively, and learns a lot about it in the process . . Systems especially need this attention, because an adequate classification cuts across familiar boundaries and at the same time draws valid and important distinctions which have previously been sensed but not defined.

In short, the task of General Systems Theory is to find the most general conceptual framework in which a scientific theory or a technological problem can be placed without losing the essential features of the theory or the problem.

This theory, then, is a marvelous vehicle for framing and describing universal relationships. Its basic precept is that, in our work on any problem, the whole should be our primary consideration, with the parts secondary. The theory also states that parts play their role in light of the purpose for which the whole exists—no part can be affected without affecting all other parts. Thus, when we want to study any system, be it organizational, organic, or scientific in nature, we must begin at the right place.

This conceptual approach is therefore quite different from our familiar reductionist, analytic, and mechanistic ways of thinking—ones whose age has come and gone. Moving beyond them won’t be easy, but it can be done.

SYSTEMS THINKING VERSUS “MACHINE AGE” THINKING

In The Fifth Discipline, Peter Senge succintly captures the situation we’re faced with. He states:

From an early age, we’re taught to break apart problems in order to make complex tasks and subjects easier to deal with. But this creates a bigger problem … we lose the ability to see the consequences of our actions, and we lose a sense of connection to a larger whole.

When did this “lesson” take hold in our society? Quite possibly in the Agricultural Age. Many social theorists believe that today’s problems stem from that age, when we found ways to dominate nature and make it subservient to our immediate needs. The Industrial Revolution furthered that dominating mode, as it was a “mechanistic revolution” fueled by the intent to take over and conquer Mother Nature. And it worked—or so we thought.

The mechanistic approach to effecting change is no longer viable, if it ever was. As Russell Ackoff reminds us, “We [have been] attempting to deal with problems generated by a new [systems] age with techniques and tools that we inherit from an old [mechanistic] one.” Ackoff believes these old techniques and tools developed as the Agricultural Age closed and the Machine Age began. In his view, the latter spawned three fundamental concepts: reductionism, analysis, and mechanization. He further believes they now must change if we want to be in step with the Systems Age.

The Fundamental Concepts of the Machine Age

1. Reductionism. This concept’s premise is that if you take anything and start to take it apart, or reduce it to its lowest common denominator, you will ultimately reach indivisible elements. For instance, in reductionism, the cell would be the ultimate component of life.

2. Analysis. A powerful mode of thinking, analysis takes the entity/issue/problem apart, breaking it up into its components. At that point in analysis, you would solve the problem, then aggregate the solutions into an explanation as a whole. Analysis tends to explain things by the behavior of their parts, not the whole!

Even today, analysis is probably the most common technique used in corporations. Managers “cut their problems down to size,” reducing them to a set of solvable components and then assembling them into a solution as a whole. It is still so much the norm that many continue to see analyzing as synonymous with thinking. Instead, synthesis or holistic systems thinking is what’s required.

3. Mechanization. This seeks to explain virtually every phenomenon by resorting to a single relationship: cause and effect. However, mechanization has a key consequence: when we find the cause, we believe we don’t need anything else, so the environment becomes irrelevant. Indeed, the whole effort of scientific study is about relationships that can be studied in isolation and in laboratories—a closed-systems view of the world.

Mechanization colored how we looked the world as a whole. It brought us assembly lines, mass production, countless machines—and the idea that we live in a mechanistic, rather than organic, world. We have gone from thinking of machines as a means for mass production to thinking of the whole world as a machine, not as “Mother Nature,” with a will and a mind of her own.

Appearance and Reality

While the reductionist, analytic, and mechanistic approaches may appear to resolve ongoing problems, they actually fail to provide long-term, permanent solutions. Analytic thinking is perhaps the biggest culprit among them, for it is such a common way of thinking that we’re hardly aware of doing it. Because its central, linear approach is to problem-solve only one issue at a time, other issues must wait their turn, and this alone can cause problems. It’s the inherent deficiency of this thinking mode—something important to remember and be on the alert for.

Simple analytic thinking focuses on cause-and-effect: one cause for every one effect. It asks the all too common either/or question. Its weakest link, and the reason it’s not working in today’s world, is that it doesn’t take into consideration the environment, other systems, and the multiple and/or delayed causality that surrounds each cause and effect. Nor does it consider a part’s interrelationships and interdependencies with other parts.

Analytic thinking, when paired with reductionism, does makes us “micro-smart”—that is, good at thinking through individual projects and elements—but it also makes us “macro-dumb” at planning for the whole portfolio. Here are a few dramatic examples of how analytic thinking has run amuck and led to needless complexity.

•  The U.S. Naval Academy Regulations—Over 1000 pages, as compared to 10 pages when the Academy opened 150 years ago. Both versions cover the same topics, but whereas the earlier one assumes readers can apply common sense, the other spells out each and every probability.

•  Heath Care—Thousands of small, specialized programs, often based on grants created for singular, simplistic problems and solutions

•  Specialized Government Districts—Thousands of unaccountable districts: water districts, assessment districts, school districts, and so forth

•  Federal Intelligence Agencies—We have 16 agencies of the federal government concerned with intelligence. They sound like alphabet soup: CIA, NSA, DIA, NIS, NCS, and so on.

•  Congressional Subcommittees—Too many to enumerate. Every time a new issue comes along, Congress establishes a new subcommittee, to the detriment of good government.

Is it any wonder we feel overwhelmed using the analytic approach to systems problems?

Furthermore, we must consider that the world of systems consists of circular entities (and feedback loops), in which multiple causality is integrally tied to multiple effects in an open and free-flowing environment. Clearly, analytic thinking cannot begin to comprehend, much less manage, the reality of such a world—which just happens to be the real world we live in.

At first glance, systems thinking may appear more complex and multilevel than analytic or reductionist thinking, but once we become familiar with its central concepts and framework, we find it helps us detect the order in complexity and is more accommodating to our understanding of reality. The conceptual linchpin of systems thinking, and of its mindset, is that all systems are circular entities. This concept, which is based on the actual nature of systems, is integral to the input-transformation-output-feedback model that forms the framework for systems thinking and reflects the natural order of life.

Once we get used to the systems thinking mindset, complexities fade away and our perspective is like that of an astronaut, someone taking a higher but no less accurate view of things … seeing the world as it really is, not as people wish it to be or assume it to be because of Machine Age ideas. Through the four elegantly simple concepts described next, anyone can adopt this mindset.

MOVING INTO THE SYSTEMS THINKING MINDSET

As we saw in the Introduction, the systems thinking mindset relies on the four concepts below. All are essential to our understanding of systems and systems change. We’ll look at each one in turn.

1. The Seven Levels of Living (Open) Systems

In his classic book, Living Systems, James G. Miller contributed this key concept of systems levels, which is being used more frequently in today’s organizations. The seven levels form a specific hierarchy of systems:

1. Cell—The basic unit of life

2. Organ—The organic systems within our bodies

3. Organism—Single organisms such as humans, animals, fish, birds

4. Group—Teams, departments, families, and similar bodies composed of members

5. Organization—Firm, company, neighborhood, community, city, private and public organizations, and nonprofit organizations

6. Society—States, provinces, countries, nations, regions within countries

7. Supranational system—Global systems, continents, regions, Earth

Our Focus in This Guidebook. We will be concerned primarily with the living systems at these three levels:

3. Organisms—Individuals

4. Group—Teams and departments

5. Organization—Companies, firms, communities

We will also focus on the intersections of these systems with one another; that is, the “collision” of systems with other systems. Those intersections are expressed as:

3A. One-to-one
4A. Between departments
5A. Organization and its environment

To conduct a systematic large-scale change effort, we must look at all three systems levels and all three collisions of levels. Also, we must be aware that the further we move towards the higher-level systems, the more complex the system will be—and the greater our need for the skills, willingness, and readiness to deal with that complexity. See the learning aid on the following page for a depiction of the six levels as the Six Rings of Focus and Readiness.

Systems Within Systems: Interrelationship. The systems hierarchy illustrates the interrelatedness and interdependence of systems, and the impact that systems have on one another. Thus does the hierarchy validate the concept of “systems within systems”—another key element to applying the lost art of systems thinking.

In viewing our organizations in this way—as levels of systems within, and colliding with, other systems—we align ourselves with the principles of openness, interrelation, and interdependence, and so cement the systems concept. When problem-solving, we look for patterns of behavior and events, rather than at isolated events, and we work on understanding how each pattern relates to the whole. We begin to see how problems are connected to other problems—and are forced to look at solving those problems in a new light. In fact, the solution to any systems problem is usually found at the next highest system (see the Einstein quotation in the learning aid). With this approach we end up with precisely what we need: fully integrated solutions to our systems problems.

2. The Laws of Natural Systems: Standard Systems Dynamics

Standard systems dynamics, found in all living systems, exhibit 12 characteristics, the focus of our discussion here. They have been adapted, with my own comments, from Academy of Management Journal (December, 1972), and organized into four categories as follows:

I.    THE WHOLE

Characteristics:

1.  Holism (Synergism, Organicism, Gestalt)

2.  Open Systems

3.  System Boundaries

4.  Input-Transformation-Output Model

5.  Feedback

II.   THE GOALS

Characteristics:

6.  Multiple Outcomes / Goal-Seeking

7.  Equifinality of Open Systems

III. THE INTERNAL WORKINGS

Characteristics:

8.  Entropy

9.  Hierarchy

10.  Interrelated Parts (Subsystems or Components)

IV. THE LONG-TERM RESULTS

Characteristics:

11.  Dynamic Equilibrium (Steady State)

12.  Internal Elaboration

Although it is important to understand each individual characteristic, keep in mind that it is the relationship between these parts and characteristics, and their fit into one whole system, that is key. Systems dynamics are all about relationships.

I. THE WHOLE

1. Holism (Synergism, Organicism, Gestalt). The whole is not just the sum of its parts; the system itself can be explained only as a totality. Holism is the opposite of elementarism, which views the total as the sum of its individual parts. For instance, we write letters, but our hands cannot write alone, as separate parts; they can only do so as part of our overall human system.

This leads us to the basic definition of a system as a holistic unit that is “the natural way of life.” A system has overall purposes and transformational synergy when it is optimally effective.

Example

Many managers believe a corporate strategic plan is just a “roll-up” of lower-level plans. This is a clear case of elementarism, one that usually results in poor implementation and that perpetuates a lot of turf battles and “silos.” People lack holistic vision and a strategic plan to serve as an overall framework for efficiency and cooperation.

Experienced Dynamics

Instead of holism, we usually see ineffective change that is parts- or activity-focused, leading to suboptimal results.

2. Open Systems. Systems are usually either (1) relatively closed, or (2) relatively open. As we saw earlier, open systems receive inputs from their environment, work with those inputs, and return them to the environment in modified form as outputs; in other words, open systems exchange information, energy, or material with their environment. Biological and social systems are inherently open systems; mechanical systems may be open or closed.

The three keys to success for any system are its ability (1) to be interactive with its environment, (2) to fit that environment, and (3) to be connected to that environment. A crucial task for any system is to scan the environment and then adapt to it.

Example

Excellent organizations are marked by their intense desire to be open to feedback and their constant search for information from their environment that will help them thrive and lead.

Experienced Dynamics

Many organizations and their cultures are relatively closed systems with a low environmental scan—a myopic view in today’s rapidly changing world.

3. Systems Boundaries. When we consider the above, it naturally follows that all systems have boundaries which separate them from their environments. The concept of boundaries furthers our understanding of the distinction between open and closed systems. The relatively closed system has rigid, impenetrable boundaries, whereas the open system has permeable boundaries between itself and a broader suprasystem. Thus an open system can more easily integrate and collaborate with its environment.

Boundaries are no trouble to define in physical and biological systems, but they are quite difficult to delineate in social systems, such as communities and organizations.

This may be why our legislative systems provide so much protection for individual rights, and less for “the common good” of a community.

In organizations, the boundaries are relatively open, which makes them somewhat vague in terms of our knowing and fully understanding their limits. In today’s society, with its worldwide, instantaneous communications, our boundaries are increasingly more open.

Example

To shift from analytic to systems thinking, we must be able to recognize systems and their boundaries; only then can we work with, and hope to change, the system.

Experienced Dynamics

We often see closed boundaries leading to fragmentation, turf battles, separation, and parochialism, when integration and collaboration is what is needed.

4. Input-Transformation-Output Model. The open system can be viewed as a transformation model. Its relationship with its environment is dynamic: it receives various inputs, transforms these inputs in some way, and exports outputs. This is the way natural and living systems operate—and the core systems thinking model and framework that you must internalize if you want to use systems thinking in a practical way. The model can be combined with Feedback (characteristic 5) and the Seven Levels of Systems Thinking (systems concept 1) to create a flow chart showing how systems change and transform over time.

Example

On the most basic level, we must take inputs (e.g., food and water) and transform them into vital nutrients if we are to survive rather than perish.

Experienced Dynamics

Because our piecemeal analytic and reductionist view of the world is so narrow, we often miss outcomes—feedback and environmental considerations.

5. Feedback. This is important to our understanding of how a system maintains a steady state. Information concerning the system’s outputs or process is fed back into the system as an input, perhaps leading to changes in the transformation process to achieve more effective future outputs. Often this informational input helps us get to the root of problems.

Feedback can be either positive or negative. Positive feedback indicates that the steady state of a system is presently effective. Negative feedback indicates that the system is deviating from a prescribed course and should readjust to a new steady state. Some systems-related field, such as cybernetics, are based on negative feedback.

Both forms of feedback stimulate learning and change. It is essential for us to receive and understand feedback, even (and very often especially) when the news is bad and suggests root causes and underlying problems we’d rather not hear about.

Example

The basic concept of the learning organization, as distinct from all the rhetoric surrounding it, directs us toward gathering as much feedback as possible, even negative feedback, so we can act on it to create new learning. Only through feedback can organizations hope to learn and grow at all systems levels— individual, team, and organization.

Experienced Dynamics

We often get very little informational input about our performance or the performance of the organization itself. What we tend to get is financial feedback—only part of the overall picture.

II. THE GOALS

6. Multiple Outcomes/Goal-Seeking. Biological and social systems appear to have multiple goals or purposes. Social organizations set multiple goals, if for no other reason than that their members and subunits have different values and objectives. Goal achievement in today’s multicultural, diverse society is particularly difficult, for we as members of that society bring such an assortment of goals to it.

Since this is a characteristic of all systems, it follows that a common, detailed vision for any organization or society is crucial to coordinated and focused actions by its members.

Example

The clash between individual and organizational goals in present-day organizations causes much conflict and lost productivity for all concerned, ultimately creating lose-lose situations. It has contributed to the dehumanization, delayering, and mechanization of work, alienating many of today’s workers.

Experienced Dynamics

Often, instead of embracing multiple outcomes, we engage in artificial either / or thinking, which leads to conflict rather than cooperation.

7. Equifinality of Open Systems. In mechanistic systems there is a direct cause-and-effect relationship between the initial conditions and the final state. Biological and social systems operate differently. Equifinality suggests that certain results may be achieved with different initial conditions and in different ways. It offers us a basis for the flexibility, agility, and choice needed in today’s dynamic world.

This view suggests that social organizations can accomplish their objectives with diverse inputs and with varying internal activities (processes). For this reason, there is usually not one “best” way to solve most problems; in other words, as the saying goes, there’s more than one way to skin a cat!

Example

Because we lack one “best” way to solve organizational problems, it is crucial for us to be “strategically consistent” to consensual, multiple goals, yet “operationally flexible” (or empowering) in working to achieve those goals. This encourages us to challenge our minds—to employ our mental skills in determining how to achieve goals. And as long as our goals are clear and based on a shared vision, we can succeed at it.

Experienced Dynamics

Too often we ignore the complexity of an issue, insisting upon, and fighting about, the “best way to do things.” We immediately look for a direct, one-to-one, cause-and-effect relationship that would explain the issue; then we try to find a simple, singular solution. But such solutions do not work in a systems world, that is, our world today.

III. THE INTERNAL WORKINGS

8. Entropy. Physical systems are subject to the force of entropy, which increases until eventually the entire system fails. The tendency toward maximum entropy is a movement to disorder, complete lack of resource transformation, and death. For instance, people with anorexia do not consume enough food to maintain their physical bodies; if the disorder continues, they perish.

In a closed system, the change in entropy must always be “positive,” meaning toward death. However, in open biological or social systems, entropy can be arrested and may even be transformed into negative entropy—a process of more complete organization and enhanced ability to transform resources. Why? Because the system imports energy and resources from its environment, leading to renewal. This is why education and learning are so important, as they provide new and stimulating input (termed neg-entropy) that can transform each of us.

“From the time we’re born, we begin to die” is an apt adage here. Our cells completely regenerate every seven years through neg-entropy, and, in a sense, we become completely new persons. Regular follow-up and feedback are key to this needed renewal.

Example

Most change efforts fail because they aren’t given enough follow-up, reinforcement, and new energy. Many managers want to get everything up and running on autopilot, but this is the antithesis of what actually makes change happen. In systems terms, it takes negative entropy—new energy—to make change occur. In fact, most executives are concerned about getting employee “buy-in,” when “stay-in” is even more difficult to get and retain over time (for more on this topic, see Haines, Sustaining High Performance).

Experienced Dynamics

Lack of negative entropy, or new energy, is what leads to obsolescence, rigidity, decline, and (ultimately) death.

9. Hierarchy. A system consists of subsystems (lowerorder systems) and is itself part of a suprasystem (higherorder system). Any living system thus has a hierarchy of components. In today’s politically correct environment, the concept of hierarchy is quite unpopular, but it is a permanent fact of life. The issue is to “flatten” the hierarchy as much as possible—to “go with the flow” of life and what makes sense, in a natural, self-organizing type of way. What we do not want is the imposition of rigid and artificial structures.

Since systems are hierarchical, the organizational system is higher than the department/unit/team as a system, which is higher than the individual employee as a system (whether we’re happy about that or not). If we don’t like the hierarchy or fit, we need to work either to change how the hierarchy operates, or to lessen it; however, it cannot be eliminated, as some would naively propose—it’s simply inherent in systems.

Example

To get an idea of how hierarchies work in the natural world, and how essential they are to it, think about the food chain—an inescapable hierarchy, found in both terrestrial and aquatic environments, and often crossing between them.

Experienced Dynamics

Instead of finding natural, common-sensical hierarchies in our organizations, we often find artificial, rigid hierarchies; they are usually subject to bloated bureaucracies based on the old “command and control,” as if we can ever truly and surely control others.

10. Interrelated Parts (Subsystems or Components). By definition, a system is composed of interrelated parts or elements in some kind of relationship with one another.

This is true for all systems— mechanical, biological, and social. Every system has at least two elements, and these elements are interconnected.

The whole idea of a system is to optimize—not maximize— the fit of its elements in order to maximize the whole. If we merely maximize the elements of systems, we end up suboptimizing the whole (2 plus 2 equals 3—less than it should, and less than we want it to).

To get a handle on this concept, consider what happens to college football players who try to artificially maximize their muscles and weight with steroids: they do serious long-term harm to their bodies, and sometimes the damage is so severe it leads to premature death.

Example

In organizations, it is vital to get all the related subsystems working together toward the achievement of business goals. However, too often departments compete with one another, individually attempting to maximize their influence in the organization, to the detriment of other departments and, ultimately, to that of the organization as a whole.

Balancing the demands of each department is difficult and should be a key role of senior organizational leaders. Unfortunately, this leads to conflict-resolution issues and skills that many leaders in both private and public organizations would rather ignore.

Experienced Dynamics

We often experience artificial and separate silos, parts and components that managers try mightily to protect; but doing so is impossible in a system with natural and related parts.

IV. THE LONG-TERM RESULTS

11. Dynamic Equilibrium (Steady State). The concept of a dynamic equilibrium in “steady state” is closely related to that of negative entropy. A closed system eventually must attain an equilibrium state with maximum entropy: death or disorganization. However, an open system may attain a state whereby the system remains in dynamic equilibrium through the continuous inflow of materials, energy, information, and feedback. This leads to balance and stability. Unfortunately, it also feeds resistance to change, creating “ruts” and habits.

Our tendency to resist change in our lives and in our organizations, and to return to balance through dynamic equilibrium, is normal and natural. However, in today’s rapidly changing environment, if we want the stability we desire, we must become adaptable and flexible to change in a personal way.

Example

Dynamic equilibrium is why culture change in organizations is far more difficult to achieve than isolated change. Culture change requires modifying all aspects of the organization’s internal workings so the whole will enter a new “steady state.”

Experienced Dynamics

Resistance to change often leads to short-term myopic views and actions that lead nowhere.

12. Internal Elaboration. Closed systems move toward entropy and disorganization. In contrast, open systems tend to move toward greater differentiation, elaboration, and detail, and a higher level of organizational sophistication. This may sound good, but it can actually lead to organizational complexity and bureaucracy in its worst form. Complexity must be continuously resisted, for it develops naturally; it is also part of the natural process of ossification, rigidity, and death.

Example

This is why the KISS method and the directives to clarify and simplify are so crucial to success in our lives and organizations. Also, the “elimination of waste,” in total quality management and reengineering terms, is a positive trend toward reversing ossification.

Experienced Dynamics

Organizational growth, with all its complexities, often leads us into confusion or outright chaos; we’re at a loss for ideas that can help us manage such a situation. Systems thinking changes all that.

3. The A-B-C-D Systems Model

Do you usually think in terms of outputs, feedback, inputs, and throughputs, and how they relate to their environment? If not, don’t feel bad—you’re not alone. All of them are phases of the A-B-C-D Systems Model, a conceptual framework that gives systems thinkers an effective way to view systems. Its name is a reflection of our definition of a system:

A set of components that work together for the good of the whole

This point underscores how essential the model is to our adopting the systems thinking mindset.

LEARNING AID

CONCEPT 2. THE LAWS OF NATURAL SYSTEMS: STANDARD SYSTEMS DYNAMICS

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Natural Laws/Desired State vs. Experienced Dynamics

1.	Holism: Overall purpose—focused synergy; transformation	1.	Parts- and activity-focused; suboptimal results
2.	Open Systems: Open to environment	2.	Closed systems; low environmental scan
3.	Boundaries: Integrated; collaborative integrated; collaborative	3.	Fragmented; turf battles; separate; parochial
4.	Input/Output: How natural systems operate	4.	Piecemeal and narrow analytic view of world
5.	Feedback: On effectiveness; on root causes of problems	5.	Low feedback; financial feedback only
6.	Multiple Outcomes: Goals	6.	Artificial either/or thinking
7.	Equifinality: Flexibility and agility	7.	Direct cause-and-effect; one “best” way
8.	Entropy: Follow-up; inputs of energy; renewal	8.	Decline; rigidity; obsolescence; death
9.	Hierarchy: Flatter organization; self-organizing	9.	Hierarchy; bureaucracy; command and control
10.	Interrelated Parts: Relationships; participation	10.	Separate parts, components, entities; silos
11.	Dynamic Equilibrium: Culture; stability and balance	11.	Short-term myopic view; ruts; resistance to change
12.	Internal Elaboration: Details and sophistication	12.	Complexity and confusion

 

FIGURE 1. Conceptual Model

 

Understanding and Using the Model. To comprehend our model (shown in Figure 1), we first must understand that a system is anything but a static entity; rather, it is a living, ongoing process that requires inputs, outputs, and feedback. The activities associated with these requirements constitute the various phases of the process.

In terms of looking at those phases in order to effect change in a system, we must begin where analytic thinking would have us end up—at the output phase. We ask “Where do we want to be?” and then think and work backwards through the system phases to create the desired future state (this is partly why some people refer to systems thinking as “backwards thinking”).

When applied to problem solving, the model focuses us on results (outputs) rather than knee-jerk solutions, and so we work toward better, longer-term answers and solutions. When everyone in an organization knows how to frame issues in this way, discussions about problems (and group problem-solving efforts in general) take on a new dimension—one in which clarity and focus are possible, despite all the complexity. Thus it is important to teach the model to organizational members at all levels.

FIGURE 2. Alternative View of the A-B-C-D Systems Model

Figure 2 further elucidates the systems thinking framework. It details the states that correspond to the A, C, and D phases, particularly that of the Phase D, Throughput. You may find this a handy addition when teaching the model to others.

The Phases of the A-B-C-D Systems Model. Each model phase leads us to a particular question that guides our thinking and problem-solving. It is essential to remember that, in asking any question, we keep in mind a fifth, ongoing question: What is changing in the environment that we need to consider? Now let’s take a closer look.

The Unlimited Uses of the Systems Model. Any set of requirements can be adapted to the model as long as you use the same A-B-C-D locator phases and include the environment. Some of the model’s many organizational applications are included in later chapters; however, as a framework and an orientation to life, the model is applicable to virtually any situation you encounter. Use it in all that you think about, act upon, and evaluate.

LEARNING AID

Concept 3. The A-B-C-D Systems Model

THE SYSTEMS-PHASE QUESTIONS, IN SEQUENCE

A. Where do we want to be? (What are our outcomes, purposes, goals?)

B. How will we know we have reached it? (How will we know we have achieved the outcomes, purposes, goals?)

C. Where are we now? (What are today’s issues and problems?)

D. How do we get from here to our desired place? (How do we close the gap from C to A in a complete, holistic way?)

ALSO: What is changing in the environment that we need to consider? (This is an ongoing question throughout all phases.)

WHY THINKING MATTERS How you think is how you act is how you are.

The way you think creates the results you get. The most powerful way to improve the quality of your results is to improve the way you think.

 

4. Changing Systems: The Natural Cycles of Life and Change

Our natural world does not operate in a linear, sequential fashion, despite all our training and traditional models. Life expresses itself in cycles of change, such as the turn of generations and the seasonal year. Even the bull and bear markets on Wall Street aren’t immune to such cycles. I call this natural rhythm of life the Rollercoaster of Change, a name that takes into account the complexities of change in our dynamic world.

The following are a few historical and natural cycles of change and learning.

The Environment	Civilizations	Historical Ages
•  Ocean tides •  Volcanoes •  Whale & bird migration •  Lunar cycle •  Day & night	•  Inca, Aztec, Mayan empires •  Chinese dynasties •  Roman Empire •  British Empire	•  Hunting & gathering •  Dark Ages •  Agricultural •  Industrial •  Information Age
Industries	Travel	Life
•  Start-Up •  High-Growth •  Maturity •  Decline •  Renewal	•  Automobile •  Ocean liner •  Mass Transit •  Airplanes •  Space shuttle	•  Birth, death, new generation •  Food chain •  Food cycle •  Growth, decline

We as human, living systems keep on changing. It is a natural part of life (and death). Change is constant. The key is finding simplicity on the far side of complexity. The Rollercoaster of Change, presented in the following learning aid, helps us get there. Its many uses will be discussed later, in a variety of tools.

LEARNING AID

Concept 4. Changing Systems:
The Natural Cycles of Life and Change

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“The Rollercoaster of Change”
(The Key to Strategic Change)

MAJOR QUESTIONS	MAJOR USES
•  Not if, but when to go through shock? •  How deep is the trough? •  How long will it take? •  Will we get up the right side and rebuild? •  At what level will we rebuild? •  How many different rollercoasters will we experience? •  Are other changes occurring? •  Will we hang in and persevere? •  How to deal with normal resistance? •  How to create a critical mass for change?	•  Personal transitions •  Employee self-management •  Stages of learning—all types •  Interpersonal relationships •  Coaching sequence •  Dialogue and discovery •  Conflict management •  Situational leadership tasks •  Teams, groups, meetings •  Strategic Planning •  Core strategies (cutting/building) •  Overall management of change