Recognizing this challenge, we began to streamline our product definition, design, and development processes. Our group vice president, Bill Johnson, instituted a formal process to review key projects and programs. While solving project issues did result in improved quality and quicker time-to-market, the data gathered in this phase gave us an indication that we were facing much deeper issues. We began to see that our problems were linked to long-term dynamics such as changing customer demands and the increasing complexity of our business environment, which would require a different approach than we had used in the past.

This was the start of a long journey for our group. Our path took many turns as we met new challenges and discovered new resources along the way, uncovering deeper and deeper levels of obstacles to our business success. The process involved people with varied roles who were willing to work together to try new approaches, learn from their mistakes, and try again. Our story will hopefully offer some guidelines for others in the middle of a similar discovery process (see “The Journey: Going Deeper into Causes”).

A Systems Approach

The first phase of our journey was to address the immediate issues of customer satisfaction and quality. Customers were moving away from Digital proprietary computing environments, and were more often demanding multi-vendor “system solutions” — families of products that worked together to solve their business problems. As one key customer said, “We want to choose the best solutions regardless of who makes it. And we want everything to work together just as if it came from a single vendor.”

To meet this need, we began experimenting with a systems approach to product design and delivery, which meant paying as much attention to the relationship between products as to the products themselves. This approach caused us to focus in a more disciplined and structured manner on actual market and customer requirements, forcing us to surface our assumptions about trends in the marketplace, the industry, the technologies, the customer, and the competitive environments.

For example, we evolved a simple but powerful process called “Customer-Based Requirements Dialogue.” Rather than beginning with the question, “What product should we build?” we began by exploring our marketplace and customer environment assumptions. Only after we had acknowledged and explicitly surfaced our assumptions did we begin talking about the market requirements: the problems we were trying to solve and the opportunities we were addressing. Finally, we defined the specifications for the system and the features for each component product. We found this new process difficult because we were more used to prescribing solutions than describing the marketplace and customer environment in which the products would be used. Although these descriptions were about future states, which meant that most of them were educated guesses, this process proved to be more effective and efficient than our traditional methods.

Our systems approach also required us to work more actively across functional and hierarchical boundaries within the networks group, because it became increasingly clear that the answers we needed were located throughout the organization, not just at the top or in one area. We began to consciously open up our decision-making processes to include diagonal slices of the organization. We also made necessary job changes to meet the needs of our new approach, creating new roles such as systems technical leadership, systems business management, and systems project leadership. These changes addressed the need to manage the relationships between products, people, projects, and processes.

Focusing on the system also forced us to reevaluate our relationships with other companies. We acknowledged that if we were moving toward open solutions in response to the customer’s changing demands, then cross-company collaboration was required. An early result was that long-time competitor Apollo Computer (now Hewlett-Packard) became a new partner in the design and development of products.

From Systems Engineering to Systems Thinking

As we continued with our fledgling attempts at a “systems” approach to solving customer problems, we discovered two important books that helped bring clarity and structure to our efforts. The first was Peter Checkland’s Systems Thinking, Systems Practice, which clearly articulated our uphill struggle as we moved from “component thinking” to “systems thinking.”

Checkland writes, “Rene Descartes taught Western civilization that the thing to do with complexity was to break it up into component parts and tackle them separately…. Systems thinking, however, starts from noticing the unquestioned Cartesian assumption.., that a component part is the same when separated out as it is when part of a whole…. The Cartesian legacy provides us with an unnoticed frame-work — a set of intellectual pigeon-holes — into which we place the new knowledge we acquire. Systems thinking does not drop into its pigeon-hole, it changes the shape and structure of the whole framework of pigeon-holes. This questioning of previously unnoticed assumptions can be painful, and many people resist it energetically.”

With this new understanding, we renamed what we had been calling “Systems Engineering” and began calling it “Systems Thinking.” This new term reflected our recognition that we had to apply a systems thinking approach to all aspects of the way we did business, not just engineering. As a result, we developed a brief, 20-question guideline for people to use to begin applying systems thinking to any problem or situation they were facing. We also developed a systems thinking work-shop to meet requests for this type of work in other parts of the company. One such seminar was delivered regularly at a management development program, which reached hundreds of middle managers and technical leaders worldwide.

Then, in late 1990, we discovered Peter Senge’s The Fifth Discipline: The Art and Practice of the Learning Organization. This wonderful book made sense out of the experiences of the preceding three years, and gave us a clear set of constructs, language, and guidelines to bolster our efforts. Now we knew we were not in this alone — there was plenty of help and knowledge available that was based on a vast body of research and practice.

Servant Leadership and Decision Making

As we improved our ability to deliver at the product level, it became clearer that we needed to gain clarity at the larger “umbrella” level of shared vision. In order to do this, we needed to explore our individual “mental models”— our internal assumptions and beliefs about the way the world works — and come to some shared understanding of the larger issues we were facing. Therefore, in the early spring of 1991, we began looking for ways to surface, examine, and systematically break through our mental models of the marketplace and industry trends.

We began with a process called “FutureMapping,” a scenario planning methodology brought to us by North-east Consulting Resources Inc. of Boston. Through this process, we developed scenarios that described industry, competitive, and product trends from the present through 1997. Over the course of the next 15 months, we held one-day working sessions that engaged over 350 key people across the group in a modified version of this process. The key benefit was that we were forced to explicitly describe our industry, market, competitive, and customer “systems,” and to identify and monitor those five or six critical assumptions that represented “forks in the road”—decision points where we had to make tough choices.

As we did this work, it became clearer that the most difficult points for us in all of these new systems processes were the points of decision making. Working with teams that crossed functions, groups, hierarchies, and companies, it was often difficult to establish clear leadership roles and points of decision-making accountability. In addition, every manager, engineer, project leader, and technical leader had to balance the need for rapid execution and delivery against the desire to stay open to new information. It was all too easy to flip to one extreme or the other — to go for consensus and remain in dialogue forever, or to make quick decisions in an authoritarian manner. Our core challenge was (and still is) to manage this balance, and learn how to live productively within this dilemma.

To address the challenge of making decisions among diverse groups of people, we embarked upon some experiments with new leadership styles. With help from Robert Greenleaf’s book, Servant Leadership, we began moving toward developing “servant leaders”— or as Peter Senge puts it, leaders whose job is not so much to have the answer, but to instill confidence in those around them so that together they will come up with the answer at the time it is needed. We received some very positive feedback from this work — leaders told us they now found it easier to make decisions and that product development moved forward more quickly. But we also learned that the decisions were only as good as the information that was placed “on the table.”

Facing Undiscussables

It seemed that the next challenge we faced was how to bring more data to the table — including those issues that people did not feel comfortable raising. So, we embarked on a series of carefully designed and facilitated dialogues between senior management and several hundred engineers, technical writers, project leaders, and supervisors to discuss the obstacles we faced in quality and time-to-market. These meetings began to surface some of the difficult issues people found hard to raise because they felt “unsafe.” Harvard Professor Chris Argyris calls these unsurfaced issues the “undiscussables” that prevent real learning in organizations. Using the framework presented in his book Overcoming Organizational Defenses, we began to acknowledge the presence of “undiscussables,” but were left with the dilemma of how to raise and resolve them productively.

Change and Upheaval

At the same time that we were facing the challenge of how to deal effectively with “undiscussables,” a major change took place in the company as a whole. In October of 1992, Digital founder and CEO Ken Olsen was succeeded by Robert Palmer. This transition heralded two years of massive downsizing and almost continuous restructuring within the company. At that point, Digital as a whole was losing approximately $3 million per day, and had absorbed more than $3 billion in losses over the previous three years.

The immediate impact on NaC was that it merged with other networking entities under a new vice president, and continued to be reorganized and reshaped into many forms. As a result, people felt very insecure, morale plummeted, and attrition rose. It was simply not the time to begin the difficult and soul-searching work of connecting at the level of integrity, honesty, and respect espoused by Chris Argyris. Although we knew how important this work was for our long-term success, we just couldn’t begin it, given the constant instability and growing state of anxiety within the group. It was challenging enough just to continue to design, develop, and deliver products and systems. So what next? As with many of the breakthroughs we had in the past, the answer was close at hand.

Bringing in the “People”

Aspect In June of 1992, I presented at a conference on organizational learning, where 1 met Sandra Seagal and David Home. Their work, Human Dynamics, offers a framework for understanding differences in the way we learn, communicate, relate, and develop as human beings. With support and funding from John Adams, now vice president and technical director of Networks Integration Software, I attended a five-day training course in Human Dynamics and became convinced that this was the missing piece that could move our work forward. Human Dynamics offered a systemic approach to the complexities and wonders of human functioning that was clear, logical, and structured, yet broad and flexible enough to encompass the infinite nuances that make us each unique human beings (for more on the Human Dynamics methodology, see “Human Dynamics: A Foundation for the Learning Organization,” May 1994).

Back in the Networks Group, we saw Human Dynamics as the technology that would enable us to rebuild the trust, safety, and empowerment we knew was desperately needed. Over the next two years, almost 500 people across the company received training in Human Dynamics. Much of this was accomplished under the auspices of the Engineering Excellence Program led by Corporate Consulting Engineer Peter Conklin. Human Dynamics was seen as a foundational technology that would enhance our ability to make the changes needed in our engineering processes. We also began to dovetail Human Dynamics with Human Systems Change, a technology from Options Consulting, Inc. (Reading, MA) that was helping us create a systemic language for the human/cultural side of change so that we could name and over-come perceived resistance.

As with the efforts of the preceding seven years, we have had some good results from our application of Human Dynamics. While it is difficult to measure them quantitatively, there are many anecdotal accounts of improved efficiency and effectiveness in interpersonal communication and team productivity. As with many new technologies, our challenge now is making this practice part of our everyday way of doing business.

Valuing the Relationships

Despite the difficulties in Digital as a whole over the seven years of this story, our portfolio of networking products has continued to be profitable. While we cannot prove a direct connection between our ongoing efforts and our continued profitability, it is clear that it was a contributing factor.

As a networking group, we have learned that relationships are equally important as products — after all, connectivity is the essence of our business. In fact, we are beginning to believe that a root cause of many of our business problems lies in the breakdown of personal relationships. Although our first inclination in business is to blame profitability problems on poorly executed strategy or a lack of management skills, we believe that the cause may well be the absence, avoidance, or breakdown of authentic connection and communication between human beings.

Peter Block puts it very well in his 1994 book Stewardship: “Money is a symptom, money is never the real issue…. An economic crisis for any organization means it is failing in its market-place. In some fundamental way it is unable to serve its customers. And if it is unable to serve its customers, it means it has failed to serve its own internal people.” We have learned that serving the most basic needs of our people — to connect, communicate, and grow in a supportive environment — does indeed produce a profitable business.

Our seven-year journey has brought us far in our ability to learn and work together in more effective ways. In some sense, we have worked “back to front.” If we were to start over again, we would without a doubt begin with the fundamental technology of Human Dynamics and proceed from there. We would then know that we were building on the most solid foundation there is—people who are aware of themselves as fully empowered human systems, learning and growing, and consciously nurturing themselves and each other in order to produce the results they most desire.

Chris Strutt holds the title of Consulting Engineer. Systems Thinking Methods, In the Network Integration Software Segment of Digital Equipment Corporation.

In a future Issue, Chris Strutt will discuss In more detail the application of Human Dynamics technology at Digital. Editorial support for this article was pro-vided by Kellie T. Wardman.

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Why Empowerment Fails

While many managers have embraced the idea of “flat” organizations composed of empowered individuals, the existence of such organizations is far from a reality. If empowerment is truly valued, why have so many companies failed to make it happen?

The answer to this question may lie in the lack of organizational structures and norms that support empowered decision-making. Fundamentally, empowerment is about the distribution of power. In organizations, this is most tangibly represented by decision-making authority — who has the power to make what kinds of decisions. But empowerment does not magically turn everyone into great decision-makers, nor does it suddenly equalize differences in skills and experience. Unless the organization’s decision-making processes are designed to ensure the quality of the decisions, empowerment efforts are destined to fail. Even worse, that failure can lead to bitterness and disillusionment.

So, how can we distribute decision-making authority in a way that truly empowers people, yet still protects the organization from undue risks that can come from uninformed decisions? This is the central challenge of walking the empowerment tightrope: balancing management authority and employee influence.

Organizational Straitjacket

When initiatives such as empowerment or employee involvement are announced, there is a tendency to promote a new way of operating by condemning the old. In the case of empowerment programs, this often translates into a belief that decisions made individually are bad (the old model) and that decision by consensus is good (the new model). But as Robert Crosby, author of Walking the Empowerment Tightrope, explains, management exclusively by consensus can be a disaster. “When overused, consensus is time consuming and is often controlled by the most rigid or resistant members.” In effect, we end up trading one form of tyranny for another.

The assumption that empowerment equals consensus decision-making can create organizational straitjackets that lead to poor-quality decisions — and, ironically, can also leave employees feeling disempowered. One manufacturing operation discovered this counterintuitive behavior when it tried to create a flatter management structure through empowerment. The intention was to increase autonomy while improving both the speed and quality of decisions. But after several months, people felt less empowered to make decisions. Worse, many decisions took longer to make, which meant that more were made “under the gun” — and were therefore based on time pressure rather than on sound thinking and adequate data.

If we look at this phenomenon from a systems perspective, we can draw out the counterintuitive dynamics that are at play (see “Consensus Decision-Making Straitjacket”). In the “new” environment of empowerment and teamwork, the “old” view of making decisions single-handedly is viewed as bad. Therefore, Manager A is reluctant to make decisions on his own, even though his position may require it. Instead, he consults with various people and asks for their input. This reinforces the consulted individuals’ belief that it is a consensus decision, so they begin to research different options and feel that they “own” the decision.

CONSENSUS DECISION-MAKING STRAITJACKET

Lack of clear structure around empowered decision-making can result in a consensus decision-making “straitjacket”—a spiral of ever-increasing resentment on the part of employees and escalating levels of stress and paralysis on the part of the manager.

Although Manager A knows he needs to decide quickly, he feels uncomfortable taking that step alone because others are now actively engaged in the process. The time arrives, however, when action must be taken. Under pressure, Manager A makes the decision even though he has not closed the loop with everyone. Afterwards, he thanks everyone for their involvement and explains the reasons for his action. Although his decision was ultimately a good one, Manager A is left with a nagging fear of being perceived as control-oriented, which further reduces his comfort level with making such decisions and leads to more ambiguous decision-making in the future (R1).

And what about the people with whom he conferred? They are now cynical about Manager A’s commitment to empowerment and the value he places on their involvement. Thus, their willingness to surface their confusion about the decision-making process decreases, and the clarity about who needs to make what decisions never gets established. This, in turn, further reduces Manager A’s comfort level (R2). Both of these loops can lead to a spiral of ever-increasing resentment and mistrust on the part of employees and escalating levels of stress and paralysis on the part of the manager.

A New Decision-Making Model

In order to be effective, any decision-making model should provide clarity along at least two dimensions: 1) the type of decision, and 2) the role of each participant. Clarifying the type of decision provides detail on the level of involvement of each person. Deciding on the specific decision role for each person describes the nature and extent of his or her involvement (see “Decision Types and Decision Roles” on page 3).

Identifying the type of decision up front can be an illuminating exercise:

• Is this a decision that you need to make alone, perhaps due to the sensitive nature of the issue? (Type I)
• Can you make the decision with the benefit of some data-gathering conversations with certain individuals? (Type II)
• Is this a decision that requires a consensus among critical stakeholders in order to ensure smooth implementation? (Type III)
• Or, is the decision better left to those who are much closer to the issue at hand? (Type IV)

Determining what type of decision one is facing also begins to surface issues around a second aspect of the decision-making model: who should be making the decision. In effect, by clarifying the decision type, you are also identifying one of the critical decision roles—namely, that of the decision manager.

Decision Manager and Decision Roles

The decision manager, as described by Paul Konnersman in his article “Decision Role Clarification,” is the person responsible for managing the overall decision process and implementation. But identifying the decision manager still leaves room for ambiguity about what type of participation others will have in the decision. Konnersman therefore defines two other roles: the consulted participant and the informed participant. A consulted participant, according to Konnersman, is contacted during the deliberating stage for the purpose of data-gathering, whereas the informed participant is brought in primarily to help with the implementation of a decision that has already been made.

The fourth role in Konnersman’s typology, the approver, can be the trickiest role to fully understand and manage. Although this role is intended to help prevent the organization from making intolerable mistakes, if it is not used properly it can create a feeling of powerlessness and cynicism about empowerment.

The “Lurking” Approver Role

The approver role is tricky because it can look a lot like the old authoritarian power monger — someone who “empowers” others to make decisions as long as it meets his or her “approval.” And yet, this role is needed when the decision manager is genuinely not in a position — either by breadth of experience or scope of responsibility — to make a decision that is organizationally robust. Although the goal of an empowered organization is to make all decisions as locally as possible, that desire needs to be balanced with the reality of the actual ability to make those decisions.

If viewed from this perspective, the approver role can be the means to judiciously manage the transition into empowered decision-making by acting as a safety net for the decision manager as well as for the organization. But if this role is abused, a virtuous circle of ever-increasing organizational effectiveness can be kicked into a downward spiral, decreasing empowerment and leading to lower quality decisions (see “ ‘Lurking Approver’ Dynamics”).

In some situations, an approver needs to intervene in order to improve the quality of a decision (B3). But if the role of the approver is not clear from the outset, it can serve to reinforce the belief that the approver was “lurking” all along, waiting to see if the decision matched what he or she wanted. If it matched, he or she can then point out how the group had been empowered to make the decision. If it did not match, then the approver role can be invoked to make the “right” decision. As a result, the group feels that they were not truly empowered to make the decision. In the future, they will be less likely to put the same level of enthusiasm or trust into the decision process — potentially leading to lower quality thinking and lower quality decisions, which may require further intervention from the approver (R4).

The Approver Role: Setting Boundaries

In such situations, it is not the approver role itself that is the problem — it is the seemingly arbitrary use of the role that leads to a sense of powerlessness. Therefore, the leverage in this system is to identify the approver role in advance, and clearly establish the criteria under which a decision is subject to approval. It is particularly important to identify the specific parameters — the time frame, organizational risk, dollar amount, scope of impact, and other criteria — that will determine when an approver must be involved. Such boundaries provide a pre-negotiated context in which the role can be used most effectively.

“LURKING APPROVER” DYNAMICS

Sometimes an approver must intervene to improve the quality of a decision (B3). But if the approver role is not clarified at the outset, the intervention may breed resentment and lack of ownership over future decisions — potentially leading to lower quality decisions and further need for intervention (R4).

For example, a group may specify that all marketing decisions are owned by the marketing director, but that they require approval by the strategy council if such decisions are in direct conflict with the international market expansion strategy. Or a company can specify a parameter, such as $1 million for capital expenditure decisions or a headcount cap for hiring decisions, above which the decision manager must get approval.

If the person who is empowered to make a decision only finds out that the decision is subject to approval after the fact, empowerment will become a hollow idea that creates increasing bitterness. If, on the other hand, the details of an approver role are outlined beforehand (or at least the possibility of the emergence of such a role is discussed ahead of time) then the actual intervention of the approver can be seen as a self-correcting mechanism. People can see that building this mechanism into the system actually enables a fuller level of empowerment, while still ensuring the quality of the decisions (B4 and R5 in “Clarifying the Approver Role” on page 5).

Walking the Tightrope

Creating a truly empowered organization is a lot like walking on a tightrope. If we completely let go of managerial authority and let individuals always make decisions on their own, we are sure to be erring on the side of abdication. If we are too cautious and afraid of letting anything go, we will surely be accused of remaining controlling and authoritarian. The path of empowerment lies somewhere between those two extremes.

The approver role is critical for accomplishing that delicate balance on the empowerment tightrope. As an organization develops along the path of empowerment, however, one would expect that the number of decisions requiring an approver would decrease and the parameters might relax over time.

No one is going to be perfect in this process — it requires a certain amount of understanding and trust. But trust is a function of at least two things: integrity and competence. All too often, we misinterpret a lack of competence to be a lack of integrity, and we lose confidence in the system and/or in the people involved. If we are a little more forgiving of others when they falter, we may be graced with more understanding when we do the same. And if we have worked to establish a well-defined decision-making structure, we will at least have created a method for consciously selecting who makes what decisions and why. With this kind of guidance — along with a little understanding — we may eventually create the kind of empowered organization that we desire.

CLARIFYING THE APPROVER ROLE

If the approver role is built into the system as a self-correcting mechanism, it can enable a fuller level of empowerment in decision-making, while still ensuring the quality of the decisions.

Daniel H. Kim is the co-founder of Pegasus Communications and the MIT Center for Organizational Learning, where he directs the learning lab research project.

Editorial support for this article was provided by Colleen Lannon.

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This is one manager’s response to his experience in Hanover Insurance Company’s “learning laboratory” – the heart of a systems-based approach adapted by the company about four years ago.

The dynamic complexities of the insurance business, including tumultuous changes in the social environment, prohibit all but the best players from being successful. Hanover, one of the largest companies writing property and casualty insurance in this country, has responded to this challenge by using systems thinking.

“By its nature,” explains Bill O’Brien, Hanover’s president, “the property and casualty industry is interconnected with many other systems. It deals with diverse and complex issues. We believe the greatest competitive advantage an organization can possess is its capacity for learning.”

It has been said that the shortcomings of systems come not from the people who work within them but from defective designs. Systems thinking (and the field of system dynamics) requires one to view the structural aspects of performance rather than just the individual performances of people.

Organizational learning transcends one person learning a skill on a case-by-case basis…

This thinking is carried into the learning laboratory where organizational learning is distinguished from individual skill learning. Organizational learning transcends one person learning a skill on a case-by-case basis; it creates a shared base of knowledge across the organization, not just within senior management.

The learning laboratory came about partly as a response to a problem Hanover needed to solve: During 1985 and 1986, Hanover found the number, size, and complexity of claims increasing, and this created a need for more people to handle the volume. Claims managers at Hanover found it difficult to recruit and hire experienced claim personnel. The pool of candidates was either too small or the skill level was not of a sufficiently high caliber to fit the company’s professional image. Therefore, a large number of trainees were brought into the work force just when Hanover needed to respond to more complex issues and to project more accurately the future size of claims.

Systems thinking was used to deal with these issues. The learning laboratory was developed to explore and test assumptions relative to claim management function.

A simulated environment

The learning laboratory uses management simulators (computer models that allow one to see the dynamic consequences of one’s decisions), which operate like the simulated cockpit pilots use.

In the learning laboratory, a simulated claim environment is created where feedbacks arc discussed and weighed with other managers who have had similar experiences. This is done using a computer simulation based on a dynamic model of relationships in the claim environment. Playing with simulated events in teams is combined with periods of debriefing, to reflect on what has occurred.

Claim managers analyze issues of the day and begin to test their assumptions about time availability and quality and how these concepts relate to adjuster capacity. It is when they question their long-held beliefs about claim management that they begin to get insights about how to manage differently. This is when their behavior can change.

One example of how systemic thinking has clarified priorities and created more balanced thinking — and practice — is its application to the issue of fluctuating workload.

Devising a means to deal with the peaks and valleys of workload is a primary function of a claim manager. At times, skilled claim adjusters are inadequate to handle the incoming and pending workload; at other times, insufficient workload can cause good work habits to slacken. Time is then filled by the work available.

How a manager responds during times of pressure and times of less activity is critical to the success of the entire organization. To be effective, his or her response must take into consideration all of the feedbacks in the system.

One manager who dealt with the workload issue after he attended the learning laboratory explained it this way: “When I came back from the learning laboratory, I had a much better understanding of what the important issues were. Before the lab, I would have said that lack of quality was the only important factor. After the lab, it was obvious to me that productivity was also a key issue. So I restructured some units to enhance their ability to settle claims.

“After I saw dramatic increases in productivity, I applied pressure to improve quality — and I have seen a difference.”

It works

When claims managers integrate the system dynamics approach into their own decision-making, they accelerate the changes that need to occur in the organization. When they “experience” the consequences of their decisions, they are motivated to look for points to intervene in the system, rather than to just rely on older, tried, and supposedly true methods to solve the problems of time availability, quality, and adjuster capacity.

Managers are encouraged to clarify and test their assumptions about why things happen as they do. They make their own mental models explicit, and by doing so can change those models that arc not useful. Besides shortening the learning curve for the many new managers in the company, the learning laboratory accelerates the acquisition of communication skills they need to pursue their goals. Systems thinking provides the language through which management can understand and communicate what to do about the dynamics they experience.

The learning laboratory is a place where managers become familiar with formulating hypotheses, measuring results, and comparing actual results to expectations. When a manger learns through experience to take a systemic view of the operational decisions that must be made, the transfer of learning from a workshop setting or laboratory to the workplace is complete.

The use of systems thinking has given Hanover a competitive advantage in dealing with the complexities inherent in the property and casualty insurance industry.

The use of insurance as a means of transferring costs seems like a simple process. But managing that process is extremely complex. Over time, the connections among cost transfer variables (pricing, taxation, risk transfer) are obscured and become blended with other feedbacks in the system.

“When I came back from the learning laboratory, I had a much better understanding of what the important issues were.”

Then, if we push one lever (such as reducing costs in an attempt to impact profitability) another may go out of balance. Solving one problem almost always creates other problems. Using a learning laboratory to understand the dynamics of systems, so that we know what kinds of problems our current decisions are likely to create down the road, has given Hanover the ability to leverage, balance, and more effectively manage the cost transfer system.

Like many other businesses, the property and casualty insurance industry’s profits are cyclical in nature. Periods of relatively good results lead to intense price competition and the lowering of underwriting standards. This invariably causes deteriorating results and leads to increased prices and tightened underwriting standards.

Over time, the industry begins to experience improved results and increased profits, which initiates the next cycle of intense competition. During periods of unprofitability, the market for insurance becomes highly unpredictable.

Hanover has distinguished itself from its competitors by providing a consistent market to both long-term policy holders and independent agents throughout several of these cycles. By exercising management discipline and understanding the dynamics of the insurance cycle, Hanover is able to balance underwriting, marketing, and investment considerations over periods of years, rather than months. We are able to manage the insurance cycle rather than be managed by it.

By combining the freedom to act with the skill to make better decisions, system dynamics has given Hanover a way to manage change.

Robert S. Bergin is property claim manager for the Hanover Insurance Company in Worcester, Massachusetts, where he is responsible for first-part claim handling philosophy and direction. Geraldine F. Prusko is responsible for litigation management at Hanover Insurance Company. She has 20 years of technical and management experience in the insurance industry and has been a trial lawyer as well as a claim handler.

This article way condensed from ‘The Learning Laboratory ” The Healthcare Forum Journal, March 1990. From The Headlines Certain phenomena occur with such regularity that they constitute a generic set of structures called systems principles. Many of these systems principles are played out in the headlines of newspapers and magazines. The following anecdotes carry lessons for systems thinkers. Eroding Goals “When Tater Tots sales fell in the period from 1985 to 1987, managers first blamed changing eating habits in the U.S. But further study revealed startling news: Cost-cutting had led plant managers to step up line speeds and change storage and cooking methods. Over a decade, the moves had changed Tater Tots. Their once-chunky insides had turned to mashed potato. The outside had lost its light and crispy coating. ‘We were pressing so hard on cost that we were affecting quality,’ says Gerald D. Herrick, president of Ore-Ida Foods Inc. ‘It’s pretty embarrassing.”‘ “Heinz Ain’t Broke, But It’s Doing A Lot Of Fixing,” Business Week, December I 1, 1989. Challenging Our Mental Models On the Chinese New Year in 1989, Mr. Huang, a researcher at AT&T Bell Laboratories who is trying to develop an optical computer, gathered his research group for a progress report. “But instead of talking logic devices and laser diodes, a deadpan Mr. Huang presented each person with an egg and a seemingly impossible mission: to balance it on end. Chinese folklore said the New Year was the perfect time to do it…Eventually, all five researchers man-aged to balance an egg. ‘When we left that room, ‘ Mr. Huang remembers, ‘no one could believe we had ever thought that balancing an egg was impossible.’ Mr. Huang hopes his research will play a similar role in convincing people that optical computing isn’t so difficult that it should be ignored.” “Speed of Light: Is Optical Computing The Next Frontier, Or Just a Nutty Idea?” Wall Street Journal, January 30, 1990. The Systems Thinker 5 April/May 1990

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Anticipating System Behavior

School districts are made up of many components, including district staff, individual schools, teachers and administrators within those schools, parent councils, and students. The sheer number and variety of these actors make it difficult to see their interdependence and to notice how an action in one part of the system affects the others. Add to this complexity policies originating from agencies outside the district, such as state education departments and the U. S. Department of Education, and the task of assessing how best to direct resources to meet students’ needs becomes almost hopelessly confusing.

Systems thinking and system dynamics tools, including casual loop diagrams, stocks and flows, and computer simulation, can shed light on the interrelationships among components and, perhaps more important, illustrate how outcomes may result from feedback loops rather than from simple, linear chains of cause and effect. These tools also make explicit the delays that often occur between a change in one component of a system and its effect on others. The interplay of feedback and delays can produce unanticipated system behavior, as shown by the mandating of smaller class sizes in California. When the legislature passed the new law, schools had to increase the number of classes they offered at each grade level to accommodate the same number of students. To do so, they needed to hire more teachers. Because becoming a teacher through traditional means requires at least four years of pre-service training, the number of teachers available fell short of meeting the needs of all schools. Suburban districts with greater resources filled their spots by recruiting teachers from urban districts, leaving those schools woefully understaffed. Proponents of the new law had failed to anticipate this unfortunate outcome of the change in class size.

By showing the potential behavior over time of multiple scenarios based on specific inputs, computer modeling offers policymakers and administrators the ability to visualize the long-term effects of specific decisions before those decisions are implemented. We can also use models to identify unexpected interactions between system components; ask “what if questions about changes in system parameters; run no-cost experiments that compress time and space; and reflect on, expose, test, and improve the mental models upon which we rely to make decisions about difficult problems. Thus, computer modeling could allow school-system leaders to make more effective decisions by building their understanding of long-term consequences of resource decisions in a complex environment.

Evaluating Professional Development Programs

To illustrate how a district can use computer modeling to analyze its options, I have created a simulation that explores the impact of professional development programs for teachers. Many school districts have responded to the call for better educational performance by implementing a standards-based curriculum. They offer professional development workshops to increase teachers’ ability to communicate this new curriculum to their students. The workshops are often formatted as multi-week summer programs.

Research has shown that teachers can learn to communicate the new curriculum through professional development training, so the question for a district is not whether summer workshops can build capacity, but whether they can do so for a critical mass of teachers in a reasonable time period. What factors play a role in this issue? Which workshops are most effective? What are the costs associated with this form of professional development? These questions are amenable to modeling because we can determine quantitative values for most of the important variables — such as the number of teachers in training and the turnover rate of teachers — and reasonable estimates for the qualitative variables — such as the effectiveness of the workshops and the relationship between the length of the workshop and the willingness of teachers to enroll in it.

I followed these steps to build the model:

1. Define the teacher stocks. All the teachers in the district fall into three stocks: Those who are not familiar with the standards; those who are attending a workshop to learn about the standards; and those who are familiar with the standards.

2. Establish the flow between stocks. Teachers who aren’t familiar with the standards can take a workshop to gain familiarity; teachers in the workshop may become familiar with the standards and move into the “familiar” stock or may not gain much from the workshop and return to the “unfamiliar” stock; and both “familiar” and “unfamiliar” teachers may leave the system each year.

3. Identify and assign values to the important system parameters and variables.

4. Incorporate funding components.

The model is based on the following assumptions:

• The number of teachers in the system remains constant at 10,000, and at the starting point, 10 percent of the teachers are already familiar with the standards-based curriculum. Workshops vary in length from one day to five weeks.
• Ten percent of the teachers leave and are replaced each year (with 10 percent of new teachers entering in the “familiar” stage), and the rate at which teachers leave the system is higher for teachers in the “unfamiliar” pool than in the “familiar” pool.
• In the baseline simulation, 1,000 teachers participate in the three-week workshop; this number can vary up or down by a factor of three.
• Fewer teachers participate in longer workshops, more in shorter ones. However, longer workshops are more effective. The initial success rate for teachers reaching the “familiar-with-standards” stage in a three-week workshop is 30 percent. This base rate increases linearly over time as more and more teachers (those for whom training was not effective the first time) retake the workshop.
• There are 25 teachers in each workshop. The cost of the workshop includes a stipend of $300/week/ teacher for each of 25 participating teachers and an additional cost of $2,500/week for the instructor, supplies, and space.

“Modeling Professional Development” illustrates the model’s basic features.

Analyzing Results

The simulation yields several non-intuitive results, the most important being that these workshops alone cannot adequately deal with the problem of building the necessary capacity in the teacher workforce. Even after 10 years of providing three-week workshops, only 52 percent of the teachers are skilled in presenting a standards-based curriculum — and this number includes teachers who were capable before they enrolled in the workshops. The results clearly show that the workshops do not produce a critical mass of teachers with the desired capabilities in a reasonable amount of time.

Another unexpected result of this analysis is that the five-week workshops result in the largest number of trained teachers over a 10-year period, even though the smallest number of teachers enrolls in them. Holding all else constant, approximately 5,200 teachers achieve the desired level of ability after participating in a five-week workshop, while only about 2,800 teachers reach this stage through one week workshops. The longer workshop is also the most cost-effective per teacher trained: $2,300 per teacher for a five-week workshop; $2,635 for a three-week workshop; and $3,100 for a one-week workshop.

We can generalize this kind of model to other areas of professional development, because the results are independent of the workshop content. Administrators have access to the quantitative data for their district (such as number of teachers in the system, distribution by length of service, teacher leaving rate, funding available for workshops) and can reasonably estimate values for the qualitative variables (such as percent of teachers who require specific professional development, workshop effectiveness, relationship of workshop length to teacher resistance and workshop effectiveness) from prior experience. Plugging these numbers into a computer simulation would give them a general tool for predicting the impact of a summer workshop on professional development in any content area.

Similar models could let stakeholders examine other questions, such as the impact of rationing workshop participation depending on teachers’ average time of service in the system.

Should administrators concentrate on those who will remain in the system longest, that is, younger teachers? Or is there value in offering training opportunities to experienced teachers, who can serve as opinion leaders in changing the system’s culture? This analysis could also be incorporated into an expanded model to include the use of mentors and school and web-based professional development. By exploring these variables as well, districts might come upon a formula for producing a multi-component professional development system with the capacity to bring a critical mass of teachers up to speed on new curriculum requirements in an acceptable time period.

As I hope I’ve shown here, computer modeling offers a valuable planning and decision-support tool for school districts. This approach permits “no-risk” analysis of competing policy choices and resource allocations and, while it does not offer definitive answers, it can help school-system leaders understand the impact of their decisions and guide them toward making better-informed allocations of scarce resources.

Daniel D. Burke, Ph. D., has a broad understanding of K-graduate educational systems. As deputy director for education, the CNA Corporation (CNAC), he leads the research and analysis activities of CNAC’s public education group. Before joining CNAC, Dan was a researcher in molecular biology and produced an extensive record of curriculum innovations. He also played an important role in the National Science Foundation’s K-12 education reform programs.

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A New Threat

SARS emerged this year as a previously unknown virus that is particularly virulent—it is easily spread and can be deadly. Because it kills approximately 15 percent of those infected—the rate is even higher among the elderly—health officials around the world have taken strong steps to mitigate the epidemic and to prevent the public from panicking. In Canada, the great majority of cases were concentrated in Toronto, the country’s largest city and capital of the province of Ontario. From its first news release on March 14 to the latest daily updates on the situation, the Province of Ontario’s Ministry of Health and Long-term Care (MoH, the main governmental department responsible for dealing with the outbreak) sought to inform the public about the progress of the disease and the measures taken to deal with it. Now that the outbreak in Toronto has been suppressed, we can appreciate the impact of this information on public perceptions of and reactions to this health crisis.

A clear and rigorous way to report and interpret data about the spread of infection would help people accurately assess the level of risk.

One element of the daily updates was the summary of relevant statistics on the number of cases of the disease. In keeping with the WHO’s style of reporting on epidemics, the MoH bulletins reported cumulative numbers, in this case the total numbers of probable and suspected cases and deaths to date. Each day, the media reported this cumulative total; some later reports also mentioned cumulative recoveries (referred to as discharges).

I can attest that it was difficult to know how bad the situation was becoming from the raw information being offered. Reporters did little to interpret the data, instead publishing stories about the public’s and their own reactions to the outbreak, to the problems of living under quarantine, and to the few cases of people breaking quarantine. The use of cumulative numbers of cases, discharges, and deaths—numbers that can only increase until the epidemic has run its course—was often confusing and misunderstood. Such information gave no sense of the progress of the disease for example, whether the numbers of cases or deaths per day were increasing, staying the same, or decreasing.

The MoH did eventually include the category of “active” cases in its reports, which gave the public a sense of how many people were currently infected. But confusion was heightened by occasional instances in which the MoH reported tens or even hundreds of potential cases with no clear indication of whether these numbers fell into the active or cumulative category. For the public, this confusion led to the panicked buying of high-quality respiratory masks, cancellation of several large conventions, reduced participation in social activities like sports and cultural events, and a slump in restaurant dining and tourism, with economic side-effects that are still being felt.

A Simple Model

In such public health crises, a simple stock and flow model could clarify the situation (see “Stocks and Flows of the SARS Epidemic”). The stocks would be the “Active” cases— “Probable” and “Suspect.” Their principal inflows would be “New Cases” of each sort discovered each day. The outflows would be the number of “Deaths” (a small figure; the total number in Toronto is 24 as of this writing) and the number of people who recovered from the disease each day, reported as “Discharges.” A final flow from “Suspect” to “Probable” cases would take care of the clinical difference between the two classes.

This model would define the primary data needed to represent different aspects of the outbreak:

• Its onset and its gathering speed with the number of new cases per day.
• Its control and eventual suppression when the number of new cases stays at zero for 20 days (twice the incubation period) and the number of active cases dwindles to zero.
• The requirements for treatment resources based on the number of active cases.
• The treatment success rate as shown by the number of discharges compared to the number of deaths.

All of this information is much more difficult, if not impossible, to assess directly from the current data stream provided by the standard reporting practices. It is not clear what part these difficulties in assessment played in the WHO’s unexpected and unprecedented decision to issue a travel advisory for Toronto (since rescinded). Nevertheless, confusion about the success that public health authorities were having in controlling SARS was certainly part of the issue and continues to inspire efforts to remove the stain on the city’s reputation as a safe place to visit and conduct business.

STOCKS AND FLOWS OF THE SARS EPIDEMIC

In a public health crisis, a simple stock and flow model could clarify the situation by distinguishing between the stock variables (“Suspect” and “Probable”), which give a snapshot of the situation at any given moment, and the flow (or rate) variables, which explain the day-to-day variations in the picture. For more information about stock and flow diagrams, go to www.pegasuscom.com/stockflow.html.

The discovery of a few suspect cases of SARS in Toronto on May 22 and the extension of the voluntary quarantine to a few hundred people demonstrate another element of the dynamic structure—potential but undetected cases. This category exists because of the lack of a precise test for the disease. Without an objective measure of who does or doesn’t have SARS, healthcare workers must make judgments, for example, that an elderly patient suffering from postoperative pneumonia does not have SARS, followed by a realization several days later that this patient does indeed have the disease. Unfortunately, this kind of significant delay in the discovery of problematic cases can perpetuate the epidemic and lead to large social and economic costs.

Using a simple stock and flow model to depict the course of future epidemics could better inform the public so they could make wise individual choices about how best to respond to the health threat.

Wise Choices

This model or a slightly more elaborate version could have reduced some of the confusion surrounding the raw, cumulative data reported during the outbreak. It would have clarified the important distinction between the stock variables, which give a snapshot of the situation at any given moment, and the flow variables, which explain the day-to-day variations in the picture. The usefulness of the stock and flow model is validated by the most recent news reports on the final success of the campaign. These reports include a graphical representation of the number of active cases. The diagram shows a downward trend at a varying rate since the peak of SARS cases on April 18 to May 15, the date of this writing. Such a graphic goes far in highlighting the pattern over time of the outbreak.

Finally, the stock and flow model would identify the important variables—the flows (“New Cases,” “Discharges,” and “Deaths”)—that have to be managed in order to control the outbreak and deal with its economic and social side-effects. For example, an increase in “New Cases” that is not soon matched by an increase in “Discharges” could be a signal to increase resources for treatment (“Discharges”) and quarantine (“New Cases”). Reports of decreasing numbers of active cases should be accompanied by estimates of the probable numbers of deaths or, more positively, by estimates of the probable number of recoveries so as not to give the false impression that success in suppressing the outbreak means no more casualties.

Toronto, like Vietnam before it and more recently Singapore, has shown that SARS can be contained by vigorous efforts to identify and isolate patients (in hospital or in quarantine). Using a simple stock and flow model to depict the course of future epidemics—such as the summertime threat of West Nile virus in North America—could better inform the public so they could make wise individual choices about how best to respond to the health threat.

R. Joel Rahn is recently retired as a professor in the Department of Operations and Decision Systems at Laval University. He has been active in teaching and research in system dynamics for over a quarter century.

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I think of this process as being a soft introduction to the value of systems thinking for addressing complex problems. I have been putting systems thinking into practice and teaching it to others for close to 15 years. During that time, I have developed a spectrum of approaches for softly stimulating acceptance and learning while helping people tackle their most daunting performance challenges. The following are some ways in which I have successfully used systems thinking with a wide variety of organizational clients.

Drop-In/Ad Hoc Applications

For a consultant or facilitator, the use of strategic moments to introduce systems concepts can be powerful. These are those spontaneously occurring situations in a business meeting when the drop-in use of a simple balancing or reinforcing loop can explain or illuminate a previously murky situation. For example, to illustrate the point that organizations get the behavior they reward, I draw the following loop:

The key in such situations is to use natural language to bring the point across. For example, say “these two things affect each other” rather than “these two variables are interdependent” or “this causes the behavior to spiral out of control” versus “this is a reinforcing loop.” The use of systems thinking jargon right off the bat can be off-putting and perhaps even perceived as hostile (, “sit-up, pay attention, you’re not smart enough yet to realize this”). Metaphors (, “this process works in the same way that a thermostat controls the temperature in the room”) assist people in feeling they have discovered something useful or relevant rather than something they “must know” or “must do.”

In addition, I remain particularly vigilant for problems that recur or never seem to go away no matter what fix the organization applies. This pattern of behavior not only indicates to me that a systemic dynamic is in effect but also that the group is probably ready to try something different. In these instances, because of the team’s frustration with the status quo, their readiness for learning is usually high.

Example. During a strategic planning meeting with the public health department of a large city, the group articulated what had sufficed for a master strategy in the past. I wrote the two items that they had been speaking about on a flipchart and connected them with arrows:

The group recognized this diagram as representative of their implicit strategy:, “To make ourselves indispensable so that we can pursue being progressive in public health matters, and to be progressive so that we will be indispensable.” Without being aware that the diagram was a systems loop, the group understood that it represented their collective thinking in a quick and visible way. The loop became a touchstone as the group made decisions about when and where this master strategy was still in effect and when and where it was not. Through this simple exercise, people from diverse backgrounds were able to reach a sophisticated understanding of the system’s behavior and make better informed decisions than before without feeling pushed to learn something new.

Tutorials

Another method I have found useful is to offer a short tutorial or “miniteach” on systems thinking. This lesson contains the basic elements with examples customized for the business model at hand. Because it links to the organization’s most vexing problems, the mini-teach can create buy-in for the methodology and value for the organization.

Workshop or Systems Think-Tank

For organizations that are more advanced in their readiness and understanding, a formalized workshop approach can further the application of systems thinking tools and methods. The learning objectives of such a workshop are:

• A deep understanding of and experience with the concepts and tools of systems thinking
• Application of systems thinking to key issues in order to uncover leverage points/strategic actions
• Increased capability to apply systems thinking to key issues

The process for such a workshop involves:

1. Introducing systems thinking tools, especially archetype templates, to offer new perspective on the “real” problems and leverage points for doing something about them
2. Thoroughly investigating one problem/area/system as a “laboratory” for whether or not systems thinking will work for the organization
3. Agreeing on fundamental actions to take
4. Assessing where to go/what problem to address next, based on the workshop experience

FAILING TO 'FIX' TECHNICIAN CAPACITY

To free up technician capacity, the company offered incentives for customers to install the high speed modem and software themselves. As the ratio of technician to customer installs declined, technician capacity freed up, reducing the need for additional capacity. However, later self-installers tended to be less computer-savvy than earlier ones; for this reason, the volume of calls for assistance and truck rolls increased, creating a greater need for capacity once again.

Archetypes

Archetypes are useful gateways into systems thinking. Because they represent a “blueprint” of human activity, they are applicable and understandable across a wide variety of individual experience. Many people respond to the stories that the archetypes encompass and recognize current or past problem patterns from the descriptions.

I find that business leaders can easily relate to the universal wisdom contained in “Shifting the Burden” and “Fixes That Fail,” although I seldom use that terminology. These archetypes in particular reveal how quick-fix problem solving fails to address root causes and undermines a team’s ability to utilize more fundamental solutions.

Example. I used the “Shifting the Burden” archetype to help a group of senior vice presidents at the home entertainment division of a movie studio to portray the decision-making process in effect between them and their executive vice presidents, their superiors. The senior VPs felt that decision-making at the highest level wasn’t timely or of high quality, leading to missed deadlines, increased costs, and dissatisfied employees. In conversations with both the senior and executive VPs, I was able to “draw out” the system (see “Declining Decision-making”).

DECLINING DECISION-MAKING

Because executive VPs felt accountable for the organization’s success or failure, they kept tight control over decision-making. The unintended consequence was lack of trust, which undermined shared decision-making in the organization. Senior VPs felt that a more sustainable solution would be for the executive VPs to delegate decision-making authority for individual projects to them.

The senior VPs perceived that the executive VPs felt accountable for the organization’s success or failure. The executive VPs’ response to that accountability was to keep tight control over decision-making—effectively making most decisions themselves. The unintended consequence was lack of trust in the organization. Also, the senior VPs felt that they weren’t empowered to make decisions of any consequence. They believed that a more sustainable solution would be for the executive VPs to delegate decision-making authority for individual projects to them.

The portrayal of the dynamic with this diagram had multiple effects. It allowed the two groups to conduct a depersonalized conversation and to collaborate to “attack the problem, not the people.” The graphic also let the executive VPs explore why they felt that they were solely responsible for the organization’s success or failure. As a result of these discussions, the executive VPs have delegated more decision-making to senior VPs. They now conduct problem-solving sessions with a focus on organization-wide issues rather than product-specific issues— focusing on decisions that only they can make.

It’s important to notice here that I never once termed this diagram an example of the “Shifting the Burden” archetype or introduced reinforcing or balancing loops. I simply identified a natural, recognizable pattern and put it into a picture with terms relevant to the leaders who were exploring the situation. Not only did

Check-ups or maintenance programs use objective measures of a system’s performance to periodically diagnose problems that might not be apparent to someone on the inside

this approach allow the VPs to come to terms with a serious and difficult situation, it also gave me license to continue to use this method elsewhere in the organization.

Organizational Assessments

I frequently use systems loops during organizational assessments, where the purpose is to evaluate what’s working and what needs attention. By presenting my observations in the form of a diagram, I have found that teams of businesspeople can come to quick agreement about the problem, which leads to quicker agreement on solutions.

Example. I conducted an assessment of the relationship between the executive director and the board of directors for a Boston-area community health clinic. The relationship had broken down and resolution was not forthcoming. Using the tools of systems thinking, I revealed in a non-blaming way what I saw to be the current relationship pattern (click here to go to “Assessing Organizational Dynamics”). As a result, the group was able to conduct a difficult conversation in a truthful manner. This process led to breakthroughs in trust, openness, and role clarity between the board and the executive director.

As I saw the situation, the quality of the relationship between the executive director and the board had declined, which in turn had reduced trust and openness about the clinic’s financial and operational situation.

The lack of openness was a reason for the increase in turnover among board members and a decline in the clarity and meaningfulness of the role of the remaining members. That decline reduced the willingness of the board as a whole to contribute and raise funds for the organization. The drop in fundraising and contribution of the board led to the perception that the board was not an entity that added great value to the organization, further eroding the quality of the executive director–board relationship.

An additional loop fed off of the main loop, wherein the decline in trust made it difficult to recruit board members and keep the size of the board at the level that was required by the workload. This rise in the work demands on the remaining board members led to an increase in their sense of fatigue and, ultimately, a surge in board turnover.

This depiction, whether completely accurate or not, got all the variables “in the room” and made them discussable. It also showed the impact that each variable was having on the others, so that all could “own” the system rather than attribute the problem to either the executive director or the board.

In using systems loops in assessment situations, it is important to communicate that they represent just one person’s way of perceiving the situation—it may be right, it may be wrong, but it gives the group a starting point to non-judgmentally consider a situation and what to do about it. In this case, systems thinking is much like a shared vision: it is not so much what it actually is that matters, but what it does for people.

People and organizations change—rapidly, strongly, thoroughly—when ready to change.

Key Lessons Learned

To summarize, here are some of the key lessons I have learned in using systems thinking as a business tool and transferring the capability to others:

• Limit the jargon—it can be off-putting to people. Use as much familiar language as possible.
• Seek out natural applications versus forced ones. Let the teaching and application come out of a current business situation. Drop in the lesson rather than force-feed the group with a systems thinking curriculum.
• Appreciate and validate people’s existing wisdom and experience. Convey that systems thinking is a col- lective language for us to think and act clearly together around that existing capacity.
• Look for instances of frustration with long-standing issues. These situations are ripe for a systems approach, and people will likely be ready to look at them with fresh eyes.
• Help people see the interrelationships that are intuitive but not collectively represented. Use simple loops and build from there.

As one client put it, “This is a means to see the complexity of the business and to recognize that most of the time we can’t do quick fixes and expect to succeed. While our culture supports ‘just fix it, now!’ we must develop a level of understanding and tolerance for complexity.” For me, this kind of understanding is one of the best outcomes of all.

Jack Regan is principal of Metis Consulting Group, Inc., a management consulting and training firm whose mission is to initiate and build workplace communities where individuals and organizations realize the results that most matter to them. Over the past 16 years, Jack has focused on the design, facilitation, and management of organizational change. He has worked with leaders and teams in a variety of industries and communities on strategic thinking, planning, and implementation, and has used his consultation expertise to enable clients to produce both demonstrable business results and relevant cultural renewal.

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I’ve had a Honda gas-electric hybrid car for less than a month. It has taught me a whole new way of driving, thanks to feedback from its instrument panel. An indicator flashes a string of orange lights when the nickel-hydride batteries kick in to help the little gas engine accelerate or pull uphill. When I decelerate or go downhill, green lights show the gas engine recharging the batteries. Light brake pressure sends the meter to a green maximum. So now I avoid sudden stops. I try to glide into stoplights, braking gently from a long distance away.

There are three odometer/ mileage meters. One I reset as I start each trip. One I reset when I fill up with gas. The third keeps track of miles and mileage over the life of the car. At the moment, that third meter reads 1,600 miles at an average 56 miles per gallon. The latter number is rising as the car teaches me to drive more efficiently. The last fill-up carried me 660 miles at an average 71 miles per gallon. Some days I can get more than 80 mpg on my commute to Dartmouth.

The most effective feedback comes from the instantaneous mileage meter, which zooms up and down according to my gas consumption at every minute. Long uphill in third gear: Ouch!—it’s under 25 mpg. Cruising on the flat: not bad, 75 mpg, maybe if I ease off the gas a bit, I can get it up to 80. Long downhill: shazam! Off the scale at more than 150!

This meter runs my life, or at least my driving. No more jackrabbit stops or starts. No way, when I see the result on the mileage meter, do I gun my engine. I find myself going slower than I’m used to. I conform almost perfectly to speed limits. My commute takes about one minute longer, a small price to pay for cutting my gas cost in half.

The habit I find hardest to shake is driving according to the urge of the driver behind me. When someone crowds me impatiently, I used to speed up—but now I see my mileage drop when I do. For a while I speeded up anyway. Then I started thinking, “Why should I contribute to the frying of the planet just because you’re in a hurry?”

Whatever you think of my driving, my point has to do with the power of feedback. Three weeks of information I never had before have changed 40 years of ingrained driving habits. I didn’t have to be coerced or rewarded; I didn’t have to change my values. I just had to see how my actions did and did not conform to my values.

The Viridian Meter

Which brings me to the Viridian Meter. There is a crazy Web site (www.bespoke.org/viridian) run by science fiction writer Bruce Sterling and dedicated to the proposition that industrial design needs to be more environmentally conscious and less ugly. The site features catalog ads for imaginary products that Sterling and his friends think someone should invent. One of them is the Viridian Meter.

“One of the most offensive artifacts of the twentieth century is the standard household electricity meter. This ugly gizmo clings like a barnacle to the outside of your home, readable only by functionaries. Clumsily painted in battleship gray, this network spy device features creepy, illegible little clock-dials under an ungainly glass dome. Look a bit closer and this user- hostile interface deliberately insults you with a hateful anti-theft warning and a foul little lockbox.”

“This crass device is designed to leave you in stellar ignorance of your own energy usage. It publicly brands you as a helpless peon, a technically illiterate source of cash for remote, uncaring utility lords.”

“But today, thanks to the Viridian Electrical Meter, the tables are turned. The Viridian Meter is not some utility spy device, but a user-owned art object!”

The ideal meter would be so beautiful or dynamic or fascinating that you would want it in your living room. You would watch it rise as someone turns on an electric hairdryer. You would cheer as more efficient lightbulbs cool its angry red, say, to soothing green. Maybe it would read in dollars instead of kilo- watt-hours, so you could watch your electric space heater dribble your paycheck away. Maybe it would show less greenhouse gas pouring into the atmosphere as you switch off lights in empty rooms.

Whatever a Viridian Meter would look like, I want one. I want it to teach me, as my new car is teaching me, the actual effects of my decisions. I want another meter to register my water use and another to gauge fuel consumption as I open doors, wash dishes, caulk windows, take long showers, or buy an efficient washing machine.

I suspect that all it would take would be some well-placed user-friendly feedback to change the world.

Donella Meadows is the director of the Sustain- ability Institute (www.sustainer.org) and an adjunct professor of environmental studies at Dartmouth College.

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