Edward de Bono, author of Lateral Thinking and I Am Right You Are Wrong, likens the patterns in our brains to well-worn grooves. He explains that if we inside pour a teaspoon of hot ink over a plate of JELL-0, the ink will dissolve parts of the gelatin as it flows over the surface and form grooves. Any additional ink is likely to flow into the already-formed grooves and further deepen them. Our brain organizes and groups related pieces of information in the same fashion.

The grooves are not just passive receptacles of new information, however; they are active “channelers” of our perceptions into already-formed patterns. When customer orders fall, for example, that information gets channeled through the “beef up marketing” or “cut prices” groove in our brain. This process serves us well as long as those grooves are relevant for making sense of the situation. It is ineffective, however, in responding to new changes in the environment, since the new information is channeled into the same old pattern. Over time, it can actually lead to patterned blindness — the inability to see anything but the established pictures we already have in our brains.

TQM and the Learning Organization

If our current grooves affect both what we see and how we interpret what we see, how can we ever break out of this circular trap? How can we overcome our patterned blindness?

One way out of old patterns is through theory. Creating a new conceptualization of an issue can open our eyes to different possibilities by allowing us to let go of what we think we already know. Becoming a learning organizaton, for example, means being committed to continually asking the question, “How do we know what we know?”

This requires the ability to see old things in new ways and also to “see” things conceptually that we have not yet seen visually. That is the important role of theory — to see in the mind’s eye what we have yet to experience or know. In that respect, theories are like windows into the unknown.

In the 1980s, TQM offered a new theory that helped cut fresh grooves into our thinking about people, systems, and management. But TQM is only one step in the journey toward becoming a learning organization. Systems thinking is another important discipline that brings additional theories, tools, and methods for building the capabilities of a learning organization. Together, TQM and systems thinking can help organizations see beyond their patterned blindness and work toward building a better understanding of their own organizational capabilities and structures. By becoming theory-builders, managers can help their organizations become creators of their own future.

Patterned Blindness

At the turn of this century, craft producers of automobiles “knew” that costs were constant regardless of volume. Because of the meticulous, labor-intensive process used, the cost of producing the 100th car was more or less the same as for the first one. But mass production, with its economies of scale, dramatically altered the cost-volume relationship. By the 1920s, mass production had virtually wiped out the craft producers.

Likewise, in the early 1980s, the Japanese shattered the cost/quality trade-off myth with high-quality, low-cost products. In the process, they invented a new way of doing business — lean production — that was every bit as radical as the shift from craft to mass production (see “Lean Production: From the Machine Age to the Systems Age,” August 1991). Those who could not adapt shared the fate of the craft producers: in the U.S. and elsewhere, whole industries were nearly decimated (steel, machine tools, motorcycles, video cameras, televisions, memory chips, etc.).

These are not examples of small competitive ups and downs, in which poor decisions led to problems in one or two companies. In these cases, the fundamental basis of competition had shifted, requiring a radical change in perspective that some companies were unable to make. It is not that the new competitors kept the technology from the others; people simply could not recognize the implications of that shift because of the grooves in their brains — patterned blindness.

A clear example of this patterned blindness appears in the book The Machine that Changed the World. A General Motors plant manager (from one of the worst plants in the study) went to Japan to visit one of Toyota’s best assembly plants. After he came back, he was asked what he thought of the plant. He claimed that he was not shown the whole plant; Toyota must have been hiding something. Why? Because the plant was much smaller than his, even though their production capacity was the same. The Toyota plant had significantly less square footage, less working inventory, and no rework area.

He saw the layout of the plant, and yet he could not see beyond the patterned grooves in his brain that told him what a “real” assembly plant looks like. The fact that Toyota did not need a rework area because the cars were driven straight off the assembly line to the shipping dock lay outside this plant manager’s groove.

Problem Solving: Helping or Tampering?

Patterned blindness often operates in a disguised form — problem solving. How many times have we heard, ‘The problem is we need the latest flexible manufacturing system…The problem is we need more patient beds…The problem is we need more sales staff…The problem is…?” These are solution statements masquerading as problem statements, and they are a product of our individual mental grooves.

When our thinking is entrenched in these types of solution responses, we do not bother looking for alternatives because the answer seems so clear. These grooves, in practice, embody our theory of the way the world works. We may think theory is an esoteric term that has no place in practical matters but, in fact, theory affects everything we see, think, and do. As Dr. Edwards Deming once said, “No theory, no learning.” Without theory, we cannot learn, because we cannot make sense out of the jumble of infinite stimuli that we are exposed to at every instant.

One of the ways Deming demonstrated his point about theory was by conducting illustrative experiments. Using a marble, a piece of paper, and a pen, for example, he showed how corrective actions intended to improve performance actually make things worse (see “The Marble Experiment: A Theory in Action”). Intuition says, “If there are deviations, take corrective actions.” Statistical theory counters, “If a system is in control, do nothing.” But in the absence of a clear theory, it is extremely difficult for most people to stand there and do nothing when it seems as if errors are being made.

Statistical Process Control

In the field of Total Quality, statistical theory was translated into a methodology called statistical process control (SPC). SPC provides a set of steps for distinguishing between special and common causes of variation. For example, control charts plotted with upper and lower limits around a target help to identify the boundaries of a system’s capability (see “Special vs. Common Causes”). Anything inside of those boundaries are classified as “common” causes for which no corrective action is necessary. Points outside of those limits are identified as “special” causes, meaning something has happened that is uncharacteristic of that system and needs to be investigated further. Special causes can be addressed by working within the existing system, but the common causes can only be addressed by changing the system itself.

Prior to the arrival of SPC, helpful “adjustments” like those in the marble experiment were actively being carried out in most manufacturing operations. If, for example, you wanted a rod whose length was 30mm ± .1mm and it came out larger or smaller, you naturally adjusted the calibration on the machine. In the absence of statistical theory with which to interpret the data, people would implement solutions (make adjustments) that actually increased the problem (greater deviations) and justified further corrective actions (more adjustments). That is, the solutions themselves guaranteed the need for more of the same solutions in the future.

Working with Multiple Theories

The application of SPC to manufacturing operations has resulted in great success because the theory is well-suited for controlling processes that are governed by physical laws and relationships. But statistics becomes less useful when we venture into the domain of social systems because many of the assumptions about predictability, repeatability, and linearity are not as appropriate. Therefore, as the use of TQM methods has become more widespread, they have been applied to a wider range of settings with decreasing levels of success.

Because social systems do not behave like mechanical and electrical systems, applying theories and tools better suited for the latter is not likely to enhance our understanding of the former. This does not mean that the theory behind TQM methods is wrong; it simply means that we have reached the limits of their usefulness.

All theories have limits that define the boundaries of their relevance. Newtonian physics, for example, was not proven “wrong” when Einstein developed his relativistic view of the world. Einstein’s theory of relativity simply defined the boundaries in which Newtonian physics worked and where it broke down. When you begin to approach the speed of light, Newtonian concepts of time and distance can no longer be treated as constants, but as relative concepts that are very much dependent on the reference frame from which you are making the measurements. For our day-to-day needs, however, Newton’s laws adequately approximate reality.

In some of his more recent writings, Deming acknowledged the limited role of statistics in the larger arena of organizational transformation. He identified three other theories that were important: systems theory, psychology, and theory of knowing. He believed that the set of four were essential for developing what he called “profound knowledge.” In his book The Fifth Discipline, Peter Senge presented five disciplines — shared vision, personal mastery, team learning, mental models, and systems thinking — that embody a range of theories about how to develop the capabilities of a learning organization.

Both Deming’s and Senge’s approaches draw on multiple theories, and both highlight the importance of understanding systems. In fact, systems thinking plays a particularly important role in developing learning organizations because the tools and methods of system dynamics enable you to not only be a user and interpreter of theory, but also an active theory builder. And theory building is essential to building learning organizations.

Feedback Loops a Theory-Building

System dynamics, pinning of systems thinking, allows us to articulate causal interconnections so that we can take high-leverage action instead of being paralyzed by complexity. System dynamics, which is grounded in feedback systems and control theory, provides a set of tools and methods for making sense of complex interconnections — similar to how TQM helps us understand variation through statistical theory. With respect to learning, TQM is particularly strong in operational learning — building greater understanding of how to do things — while systems thinking is relatively strong in conceptual learning — developing richer theories about why things work the way they do.

In the systems thinking toolkit, there are two types of feedback loops we can use to build our own causal theories of organizational behavior — reinforcing and balancing. A reinforcing loop represents a process where a change in one direction is continually amplified in the same direction (see “Anatomy of a Reinforcing Loop,” February 1994). In a balancing loop, a change in one direction produces a response that will try to take the system in the opposite direction. It is basically a control loop (see “Balancing Loop Basics,” p. 7).

Causal Loop Theory Building

With these two basic types of loops, we can construct rich theories about the causal interrelationships that drive our organizational behavior. Causal loop diagrams not only provide a language for representing dynamic structures, but they also provide a way for us to make explicit and share the individual views of the world that govern our actions. By surfacing our individual assumptions about our organizations, we can work toward building a coherent and consistent working theory about our organization and our environment.

Special vs. Common Causes

Special causes lie outside both the upper and lower control limits and are dealt with by working within the curers system. But because common causes lie within the control limits, addressing them requires a change in the system itself.

For example, one theory you may have is that increasing levels of feedback to employees will lead to increased performance over time, which leads to even more feedback (R1 in “Performance-Feedback Theory”). The pattern of behavior suggested by this loop is one of exponential growth. This is a testable theory. Data collection may reveal that performance rises initially, but after a while it plateaus. Someone else may suggest that performance can actually decrease if the quality of feedback is low, and that increasing feedback may actually lead to a decrease in the quality of the feedback (B2). A third person may add that it is not the increasing feedback that leads to lower quality of feedback, but the amount of time expended in giving feedback. As the time expended increases beyond a certain point (indicated by a delay), the quality of feedback suffers.

This example describes the beginnings of a theory about how feedback and performance are linked. Working through this as a team can reveal our collective understanding of what we think is going on in our organization. Causal loop diagrams and systems archetypes therefore provide us with a way to construct our theories; statistical tools can help us test the validity of the causal connections we have identified. In this way, both systems thinking and TQM are essential to the theory-building process.

Cutting New Grooves with Theory

Buckminster Fuller used to say that we start with the universe, and then recognize that any distinctions from then on are entirely arbitrary. In other words, the boundaries that we draw are not a product of nature but of our thoughts. Thus, theory plays a critical role in how we create the conceptual patterns through which we see our world and how susceptible we are to patterned blindness.

If we view the world through our theories (or patterns in our brains) then by becoming active theory builders we can greatly enhance the learning capacity of our organizations. Systems thinking and TQM provide a complementary set of theories and tools for developing an organization’s theory-building capabilities. Our ability to develop new theories will allow us to get out of existing grooves in thinking, to envision a whole different future, and then take the necessary steps toward creating that future. That is the exciting promise and potential of becoming a learning organization.

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Articulating Reality

Causal loop diagrams provide a language for articulating our understanding of the dynamic, interconnected nature of our world. We can think of them as sentences which are constructed by linking together key variables and indicating the causal relationships between them. By stringing together several loops, we can create a coherent story about a particular problem or issue.

The next page includes some suggestions on the mechanics of creating causal loop diagrams. Below are some more general guidelines that should help lead you through the process:

• Theme Selection. Creating causal loop diagrams is not an end unto itself, but part of a process of articulating and communicating deeper insights about complex issues. It is pointless to begin creating a causal loop diagram without having selected a theme or issue that you wish to understand better. “To understand the implications of changing from a technology-driven to a marketing-oriented strategy,” for example, is a better theme than “To better understand our strategic planning process.”
• Time Horizon. It is also helpful to determine an appropriate time horizon for the issue — one long enough to see the dynamics play out. For a change in corporate strategy the time horizon may span several years, while a change in advertising campaigns may be on the order of months.

Time itself should not be included as a causal agent, however. After a heavy rainfall a river level steadily rises overtime, but we would not attribute it to the passage of time. You need to identify what is actual driving the change. In computer chips, $/MIPS million instructions per second) have been decreasing in a straight line over the past decade. It would be incorrect, however, to draw a causal connection between time and $/MIPS. Instead, increasing investments and learning curve effects are likely causal forces.

• Behavior Over Time Charts. Identifying and drawing out the behavior over time of key variables is an important first step toward articulating the current understanding of the system. Drawing out future behavior means taking a risk — the risk of being wrong. The fact is, any projection of the future will be wrong, but by making it explicit, we can test our assumptions and uncover inconsistencies that may otherwise never get surfaced. For example, drawing projections of steady productivity growth while training dollars are shrinking raises the question “If training is not driving our growth, what will?” The behavior over time diagram also points out key variables that should be included in the diagram, such as Training Budget and Productivity. Your diagram should try to capture the structure that will produce the projected behavior.
• Boundary Issue. How do you know when to stop adding to your diagram? If you don’t stay focused on the issue, you may quickly find yourself overwhelmed by the number of connections possible. Remember, you are not trying to draw out the whole system – only what is critical to the theme being addressed. When in doubt about including something, ask “If I were to double or halve this variable, would it have a significant effect on the issue I am mapping?” If not, it probably can be omitted.
• Level of Aggregation. How detailed should the diagram be? Again, the level should be determined by the issue itself. The time horizon also can help determine how detailed the variables need to be. If the time horizon is on the order of weeks (fluctuations on the production line), variables that change slowly over a period of many years may be assumed to be constant(such as building new factories). As a rule of thumb, the variables should not describe specific events (a broken pump); they should represent patterns of behavior (pump breakdowns throughout the plant).
• Significant Delays. Make sure to identify which (if any) links have significant delays relative to the rest of the diagram. Delays are important because they are often the source of imbalances that accumulate in the system. It may help to visualize pressures building up in the system by viewing the delay connection as a relief valve that either opens slowly as pressure builds or opens abruptly when the pressure hits a critical value. An example of this might be a delay between long work hours and burnout: after sustained periods of working 60+ hours per week, a sudden collapse might occur in the form of burnout.
  

  TOOL BOX: GUIDELINES FOR DRAWING CAUSAL LOOP DIAGRAMS

  

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Having worked with a number of new enterprises and groups within large organizations that have achieved success and rapid organizational growth, we have come to believe there is a dark side of success. In years of exposure to these kinds of situations, we have seen patterns that appear independent of the individuals involved, in which accomplishment leads to dysfunction, and accolades give way to frustration and dissatisfaction. If ignored by senior executives and management teams, these patterns can lead to the spiraling decline of the organization. If, on the other hand, leaders anticipate and deal with these dynamics in a timely and disciplined way, they can lead their organizations to sustained success on both a business and a human level.

In his recently published book DEC Is Dead, Long Live DEC: The Lasting Legacy of Digital Equipment Corporation (Berrett-Koehler, 2003), MIT management professor emeritus Ed Schein identifies a number of “invisible” consequences of the rapid growth of DEC in the 1960s–1980s. These insights emerged from his 26 years of consulting with the CEO and senior management team. In cases we have studied, we also recognized some of these same consequences in their early stages.

As organizations grow and disperse geographically, four things tend to happen.

What happens in organizations as part of the growth process that almost inevitably leads to dissatisfaction?

• First, employees lose familiarity with one another, and work relationships become less predictable and more difficult to manage.
• Second, open communication both upward and laterally in the organization becomes more challenging and time-consuming.
• Third, the organization as a whole finds it difficult to achieve strategic focus.
• Finally, anxiety grows among executives and employees alike.

These problems can escalate over time and, left unaddressed, bring even the most vibrant organization to its knees.

So how do you identify and constructively deal with these issues before it’s too late? A recent case study illustrates some of what we believe are generic systemic patterns in rapidly growing organizations that are variations of the “Limits to Growth” systems archetype, as well as potential interventions for managing the challenges of success.

Growing Challenges

A highly successful nonprofit organization had just opened a second office and hired new employees to serve the dramatically increasing customer base. Shortly after, a new president/COO came on board to help the CEO deal with the growing organizational size and complexity.

As the new COO worked toward creating a strategic plan, she became increasingly uneasy. She saw problems regarding:

• The capacity of managers to deal with the challenges of a larger and more complex organization;
• Negative and sometimes hostile attitudes of some senior staff members;
• Executives who used the excuse of not understanding the organization’s goals as a license to do their own thing; and
• The unwillingness of some of the veterans to deal with the process and human implications of growth.

In interviews we conducted with the COO, she told us of her frustration and anger at several members of her management team. She had spent many unproductive hours trying to work with them, to no avail. She had reluctantly reached the conclusion that they were having a negative impact on the rest of the staff as well and would have to go.

At the invitation of the CEO and COO, we began to investigate the situation. We conducted a series of interviews with the senior management team and identified five key issues:

• Lack of clarity and agreement about the meaning of their shared vision;
• Employees’ feelings of being excluded from the team and lack of understanding regarding the needs of the larger organization;
• Competition and turf battles resulting in part from the opening of the second office;
• Lack of clarity and enforcement regarding recent delegation, empowerment, and accountability decisions; and
• Inadequate management training in the skills required to lead a more complex and stratified organization.

What was it that caused all of these issues to surface at about the same time in an apparently well-run and successful organization? A systemic view of the situation, developed by participants in three two-day “Learning Labs” over a six-month timeframe, provided some provocative insights. Participants in the Learning Labs included the CEO, COO, and all senior managers. By working with causal loop diagrams of the dynamics they described, the group was able to identify some leverage points for change and ultimately reverse the negative dynamics that had begun to dominate the organization.

SUCCESS ENGINE PART I

The Engine of Success

Our initial task was to try to understand what had enabled the organizazation’s growth and success in the recent past. Once we clarified the core process the management group viewed as responsible for their earlier accomplishments, we could explore ways for them to redirect their efforts and sustain that success into the future.
In this case, the group identified clarity of goals as having played an essential role in the past. Because of its relatively small size in earlier years, all employees participated in clarifying the organization’s objectives. With clear goals, the organization was able to effectively target its resources toward high-leverage activities. Identifying such focused activities also allowed employees to align all their efforts — from mission through strategy to final results — for consistent outcomes. This alignment ultimately led to high levels of performance. And once people saw the tangible benefits that resulted from having clear goals, they were even more willing to invest time and energy in the process (see “Success Engine Part I”).

With the organization’s rapid growth, communication among business functions became more difficult, and senior managers and employees had come to hold widely varying interpretations of what the goals of the organization actually meant. The management team realized that clarifying goals and getting organizational alignment once again would have a positive impact on employee morale and teamwork.

SUCCESS ENGINE PART II

In addition, with clear goals and a compelling mission, stakeholders, including board members, healthcare providers, and members of third-world governmental agencies, would feel more committed to the effort. Increased support from stakeholders would help to boost employee morale. The team believed that when people feel optimistic about their organization’s prospects, they can more productively engage in teamwork and feel more comfortable engaging in open, honest communication. Candid communication and improved teamwork then permit the deeper dialogue that leads to even greater clarity about shared vision and goals (see “Success Engine Part II”).

The management team came to the conclusion that, by making the mission and goals absolutely clear, consistent, and compelling, they could ensure that each employee knows how their everyday actions contribute to overall organizational success. Workers could also plan their activities with total focus, avoid any projects or activities that do not contribute value, and prioritize the rest based on their level of contribution to organizationwide objectives. Through the causal loop diagrams, the team was able to see how they had created an engine for growth and success in the past, and gained confidence that they could do so again in the future.

THE DARKER SIDE OF GROWTH PART I

The Dark Side of Growth

Having come to an understanding of how their organization could operate effectively, the management team then focused their energies on how the system was currently operating and what was impeding or could impede their progress. They recognized that there is in fact a dark side to growth that comes with success.

As the team discovered, as growth continues, functions and departments become larger in size and more specialized in their activities. Consequently, they tend to become differentiated from each other, and communication between and among them becomes more difficult than when the organization was smaller (see “The Darker Side of Growth Part I”).

THE DARKER SIDE OF GROWTH PART II

As communication and understanding decreases, workers find it more challenging to understand how, why, and by whom decisions are made. Morale begins to decrease; many employees become less engaged than previously; and the organization’s success is imperiled.

In addition, as the decision-making process becomes murkier, the lack of clear shared goals and priorities reduces the level of alignment in the organization and erodes trust. For when we can no longer be sure that we want the same things as our managers or coworkers, how can we have confidence in our ability to work together? Reduced trust further reduces morale, engagement, productivity, and, in the long run, organizational success. As defensiveness and suspicion grow:

• Negativism and provincialism rise, which undermines interdepartmental communication even further and makes organizationwide support for decisions less likely.
• Actions taken to mitigate the negativism and provincialism cause people to focus on why decisions don’t work — the problem — instead of on what we can do together to meet our goals — the solution. Leaders’ efforts to respond to the defensiveness lead to inconsistencies in priorities, and drain time and energy.
• The perceived inconsistencies in priorities reduce alignment among employees, thereby increasing competition for resources and further boosting defensiveness and suspicion (see “The Darker Side of Growth Part II”).

The Emotional Side of the Structure

From our interviews with the management team and conversations during the Learning Labs, we could see some significant emotional reactions that were resulting from the organization’s rapid growth. Levels of anger and defensiveness had begun to rise over time, while some workers’ self-esteem and feelings of belonging had plummeted. This pattern was consistent with our experiences in other organizations.
These problems again seem to stem from the fact that, as growth increases, groups can no longer include everyone in every decision. When people feel excluded, they become defensive and suspect others’ motives. They also begin to doubt their own abilities to contribute, which leads to anger in some and reduced self-esteem in others.

THE DARKER SIDE OF GROWTH PART III

The Outcomes

The development and analysis of the causal loop diagrams through interviews and the Learning Labs resulted in two important conclusions:

• The problems the organization was facing were not unique, but were the result of their very success and rapid growth.
• There were no villains in the story, only people trying to do their best in a systemic structure that generated some unfortunate and at times dysfunctional behavior.

The systems map indicated two key leverage points for immediate action: creating more clarity around the vision and goals, and improving the transparency and understanding of the decision-making process. The management team also identified a longer-term action: to hold “dialogues” on a regular basis to provide a safe mechanism for dealing with the emotional issues that surfaced.

In a rapidly growing organization where there is significant momentum and stress around accomplishing all the tasks associated with that growth, the decision itself to take time for reflection requires courage on the part of leaders.

With some initial reluctance, senior managers agreed to revisit the shared vision and goals to clarify any ambiguities and ensure that they were consistent with each other. They evaluated the outcomes expected from each goal, the metrics by which they could define success, and the method to be used to resolve conflicting priorities that might arise. During this process, inconsistencies and lack of clarity in the meaning of some of the objectives were revealed. The team also came to understand why some staff members responsible for specific goals were not aligned on priorities or action plans. In fact, in one dramatic example, at one point, the CEO confessed, “I guess I fudged that one to make it acceptable to all the board members.”

Once the group agreed on the goals, they worked to create a transparent decision-making process and establish a means for quickly disseminating decisions and their rationale to all employees. The team agreed to delegate decision-making authority to the level as close as possible to the actual work. In fact, instead of specifying what authority they would delegate, members created a “reservation of authorities” document, with a rationale for each decision-making authority that was reserved for senior management only.

The group communicated the results of this effort to all employees. As a whole, the organization launched an initiative to tie department and individual work assignments and performance reviews directly to the organization’s goals. Six months after completion of the project, the CEO and COO reported:

• They had a more cohesive management team.
• The decision-making process is working, and people are no longer complaining about not understanding what decisions were made or why.
• The organization is using performance reviews for each employee and an overall scorecard for senior management that tie directly to the organization’s goals.
• Employees are more aware of and skilled in surfacing mental models and understanding and dealing with different perspectives.</li.
• Teams occasionally slip back into a silo mentality and have not yet fully internalized the systems view, but they are continuing to work on doing so together.

The Issue of Inclusiveness

As we have shared this work with colleagues, we have been struck by the degree to which they report having encountered similar business and emotional dynamics in other organizations. It appears that many of these issues are, in fact, quite generic in situations where there is rapid organizational growth. Usually, senior managers fail to recognize and constructively deal with these patterns. Instead, the “blame game” often seems to prevail, thus precluding people from seeing and addressing situations from a systemic perspective to the detriment, and sometimes the demise, of the organization.

The issue of inclusiveness seems to be at the core of the emotional dynamics that arise in rapid organizational growth situations. People want to be a part of and contribute to their organization. When they feel thwarted, intense feelings and sometimes dysfunctional behaviors arise.

Executives and managers who subscribe to the myth that you can simply grow out of your problems do so at their own peril. As illustrated in the diagram, if organizations do not address these issues, a cycle of dysfunctional thinking, feeling, and acting can escalate and, over time, undermine success.

To avoid this drastic outcome, as happened in this case, senior managers first need to take the time to reflect on and understand the systemic structure in which they are operating. In a rapidly growing organization where there is significant momentum and stress around accomplishing all the tasks associated with that growth, the decision itself to take time for reflection requires courage on the part of leaders. Managing success then involves proactively clarifying and creating alignment around strategic goals, understanding the complexities of their systemic structure, and implementing a clear and transparent decision-making process along with an ongoing infrastructure to allow employees to voice and discuss their concerns. As shown in this case study, such steps can constructively transform an organization and enable continued growth and success.

Jeff Clanon is a founding consultant member and the director of partnership development for the Society for Organizational Learning. The Society (SoL) is a nonprofit, member-governed organization dedicated to building knowledge about fundamental institutional change through integrating research, capacity building, and the practical application of organizational learning theory and methods. SoL evolved from the Center for Organizational Learning at MIT, where Jeff was the executive director for five years. Fred Simon is an independent consultant, a founding member and member of the governing council of SoL, and an adjunct faculty member of the University of Michigan. He worked for Ford Motor Company for 30 years, where he pioneered new approaches to creating leadership at all levels. For more information about SoL, visit www.solonline.org.

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TEAM TIP

When reflecting on why certain systems behave the way they do, we regularly look for patterns of conflict among strategic resources within the organization. Strategic resources are those resources that management knows are important to the survival and long-term health of the organization. This conflict among strategic resources often seems to be due in great measure to what we call the “global to local paradox” of management practices.

Management and operations rarely communicate effectively because they are seeking opposite results from the same organization.

The global to local paradox reflects the impact of the difference in philosophy in various levels of the organization as to what to do with strategic resources. The global perspective refers to management’s goals and incentives, as defined by their role in getting the overall organization to achieve the goals and incentives of its shareholders. The local perspective refers to the goals and incentives that motivate people within the different areas to do what they do every day in performing the work of the organization.

The Paradox

The global to local paradox is the difference between management’s desire to continually grow global output at increasing rates for the shareholders over time versus operation’s need for local stability to maximize asset use, provide predictable returns from investor’s capital, and continually satisfy worker’s personal needs. Some implications of this unintended conflict are clear.

Management and operations rarely communicate effectively because they are seeking opposite results from the same organization. In response to shareholders’ demands, management pushes operations to take advantage of market opportunities and to grow output exponentially. This is what management gets paid to do. Operations strives to address growth within their capacity and cost constraints, mainly by boosting productivity. This is what they get paid to do. In essence, management is paid to focus on bringing tomorrow to reality, and operations is paid to focus on optimizing today’s reality.

Much focus in current management practice is placed on identifying and implementing methodologies for aligning the global and local goals toward satisfying shareholders. If the organization is not achieving its goals, it is assumed that something is not aligned. Since management’s goals and incentives tend to be identified more directly with those of shareholders, then, by definition, what we are really saying is that the local goals are not aligned with the global goal. This assumption leads to the conclusion that local goals need to be modified and shifted in the global, or shareholder, direction.

GLOBAL TO LOCAL PARADOX

In this example of the “Accidental Adversaries” archetypal structure, managements’ focus on growth (the global perspective) unintentionally undermines operations’ ability to optimize performance (the local perspective). The solution is to map out the organizational dynamics to develop a sustainable set of expectations for the firm as a whole.

In response, management places growth and flexibility demands on operations, requiring much faster turnaround times and internal growth rates than the typical productivity gains operations can deliver from optimization efforts. To solve the problem, management searches for additional capacity, internally or externally. Operations, in turn, is subjected to a constant stream of criticism regarding their inability to keep up the pace. This conflict not only stresses the relationship among the individuals in the firm, but also reduces the potential for achieving results — people spend more and more energy defending themselves from attack. We see this pathology in newspapers everyday.

What Is The Systemic Under-standing of This Paradox?

This paradox is an example of the “Accidental Adversaries” archetypal structure. In “Global to Local Paradox,” the virtuous cycle (loop R1) shows management’s focus on growth. As the organization grows, shareholders exert more and more pressure on management for returns, pushing them to find new opportunities. Over time, increasing the return on investment becomes increasingly difficult, as fewer opportunities are large enough to fill the new expectations. The company either must make more, smaller acquisitions or initiate a major transformation.

While management is looking for a steady ramp up in growth over time (loop R2), additions to internal capacity influence the operations area, or local perspective, in step changes. Each new acquisition presents the same challenge to the people doing the work inside the firm: They must determine which elements from the new acquisition stay and which go, and then they must figure out the best way to optimize the new mix. Operations research literature indicates that this constant adoption of new elements in a world that is trying to optimize creates tremendous tension for the folks doing the work on a daily basis.

Moreover, operations is judged on their ability to keep costs down and optimize the existing asset base. However, to truly do their job well, they need a stable environment in which to focus on optimizing the resources under their control. There is a physical limit to what they can get done at any point in time. This local perspective is seen in loop R3, as operations pushes hard on optimization efforts to achieve their goals. The essence of the global to local paradox is shown in the diagram in the variables:, “Growth Expectations by Management” versus “Optimization Efforts” by the operations team.

What Can We Do?

The most challenging issue facing the people living this conflict is that it crosses the strategic and operational interests of the organization. The folks doing the work do not often have all of the information that those running or financing the firm have. They are paid to look at very different pieces of the organization and rely on very different mental models in evaluating what to do next.

So, what can we do to mitigate the effects of the paradox? As with most systemic issues, awareness that the conflict exists is the best place to start. Developing a systemic view of the conflict with a more detailed causal loop diagram or in some cases stock and flow model is fundamental. This causal map facilitates study of the archetypal pattern of behavior and unravels the roots of the underlying behavior this paradox creates. In addition, the causal map invites the organization to investigate the diverse motivations across functional lines in the organization, which create potential internal conflict (see “Breaking Down the Functional Blinders: A Systemic View of the Organizational Map,” The Systems Thinker, Vol. 10, No. 10, p. 6-7).

In some cases, when the group wishes to test the cause-effect relationships in their map, they build a dynamic business simulator. What is critical is to make explicit the linkages among the key resources, expectations, and incentives that each group holds to be important in a way that shows respect and rigor around each view. One way to do so is to involve the entire team in developing the computer model. Engaging shareholders, management, and operations in discussions around the results of the systemic understanding of the causal map is a highly leveraged method for building communication bridges across the paradox.

Practically, there will be issues that the senior management team cannot share explicitly with a broader audience during these sessions, such as the intent to acquire or sell specific assets. Yet the discussion of what effects such actions may have on the ability to achieve stated goals should be included. By understanding what motivates groups at the local level, management can better understand the effectiveness of the incentives they have put in place in generating desired behavior from the different areas of the firm.

In one case, a large capital equipment manufacturer’s sales were rebounding from a cyclical downturn, yet the firm was not generating the expected improvements in profit.

Systems tools expose many fundamental, unquestioned assumptions.

Management thought the marketing group was doing a fantastic job, while the assembly group was letting the firm down through late deliveries and financial penalties. Looking at the dynamics and incentives in detail, it soon became clear that management had set up the conditions for this underperformance to happen. Marketing was being paid based only on orders placed and did not have to worry about the firm’s ability to deliver on time. The marketing director commented “I know how to fix this, but you pay me to accelerate sales, so I will stick to selling as much as I can.”

Though obvious now, by changing the incentive so that marketing was paid based on orders delivered on time, management ensured that the marketing and assembly groups now worked closely together to sell only those units that could be delivered on time. By relinquishing a bit of market share, they were able to maximize profit and invest in additional capacity. Referring to the diagram, changing the marketing incentive released pressure on the “Additional Growth Demand on Operations” variable, slowing down the need for operations to expedite orders. To do so, management had to realign its “Growth Expectations” with the existing internal capacity.

Finally, systems tools expose many fundamental, unquestioned assumptions around the philosophy of “This is the way things are done here.” In working together, shareholders, management, and operations can minimize the effects of the global to local paradox and develop and achieve a sustainable set of expectations and results for the firm.

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Adding thought processes explicitly to causal loop diagrams is one of a series of steps we call Going Deeper. By mapping mental models onto a diagram, we can begin the process of exploring the more subtle aspects of the system.

The Steps of the Process

CASH FLOW AND BORROWING

A young couple facing cash shortages finds themselves forced to borrow from their credit cards (B1). However, the high loan payments on the accumulated debt push them into deeper cash flow problems, forcing them to borrow still more (R2).

Going Deeper begins with a causal loop diagram of a systemic issue. Once the diagram is finished, the first step is to look for the links that represent human choice (as opposed to those that represent hard physical mechanisms). For example, if we have a link that says a change in revenues affects profits, we’re dealing with arithmetic laws. But a link between change in revenues and investments in R&D represents a process that involves quite a bit of human choice.

Once we have selected a link or two that represent human choice, we want to ask ourselves: Why is that choice being made? To explicitly represent the thought process, we add a thought bubble to the link. Like the thought bubbles in cartoons, which represent what the character is thinking but not saying, these thought bubbles represent the intangible thought processes that may or may not be visible to the people involved. When filling in the thought bubble, it is usually helpful to project ourselves into the situation and perhaps even role play it. The thought bubble should capture the line of thinking that makes the actions represented in the loop rational from each individual’s point of view.

Borrowing Example

To see how the process works, let’s look at the story of a young couple, Joan and Bob, who find themselves forced to borrow from their credit cards to get through a sequence of cash shortages. Unfortunately, the high interest and payments on their accumulated debt eventually pushes them into deeper cash flow problems, forcing them to borrow even more to stay afloat.

• Draw the causal loop diagram. In this story, as cash flow problems go up, borrowing goes up. As borrowing increases, the cash flow problems go down (B1 in “Cash Flow and Borrowing”). But over the long term, as borrowing goes up, loan payments go up, and cash flow problems increase (R2). This follows the “Fixes That Fail” storyline.
• Add a thought bubble to the link(s) that represent human choice. In this loop, human choice comes into play in the decision to “solve” the cash flow problem by borrowing, so we want to add the bubble to the arrow between “Cash Flow Problems” and “Borrowing.”
• Presume rationality. To fill in the thought bubble, we want to ask ourselves, “Assuming that these people are acting rationally from their point of view, what is the thinking that leads to the choice to take on extra debt?”
• Suggest several possibilities. Perhaps they might think they just need to get through this tough situation and things will get better afterwards (, “Once we get clear of our school loan debt, things will get easier.”). Or perhaps they feel they have no choice at this point (, “We can’t not pay our bills! We know the borrowing is creating problems, but we’ll have to solve them later.”).
• Project the emotion of the situation into the thought bubble. We might want to add, “What will the neighbors think if our car is repossessed!”
• Capture multiple perspectives. Perhaps Joan expects that their cash problems will get better once she earns her degree and enters the job market, whereas Bob is counting on that promotion the boss promised him “once he proved himself in the company.” By projecting viewpoints from multiple perspectives, we can get a fuller sense of the situation.

The whole purpose of the Going Deeper process is to give visibility to non-obvious reasons why the system is functioning the way it is. If we leap to simple conclusions (, “they should know better than to build up credit card debt”) or blame systemic problems on individuals (, “they’re just not being responsible”), we may miss the larger learning that could come from a deeper analysis, and the ability to take that learning and apply it to other situations.

Software Development

In another setting, a manager in charge of a new release for a well-established software product envisioned a tidy package with some specific functionality. The plan was to develop it within a short time frame, using a small development team. In September, when they began the project, the release was scheduled to ship in March, but it was delayed to July when a few more features seemed necessary. In November, it was delayed again to add even more features. In December, the release was again rescheduled—a full 12 months later than originally planned!

SOFTWARE DEVELOPMENT DELAY

In a software development project where the number of features added to the product extends the development time and the delivery date (R3), we may want to use a thought bubble to explore why a delay results in more features being added.

To capture this story in a loop, we would say the more features, the longer the projected development time, which means the further out the projected delivery date. And it seems like the later projected delivery date is causing even more features to be added. But how is this occurring (R3 in “Software Development Delay”)?

If we want to go deeper into the thought processes involved, we would put a thought bubble between “Projected Delivery Date” and “No. of Features,” so we can explore why features are being added. One possibility may be that marketing thinks that the longer the wait, the higher the customers’ expectations (, “They won’t think it was worth the wait. We’ll look like turkeys!”). From the developers’ perspective, the delay may be seen as an opportunity to experiment and add new features (, “Now I have the time to put in that new XYZ feature I’ve always wanted to design.”).

Sometimes the process of filling in the thought bubbles leads to additional variables that might be included in the diagram. For example, we might hypothesize that the longer the decision remains open, the more bugs are discovered in the current release, and the more opportunities are identified for future improvements (another reinforcing loop). By continuing to dig deeper into the thinking process, we may unearth systemic interconnections that were not obvious upon initial inspection of the problem.

From Understanding to Action

In dealing with complex situations, we want more than just understanding—we want to design effective actions. Examining our mental models and achieving deeper insights can propel a team toward action in a way that doesn’t happen if you stop after drawing a causal loop diagram. By using both the systems thinking and mental model framework to explore a problem, we can more effectively move from superficial understanding to deeper understanding, thereby liberating action.

Richard Karash has been teaching systems thinking and the disciplines of organizational learning since 1991. He was a senior staff member at Innovation Associates, a founding trustee of the Society for Organizational Learning, a founding member of the SoL Coaching Community of Practice, and co-creator of “Coaching from a Systems Perspective.” He teaches in leadership programs, trains professionals, and does executive coaching.

Editorial support provided by Colleen Lannon.

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A Collapsing Stock

It is only within the last fifty years or so—after generations of benefitting from a seemingly inexhaustible supply of fish off the coast of Cape Cod—that regional fisherman have come face to face with the limits described in the

“Tragedy of the Commons” systems archetype (see “The ‘Tragedy of the Commons’ Archetype”). Mid-20th century technological improvements in fishing methods and equipment accelerated fishing efficiencies in a way that completely changed the environment. As Robert Johnson and Jon Sutinen note in their recent report, “One Last Chance: The Economic Case for a New Approach to Fisheries Management in New England,”, “Species that provided a historical foundation for economic growth in New England— Atlantic halibut, cod, flounder, and others—have been fished to decline, biological collapse or commercial extinction.”

In 1976, recognizing the dangers both to fish stocks and to the economy, the federal government passed legislation imposing catch restrictions on this iconic fishery, and on others in the U. S. But, there was a fatal flaw in the government’s initial approach to regulation. In his excellent book, Naked Economics, Charles Wheelan cites a BusinessWeek column by Gary Becker, describing the short-sightedness of regulations pertaining to striped bass fishing on Cape Cod:, “At the time [Becker] was writing, the government had imposed an aggregate quota on the quantity of striped bass that could be harvested every season. Mr. Becker wrote, ‘Unfortunately, this is a very poor way to control fishing because it encourages each fishing boat to catch as much as it can early in the season, before other boats bring in enough fish to reach the aggregate quota that applies to all of them.’ Everybody loses: The fishermen get low prices for their fish when they sell into a glut early in the season; then, after the aggregate quota is reached early in the season, consumers are unable to get any striped bass at all.”

Aggregate limits were scrapped in the mid-1990s in favor of complex controls on individual fishing activities— referred to collectively as “days-at-sea” limits. These were no more successful, as Johnson and Sutinen point out: “When vessels only have a limited number of days-at-sea, it creates a perverse incentive to catch fish as quickly as possible during available days. Responsible fishermen who could otherwise take the time to fish in a safe, profitable and ecologically conscientious manner are induced to put aside these goals in an attempt to catch as many fish as possible in the few days they have available. Fishermen are given little incentive to avoid overfished stocks and target healthier populations; in order to reduce pressure on overfished stocks, effort controls become so restrictive that it is no longer possible to harvest an optimal quantity of the few remaining healthy stocks. The result is inefficient, costly, unsafe and more damaging to the environment. As fish stocks and profits decline, perverse incentives only increase.”

Cooperative Management

But, as the recent promising developments would suggest, the situation is not hopeless, and the most sustainable solution may very well come from the people closest to the problem: the fishermen. The latest evolution in stock regulation in New England focuses on cooperative fishery management, in which groups of fishermen—known as “sectors”—are given a renewable privilege to harvest a specific quantity of fish.

The sector approach offers fishermen flexibility around when and where to fish. By sharing, trading, or consolidating catch privileges among sector members, fishermen can reduce their costs and eliminate the practice of throwing back waste fish that they’ve over caught. With the individual days-at-sea limitations eliminated, they will be able to concentrate on increasing the quality and value of the fish they catch without worrying about lost fishing time.

The new rules may not be perfect; some are concerned about fairness, and enforcement mechanisms will have to be carefully monitored. But, these first steps toward a cooperative, community-based management structure seem to offer evidence that New England fishermen are ready to moderate the collective impact of their individual efforts in the interest of sustaining this irreplaceable resource for everyone— and that government agencies are willing to give those closest to the situation the tools to manage it.

Vicky Schubert is marketing director at Pegasus Communications.

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Causal loop diagrams provide a language for articulating our understanding of the dynamic, interconnected nature of our world.

Articulating Reality

Causal loop diagrams provide a language for articulating our understanding of the dynamic, interconnected nature of our world. We can think of them as sentences that are constructed by linking together key variables and indicating the causal relationships between them. By stringing together several loops, we can create a coherent story about a particular problem or issue.

Following are some more general guidelines that should help lead you through the process:

• Theme selection. Creating causal loop diagrams is not an end unto itself, but part of a process of articulating and communicating deeper insights about complex issues. It is pointless to begin creating a causal loop diagram without having selected a theme or issue that you wish to understand better. “To understand the implications of changing from a technology-driven to a marketing-oriented strategy,” for example, is a better theme than “To better understand our strategic planning process.”
• Time horizon. It is also helpful to determine an appropriate time horizon for the issue—one long enough to see the dynamics play out. For a change in corporate strategy, the time horizon may span several years, while a change in advertising campaigns may be on the order of months.

  Time itself should not be included as a causal agent, however. After a heavy rainfall, a river level steadily rises over time, but we would not attribute it to the passage of time. You need to identify what is actually driving the change. In computer chips, $/MIPS (million instructions per second) decreased in a straight line in the 1990s. It would be incorrect, however, to draw a causal connection between time and $/MIPS. Instead, increasing investments and learning curve effects were likely causal forces.

• Behavior over time charts. Identifying and drawing out the behavior over time of key variables is an important first step toward articulating the current understanding of the system. Drawing out future behavior means taking a risk—the risk of being wrong. The fact is, any projection of the future will be wrong, but by making it explicit, we can test our assumptions and uncover inconsistencies that may otherwise never get surfaced. For example, drawing projections of steady productivity growth while training dollars are shrinking raises the question, “If training is not driving our growth, what will?” The behavior over time diagram also points out key variables that should be included, such as Training Budget and Productivity. Your diagram should try to capture the structure that will produce the projected behavior.
• Boundary issue. How do you know when to stop adding to your diagram? If you don’t stay focused on the issue, you may quickly find yourself overwhelmed by the number of connections possible. Remember, you are not trying to draw out the whole system—only what is critical to the theme being addressed. When in doubt, ask, “If I were to double or halve this variable, would it have a significant effect on the issue I am mapping?” If not, it probably can be omitted.
• Level of aggregation. How detailed should the diagram be? Again, the level should be determined by the issue itself. The time horizon also can help determine how detailed the variables need to be. If the time horizon is on the order of weeks (fluctuations on the production line), variables that change slowly over a period of many years may be assumed to be constant (such as building new factories). As a rule of thumb, the variables should not describe specific events (a broken pump); they should represent patterns of behavior (pump breakdowns throughout the plant).
• Significant delays. Make sure to identify which (if any) links have significant delays relative to the rest of the diagram. Delays are important because they are often the source of imbalances that accumulate in the system. It may help to visualize pressures building up in the system by viewing the delay connection as a relief valve that either opens slowly as pressure builds or opens abruptly when the pressure hits a critical value. An example of this might be a delay between long work hours and burnout: After sustained periods of working 60+ hours per week, a sudden collapse might occur in the form of burnout.

See detailed guidelines for drawing causal loop diagrams.

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The Rebuilding Process

In 1996, Schena was assigned to run Caterpillar’s Brazilian operation, located in the troubled city of Piracicaba. Up until that time, the division’s performance had been less than stellar, and Schena determined to breathe life into the organization by motivating employees to rebuild the business themselves (see R1 in “Limits on Skilled Workers”). This approach and the resulting employee engagement not only helped turn the company around, but in 1999 earned the facility a notable operational excellence certification and the country’s most prestigious quality award. Today, Caterpillar Brazil continues to be number one in the company in terms of financial returns and employee satisfaction.

However, at a certain point, Chris and his management team began to recognize that the state of the larger community could threaten the organization’s ongoing success. The urban area surrounding the factory suffered from high crime and a failing educational system. It soon became clear that the lack of skilled workers could halt the division’s upward trajectory (see B2).

LIMITS ON SKILLED WORKERS

As employees became engaged in rebuilding the division, they created high levels of success (R1). With the rise in success came the need to hire more workers. Because of problems in the surrounding community, management anticipated that, at a certain point, the availability of skilled workers would begin to decline (B2). To overcome this limit, Cat Brazil invested in programs to boost the skills of the local population and make the city appealing to workers from elsewhere.

Overcoming the Limit

To overcome this potential limit, Cat Brazil embarked on worker education and health programs, among other initiatives. In addition, the organization launched a project known as Piracicaba 2010. This effort brought together local officials, entrepreneurs, CEOs, and other community and media leaders to develop a vision and strategy to attract talented people to the city. The goal was to make Piracicaba a model of sustainable development and an excellent place to live.

Caterpillar Brazil offered its resources and strategic planning capability to jump-start the effort, and many employees enthusiastically volunteered their own time toward the effort. Within six months, the initiative was mature enough for the team to hold a town meeting to expand community participation., “By getting citizens to talk to each other regularly in the pursuit of a common goal rather than their own smaller agenda,” says Chris, “the community was able to work together to make the environment more attractive and safer. In fact, now the city not only attracts more professionals but more businesses as well.” A couple of years ago, the Brazilian government selected Piracicaba 2010 as a pilot program for the country to exemplify what needs to be done to regenerate its cities. Since 2002, Brazil’s government has granted funding to run the program, and similar projects have sprung up throughout the country.

Removing Barriers

Sustaining success means more than pushing on an organization’s growth engine; it also involves removing barriers that might impede that growth. As the Caterpillar Brazil story illustrates, the process of removing those hurdles can open up new possibilities both within and beyond the organization’s boundaries, creating an ongoing cycle of growth.

Janice Molloy is managing editor of The Systems Thinker. Kali Saposnick is publications editor at Pegasus Communications.

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Below are summaries of these archetypes, including a description of the structure, the mental model that drives it, and a key strategy for dealing with it.

The “Positive” Archetypes

In 2000, we were testing our systems thinking approach with a group of people when Esther Wilcox Hudson, one of our colleagues, questioned the perspective from which the 10 archetypes operated. Esther noticed that they described a complex system from the perspective of what was not working—a pessimistic or negative focus. She felt that there was an important part of the system that was not being analyzed: the aspects of the system that were working —an optimistic or positive focus. From Esther’s idea, we created a set of 10 positive archetypes that are counterparts to the original archetypes.

Archetypes are not actually negative or positive. The results that these archetypes produce are what you may define as either negative or positive. We use the terms negative and positive because that is what people in organizations are comfortable using. You can think of the negative and positive aspects of the archetypes as if they are two sides of a coin: one side is the positive form of the archetype and the other side is the negative form. Every system is in constant change. The system you are experiencing sometimes manifests its positive nature and sometimes manifests its negative nature.

For example, consider the “Tragedy of the Commons” systems archetype. In this structure, a common resource is being overused or depleted. In an organization, this resource might be the IT department. When people from throughout the company call on IT to drop everything to help them with their computer problems, the IT staff ends up overworked and overstressed. Staff members may begin to leave the organization, making the problem even worse for those who remain.

The flip side of “Tragedy of the Commons” is “Collective Agreement.” In this form of the archetype, people understand what it means to use a common resource. Access to the common resource is regulated in some way, so that all parties benefit and the common resource is sustained.

The 10 positive archetypes and their underlying mental models are described below.

Marilyn Herasymowych, a senior consultant with more than 17 years of experience, is the founder and a managing partner of MHA Institute Inc. (www.mhainstitute.com). For the past 10 years, she has focused on learning in the workplace, consulting with individuals, teams, and organizations in both the public and private sectors. Henry Senko, a manager and senior consultant with more than 20 years of experience, is a managing partner of MHA Institute Inc. His specialty is working with managers and teams to design work processes that incorporate learning as a part of daily work routines.

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