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In a normal meeting we hear none of this, yet such issues are often foremost in everyone’s minds. We might discuss the new advertising campaign, next month’s budget, or the status of a project, but no one knows what is really going on with the others in the room. And by ignoring these undertones, we prevent ourselves from being fully present with each other.

As managers spend more and more time in increasingly unproductive meetings, it is becoming critical that we create environments for more productive conversations. The checking process is a quality tool for good communication that can create such an environment. Although the mechanics are extremely simple and require little time, the check-in process can dramatically increase the effectiveness of any meeting.

The check-in process is an invitation to share what is most present in participants’ minds. Each person is asked to respond to the question, “What’s on your mind right now?”

The purpose of this process is to bring concerns and issues into the open so there are no unspoken thoughts or distractions from the meeting. The check-in is an invitation to be fully present—not just present with the “official story,” but with whatever is on our minds. We are legitimately allowed into the meeting with our whole array of concerns and interests (see “The Check-in Process”). Empathic listening is an integral part of the check-in process.

Empathic listening implies adopting an open, non-judgmental stance toward the speaker and positioning ourselves in his/her situation. It means asking ourselves questions such as, “What is going on with me that encourages me to pay attention to some things and disregard others?” “How is my attitude filtering out thoughts and feelings?” “How is the speaker expressing his or her truth?” “What does this truth reveal about his or her mental models?” “What does my reaction reveal about my mental models?”

Benefits of the Process

Any time we go into a meeting, we approach it with expectations—about what the agenda is, who will say what, how the process will evolve, etc. These expectations bias our listening, so we pay selective attention to what fits our ideas and ignore what doesn’t. If we don’t put a check on this bias, we will end up in a situation where each person talks and listens to his or her own projection of who the other person is. The conversation becomes a hall of mirrors where everybody interacts with their own self-fulfilling expectations.

It is only when we speak from our hearts that we become fuller than the frozen models and presuppositions that others hold about us. It is only when we begin to listen without judgment that we open the door for a deeper understanding and dialogue.

The check-in process opens up that space for understanding and fuller communication by allowing us to bring concerns into the group. Once we acknowledge that something is on our mind, it is much easier to focus on the meeting. When we repress our concerns, we might place them out of sight, but we also place them out of control. When we express our concerns, we can actively choose to let them rest or deal with them openly. That brings our mind fully to the present experience.

For example, in one check-in, one member of the group shared that she was under a lot of stress and felt that her other commitments were more important than the meeting. At the end of the check-in, the group discussed whether it was really necessary for her to participate. Through this conversation, she understood much better why she was there and decided to stay—in spite of the group’s permission for her to leave.

In another check-in, several people said that they did not understand the purpose of the meeting and why they had been invited. At the end of the check-in, the leader explained what he believed was the objective of the meeting and the group discussed whether it made sense to continue. They agreed that there were some critical players missing and decided to postpone the meeting until those members could attend. Afterward, the leader commented that without the check-in process they would probably have wasted three hours in the meeting, without anybody understanding why they were there.

The check-in process can also be helpful for the many people who have trouble speaking in groups. For them, the process provides an opportunity to express themselves. Having their voice heard right from the start reduces any anxiety they might feel and can help them become more comfortable participating in the meeting. As one participant explained, “After you check in, the first time you talk is not really the first time but the second. You’ve already broken the ice.”

Nothing encourages people to share their views more than the knowledge that they will be listened to with empathy. We jump in and out of tasks so frantically that we often have little time left to create the field of appreciation that enables full self-expression. This type of listening can extend beyond the check-in process. Once people begin listening to each other with empathy, they simply can’t go back to their ordinary meeting style. The empathy remains even as they advocate for their views, inquire into other views, and make decisions together.

Once people begin listening to each other with empathy, they simply can’t go back to their ordinary meeting style.

One manager who tried the check-in process was shocked to see some people break down and cry as they spoke. “It’s really sad to realize how much pain and suffering there is in organizations today,” he commented later. “And the saddest thing is that no one has ever asked these people, ‘Tell me about you. Tell me what’s on your mind.’” Pain and suffering are not popular topics, but they are pervasive in corporate life. Dealing with them is a necessary step in the healing process that can lead to the creation of a learning organization.

Check-Out

The meeting is over. You are unhappy with the outcome. Vivian is upset because the meeting ran over; she will not finish her report. Bart can only think about his pregnant wife. Everybody rushes to the next meeting, hoping it won’t be as bad as this one. Later, at the water cooler or after hours over drinks, they speak their minds. In fact, that is where the real issues come out. How can we bring that reflection and processing time into the meeting, where the participants can benefit from it?

The check-out process can improve the quality of meetings by bringing closure. At the end of most meetings everyone rushes out in order to get to their next meeting. Who has the time to reflect on the process? Or to check that there is a common understanding of the situation and that the commitments are clear? Even if the final two minutes in the agenda are reserved for concluding remarks, that time is usually spent on a summary blanket statement. No space is made to include individual perspectives, to reflect on what worked or what didn’t work for each participant, or to know where each person stands. There may be issues needing further consideration, or doubts requiring further inquiry. There may be the need to talk some more.

The check-out process allows each person to say what they want, and be appreciated and celebrated by the group. They might ponder the process, consider the content, ask questions, or even make requests for further conversations.

• • •

The Native American people had a simple rule for their check-ins and check-outs (they called them “council rounds”): be brief, and speak from the heart. How would our business meetings change if we took a little time to bring ourselves fully into them? What if meetings began with everyone’s mind as present as their body? What if they finished with a note of reflection and appreciation for the time shared?

What if, in your next meeting, you shared this article with your colleagues, asked them to take a few seconds to breathe and become aware of their thoughts, and, well, you know how the process goes.

Fred Kofman is an assistant professor of accounting and management at the MIT Sloan School of Management and works at the Organizational Learning Center.

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• • •

The Postal Service has long been plagued by budget deficits and rate increases. In 1990, the year of the last postage increase, Postmaster General Anthony Frank faced soaring labor costs that fueled a growing budget deficit. His solution was to increase automation. When that failed to case the deficit, he pushed through the 29-cent postage stamp.

In 1994, current Postmaster General Marvin T. Runyon is once again faced with a growing deficit, due largely to a payroll that consumes 80% of the budget. His plan: introduce an early retirement package to trim the staff and allow the Post Office to benefit from the previous investments in computerization and automation. However, if history repeats itself, U.S. citizens will again ante up for a first-class rate increase.

The Post Office’s ongoing woes can be characterized as a “Fixes that Fail” situation, in which a problem symptom demands immediate resolution. A quick solution is implemented, which alleviates the symptom in the short term, but the unintended consequences of the “fix” only magnify the problem’s severity in the long term. Over a period of time, the problem symptom returns, often more dramatically than before.

In the Post Office, the problem symptom is a recurring budget deficit. Although the Postal Service is required by law to break even, and usually does for about three years after each rate increase, rising costs—particularly work-force costs–eventually drag it back into the red. Runyon’s suggested fix was an early retirement program he hoped would shave 30,000 employees off of the Post Office payroll and ease the budget deficit (loop B1 in “USPS ‘Fixes That Fail’ “). Although the program was available to all employees who met certain seniority requirements, it was targeted toward supervisors who did not work directly with the mail.

Instead of attracting the targeted audience, approximately half of the 47,000 workers who opted to leave were letter carriers and clerks who were necessary for day-to-day operations. The retirement program thus cost the Post Office essential, experienced workers, who were replaced by workers requiring training and skill development. Overall productivity dropped, necessitating an increase in hours worked, which further exacerbated the deficit problem (R2).

The fallback plan to counter the growing deficit is to raise the price of first-class mail. Instituting rate increases is a strategy that the Post Office has used often, when other cost-cutting measures have failed. However, the increase in revenues from new postage rates may only obscure the need to trim the workforce or to implement more fundamental cost-cutting measures (another short-term “fix”).

USPS “Fixes That Fail”

To combat its deficit, the Post Office instituted an early retirement program to reduce the workforce and payroll (B1). However, many essential workers left, causing less experienced replacements to work longer hours to maintain service standards (R2).

The recent efforts toward workforce reduction may indicate that there is a move in the direction of cost-cutting rather than a complete reliance on rate increases. However, the ability to cut personnel is influenced by the postal unions and their allies in Congress. In addition, if efforts to reduce the workforce and to increase automation fail—and subsequent rate increases outpace inflation—they could continue to drive customers away. Fewer customers mean less revenue to cover the same expenses, leading to another rate hike. This spiral could result in “rates so high that, with-out regulations limiting postal competition, no one would use the USPS” (see “U.S. Postal Service: Are Rate Hikes Paying Off?” Oct. 1990).

If the Post Office is to compete with fax machines, overnight carriers, and specialized courier services, the unions and the Postal Service need to join together to create a more efficient, cost-effective mail system. Creating a vision that all parties can believe in may be a starting point for a better working system. Otherwise, the Post Office could face new problems, in the form of pressure to allow competitors into the first-class mail market.

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We clearly need ways of improving our thought processes, especially in groups where finding a solution depends on people first reaching a common formulation of the problem. Dialogue, a discipline for collective learning and inquiry, can provide a means for developing such shared understanding. Proponents of dialogue claim it can help groups reach higher levels of consciousness, and thus to become more creative and effective. The uninitiated, however, may view dialogue as just one more oversold communication technology.

I believe that in addition to enhancing communication, dialogue holds considerable promise as a problem-formulation and problem-solving philosophy and technology. It is a necessary vehicle for understanding the cultures and subcultures in which we live and work, and organizational learning will ultimately depend upon such cultural understanding. Dialogue thus becomes a central element of any model of organizational transformation.

If dialogue is to become helpful to organizational processes, it must be seen as accessible to everyone. In order to demystify dialogue, therefore, I’d like to focus on the process — how to get started, and how and why dialogue often breaks down — while exploring some of the issues that groups must address if they are to create an effective dialogue process.

We clearly need ways of improving our thought processes, especially in groups where the solution depends on people reaching a common formulation of the problem.

Dialogue vs. Discussion

To understand the different phases of the dialogue process, I have found it helpful to draw a road map based on Bill Isaacs’ basic model (see “Ways of Talking Together,” p. 2). The diagram maps different forms of conversation in terms of two basic paths — dialogue and discussion.

One basic question that all groups must face before entering into dialogue is, “How do we know whether discussion and/or debate is more or less desirable then dialogue? Should we always go down the dialogue path?” I would argue that discussion/debate is a valid problem solving and decision-making process only if one can assume that the group members understand each other well enough to “talk the same language.” Such a state of shared understanding, however, probably cannot be achieved unless some form of dialogue has previously taken place. The danger in premature discussion is that the group may reach “false consensus”: members assume they mean the same thing in using certain terms, but only later discover subtle differences in meaning that have major consequences for action.

Dialogue, on the other hand, is a basic process for building common understanding. By letting go of disagreement, a group gradually builds a shared set of meanings that make much higher levels of mutual understanding and creative thinking possible. As we listen to ourselves and others, we begin to see the subtleties of how each member thinks and expresses meanings. In this process, we do not strive to convince each other, but instead try to build a common experience base that allows us to learn collectively. The more the group achieves such collective understanding, the easier it becomes to reach a decision, and the more likely it is that the decision will be implemented in the way the group meant it to be.

Getting Started

In the groups that I have observed, the facilitator started by arranging the setting and then describing the concept of dialogue. The goal is to give the group enough information to understand dialogue sufficiently to begin the conversation. Next, small group discussion and reflection is used to link dialogue to past experiences of “real communication” (see “Role of the Facilitator: Setting the Context,” p. 3). This introductory session has several objectives which frame the session and allow a more effective dialogue to occur:

• Make the members feel as equal as possible. Having the group sit in a circle neutralizes rank or status differences in the group, and conveys the sense that each person’s unique contribution is of equal value.
• Give everyone a sense of guaranteed “air time” to establish their identity in the group. Asking everyone to comment ensures that all participants will have a turn. In larger groups, not everyone may choose to speak, but each person has the opportunity to do so, and the expectation is that the group will take whatever time is necessary for that to happen.
• Set the task for the group. The group should understand that they have come together to explore the dialogue process and gain some understanding of it, not to make a decision or solve an external problem.
• Legitimize personal experiences. Early in the group’s life, members will primarily be concerned about themselves and their own feelings; hence, legitimizing personal experiences and drawing on these experiences is a good way to begin.

The length and frequency with which the group meets will depend upon the size of the group, the reason for getting together, and the constraints on members. The meetings that I participated in at MIT were generally one-and-a-half to two hours long and occurred at roughly two-to-three-week intervals.

After watching various groups go through a first meeting, I often wondered how the second meeting of each group would get going. I found that the best method was to start by asking everyone to comment on “where they were at” and to go around the circle with the expectation that everyone would speak. Again, what seems to be important is to legitimize “air time” for everyone and to imply tacitly that everyone should make a contribution to starting the meeting, even though the content of that contribution can be virtually anything (see “Check-In, Check-Out: A Tool for ‘Real’ Conversations,” May 1994).

WAYS OF TALKING TOGETHER

The facilitator has a choice about how much theoretical input to provide during a dialogue session. To determine what concepts to introduce when, I have drawn a road map of the dialogue process based on Bill Isaacs’ model, which describes conversation in terms of two basic paths — dialogue and discussion.

Deeper Listening

As a conversation develops in the group, there inevitably comes a point where we sense some form of disconfirmation. Our point is not understood, or we face disagreement, challenge, or attack. At that moment, we usually respond with anxiety and/or anger, though we may be barely aware of it. Our first choice, then, is whether to allow that feeling to surface and trust that it is legitimate.

As we become more aware of these choices, we also become aware of the possibility that the feeling might have been triggered by our perception of what the others in the group did, and that these perceptions could be incorrect. Before we give in to anxiety and/or anger, therefore, we must determine whether we accurately interpreted the data. Were we, in fact, being challenged or attacked?

This moment is critical. As we become more reflective, we begin to realize how much our initial perceptions can be colored by expectations based on our cultural learning and past experiences. We do not always accurately perceive what is “out there.” What we perceive is often based on our needs, expectations, projections, and, most of all, our culturally learned assumptions and categories of thought. Thus the first challenge of really listening to others is to identify the distortions and bias that filter our own cognitive processes. We have to learn to listen to ourselves before we can really understand others. Such internal listening is, of course, especially difficult if one is in the midst of an active, task-oriented discussion. Dialogue, however, opens up the space for such reflection to occur.

Once we realize that our perception itself may not be accurate, we face a second, more fundamental choice — whether actively to explore our perception by asking what the person really meant, explaining ourselves further, or in some other way focusing specifically on the person who produced the disconfirming event. As we have all experienced, choosing to confront the situation immediately can quickly polarize the conversation around a few people and a few issues.

An alternative choice is to “suspend” our feelings to see what more will come up from ourselves and from others. What this means in the group is that when I am upset by what someone else says, I have a genuine choice between (1) voicing my reaction and (2) letting the matter go by suspending my own reaction. Suspending assumptions is particularly difficult if we perceive that our point has been misunderstood or misinterpreted. Nevertheless, I have found repeatedly that if I suspend my assumption, I find that further conversation clarifies the issue and that my own interpretation of what was going on is validated or changed without my having actively to intervene.

When a number of members of the group begin to suspend their own reactions, the group begins to go down the left-hand path toward dialogue. In contrast, when a number of members choose to react by immediately disagreeing, elaborating, questioning, or otherwise focusing on a particular trigger that set them off, the group goes down the path of discussion and eventually gets mired in unproductive debate.

Suspending assumptions allows for reflection, which is very similar to the emphasis in group dynamics training on observing the “here and now.” Bill Isaacs suggests that what we need is proprioception — attention to and living in the moment. Ultimately, dialogue helps us achieve a state in which we know our thoughts at the moment we have them. Whether proprioception is psychologically possible is debatable, but the basic idea is to shorten the internal feedback loop as much as possible. As a result, we can become conscious of how much our thoughts and perceptions are a function of both our past learning and the immediate events that trigger it. This learning is difficult at best, yet it lies at the heart of the ability to enter dialogue.

Group Dynamics

The dynamics of “building the group” occur parallel to the process of conducting the dialogue. Issues of identity, role, influence, group goals, norms of openness and intimacy, and questions of authority all have to be addressed, though much of this occurs implicitly rather than explicitly. The group usually displays all of the classical issues that occur around authority vis-à-vis the facilitator: Will the facilitator tell us what to do? Will we do what we are told? Does the facilitator have the answers and is withholding them, or is he or she exploring along with the rest of us? At what point can we function without the facilitator?

Issues of group growth and development have to be dealt with if they interfere with or confuse the dialogue process. The facilitator should therefore be skilled in group facilitation, so that the issues can be properly sorted into two categories: those that have to do with the development of the dialogue, and those that have to do with the development of the group. In my own experience, the dialogue process speeds up the development of the group and should therefore be the primary driving process in each meeting. A major reason for this acceleration is that dialogue creates psychological safety and thus allows individual and group change to occur, assuming that some motivation to change is already present (see “Containment”).

The group may initially experience dialogue as a detour from or a slowing down of problem solving. But real change does not happen until people feel psychologically safe, and the implicit or explicit norms that are articulated in a dialogue session provide that safety by giving people both a sense of direction and a sense that the dangerous aspects of interaction will be contained. If the group can work on the task or problem using the dialogue format, it should be able to reach a valid level of communication much faster.

Task vs. Process

Once a group experiences dialogue, the process tends to feed on itself. In several cases, I have been in groups that chose to stay in a circle and continue in a dialogue mode even as they tackled concrete tasks with time limits. I would hypothesize, however, that unless a dialogue group is formed specifically for the purpose of learning about itself, it eventually needs some other larger purpose to sustain itself. Continuing to meet in a dialogue format probably does not work once members have mastered the basic skills.The core task or ultimate problem, then, is likely to be the reason the group met in the first place.

Dialogue is, by definition, a process that has meaning only in a group.

The best way to think about dialogue is as a group process that arises initially out of the individual participants’ personal skills or attitudes. Dialogue is, by definition, a process that has meaning only in a group. Several people have to collaborate with each other for dialogue to occur. But this collaboration rests on individual choice, based on a certain attitude toward how to get the most out of a conversation and on certain skills of reflection and suspension. Once the group has gained those attitudes and skills collectively, it is possible to have even highly time-sensitive problem solving meetings in a dialogue format.

Most people have a general sense of what dialogue is about and have experienced versions of it in their past relationships. Therefore, even in a problem-solving meeting, a facilitator may suggest that the group experiment with dialogue. In my own experience, I have found it best to introduce early on in a meeting the idea that there are always assumptions behind our comments and perceptions, and that our problem-solving process will be improved if we get in touch with these assumptions. Consequently, if the conversation turns into too much of a discussion or debate, I can legitimately raise the question of whether or not the disagreement is based on different assumptions, and then explore those assumptions explicitly. Continually focusing the group on the cognitive categories and underlying assumptions of conversation is, from this point of view, the central role of the facilitator.

One of the ultimate tests of the importance of dialogue will be whether or not difficult, conflict-ridden problems can be handled better in groups that have learned to function in a dialogue mode. Because severe conflicts are almost always the result of cultural or subcultural differences, I would assume that initial dialogue in some form will always be necessary. Dialogue cannot force the conflicting groups into the room together, but once they are there, it holds promise for finding the common ground needed to resolve the conflicts.

Edgar H. Schein is Sloan Fellows professor of management emeritus and a senior lecturer at the Sloan School of Management. He chairs the board of the MIT Organizational Learning Center and is the author of numerous books on organization development, such as Process Consultation, Vol. 1 and 2 (Addison-Wesley, 1987, 1988).

This article is edited from “On Dialogue, Culture, and Organizational Learning” by Edgar H. Schein, which appeared in the Autumn 1993 issue of Organizational Dynamics. Reprinted with permission of the publisher, American Management Association, New York, NY. © 1993.All rights reserved.

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Thus begins Ishmael, a compelling exploration of our shared assumptions about the world. Winner of the Turner Tomorrow Fellowship, awarded for fiction that offers creative and positive solutions to global problems, Ishmael is a powerful inquiry into the far-reaching implications of our cultural “story.”

As Ishmael, the teacher, explains to his student, the narrator, “Mother Culture, whose voice has been in your ear since the day of your birth, has given you an explanation of how things came to be this way. You know it well; everyone in your culture knows it well…. As we make our journey here, we’re going to be reexamining key pieces of that mosaic…. And when we’re finished, you’ll have an entirely new perception of the world and of all that’s happened here.” As you read through Ishmael, you take part in that same journey, participating in a conversation between a man and a gorilla that may profoundly change the way you view the world.

From Events to Interrelationships

A pragmatic view of systems thinking is that it is a body of tools and methodology for solving difficult, highly interdependent problems. But ultimately it is about expanding our worldview.

Recently, the historian Tom Berry asked, “By improving our organizations, are we simply making them better at destroying the earth or such questions cannot be ignored if one truly takes a systemic perspective, yet they are profoundly challenging because they cause us to inquire into deeply held cultural assumptions. The book Ishmael speaks to this deeper purpose.

I believe that the larger environmental crisis that threatens us cannot be averted without profound changes in the predominant patterns of thinking and interacting within our institutions. This shift in orientation—from objects and events to interrelationships—must infiltrate broadly and deeply if it is to start to have a real cultural impact. Ishmael is one way to begin that shift.

The latest Chapter in an Ongoing Story

The late physicist David Bohm, a leading thinker about dialogue, believed that human beings began to lose their capacity for thinking together long ago. He believed that the progressive fragmentation of the social order that started with the agricultural revolution has led to a progressive fragmentation of thought, which has increasingly characterized the last 10,000 years of human civilization.

Strikingly, Ishmael takes the same perspective: “So you see that your agricultural revolution is not an event like the Trojan War, isolated in the distant past and without direct relevance to your lives today. The work begun by those Neolithic farmers in the Near East has been carried forward from one generation to the next without a single break, right into the present moment. It’s the foundation of your vast civilization today in exactly the same way that it was the foundation of the first farming village.”

According to Ishmael, our current social problems stem from our disconnection from nature that began with the agricultural revolution—the belief that our job is to dominate nature and make it subservient to our will. Over the past 100 years, the consequences of that belief have become increasingly severe as we have developed the power to implement this perspective on a global scale. Beyond the obvious impact on the global environment, we now have the ability to alter the genetic code. As Ishmael points out, we human beings are the first species in the history of evolution on this planet that systematically destroy other species. In essence, we are toying with the basics of the evolutionary process.

Underlying these actions is a belief that evolution ended with the appearance of humans. Instead of acknowledging that we are just the latest chapter in an ongoing story, we humans think the story ended with us. This assumption has set us, in our minds, outside of the evolutionary process. We are literally “outlaws,” living outside the laws of nature. This attitude has dire consequences: by pretending that evolution doesn’t exist for us, we are actually taking actions that may make it true. Evolution may indeed end with us, or at least the evolution of our species.

Cultural Inquiry

The gorilla, Ishmael, begins his teaching by asking the question, “On the basis of my [personal] history, what subject would you say I was best qualified to teach?” When the narrator is unable to answer, Ishmael responds, “Of course you do. My subject is ‘captivity.’ ”

Although he was captured and sold to a zoo as a young gorilla, Ishmael does not seek to teach about the captivity behind bars, but one of a more subtle and far-reaching nature. “Among the people of your culture, which want to destroy the world?” he asks. The narrator responds, “As far as I know, no one specifically wants to destroy the world.”

“And yet,” Ishmael continues, “you do destroy, each of you. Each of you contributes daily to the destruction of the world. Why don’t you stop?”

The narrator shrugs. “Frankly, we don’t know how.”

“You arc captives of a civilizational system that more or less compels you to go on destroying the world in order to live.”

Herein commences a process of deep cultural inquiry between Ishmael and the narrator. This inquiry is not into corporate culture or Western versus Eastern culture, but an exploration into our prevailing industrial culture (which is increasingly becoming the global culture) and how it differs from the traditional cultures of pre-industrial and pre-agricultural societies. The simple goal of this inquiry: to become aware of the nature of our continuity. As the narrator gradually realizes, what prevents us from freeing ourselves is, first and foremost, not realizing that we are prisoners of our own beliefs of the “story” we have been telling ourselves throughout history. What keeps us imprisoned is that we’re “unable to find the bars of the cage.”

As Ishmael explains, “Two fundamentally different stories have been enacted here during the lifetime of man. One began to be enacted here some two or three million years ago by the people we’ve agreed to call Leavers and is still being enacted by them today, as successfully as ever. The other began to be enacted here some ten or twelve thousand years ago by the people we’ve agreed to call Takers, and is apparently about to end in catastrophe.”

It is very difficult for people to inquire into their own culture. Culture, by definition, is what we see through, not what we see. Because we do not perceive our culture, it is extraordinarily difficult to sustain an inquiry into our shared cultural assumptions. Certainly it would be difficult for two members of industrial society to explore the deepest assumptions of their culture, for they share those assumptions. In many ways, such a conversation requires another perspective that differs radically from our own.

Ishmael, the gorilla, represents the entirety of what humankind is trying to control. By making man the student and Ishmael the teacher, Quinn reverses the relationship of dominance that has characterized our approach to nature. In addition, by asking us to suspend our disbelief that a man can talk to a gorilla, the author is, in some sense, metaphorically challenging our belief that we are separate from other species.

In this way, Ishmael is a striking illustration of what I believe real dialogue is about. We often think of dialogue as a group of people sitting in a circle, but in fact the root diet logos simply refers to a deep inquiry that opens up a new flow of meaning. In that sense, dialogue can occur within an individual, in a group of a thousand people, or in any setting where there is a deep movement.

The method of inquiry that Ishmael uses for his student are like Zen koans—puzzles that cannot be resolved by our normal ways of thinking and require a totally different framework. “What is our culture’s creation myth? What is the meaning of our world?” These are the types of questions that the student in Ishmael struggles to answer. Because of this structure, the reader can jump in at almost any point and get a sense of the nature of that inquiry. I carry a copy of Ishmael with me, and often just pick it up and start reading on any page. Within 10 or 15 minutes, I’m back into that flow of inquiry.

Strutter and Meaning

In evaluating a book, we tend to judge content and process as if they are separable. Such an assumption is, however, part of the deep fragmentation that pervades our culture. Literature is not just about presenting compelling ideas. In a great book, the method of exposition is as compelling as the ideas themselves. The power of Ishmael is that its method, process, and content are so tightly integrated. The very premise of the book engages people at a level beyond any mere exposition of its central issues.

For this reason, I believe Ishmael may indeed contribute to the very type of cultural change Quinn believes is necessary. By opening us to a whole different type of dialogue about our culture, it may create an opening in that culture.

Ishmael raises a central paradox about culture: no individual by herself or himself can change culture, yet culture can’t change without individual changes. I don’t know of any other book that stimulates us to think in such new, different, and much clearer ways about our cultural dysfunction as does Ishmael. This is a book that appeals to each of us as individuals, and challenges us to begin making the individual changes necessary to create a collective cultural transformation.

Peter M. Senge is the director of the MIT Organizational Learning Center and author of The Fifth Discipline: The Art and Practice of the Learning Organization.

Daniel Quinn, the author of Ishmael, will be a keynote speaker at the 1994 Systems Thinking in Action Conference in November. Ishmael is available through Pegasus Communications, Inc. (617) 576-1231. Editorial support for this article was provided by Colleen LannonKim.

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Now you are wondering what the behavioral consequences of this strategy might be. Although the loop provides a general description of the staffing process, it gives no indication of how this strategy actually plays out over time. You know there are significant time delays involved in the process: the time it takes to recognize the gap, act on it, and hire or lay off staff. You wonder if there will be a smooth transition to the desired level, or if there will be large jumps in staffing numbers.

Here is where the computer model comes in. In the world of archetypes and causal loop diagrams, all of the elements of a system are defined without quantifying any numerical values, so you can only speculate about what behavior the system will produce. On a computer, however, you must quantify your assumptions about how elements are interrelated, which prompts deeper inquiry. Computer models also provide a way to test your hypotheses before acting on them.

But how do you get from archetypes and causal loop diagrams to computer models? The following steps provide a process for converting a causal loop diagram into a structural diagram as preparation for creating a computer model.

1. Identify the Behavior of the System

One of the questions beginning modelers often ask is, “How will I know if my computer model accurately represents the loops I’ve identified and the story I’m trying to tell?” Sketching the behavior of the system up front can help answer that question because it provides a reference point for gauging how well the model matches the expected behavior of the system. Past trends can be very useful at this stage.

In the employee staffing example, if the actual number of employees is less than the desired level, we will begin to hire employees to increase the numbers to be more in line with the desired level. Chances are, the number of employees won’t increase steadily until it reaches the target number. Instead, we will probably overshoot and oscillate around the target as our employee numbers fluctuate over time (see “Staffing over Time”). This diagram of the behavior we expect in the system should at least qualitatively match the output we get from our computer model later on.

2. Identify the Accumulators

When converting a causal loop diagram into a structural diagram, we begin by identifying the major elements — the accumulators and flows. In general, each loop in a causal loop diagram contains at least one accumulator — a stock of something that accumulates over time, like inventory, people, money, etc.

Staffing Policy

Employee staffing can be described by a simple balancing loop that says if there is a gap between current staff and desired staff, actions are taken (hiring or layoffs) to bring the anent level in line with the desired (B1).

A key characteristic of accumulators is that they are not a function of time. Therefore, a good way to identify the accumulators in a diagram is to use the “Freeze Test”: if we froze the system, what would be the things we could count? In the staffing example, we would be able to count the number of employees in the building, the current staff. In our structural diagram, we would represent this by creating an accumulator called “Current Staff.”

3. Identify Flows

Next, we want to identify the flows. Flows are like taps on a faucet, controlling the stream of contents into or out of the accumulator. To find the flows in our diagram, we would ask how the accumulation of staff changes. What causes the current staff number to go up or down? The number of people being hired or laid off. We can represent that relationship by drawing the flow between “Hiring or Layoffs” and “Current Staff” (see “Drawing a Structural Diagram”). Another good rule of thumb for identifying flows is to look for those things that are dependent on time.

4. Identify Other Relationships

Staffing over Time

Time Drawing the behavior of the system up front provides a reference point to gauge how well the model matches the behavior you expect from the system.

To complete our diagram, we need to characterize the other significant relationships in the system. If we know that hiring and layoffs affect current staff, our next question might be, “What drives hiring and layoffs?” The answer would be the staffing gap. “Staffing Gap” is not an accumulator, because it cannot be physically counted if we freeze the system, nor is it a flow, because it is not dependent on time. The best way to describe the “Staffing Gap” is that it is simply a mathematical relationship between current and desired staff (“Current Staff’ minus “Desired Staff’ equals “Staffing Gap”). Such mathematical relationships are called “auxiliaries” because they help define the relationship between different parts of the diagram. We can show both “Staffing Gap” and “Desired Staff’ as auxiliaries by drawing circles with arrows linking them. We also want to show that our “Staffing Gap” is dependent on the current staff, so we draw an arrow from “Current Staff” to “Staffing Gap.”

Drawing a Structural Diagram

Causal loop diagrams and archetypes usually do not contain enough specificity about the relationships between the variables to create a computer model. By drawing a structural diagram of the system, we can identify the different types of variables in the system and how they affect each other.

S. Double Check that the Diagram Matches the Story

Once we have completed the structural diagram, we want to double check to make sure that it retains the same story as the causal loop diagram or archetype. If we walk through our diagram, we can see that it looks similar to the balancing loop, except that we have identified the different types of variables (i.e. accumulators and flows) in the system.

We may find that our structural diagram has more elements than our causal loop diagram. That is to be expected, because as we get more specific about the way the variables interact, we may need to add additional elements to further define those relationships. For example, we could have added “Retirement” or ‘Turnover” to be more explicit about how other flows affect current staffing.

6. Establish the Boundary of the Model

Before we move from the structural diagram into building the model, it is important to establish the boundary of the system we will be modeling. Otherwise, the temptation will continually be to expand the model, as we discover more and more factors that affect the system.

The term “Desired Staff,” for example, could be considered a dynamic rather than static variable. If we were to expand our model to include factors that determine the desired staff, we might add additional links to the company’s financial health, expansion plans, etc. However, we are focusing our model just on the factors that directly influence current staffing in order to understand how changes in desired staff impact our current staff. Within the boundaries of the problem we are studying, therefore, we can treat “Desired Staff’ as fixed. Later, when we simulate, we can explore how varying the “Desired Staff” affects the overall behavior.

Now that we have created structural diagrams from our causal loops, the next step is to bring the structure to life. For a discussion of the steps in this process, see next issue’s “Toolbox.”

The example and diagrams used in this article were taken from “Moving Into Computer Modeling” by Michael Goodman, which appears in the upcoming Fifth Discipline Fieldbook (Doubleday: forthcoming July 1994) .

Michael Goodman is vice president of Innovation Associates (Framingham, MA) and a frequent contributor to The Systems Thinker. He has been involved in the field as an educator and consultant for over 20 years.

Editorial support for this article was provided by Colleen Lannon-Kim.

The post From Causal Loop Diagrams to Computer Models–Part I appeared first on The Systems Thinker.

This shift in research priorities is at the heart of the most massive change in U.S. science since World War II, according to a recent Business Week article (“Could America Afford the Transistor Today?” March 7, 1994). Not only did corporations cut long-term research funding by 15% in the late ’80s, but now the United States’ 2.5 million scientists are being pressured to focus more on short-term goals.

The U.S. government is also placing constraints on the $76 billion of research it funds annually, as it increases spending on “commercially important” technologies. For example, Congress recently ordered that 60% of the National Science Foundation’s $2 billion research budget must be spent on technology, products, and jobs that are relevant to national needs.

Scientists argue that these changes in the focus of R&D are leaving two particular gaps in U.S. research: ground-floor research, which includes “undirected” research and the generation of new ideas; and “mezzanine” research, which involves developing prototypes from promising ideas and is therefore high-cost and high-risk.

Some critics of the cuts in research believe such actions will reduce the stream of new ideas and products, and therefore may adversely affect U.S. competitiveness in the future. As inventor Jerry Woodall, who helped create ultrafast light detectors for the Information Superhighway, told Business Week, “If nobody supports blue-sky research, 10 years from now we won’t have things like my new devices.”

Woodall has a point. The progression of research from initial discoveries to useful products resembles an aging chain with inherent time delays that can span decades. The analogy is like a garden hose: if you shut off the spigot, water will continue to pour out of the hose for a while. The water will slowly reduce to a trickle, however, and eventually nothing will come out at all.

Therefore, the effect of funding cuts at the beginning of the chain may not show up for years. An accumulator and flow diagram of the R&D process illustrates the delays: the different types of knowledge (basic, applied, and development) are represented by the accumulators, while usable ideas flow through the chain as the research progresses over time (see “R&D Knowledge Accumulation”). Although such a diagram may appear overly simplistic, it can serve as a useful framework to see the inter-relationships between the different types of research and their funding. In this diagram, the total funding available for R&D is divided between the types of research, affecting the rate of the flow of ideas through the chain and, ultimately, the development of new products. As the diagram suggests, a potential decrease in new product ideas flowing through the pipeline can have serious consequences for U.S. corporations.

Discussion Questions

• Are there other aging chain structures that affect the delays in the R&D aging chain?
• What are the long-term implications of this shift in research focus?
• What are some of the nonlinearities that can affect down-stream research in unexpected ways?
• What might be the sources and lengths of the delays in your own company’s R&D chain? What would it take to change any of these factors?

R&D Knowledge Accumulation

The cascade of stocks in the Aging chain diagram depicts the interdependent nature of the different types of scientific knowledge. The structural delays inherent in this system affect the rate of development of ideas. This rate can be sped up or slowed down by certain factors, such as focusing more funding in specific research areas.

Discussion

Most breakthroughs in science have come about through the pursuit of knowledge for knowledge’s sake — what is usually referred to as basic research. This research, in turn, provides the “raw materials” for converting new-found knowledge into practical applications. As the accumulator and flow diagram shows, proving that something is possible is a long way from ensuring a commercially viable product. Superconductivity is a recent example: initial enthusiasm about its potential has given way to the hard reality of the many years it will take to benefit from its widespread use.

Securing a viable long-term R&D policy requires understanding and managing the dynamics of the aging chain structure. The speed with which knowledge accumulates along the chain can be affected by many factors. First, there are the structural delays that affect the rate of accumulation of each kind of knowledge along the chain. It takes time to research, document, and disseminate new knowledge as it is being generated. It also takes time for people to receive, review, and digest the new knowledge and find ways to use it.

Other factors, such as the number of qualified scientists devoted to different types of research, can influence the delays in the R&D system. The development of scientific talent can be seen as another aging chain structure: it begins with grade school children taking an interest in science and continues to the Ph.D. level, where graduate students choose their field based in part on the current job market. The long delays in the development of scientific talent means that we may not feel the repercussions of shifts away from basic science for 20 to 40 years. One expert stresses that it therefore is critical to invest in developing scientific talent to ensure that we can “power up research if once-sleepy fields are transformed by discoveries.”

Another important factor that affects R&D is the design, development, and manufacture of sophisticated research equipment. This includes not only the physical products used by scientists, but also the process knowledge of how things are made. The development of equipment and expertise also has inherent delays and outflows that affect the R&D aging chain. Industries that are dependent upon the existence of robust R&D investment could disappear if the research base that demands their products dries up.

Dangerous Long-term Shifts

Obviously, the flows can be influenced at each point by concentrating more resources in specific areas, e.g., Product Development Research, or by decreasing the amount of funding in other areas, e.g., Fundamental Undirected Research or Mezzanine Research. Given the long delays involved, making major shifts in such funding decisions can produce undesirable long-term results that are difficult to remedy quickly.

The development of scientific talent begins with grade school children taking an interest in science and continues to the Ph.D. level, where graduate students choose their field based in part on the current job market.

This trend toward applied research, for example, though promising in the short-term, sets the stage for some dangerous long-term dynamics. A redirection toward product development research will probably have better commercial payoffs in the short term, which will lead to even stronger arguments in favor of the shift. This success may then affect long-term policy decisions, where the bias toward product development research will grow and investment in basic research will continue to dwindle (reminiscent of the “Success to the Successful” archetype).

A shift in long-term policy may set up a reinforcing cycle where increasing rounds of investments in product development will lead to increased commercial success, further reinforcing the belief that the shift is the right decision to make. In the meantime, however, cutbacks in basic research will begin to empty the pipeline of new ideas, which will make it increasingly difficult to develop new products. When that happens, rather than investing in basic research (because it will take so long), the tendency will be to crank up product development funding even more and fund basic research even less (see “Nonlinearities in Knowledge Accumulation”).

A Balanced Approach

Some industry experts offer other justifications to challenge possible shifts in long-term policy. Eastman Kodak chief executive George M.C. Fisher, for example, argues that the current changes in research are based on fallacy in that “many failures of US companies to roll out new products lie not on research, they say, but in flawed business visions” (Business Week).

This possibility is evident in the many examples of companies that developed research, but then watched another company take over and benefit from its successful application. Business Week cited such examples as Xerox’s development of the personal computer followed by Apple Computer’s commercialization of the product, or IBM’s development of high-speed microprocessors that were then made profitable by Hewlett-Packard and Sun Microsystems.

Even when U.S. companies do allocate money for long-term research, it is not without expectation of high returns. Some companies are actually reducing the time they will wait for a return. A senior executive at Texas Instruments, for example, reported that since the mid-1980s, the average payoff required of long-term research has been halved to about five years. Other companies ask for even quicker response — at Communications Intelligence Corporation, “long term” has been redefined as two years.

To ensure that we maintain a balance in working with these issues, Alfred P. Sloan Foundation president Ralph E. Gomory advocates a two-part approach, according to Business Week. First, in order to remain competitive, we need to make certain that the U.S. stays on the cutting edge in all major areas of science. Second, we need to increase funding for results-oriented work and invest in areas that promise high return. Other experts also suggest trimming in areas where progress has slowed.

Nonlinearities in Knowledge Accumulation

The complexity of aging chain dynamics contains important nonlinearities of which we need to develop a better understanding if we are to manage the R&D process more effectively. One issue is the need to have a certain critical mass of knowledge, scientists, and equipment. For example, if the accumulator of new Basic Knowledge gets below a certain level, the accompanying decrease in the output of usable ideas may drop much more rapidly than the drop in the Basic Knowledge base itself (see “Nonlinearities in Knowledge Accumulation”). Similarly, if the concentration of scientists in a particular field drops below a critical level, it may have an adverse effect on the productivity of the remaining members. Trying to identify and manage those critical threshold values will be an important factor in the success of U.S. R&D.

Many scientists and industry experts are already concerned that we may be dropping below critical mass in some areas, and they caution that the current shift in research leans too far in the short-term direction. The U.S. has led the development of the aerospace, drug, and nuclear power industries since World War II, and some believe that if current research shifts away from basic research, “entire industries may never be born.”

According to Business Week, major U.S. companies spend less than 22% of their R&D budgets on long-term projects. The Japanese, on the other hand, allocate nearly 50% of their research funds toward the long-term, according to the industry-sponsored Council on Competitiveness. Cuts are not just occurring in specific areas of research, however. “In a survey by the Industrial Research Institute of 253 big R&D spenders, 41% say they would reduce total R&D in 1994, versus 20% that plan increases. Three times as many plan to cut long-term research funding as to raise it” (Business Week). Meanwhile, although the Japanese only spend $26 billion annually on R&D, this figure is rising by almost 8% per year. This, according to Business Week, is “a rod flag for the U.S.”

Managing Aging Chain Structures

Managing aging chain structures poses a generic challenge for most organizations with R&D departments because they must wrestle with the same issues that the U.S. is facing at a national level. There is no single right answer, since the unique circumstances and goals of each organization will determine the appropriateness of actions taken. There are, however, some basic issues that should always be made explicit and should be addressed whenever one is dealing with an aging chain structure:

• Identify and quantify the nature and length of delays inherent in the system. This includes identifying parallel structures that are relevant, as well as citing specific actions that can affect the length of the delays.
• Identify any nonlinearitics that may have a crippling effect on the system so you can avoid dipping below critical values. For example, if you hire new people too rapidly, the ratio between new and experienced people can get so high that overall productivity can plummet.
• Think through how short-term policies can reinforce themselves over and over again, at the expense of long-term health.

Nonlinearities in Knowledge Accumulation

As the current shifts in R&D focus play out, cutbacks in basic research will begin to empty the pipeline of new ideas, which will make it increasingly difficult to develop new products. When that happens, the tendency will be to increase product development funding and fund basic research even less. This will set up a short-term reinforcing cycle of success (R1 ).

Understanding aging chain dynamics requires more than a simple pen-and-paper sketch of the accumulators and flows — it eventually requires building computer simulation models in order to see the long-term dynamics. Identifying the key structures, however, is an important first step toward building a better understanding. If you have my comments on this article or R&D issues, please write: Feedback/Followup, The Systems Thinker, PO Box 120 Kendall Square, Cambridge, MA 02142-0001.

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This radical restructuring of the employment contract comes at a time when businesses arc facing a whirlwind of challenges. The nature and scope of changes such as downsizing, re-engineering, and new competitive rules suggest that they are in fact part of a larger trend toward an emerging new model of corporate organization. But what will be the role of workers and management in this new organization? The current upheaval offers the perfect opportunity to create not just another contract, but a new covenant for employment — one based on the concept of stewardship rather than patriarchy.

A New Employment Covenant

Peter Block, author of the book Stewardship (Berrett-Koehler, 1993), describes stewardship as “the willingness to be accountable for the well-being of the larger organization by operating in service, rather than in control, of those around us. Stated simply, it is accountability without control or compliance.” In Stewardship, Block offers a vision of a new type of organization based on a fundamental belief that all employees should be treated as mature adults who can be held responsible for themselves and their actions.

This new model strives to create an environment in which people can fully participate and contribute to the goals of the larger organization. Such a commitment goes beyond the traditional concept of an employment “contract” — it would be more accurately called a “covenant.” While a contract tends to focus one’s efforts on keeping within the letter of the law and preventing what we do not want (patriarchy), a covenant emphasizes operating in the spirit of the law and focusing on creating what we do want (stewardship).

At first blush, the new employment covenant sounds almost utopian — after all, who can argue with people taking their future into their own hands, finding or creating interesting work for themselves, and becoming responsible for their own careers? These ideas have the makings of a great vision, but there are fundamental questions that need to be addressed: What will the new covenant look like, how will it be implemented, and perhaps most importantly, who has the power and responsibility to make it a reality?

Leadership and Governance

At the heart of the new employment covenant is the issue of governance—how we distribute power, privilege, and control. If we are truly committed to bringing about this new covenant, we need to work to create fundamental structural changes to support it.

The governance structures in most organizations still treat people as if they need to be taken care of and “controlled,” either because they are incapable—for reasons of both individual maturity and organizational complexity—or simply untrustworthy. The old employment contract had at its foundation an implicit assumption that our leaders somehow knew more than we did, so we could trust them to make the right choices and take care of us. In return we gave them the authority to make decisions on our behalf. But, as Block points out, “When you ask someone to take care of you, you give them at that moment the right to make claims on you.”

By following this implied contract, we have colluded in sustaining a system in which we give up individual initiative, responsibility, and accountability in exchange for “guaranteed” rewards. But the new covenant challenges this basic belief. According to Fortune, “For some companies and some workers, [the new covenant] is exhilarating and liberating. It requires companies to relinquish much of the control they have held over employees and give genuine authority to work teams…. Employees become far more responsible for their work and careers: No more parent-child relationships, say the consultants, but adult to adult.”

°Shifting the Burden° in Reverse

From a systemic viewpoint, the new covenant has the potential to reverse an entrenched “Shifting the Burden” structure. In most companies, management-imposed systems and policies have been the predominant way of dealing with organizational crises (BI in “When Policies Turn into Parenting”). This has led to the continual underdevelopment of individual initiative and responsibility (B2), which, over time, leads to more organizational crises and further justifies the need to develop more systems and policies to help “tend the flock.”

Through this process, the belief among employees that “the system takes care of me” increases (R3), which further undermines individual development. The burden of responsibility is “shifted” to those in higher positions through well-intentioned, seemingly progressive human resources policies. It is a simple extension of the familiar parenting model.

Recognizing that we are caught in this structure is one thing; reversing the dynamic, however, is a more difficult challenge. If the new covenant is to take hold, managers must be willing to reflect on their own role in the system and consider alternative roles beyond that of caretaker and controller. Otherwise, the new employment covenant will become (or will be interpreted as) simply another exercise of power, with those at the top of the organization imposing rules on everyone except themselves. If that is the case, then the changes are likely to be neither effective nor deep. As Block states, “unless there is also a shift in governance… [change] efforts will be more cosmetic than enduring.”

Fear of Losing Control

One of the particular issues managers must face is the fear associated with letting go of control. This may not stem from a lack of trust in people, per se, but from a mistrust of our own understanding of the complexities that we manage. That is, because we don’t trust the overall capability of the enterprise as a system, we act in ways that treat people as if they are themselves untrustworthy. This insecurity drives us to over control, rather than allow individuals to exercise their best judgment.

According to Block, stewardship requires the belief “that with good information and good will, people can make responsible decisions about what controls they require and whom they want to implement them.” Having good information and good will may not be enough to make intelligent decisions, however, if we are not aware of the larger context in which they are being made.

°Tragedy of the Commons° Lessons

Without a global perspective, it is easy to make decisions that are beneficial to certain parts but that sub-optimize the whole. The “Tragedy of the Commons” structure offers many examples of this situation. The main lesson of this archetype is that the leverage does not lie at the individual level.

“Tragedy of the Commons” plays itself out wherever there is a common resource (people, physical space, budgeted dollars, etc.) that must be shared by equivalent players (those with equal power in the organization). Each person or department tries to maximize their use of the resource. When the sum of their requirements exceeds the resources that are available, there is no incentive for anyone to give up their piece. In this case, good information and good will alone are not enough to make the best decisions for the organization; a higher authority is needed.

This does not automatically mean that a “boss” steps in and makes the decisions for the teams. Instead, what is needed is an appropriate governance structure that everyone agrees to follow in advance of any specific decision having to be made. This could take the form of a set of criteria against which individual needs are weighed, a review board that is charged with maximizing the organizational use of a resource, or a system of checks and balances that recognizes when divisional needs must be sacrificed for the benefit of the whole company. The role of a leader, in these cases, is not to dictate from the top, but to help identify and create the appropriate governance structures.

Changes at Multiple Levels

So how can we make the new employment covenant a sustainable reality? The first step in this process is to be vigilant about how day-to-day decisions are being made. We cannot, in the name of efficiency, override the spirit of partnership and drive the process without full participation. All those being affected by the new covenant must be involved in mapping out the new structures and policies from the start. Getting everyone involved will require significantly more time than a traditional top-down “roll out,” but in the end, it may be more efficient and effective. If everyone’s participation is important to achieving the goal (which is the purpose of shifting responsibility back to the individuals), then anything that bypasses anyone’s involvement will be less than effective.

The second step is to examine the structures that are embedded in our organizations as a product of patriarchy (such as “Shifting the Burden” dynamics) and begin to clarify the challenges of moving to a structure that is based on partnership. After decades of living with patriarchy, people may require some adjustment time before they can fully step into the new model.

Most importantly, changes must happen at multiple levels simultaneously in order to be significant and enduring (see “New Model for Leadership”). The vision of stewardship is rooted in a shared sense of purpose that is based on choosing service over self-interest. This vision and its underlying values and beliefs will, in turn, guide the understanding of current reality and the creation of new systemic structures that will help translate the ideals into reality.

When Policies Turn into Parenting

The new employment covenant is working to reverse an entrenched “Shifting the Burden” structure, in which the burden of responsibility has “shifted” to those in higher positions.

But it is at the level of everyday events and patterns of behavior that we will demonstrate whether we are serious about making fundamental changes. The congruence between daily actions and shared vision will answer the question, “How serious are we about walking the talk?” If daily actions are governed by efforts to maintain safety, then everyone will hedge their bets and the dynamics of entitlement and patriarchy will likely continue. If, on the other hand, there is a sense of adventure and risk-taking, then empowerment will be a natural reinforcing by-product of such actions.

The Stewardship Challenge

Stewardship can spring up anywhere in an organization. Stewardship is leadership in the moment, not leadership by position. This means that we should not only look up the organizational chart for leaders, but across and down as well. Hierarchy then becomes less of a system of power and control and more of what it should be — a system of organization that makes distinctions between different types of work and responsibilities. Stewardship ultimately challenges us as individuals to make those choices and then live by them, as we acknowledge that the responsibility for leadership lies squarely on everyone’s shoulders.

Stewardship (Berreu-Koehler, 1993) is available through Pegasus Communications, Inc. (617) 576-1231.

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1. Specify Numeric Values

The first step in bringing our diagram to life is to assign quantities to the policies and decisions that are mapped in the diagram. For example, let’s say our current staff is 1500 people and our desired staff is 2000. A question we need to consider is, “How quickly do we want to close the gap?” The aggressiveness of our time horizon will determine the flow of people in and out of “Current Staff.” Let us assume that we want to close one-half of the gap each month. We could then define “Hiring or Layoffs” as 0.5*Staffing Gap (see “Defining the Variables”).

2. Check for Consistent

After assigning numerical values, we should conduct a quick check to make sure we have defined the variables correctly and that the dimensions are consistent. For example, both our current staff and desired staff will be measured in numbers of people, as will the staffing gap (the number of people needed to close the gap). The “Hiring or Layoffs” flow should represent the number of people flowing into or out of the company over a period of time (people/ month). From our quick check, it looks like the variables are all consistent (people and time). If we had found one variable with a different measurement, such as dollars, it would signal a need to recheck our definitions.

3. Check for Delays

Since delays play an important role in the dynamics of any system, we need to make sure they are captured explicitly in the computer model. Our original story mentioned several significant delays: the time it takes to recognize the gap between current and desired staff, the delay before deciding to act on it, and the time it takes to actually hire or lay off staff. Suppose we know that it takes approximately three months to hire and train a new person. We can include this information in the computer model either by using a built-in delay feature found in most software packages, or by modeling it explicitly with an additional stock.

4. Determine Time Horizon of the Simulation

One of the lessons learned from years of computer simulation work is that we often underestimate the time necessary for the dynamics of a system to play out. A good rule of thumb is to let the simulation run three to five times as long as the longest explicit delay in the system. Since we know there is a three-month delay between the recognition of a staffing gap and when people actually come on board, we want our simulation to run at least nine to 15 months. To appreciate more fully the long-term dynamics, we will let it run for two years.

5. Build Confidence in the Model

Before actually experimenting with different policies in the simulation, we want to build our confidence that the model is an accurate representation of the system we are studying. One way to determine if the model is robust is to conduct a series of simple tests to verify that simulation results match real or historical data of what we know or expect will happen. If, for example, our current staff is 2000 people and our desired staff is also 2000 people, we would expect that no hiring or layoffs would occur. Running that test should produce a straight line. If, however, the graph of “Current Staff” bounces around or increases, the model needs to be checked for errors.

6. “What If” Scenarios

Asking whether something will happen can lead to non-productive conversations about why one outcome is more likely than another. But when we ask what if something were to happen, we can enter into a productive exploration of the possible consequences.

Defining the Variables

The first step in bringing our accumulator and flow diagram “to life” is to define the policies and decisions that are mopped in the diagram so we can see how they will play out over time.

Therefore, once we have confidence in the model, we want to run a “base case” scenario to see if we get any interesting insights into the structure. For example, if we try to close one-half of the gap each month with a three-month delay for each new hire, we discover that we overshoot and oscillate around our target number of 2000 (see “‘What If’ Scenarios”). We end up hiring more people than we need because our hiring policy and the number of “Current Staff” doesn’t account for people we have already begun to hire.

We may also ask what would happen if we shortened the delay in the hiring process itself, instead of trying to increase the number of people we hire. Let’s say we make a real push to get people on board in two months (by resetting our delay function to two months instead of three). What would we expect? As the graph shows, this goal would allow us to approach our target employee number more smoothly.

Another scenario we can explore is changing our level of aggressiveness — let’s say we will try closing 100% of the gap each month (“Hiring and Layoffs” = l*Staffing Gap). What do we expect to happen? The result may be surprising — we will overshoot the target by a much greater number. This scenario creates larger oscillations because the number of people-in-process that are unaccounted for is greater.

What If Scenarios

These two scenarios compare possible staffing strategies. As the right-hand graph shows, shortening the hiring delay to two months allows us to approach ow target number more smoothly.

Consider the Pipeline

If we account for the pipeline of “hires in progress” when we compute the staffing gap, we actually alter the structure by adding a new balancing process (82). This will allow us to close the staffing gap smoothly.

Is there a way to eliminate the oscillations altogether? What if we account for the number of people already in the hiring pipeline when we compute the gap? By changing our model to make the delay more explicit — as a pipeline of people in process — we can test this scenario (see “Consider the Pipeline”). If we run this simulation with the assumption that we will close one-half of the gap each month (“Hiring or Layoffs”= 0.5*Staffing Gap), we will in fact eliminate the oscillations. By accounting for the pipeline, we are actually altering the structure by adding a new balancing loop (B2).

Learning Curve

Although our staffing issue is a somewhat simplistic example, working through these steps forces us to articulate and test our beliefs about a problem, offering a way for us to refine our mental models. For this reason, modeling is a very powerful tool. However, the learning curve for modeling can be steep. You can teach someone to use a modeling program in a few hours, but learning how to design a model that produces usable results and advances a team’s learning requires a much more significant investment. Constructing good computer models, like drawing good causal loop diagrams, requires the inclusion of multiple perspectives, the commitment to surface and challenge our mental models, and continual practice.

This article is based in part on “Moving Into Computer Modeling” by Michael Goodman, which appeared in The Fifth Discipline Fieldbook (Doubleday, 1994). For more information about the various modeling programs available, see pages 547-548 of The Fifth Discipline Fieldbook.

Michael Goodman is vice president of Innovation Associates (Framingham. MA) and a frequent contributor to The Systems Thinker. He has been involved in the field as oxi educator and consultant for over 20 tears.

Editorial moon for this article was provided by Colleen Lannon-Kim.

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The division was in serious financial trouble. Up until then, it had been coping with its financial problems by cutting positions, which seemed to improve profits temporarily. Now, faced with new pressures, it seemed obvious to the financial group within the division that it was time to cut the workforce again. Others in the division, however, felt that downsizing was exactly what the company did not need to do. This group argued strongly that improving service quality was the solution to their financial woes.

When representatives from these two conflicting groups were brought together, the debate became almost hostile. It was clear that the issue of downsizing was painful to both sides. Because of the need to explore this topic further, our consulting team was invited to work with members of the division using a systems thinking approach.

Fragmented Views

We started the project work with a one-day training session for a cross-functional group of managers from the division. During the segment on systems thinking, we drew causal loops that explored the issues of downsizing and service quality in the Equipment Servicing Division, including a “Fixes that Fail” diagram (see “Downsizing that Failed?”). The central question that emerged from this session was whether the financial gains from downsizing would be offset by a decline in service quality, and ultimately a decline in sales.

To explore this question further, we decided to rake the next step and build a computer model. The first model we created was very simple, and was used in a series of small group sessions to help the managers become comfortable with the modeling software and with the basic dynamics of the system (see “Downsizing and Service Quality Model,” p. 10). The modeling tool we used was ithink’s predecessor, STELLA, which was used without any other interface.

The small group sessions were helpful in clarifying the assumptions behind the two contradictory views of the business. For example, when the VP of Finance — a lead supporter of the downsizing — tested his approach in the model, he was puzzled to see the financial situation continue to slide. When he reflected on this surprising result, he was finally able to articulate his mental model: he believed that he could cut staff and that there would be no ripple effects—that everything would “stay the same.” The data he had previously used to support this position was that downsizing in the past had led to a temporary increase in profits. Although typically there was a later downturn in profits, he attributed this to competitor activity. Our model, however, had no active competition, and the downturn still occurred. Thus the model seemed to suggest that the decline in profitability could be due to the delayed effects of reduced service quality on sales. For the first time, the VP was forced to consider feedback within the system — the potential unintended consequences of a reduction in workforce (see “Unintended Consequences,” p. 11).

The promoters of improved service quality were equally fragmented in their thinking. They believed that if the division just added more people, quality would increase, and that would improve their revenue stream. They also had data to support their view — the company had discovered through market research that its service quality rated poorly compared to its competitors. However, when this group worked with the model, they found that adding people did improve service quality and sales, but with consistently unprofitable results. By ignoring the high cost burden of the increased service force, they too were assuming that you can change one aspect of the system and that “everything else stays the same.”

Downsizing that Failed?

To “fix” its ailing Equipment Servicing Division, COPEX had tried reducing the number of employees in the post, which decreased us personnel costs and improved profits temporarily (B1). But the drop in numbers of service personnel may have led to decreases in service quality, bringing sales and service revenue down and making profits fall even further (R2).

Learning and Leverage

After our small group sessions, we went on to create a second model that incorporated enough detail to represent some of the specific initiatives the division was considering. To work with this larger model, we brought the group together for a one-day session to consider various strategies for improving the business. As the group tested various alternative strategies, their level of understanding deepened. One compelling lesson that emerged was that any proposed initiative would not affect results in the short term, and thus the company would face continued financial pressure for the foreseeable future.

The most important insights, however, were about the fundamental architecture of the business. The reason that the original policies (lay off workers vs. add service capacity) failed to create a sustainable business was that the basic relationship between cost and revenues in this division was unworkable. For example, keeping enough personnel on hand to provide competitive service quality would cause an unprofitable overhead structure, but reducing personnel to a profitable level would yield low service quality and inhibit growth. The lesson was clear: it was impossible to achieve growth without a fundamental restructuring of the business line.

The real leverage for dramatically changing the business line was to modify any one of the basic parameters that determined costs and revenues, such as Revenue per Product, Failures per Product, Time Spent per Service, and Average Salary (see “Critical Business Parameters”). For example, a reduction in breakdowns would require fewer technicians per installed machine, which would decrease overhead and improve profitability while actually increasing service quality.

It is important to recognize that improving the breakdown rate was not the answer — it was only one possible structural change that would bring about the desired results that the group wanted.

Downsizing and Service Quality Model

The initial computer model that was created for the Equipment Servicing Division was designed mainly to help the managers become comfortable with the modelling software and with the basic structure of the system. Although is looks visually complex, this simple STELLA model helped the managers look as their assumptions more explicitly.

Improving the breakdown rate would allow the business to continue to grow and to remain profitable with that growth strategy.

Another critical lesson for the group was that policies across divisions within the company were all interdependent. Before their experience with the model, the managers viewed the company in a highly fragmented way. Even within the Equipment Servicing Division, the financial and quality camps saw the others as “obstacles” to be overcome. As a result of our intervention, the groups saw the need to look more systemically at the issues, and formed cross-division teams to continue the work.

A final realization for this group was that downsizing might be as much the disease as the cure. The group voted to postpone additional downsizing for at least a year.

Epilogue

I wish I could say that they lived happily ever after. The business line is still alive, which was in some doubt at the time, but they continue to have difficulties. I suspect that having cross-divisional teams was a very difficult structure to maintain, given their historical operations. I do feel, however, that our work helped them become more insightful and systemic in their approach.

Running through different simulations began to give them an understanding of the delays inherent in their service business — which was half the battle. For the first time, the group was able to test their assumptions about the way their business worked — and when you are caught in a “Fixes that Fail” or other problem-solving dynamic, exploring assumptions is always a good place to start.

Unintended Consequences

The simulation revealed the “better before worse” effects of downsizing on profitability, which may have resulted from the delayed effects of reduced service quality caused by the downsizing. (Note: This diagram is from a HyperCard interface that was developed for the model at a later date, in conjunction with Brian Kreutzer of Gould-Kreutzer Associates.)

Critical Business Parameters

The real leverage for the Equipment Servicing Division was to restructure their business by Editorial support for this article was provided fundamentally changing some of the parameters that were within its control, such as Average by Kellie T. Wardman. Salary, Time Spent per Service, Failures per Product and Revenue per Product (in bold italic).

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