• There is one team member who always seems to be “the problem.”
• You find yourself thinking, “Why are we having this argument again?
• You have a sense of déjà vu when team members say they will do something that you know will never happen.
• You find yourself becoming increasingly passive in the face of the group’s growing inertia.
• No one seems to have the courage or energy to initiate a discussion about obvious process problems.

These are just a few of the symptoms displayed by teams that are trapped in a predictable dynamic of rising interpersonal turmoil and falling productivity.

The vast majority of us have experienced one or more of these, “Team Traps”; that is, vicious cycles of unproductive behavior that undermines group performance. The affected team can be a family system, a small work group, or any kind of business team from an executive-level task force to a product development group. In such situations, team members often feel frustrated and helpless. These feelings can lead people to take drastic actions, such as giving up on the project or even sabotaging it, which further escalates the group’s level of tension and inability to take effective action.

There is no shortage of books on teams or team problems. Yet most of the descriptions of, and proposed solutions to, dysfunctional team behavior focus on the task or event level of team performance. These resources offer little insight into the underlying structure of relationships that is driving the complex human interactions. For instance, much of the literature stresses the need for teams to agree on a charter and to clarify roles that the members will play. However, the same books offer little analysis of the dynamics that may prevent groups from reaching these kinds of agreements. Even books on conflict resolution tend to focus on the “how tos of negotiation” rather than on the emotional dynamics that can undermine the negotiation process.

Because teams are complex systems, any attempt to “fix” them without understanding the structural causes of their problems runs the risk of becoming a “Fix That Fails.” In such a case, the intervention may be unsuccessful or may create unintended consequences that are even more challenging than the original dilemma. This article describes how the application of systems thinking and human systems concepts can yield a robust “picture” of a team’s underlying structure and pattern of interpersonal dynamics. This perspective can help us to effectively predict and correct or better yet, avoid common Team Traps.

Structure in Social Systems

The structure of any complex system is made up of the relationships among its various components. In the case of a business, which is a kind of social system, these elements include flows of people, money, information, and material, as well as employees’ goals, performance, and emotions.

The only effective way to change a team’s behavior is to identify and modify this web of relationships and interconnections. To do so, we can approach surfacing the root causes of a team’s dysfunction the way a physician diagnoses a patient’s illness by analyzing symptoms and drawing conclusions about the underlying disease or condition causing those symptoms. Ina person an individual “human system” the doctor might intervene by prescribing medication to help the body overcome the ailment, recommend dietary changes to eliminate nutritional elements that have negative effects, or recommend new habitssuch as regular exercise to set into motion reinforcing loops for health.

In a social system, the dimension of the human mind adds another layer of complexity. Individuals’ perceptions, assumptions, beliefs, and emotions all play a role in team dynamics by affecting the actions that people take and the results that they achieve. For this reason, no diagnosis of the “disease” plaguing a human system is complete without an understanding of the emotional drivers at work. But in business organizations especially, we often disregard these important factors. Exploring feelings in a work setting can be threatening and frightening to those of us steeped in a work ethic that calls on us to “suck it up” when things go wrong. When a team fails to fulfill its mission, we focus on refining the task or adjusting the team’s make-up, not on surfacing the interpersonal dynamics that disabled the group’s performance. Nevertheless, it is precisely those situations where emotions remain unexplored that devolve into intractable and disheartening team experiences what we call “Team Traps.”

Team Traps: “Archetypes” of Social Systems

In our study of team performance, we have identified 12 common structural dynamics that teams easily fall into and that interfere with a group’s ability to achieve their purpose. Each of these Team Traps tends to stop groups from doing productive work (see, “Team Traps” on p. 1). These dynamics occur often enough to be considered “archetypal”; in some cases, they are variations of the classic systems thinking archetypes. Most dysfunctional teams tend to get mired in two or three of these Team Traps at any given moment.

Individuals’ perceptions, assumptions, beliefs, and emotions all play a role in team dynamics by affecting the actions that people take and the results that they achieve.

The Team Traps were identified and tested based on empirical research over a 30-year period. They have been cross-referenced with other human system models, such as stages of group development and Kantor’s system types, which are explained below. Teams generally fall into these traps while deciding on a common purpose, managing internal and external boundaries, resolving conflicts, making decisions, assigning accountability, and other important process steps. The Team Traps concept highlights how these process issues affect task issues, and vice versa. For example, a team stuck in escalating conflict between two key members either grinds to a halt on its deliverables or develops an elaborate “work-around” that limits the amount of interaction the combatants have, also slowing down the task at hand.

At a moderate level, the symptoms of the Team Trap dynamics include frustration by group members, or frantic but unproductive efforts to achieve the stated goal. At a severe level, teams caught in these traps become disabled; that is, they are no longer able to work together as a group to fulfill their common mission. The long-term effects of these dysfunctional patterns of behavior can prove even more destructive than merely undermining the current project they can corrode or even destroy team members’ confidence and level of trust well into the future.

So, how can we escape from or, even better, avoid, these quagmires? Because each Team Trap involves both task and relationship issues, we have found that using a combination of tools from the fields of systems thinking and human systems can be a potent force for altering these common structures.

Integrating System Dynamics and Human Systems

Although they share a common ancestry, the fields of human systems and system dynamics have remained relatively separate since the 1950s. The major work in human systems has been carried out in anthropology, psychology, and family therapy. System dynamics has its origins in the “hard” sciences of physics, mathematics, biology, and later computer science. The systems thinking movement has begun the process of integrating the two fields through the five-disciplines model introduced by Peter Senge. By analyzing team behavior on a structural level with causal loop diagrams and using human systems tools and concepts to frame and explain those loops, we hope to carry that integration one step further.

Using causal loop diagrams, we can map the interplay of task and emotional processes. For example, in the Inability to Reach Closure Team Trap, as the amount of work the team completes (task) goes down, frustration (emotion) increases (see “Inability to Reach Closure Loop”). As frustration increases, the number of actions that individuals take outside of the team framework (task) grows, which interferes with focused team action (task), and further decreases the amount of work being accomplished. Causal loop diagrams provide a richer understanding of human systems than an event level analysis that focuses only on tasks, and can help us uncover the role that emotional factors play in perpetuating the system.

Causal loop diagrams also provide a testing ground for potential solutions. Using an agreed-upon representation of the dynamics, managers, team-leaders, and facilitators can explore why intuitive solutions don’t work, and test exactly what approaches might be successful and why. For instance, a common reaction to the Unresolved Overt Conflict Team Trap is for one team member to plead with the two adversaries to “be reasonable,” to notice how their behavior is destroying the team’s ability to accomplish anything, and to compromise. Although this intervention may seem appropriate, it seldom works, because it does not address the emotions underpinning the harmful behavior.

Causal loop diagrams let us identify the high-leverage areas for successful intervention. For instance, in our example of Unresolved Overt Conflict, the first step might be to acknowledge the disagreeing parties’ underlying fears which are usually that they are not being heard and try reversing the process that evolved to make them feel disrespected to begin with. Only after each team member feels that the others hear and value his or her perspective and experience can the group resume its original work.

In system dynamics, possible structural interventions include adding a link, breaking a link, and changing a delay. An example of adding a link to a social system like a business would be to create a measurement system to track work completed. Another new link might be to develop a forum for talking about underlying fears that maybe fueling conflict. An example of changing a delay would be to establish periodic status meetings to decrease the gap between actual project progress and perceived project progress. Finally, instituting meeting rules that disallow overt challenges to ideas might constitute breaking a link. The knowledge generated by these kinds of systemic interventions can powerfully advance team learning.

Part of the challenge for intervening in social systems lies in identifying the kinds of structural changes that might be effective. It’s easier to simply react to the situation as an individual than to figure out what is causing the collective team behavior. It’s also much easier to talk about the work to be done than to honestly explore pivotal emotional issues that are holding up progress. As mentioned above, we have found that applying human system tools in tandem with systems thinking tools creates tremendous synergy. The human system approaches provide an additional framework for diagramming social systems and for identifying possible high-leverage actions. Two human system tools by the family systems therapist David Kantor are particularly valuable: The Four-Player Model and System Types.

Four Player Model: Intervening Systemically

In this context, we call Kantor’s Four-Player Model the Four Team Roles (for more detail on this model, see, “Dialogic Leadership” by William N. Isaacs in V10N1). According to this model, every sequence of interactions can be described as the interplay of people filling four roles: Mover, Opposer (or what we call Challenger), Follower (or Supporter), and Bystander (or Mirror). A meeting or conversation begins with an initial action by the Mover. Other people either support or challenge the action, or call attention to the process (Mirror).

This framework is useful for analyzing team behavior, identifying variables in causal loop diagrams, and designing solutions to the Team Traps. How does this work in practice? Let’s look at one particularly disabling Team Trap: False Consensus. False Consensus is characterized by the following list of symptoms:

• People silently nod their heads in support of an initiative even though they don’t really agree with what is happening.
• A lack of discussion results in faulty decisions.
• Controversy is discouraged out of fear of slowing down the process.
• People say one thing but think or do another.
• Team members undermine the decision after the meeting.
• Because participants don’t really “buy in,” they don’t follow through on assigned tasks

In a False Consensus scenario, someone, usually the team leader, wants something to be done to address a problem or exploit an opportunity (R2in “The Dynamics of False Consensus”). Fearing repercussions if they question (Challenge) this action, the rest of the group gives a “head nod” to the leader, resulting in false agreement and consequently poor follow-through.

Because no one actually takes action to implement the leader’s idea, the original problem intensifies, resulting in stronger “moving” by the leader. Notice how the causal loop diagram includes both task and process variables, and how emotion (fear of repercussions) drives the behavior (head-nodding) that ultimately worsens the situation.

The team members’ fear of repercussions and the strength of their conviction that the Mover’s actions are wrong-headed make them angry. These emotions quickly find expression in covert conversations around the water cooler and in the hallways, which legitimize the inaction and lack of productivity (R3). Not only does this behavior exacerbate the original problem, but it also isolates the team leader, again increasing his or her level of frustration and tendency to push for action (what Kantor refers to as a, “Stuck Mover”).

At this point, the entire team feels stressed. Certain individuals may try to solve the problem by approaching the Mover to discuss the situation. However, the longer the issue persists, the more defensive the team leader may feel. This defensiveness can stymie any attempts to initiate a dialogue (R4). Because the team members do not feel that they can overtly challenge the leader, they continue to resist the plan covertly (R5).

THE DYNAMICS OF FALSE CONSENSUS

The Mover wants something to be done. Team members’ fear of repercussions leads them to appear to accept the mandate, but they fail to take action (R2). These fears find expression in covert conversations, which legitimize the inaction and cause the leader to feel defensive (R3). This defensiveness stymies attempts to initiate a dialogue (R4). Because the team members do not feel that they can talk to the leader, they continue to resist the plan(R5). Leverage lies in supporting rather than challenging the Mover.

Supporting the Mover may seem counter intuitive, even for experienced facilitators. In addition, team members may have difficulty forgiving the Mover for his or her heavy handedness in pressing for action. Never the less, we have seen numerous breakthroughs achieved when a team member or an outside facilitator validates a Mover’s motives. After all, the Mover is at least trying to solve the perceived problem or capitalize on the opportunity. Validating his or her intentions makes the Mover feel understood, which lessens the need to push for action.

Validation also opens the door to the possibility of a new solution to the ongoing challenge. It makes the Mover more able to hear others’ perspectives and to consider alternative solutions to the problem. This openness in turn sets the stage for a dialogue about the emotions — such as fear of repercussions that have been fueling the process. In such cases, creating a causal loop diagram and using insights from human systems can lead to a new understanding of both the problem behavior and the structural solution.

System Types: Differing Vulnerabilities

David Kantor and later Larry Constantine have postulated that all human systems fall into four types: Closed, Random, Synchronous, and Open (see “System Types”). Each system type has its own characteristic set of mental models, behaviors, operating rules, and feedback systems. For instance, Closed systems are classically hierarchical, and Random ones are individualistic. Open systems stress collaboration, while Synchronous ones emphasize values and alignment.

Theory and practice indicate that there is no one “best” type of system. Each has its own strengths and vulnerabilities, and each may be especially prone to certain Team Traps. For example, Open systems may try too hard to build consensus and therefore can fall prey to the Inability to Reach Closure Team Trap. The high degree of flexibility and lack of emphasis on leadership shown by Random and Open systems also make them vulnerable to Overt Conflict. With their inherent rigidity, Synchronous and Closed systems may be overly hierarchical and experience a surplus of covert activity. Random and Synchronous systems, with their lack of cohesion, may forget to include customers and stakeholders in their decision-making, or may fail to ensure adequate communication and participation throughout the organization.

Moreover, because of their differences, each system type may require a unique solution to the same problem. For example, accountability issues can be resolved more easily in Closed systems, in which people are already familiar with policies and procedures, than in Random systems, in which members find the concept of evaluation alien. Similarly, Open systems, which value direct communication, can resolve Overt Conflict more quickly than can Synchronous systems, which tend more toward indirect communication.

Knowledge of the Four Team Roles can help facilitators track human interactions on the behavioral level. Causal loop diagrams can analyze the Team Traps on the structural level and provide a testing ground for proposed interventions. The System Types provide additional data on the potential vulnerabilities of the group to certain Team Traps, and the types of interventions that might succeed in that context.

Unspringing Team Traps

SYSTEM TYPES

Addressing the Team Traps concept at the structural level can provide real, lasting solutions to previously intractable problems. An awareness of the most common team disablers, guidance for a structural intervention, and an understanding of the Four Team Roles and the System Types provide a powerful toolbox for teams in trouble. This multifaceted approach to the Team Traps can also help groups learn to work on the system, not merely in it, which is generally the most effective way to improve group dynamics. Perhaps even more important, familiarity with these common traps can help participants and facilitators anticipate a team’s tendency toward one or more of the Team Traps and diffuse negative patterns of behavior before they become entrenched. The highest leverage actions may not always be the easiest to implement, but they are likely to be the most effective over the long run.

The post Taking the Teeth out of Team Traps appeared first on The Systems Thinker.

But no exponential growth process can continue forever. A system that is dominated by reinforcing loops will quickly encounter one or more limits. These limits will eventually cause some balancing loop to become dominant, a process known as shifting dominance. By better understanding reinforcing processes and shifting dominance, practitioners can more easily detect them in their early stages and intervene appropriately before they spiral out of control.

Purpose

Participants engage in this exercise to:

• experience some important physical features of a process that exhibits doubling and exponential growth
• confront the phenomenon of shifting dominance
• practice drawing and interpreting behavior over time graphs and causal loop diagrams.

Context

“Paper Fold” provides a wonderful illustration of the power of reinforcing processes. When we are struggling to help our clients or audience understand the behavior of some reinforcing loop that resides at the heart of a relevant issue, we often find it useful to take five minutes to do this activity. We like this exercise in part because of its simplicity and portability. If presented in the spirit of inquiry, exploration, and playfulness, “Paper Fold” can help participants confront their own misperceptions about causality and exponential growth in a nonthreatening way.

Equipment and Set-up

You need one small cocktail napkin or paper-towel square for each participant. A sheet of regular typing paper is too thin to work well.

If you don’t have enough napkins for everyone, you can hold one up and demonstrate folding it as outlined below. However, having people watch the exercise rather than experience it for themselves may reduce its impact.

Instructions

Instruct the group to do the following: “Take the napkin (or paper-towel square). Fold it in half, fold it in half again, and fold it in half again. Now fold it in half a fourth time. After four folds, it is about 1 cm or a 0.4 inch thick.” Continue, “Of course, you could not fold the napkin in half 29 more times. But if you could, how thick would it be?”

Because the answer to this question is highly counterintuitive, most people will not know it. To stimulate discussion, we suggest a number of different thicknesses and ask participants to raise their hand for the answer that seems most reasonable. For example, we say, “Who thinks it would be less than a foot thick? How about from the floor to the ceiling? How about from here to the top of the building?” Then we share the correct answer: “Folded 29 more times, this napkin would be 3,400 miles thick, the distance from Boston, MA to Frankfurt, Germany.”

Debrief

Most participants consider the correct answer totally preposterous and assume there is a trick to it. In debriefing the exercise, we suggest first demonstrating the math behind the answer. Use slides or a white board to show the dramatic outcome of doubling anything 33 times: 1, 2, 4, 8,16, etc. Doubling something 29 times increases it by a factor of about 540 million. After four folds, the napkin is about 0.4 inches thick. Doubling it 29 more times would produce a thickness of 216 million inches. A mile is about 63,400 inches, so the folded napkin would be a little over 3,400 miles thick.

At this point it is useful to ask people to draw the behavior over time graph for the thickness of the napkin, assuming that they could accomplish one fold every second for 33 seconds.

Depending on the time available, you may want to prepare other examples to further explore this dynamic. Population growth is a dramatic illustration that piques people’s interest. You can say, “We chose to illustrate 33 doublings in this activity for a reason. Today’s global population is almost 33 doublings from the first person on Earth. More than 6 billion people currently live on the planet. In other words, an individual relates to the planet’s population as the thickness of a single sheet of paper relates to the distance from Boston to Frankfurt.”

A traditional French riddle also illustrates the surprising nature of exponential growth: Suppose a water lily is growing on a pond in your backyard. The lily plant doubles in size each day. If the lily were allowed to grow unchecked, it would completely cover the pond in 30 days, choking out all other forms of life in the water. For a long time, the plant seems small, so you decide not to worry about cutting it back until it covers half the pond. How much time will you have to avert disaster, once the lily crosses your threshold for action? The answer is, “One day.” The water lily will cover half the pond on the 29th day, leaving you only 24 hours before it chokes out the life in your pond.

The behavior in all of these instances seems counter-intuitive. We generally expect things to follow linear patterns of growth. Linear growth occurs whenever a factor expands by a constant amount each time period. But positive feedback causes a factor to expand by a constant percentage each time period. In this second case, the change process starts slowly; in folding the napkin, no significant change is noticeable for many doublings. Then, although the underlying growth process hasn’t changed at all, an explosion seems to occur. The 34th doubling would actually add another 3,400 miles to the napkin’s thickness, as much as has accumulated throughout all past history.

To understand this behavior, it is useful to show a causal loop diagram of the underlying loop structure. If you have time, ask participants to work together in small groups to draw the simplest possible diagram that explains the growth in the napkin’s thickness.

Here, R1 is the dominant loop. For a constant folding rate, the greater the thickness of the napkin, the greater the amount added by folding. As the amount added by folding goes up, the thickness of the napkin increases as well.

Variation

If you have time, create two-person teams. One person folds and the other plots the thickness on a simple behavior over time chart, with the number of seconds (assuming one fold per second) on the horizontal axis and the thickness of the napkin on the vertical axis.

Did the groups’ behavior over time graphs look like the figure on p. 5? Obviously not. The teams find that it is impossible to fold the napkin more than seven or eight times. At that point, the thickness stops growing. The exponential growth plateaus once you can no longer fold the napkin What causes this behavior? The answer is: shifting dominance.

Initially, change in the napkin’s thickness is influenced only by the reinforcing loop (R1). At that point, growth in the napkin’s thickness does not produce any palpable increase in its stiffness. But as the thickness increases, the stiffness starts to increase. The resistance to folding grows until no amount of human effort can produce another fold. The balancing loop (B2) has become dominant.

Shifting dominance is an important phenomenon for all managers to comprehend. When it occurs, successful policies that have been learned and refined over time no longer work; they may even become counterproductive. Management lore is full of stories about leaders who mastered one way of attaining success by identifying and pushing on the dominant reinforcing loop governing progress in their firm. But then some limit emerges, perhaps in the market or among competitors. Because the company’s data system probably focuses only on the variables in the loop that used to be dominant, management’s control systems do not even register the change. Performance eventually falters, and management’s response is to push even harder on the policy levers that used to work—to no avail. By the time there is indisputable evidence that new loops are dominant, it may be too late to avoid permanent damage. Understanding the dynamics of shifting dominance can help managers react to changing conditions before it’s too late.

Linda Booth Sweeney is a doctoral student at Harvard’s Graduate School of Education. Her research focuses on systemic innovation practices and the development of systemic thinking skills. Dennis Meadows is director of the Laboratory for Interactive Learning at the University of New Hampshire. He has co-authored eight books that illustrate the use of systems thinking to understand complex social and environmental issues.

The post Paper Fold: An Exercise in Exponential Growth appeared first on The Systems Thinker.

After lunch, you all decide to sketch out a causal loop diagram of the situation. You’ve heard that as one of the basic tools of systems thinking, CLDs can open up new insights into a problem; you’ve also heard that they work best when you state the variable names in certain ways.

Getting Started

But what makes good variable names, and how do you identify them from a gripe session like the one described above? Here are a few guidelines to get you started (also see “Will the Real Variable Name Please Stand Up,” V9N1):

• Use nouns instead of verbs, action terms, or words suggesting a direction of change.

Example: Number of Products Sold NOT Sell Revenue NOT Increasing Profits By using nouns, you let the CLD arrows show the action.

• Use a neutral or positive term whenever possible.

Example: Morale NOT Bad Feelings Job Satisfaction NOT Job Dissatisfaction Such terms help you avoid confusing double-negatives that can happen when reading a CLD. (For example, “job satisfaction declines” is much easier to grasp conceptually than “job dissatisfaction declines.”)

• Identify hard-to-measure variables, such as “Experience Level” or “Trust,” as well as more concrete variables like “Orders” or “New Hires.” Those intangible variables are often just as important—if not more so—than the quantifiable ones.

Once you’ve properly named the key variables in your problem situation, you can start to identify the causal relationships between them and link them in one or more balancing or reinforcing loops.

So, let’s return to your gripe session with Thomas and Marina. As the three of you prepare to identify key variables from the problem situation, you agree to act as the moderator for this part of the process. Your job is to ask questions that will help Thomas and Marina find potential variable names in your earlier conversation. But don’t stop with just the spoken words—sometimes you can detect perfectly good variable names in unspoken signals like facial expressions or tone of voice.

To begin, let’s work our way through the conversation. All the while, we’ll examine the various comments—and any important nonverbal happenings—for promising variable names. Look again at the first statement that was made: “I don’t get it. Why do people keep leaving?” Your question to Thomas and Marina might be: “What specific, neutral noun phrase could convey the meaning in this statement?” Possible answers could include “Customer Service Turnover” or “Number of Customer Service Resignations.” Congratulations—you’ve nailed down your first variable name!

Now let’s look at the second statement from the conversation, made by Marina: “This is getting bad—I don’t see how the rest of us can deal.” If you were to ask Marina, “What do you mean?” she might respond with, “Well, every time someone in customer service leaves, there are fewer of us left to process the incoming phone orders—our workload just gets worse.” Voilá! You can now formulate another variable name: “Workload.”

TURNOVER IN CUSTOMER SERVICE

As customer service representatives resign, the workload increases for the remaining staff. Morale falls, as the reps scramble to keep up with the incoming calls. Eventually, even more people resign, leading to yet bigger workloads and worse morale.

Let’s next take Thomas’s statement: “It’s worse than that—nobody can ask you folks for anything these days without getting their heads bitten off!” “What’s happening here?” you ask Thomas. He replies, “They’re so irritable!” You nudge him to think of a noun, and he comes up with another variable name: “Morale.” As you reflect on the tension that you sensed in Marina, and on Thomas’s observations about short tempers, these nonverbal clues confirm that morale is indeed a key variable.

From Variables to CLDs

Once you’ve properly named the key variables in your problem situation, you can start to identify the causal relationships between them and link them in one or more balancing or reinforcing loops (see “Causal Loop Construction: The Basics,” V7N3). When you have completed the diagram, walk through the loops and “tell the story” to be sure they accurately capture the behavior being described (see “Turnover in Customer Service” on p. 9).

In real life, identifying variable names involves many more iterations than we’ve shown in this case. However, it’s this very act of refining the names that lets you construct a powerful CLD—one that will yield rich insights into the problem and maybe even point the way to a solution. In this case, Marina might share the loop with others in her department. The group could brainstorm possible interventions, such as accelerating the hiring of replacement workers or temporarily reducing the workload by postponing nonessential tasks. Of course, they will want to map out the potential unintended consequences of each of these proposals as well, to make sure the solution doesn’t make the problem worse!

Lauren Keller Johnson is a freelance writer living in Lincoln, Massachusetts.

The post In Search of the Perfect Causal Loop Variable appeared first on The Systems Thinker.

• Are the possible ecological dangers of pesticides worth the potential benefits of increased crop yields and lower disease rates?
• Is an aggressive foreign policy a deterrent to belligerent nations or will it create a more fertile atmosphere for war?
• In a novel, can we analyze the protagonist’s actions from more than one viewpoint?

Connection circles are thinking tools designed to help students understand complexity. Using them as graphic organizers, students generate ideas about changing conditions within a system. They choose the elements they think are most important to the change and draw arrows to trace cause-and-effect relationships. In this way, connection circles help students delve into an issue and manage a number of different ideas at once.

Connection circles are an intermediate step to creating causal loop diagrams (CLD). Students often don’t know where to start in creating a CLD. Connection circles let them generate ideas about elements and connections first. Then, they can unravel the feedback loops that drive the changes in the story.

How They Work

In this article, we demonstrate how to use connection circles to understand a magazine article about the health risks associated with rising french-fry consumption (, “Eyes on the Fries” by Rene Ebersole, Current Science, March 1, 2002).

1. Choose a story. It may be a newspaper or magazine article, a book chapter, or a work of fiction. The more change over time that occurs in the story, the more effective the connection circle will be.

2. Simplify the article. Although connection circles allow students to understand complex articles, vocabulary and content could still be beyond the readers’ range. In addition, a piece of writing may include a level of detail that distracts students from the big ideas and themes. Briefly discuss the central problem in the article.

3. Create teams of four students each. Although this format is not necessary, we have found that collaborative conversations improve students’ thinking. Ask students to read the article— independently, shared orally in groups, or aloud as a class.

4. Give each student a copy of the connection circle template (a circle printed in the middle of a piece of 8 1/2˝ x 11˝ paper) and briefly explain the first step of the “Connection Circle Rules.”

5. As a class, brainstorm two or three elements, and ask students to write them around the outside of their connection circles. Draw a connection circle on the board or overhead to use as a class example (see “Sample Circle”).

SAMPLE CIRCLE

Throughout the lesson, guide the discussion to ensure that students are specific in their language and that they describe either some sort of change or something that can change., “French Fries” figure prominently in the story, but that label is too vague. A more useful label to show the change in quantity might be “French Fries Sold” or “French Fries Eaten.” Similarly, “McDonald’s” is a major topic of the article, but what quantity about McDonald’s might increase or decrease? Phrases such as “Number of McDonald’s Restaurants” and “McDonald’s Profits” might more accurately describe factors in the story that can shift over time.

Also remind students that elements may be tangible, such as “Number of Restaurants,” or intangible, such as “Concerns About Health Risks” or “Desire to Change the Law.” Often intangible elements are key to the changes in the story.

7. Ask volunteers from each team to suggest elements for the sample class circle. Students may add or delete elements from their circles as they hear others’ ideas. Although the class may suggest and discuss many different elements, the final circles should have no more than five to 10 elements.

8. Ask a volunteer to describe a causal connection between two of the elements around his or her connection circle.

• Does an increase or decrease in one of the elements cause an increase or decrease in one of the others? For example, as the number of french fries eaten goes up, it causes the fat consumption to go up as well.
• To represent this statement, draw an arrow from “Number of French Fries Eaten” to “Fat Consumption,” as shown in “Connecting Elements.”

Here are two other possible connections:

• An increase in fat consumption can cause an increase in concerns about health risks.An increase in the number of McDonald’s restaurants will likely cause an increase in french fries sold.

9. Let students work in teams to connect the elements in their connection circles.

• Emphasize that elements are not limited to one connection and that some elements may not have any connections.
• Students should be prepared to state explicitly how and why the connections work. For example, in our sample connection circle, an arrow leads from “Fat Consumption” to “Concerns About Health Risks.” The reasoning is that an increase in fat in a person’s diet causes an increase in susceptibility to higher levels of cholesterol, obesity, and other conditions detrimental to well being.

10. Ask students to search their circles for paths that make a closed loop. In other words, can they begin at one element of the circle, follow connecting arrows to other elements, and end up back at their starting point, as shown in “Closing the Loop.” Students should trace each loop in a different color.

Ask students to draw each closed loop separately and tell the story of that loop. For example, an increase in the number of french fries sold causes an increase in profits. The corporation can then use those profits to open more restaurants. An increase in restaurants causes an increase in french fries sold, and the loop begins again, reinforcing itself each time around.

11. Distribute a blank overhead transparency sheet to each team. Assign one student in each group to draw a feedback loop on the sheet to share with the class.

CONNECTING ELEMENTS

CLOSING THE LOOP

So, an increase in “French Fries Sold” causes an increase in “French Fries Eaten” and, in turn, “Fat Consumption.” Higher fat consumption can lead to a rise in concerns about health. When concerns grow sufficiently, the sale of fries may decrease, as customers try to eat healthier foods. Continuing around the loop again, a decline in “French Fries Sold” means that fewer are eaten and consequently a drop in “Fat Consumption.” A drop in fat consumption decreases “Health Concerns.” With fewer health concerns, over time, “French Fries Sold” might increase, sending the loop around again.

This feedback loop is self-balancing. Tracing around the loop, an initial increase in one element eventually comes back to cause a decrease in that element, balancing back and forth each time around the loop.

12. When the work of each team is displayed, challenge students to discover loops that share a common element. In our sample connection circle, “French Fries Sold” appears in at least two feedback loops. As students talk their way around the loops, they describe the changing behaviors of the elements in the story.

Bringing the Lesson Home

Students like using connection circles to figure things out. The tool may appear complicated at first, but after one class demonstration, students are usually ready and able to use it in a wide range of applications. Here are some questions to help guide the discovery process:

• Which elements have lots of arrows going in and out? Why? An element with lots of arrows in and out tends to be a leverage point in the story. Because of all their connections, key elements create lots of changes. In a connection circle about “Eyes on the Fries,”, “French Fries Sold” might have lots of arrows going in and out because it drives the key issues raised in the article.
• What is the significance of an element that has no arrows pointing to it? When an element has no arrows pointing to it, it is not being changed by any other element represented in the circle. If it is important, the student may need to add another variable that causes the first variable to change.
• What is the significance of an element that has no arrows coming from it? No arrows out means that the element doesn’t influence anything that is currently in the circle. The student may need to add one or more new elements.
• What is the significance of an element with no arrows connected to or from it? No arrows at all means the element is not critical to the part of the story being traced, or other elements have been omitted that need to be included.
• What does it mean when a pathway of arrows leads back to the starting element? When a pathway of arrows loops back to the original element, there is feedback in the story. Each closed loop identified is a feedback loop. When one element in the loop changes, the effect ripples through the whole loop, eventually affecting the original element as well.

  For example, in R1 of “Reinforcing and Balancing Loops,” as the “Number of McDonald’s Restaurants” goes up, “French Fries Sold” also goes up, causing “Profits” to rise. Higher profits tend to increase the number of restaurants being opened, starting the process again. This is a reinforcing loop, commonly known as a vicious or virtuous cycle.

  Another kind of feedback loop is a balancing loop. In contrast to a vicious cycle, a balancing loop does not spiral in the same direction, but rather see-saws back and forth. For example, in B2 of “Reinforcing and Balancing Loops,”, “French Fries Sold” increases “French Fries Eaten,”, “Fat Consumption,” and, ultimately, “Health Concerns.” If health concerns grow strong enough, french fry sales will be driven down.

  Follow the loop around a second time and notice what happens to the elements. When health concerns grow, the number of french fries sold and eaten go down. Fat consumption is reduced, and eventually health concerns should lessen. Over time, with fewer health concerns, people might start to buy more french fries again.

• What happens when elements from the connection circle are in more than one feedback loop? The loops will interact in ways that make the behavior interesting and often quite complex! As demonstrated in the previous paragraph, the sale of french fries creates profits but also creates health concerns. Profits increase the number of restaurants, and more restaurants mean more french fries sold. But health concerns tend to reduce the number of french fries sold. The loops push in different directions, causing tension and complexity in the story.

  The goal of using this tool isn’t to find one specific connection circle that will correctly describe a given topic or article. Rather, the circle is designed to generate ideas and to clarify thinking about complex issues.

  Connection circles help us brainstorm about what is changing and trace webs of relationships within systems to understand those changes. The connection circle examples in this story demonstrate one way to interpret “Eyes on the Fries,” but they are not the only way.

  Teachers and students will be happy that thinking, not memorizing, is the key to learning from this activity. Try creating connection circles and watch your students start paying attention to the shape of change.

REINFORCING AND BALANCING LOOPS

This article is adapted from a chapter in The Shape of Change (Creative Learning Exchange, 2004), by Rob Quaden and Alan Ticotsky, with Debra Lyneis. Illustrations by Nathan Walker. For information about or to purchase the book, go to http://www.clexchange.org/shapeofchange/ or to http://www.pegasuscom.com.

Rob Quaden and Alan Ticotsky are teachers in the Carlisle Public Schools in Carlisle, Massachusetts. Quaden is an eighth-grade algebra teacher and Carlisle’s math curriculum coordinator. Ticotsky is Carlisle’s science curriculum coordinator and a former elementary classroom teacher. Deb Lyneis works at the Creative Learning Exchange, helping teachers publish their system dynamics curriculum material for other teachers to use.

The post Learning About Connection Circles appeared first on The Systems Thinker.