In fact, such an event did occur in Sweden in 1992, when the OK Petroleum company successfully lobbied for an increase in the country’s tax on leaded gasoline. This surprising action stemmed from OK’s development of a high-octane (98) lead-free automobile fuel, which burned cleaner than other fuels while still maintaining high performance. The Swedish government agreed to the tax because it was in alignment with its own clean air policies and with international conventions that it supported. Since OK had the only lead-free product on the market, the gas tax gave the company a significant price advantage at the pumps. “The competition was forced to follow suit,” explained OK’s Per Wadstein, leading to cleaner air for all of Sweden.

Economy vs. Ecology

Economy and ecology arc often pitted against each other in the “profitability versus environment” debate. There is a perception that companies can either prosper financially or take care of the earth, but not both. However, as OK Petroleum showed, these pursuits do not have to be mutually exclusive. In fact, ecology and economy derive from the same Greek root, eco, meaning house. (Ecoloqy stands for “study of the house,” and economy means “management of the house.”) This etymology suggests that the two concepts are not contradictory, but actually part of the same larger idea. I low, then, can we study and manage our “house” (the earth) in ways that benefit both industry and society over the long term?

The “Systems ‘Thinking for a Sustainable Future” initiative, based at the MIT Center for Organizational Learning, provides a set of principles, practices, and processes that recognize and reinforce the synergistic link between long-term economic and ecological development. It seeks to provide industrial decision-makers with both a conceptual, framework stud practical tools for building financially healthy companies that arc also ecologically sustainable. In addition, the initiative attempts to foster learning environments in which various stakeholders can grapple with the larger issues of the day. The hope is that within these settings, the participants will create presently unimaginable solutions to some of the world’s most intractable problems.

Sustainabillty

What do we mean by “sustainable”? A sustainable society is one that is self-perpetuating over the long term—meaning that it uses resources at a rare that does not exceed the rare at which they can be replenished, and that it produces waste materials at a pace that does not exceed the rare at which they can be reabsorbed by the environment. Within this framework, a sustainable organization can be described as a company that provides customers with goods and services for living a satisfying life, while maintaining both a healthy balance sheet and a healthy balance with the natural world.

Creating environmentally sustain-able business practices used to be considered a choice for businesses—an optional activity for those companies that had the time, energy, and interest. But now it is becoming a more mainstream concern, due to several trends:

• The marketplace is demanding “greener” products that reflect environmentally responsible management. Supermarket aisles are filled with products that proclaim their eco-friendliness—from phosphate-free detergent and acid-free paper to recycled cardboard and “dolphin-safe” tuna.
• Material resources are becoming more scarce, resulting in a rise in production costs in many industries. For example, integrated steel producers virtually disappeared in the U.S. during the 1980s because the costs of mining iron ore grew financially prohibitive as the availability of that resource decreased.
• Regulatory compliance is becoming an increasingly costly concern. One petroleum company’s environmental compliance costs topped $1 billion in 1994—a figure that exceeded the company’s net profit for the year.

How can business managers think systemically about a sustainable future? How can they balance needs for economic prosperity and ecological survival? To address these challenges, companies need to expand their current strategic thinking to include economic and ecological concerns—creating what W. Edward Stead and Jean Garner Stead call “sustainability strategies.”

A Conceptual Framework

The Natural Step movement. which originated in Sweden, offers clear conceptual framework for creating such sustainability strategies. Lei Dr. Karl-Henrik Robert. The Natural Step has proven to be one the most effective sustainability movements in the world, aligning diverse social business and ecological interests around fundamental scientific principles of natural systems. The Natural step process has been studies: and practiced by corporate managers, urban community members, youth at risk, and schoolchildren; it has been shared via books, audiotape, board game, or CD-ROM with every household in Sweden. It is an approach that does not blame any one sector of society for our current problems, but rather encourages all of us to find ways to contribute CO effective solutions.

The guiding principles of The Natural Step, known as the “four systems conditions,” are derived from the basic hews of thermodynamics: matter cannot disappear, and matter tends to dispense (see “The Four Systems Conditions”). By using the four systems conditions to evaluate whether their products and services are economically and ecologically sustainable, some of Sweden’s largest corporations have produced significant changes in their business strategies.

For example, the ICA supermarket chain in Sweden was asked frequently by its customers whether its refrigerators and freezers emitted CFCs, which are linked to ozone layer damage. After familiarizing themselves with the four systems conditions, ICA’s leadership engaged in a conversation with Electrolux (Eureka in the U.S.), their primary vendor of refrigeration products. Aware that CFCs, a non-biodegradable, unnatural compound, violated systems condition 2, ICA’s leaders asked Electrolux what it would cost to eliminate this compound from their existing inventory. After some technical hedging, Electrolux designers answered that it would take 1 billion Swedish crowns (approximately $140 million) to convert to soft freons—another persistent and unnatural compound, but one that is thought to be less damaging than CFCs. The CEO’s response was, “You want me to invest 1 billion crowns in a product, of which the only thing I know for sure is that it is doomed to failure?! Please come up with a more suitable alternative.”

Electrolux, which had not previously encountered The Natural Step, subsequently phoned Dr. Robert and asked him to come “talk about your damned systems conditions.” A short time later, the Electrolux team announced the development of an interim compound that does not harm the ozone and that is now successfully being manufactured and marketed as a “green” refrigerant. The company is also well on its way to producing a refrigerant that is biologically harmless. As a result of its work with Dr. Robert and his colleagues, Electrolux has begun employing The Natural Step method throughout the company, and is now using the four systems conditions as a framework for its strategic planning process.

Integrating Sustainability Strategies and Organizational Learning

While the four systems conditions offer a basic conceptual framework for creating sustainable business strategies, they do not provide a specific process whereby those principles can be used to develop and implement such strategies. This is where the disciplines and tools of organizational learning can help. For example, the tools and methodology of systems thinking provide a means to test the long-term implications of policy decisions on the wider environmental system.

Systems thinking can also provide an overarching framework for understanding the industrial, governmental, and environmental interactions that play a role in sustainable development (see “The Sustainability Challenge”). An overall increase in industrial productivity (such as the U.S. has experienced for most of the 20th century) leads to a reinforcing cycle of economic growth and profitability (R1), but it can also lead to an accumulation of industrial wastes in the environment. In the U.S., this has led to heightened regulatory pressures designed to reduced waste.

At the same time, increased consumer awareness of the environmental impact of production is leading to emerging new market opportunities in terms of “clean” technologies (B3), which, for those companies that invest in them, can lead to profitable alternatives to unsustainable production techniques (R4). However, the subsequent increase in regulatory compliance costs can constrain profits (B2), which can potentially limit industry’s ability to invest in “clean” technologies (R4).

The disciplines of team learning and mental models also have much to offer in that they can help generate more informed, productive conversations. In the ecology/economy debate, dialogue skills of genuine inquiry, deep listening, displaying one’s own line of reasoning, and respect for other view-points are critical, as are the ability to surface our mental models and to inquire into those of other people (see “The Power of Mental Models”). Through the use of dialogue and role-playing, we can gain deeper understanding of diverse points of view and bring out new ideas and solutions that a single point of view might not have produced.

In a recent learning laboratory at a petroleum company, for example, role-reversal, dialogue, and consensus-building tools were used to develop a new framework for environmental leadership. As part of the workshop, employees from the environmental engineering division took turns role-playing the traditional contestants in the environmental debate: “Government Bureaucrats,” “Tree-Hugging Environmentalists,” and “Big Bad Business.” By humorously taking on their worst perceptions of each other, participants were able to see beyond the stereotypes that they had placed on their professional adversaries.

The Sustainability Challenge

Heightened consumer awareness of accumulated industrial wastes has led to heightened regulatory pressures designed to reduce waste. However, the subsequent increase In regulatory compliance costs can constrain profits (B2) which can potentially limit Industry’s Investment in “clean” technologies (R4).

In the dialogue that followed, the engineers gained insights into the motivation, logic, and humanity of the various stakeholders, and were better able to understand the validity and utility of each point of view, even if the perspective challenged their own position. The engineers found that their subsequent meetings with EPA representatives on a difficult Clean Air Act project were significantly enhanced in terms of quality of communications, creativity of thinking, and efficacy of solution generated—all as a result of their experience in the workshop.

Organizational Learning for a Sustainable Future Integrating sustainability strategies and organizational learning—one approach focused on content (where we need to. go) and the other focused on process (how we’ll get there)—may hold unprecedented potential for producing sustainable ecological and economic development. We have termed this synergy Sustainable Organizational Learning (SOL). Although the development of SOL is only in its initial stages, we can imagine a variety of learning practices through which SOL practitioners will work toward long-term economic and ecological sustainability:

• Aligning industrial cycles and natural systems. Conversations around strategy and future planning will include the question, “What business activities should we engage in that will be aligned with the systems conditions for sustainability?” The answers to this question will strongly influence investment decisions with respect to new products and services. In this way, SOL practitioners will begin to align their company’s industrial cycles with natural systems.
• Building cross-company consortiums. By building consortiums of companies engaged in a similar inquiry, sustainable learning organizations will participate in company-to-company conversations that will enable them to learn from each other’s challenges and successes in the pursuit of sustainability strategies.
• Engaging in ongoing practice. By studying and practicing the disciplines of SOL, practitioners will foster new learning in themselves, their compa

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What Does Systems Thinking Involve?

Why Use Systems Thinking?

Systems thinking expands the range of choices available for solving a problem by broadening our thinking and helping us articulate problems in new and different ways. At the same time, the principles of systems thinking make us aware that there are no perfect solutions; the choices we make will have an impact on other parts of the system. By anticipating the impact of each trade-off, we can minimize its severity or even use it to our own advantage. Systems thinking therefore allows us to make informed choices.
Systems thinking is also valuable for telling compelling stories that describe how a system works. For example, the practice of drawing causal loop diagrams forces a team to develop shared pictures, or stories, of a situation. The tools are effective vehicles for identifying, describing, and communicating your understanding of systems, particularly in groups.

When Should We Use Systems Thinking?

Problems that are ideal for a systems thinking intervention have the following characteristics:

• The issue is important.
• The problem is chronic, not a one-time event.
• The problem is familiar and has a known history.
• People have unsuccessfully tried to solve the problem before.

Where Should We Start?

When you begin to address an issue, avoid assigning blame (which is a common place for teams to start a discussion!). Instead, focus on items that people seem to be glossing over and try to arouse the group’s curiosity about the problem under discussion. To focus the conversation, ask, “What is it about this problem that we don’t understand?”

In addition, to get the full story out, emphasize the iceberg framework. Have the group describe the problem from all three angles: events, patterns, and structure (see “The Iceberg”).
Finally, we often assume that everyone has the same picture of the past or knows the same information. It’s therefore important to get different perspectives in order to make sure that all viewpoints are represented and that solutions are accepted by the people who need to implement them. When investigating a problem, involve people from various departments or functional areas; you may be surprised to learn how different their mental models are from yours.

How Do We Use Systems Thinking Tools?

Causal Loop Diagrams. First, remember that less is better. Start small and simple; add more elements to the story as necessary. Show the story in parts. The number of elements in a loop should be determined by the needs of the story and of the people using the diagram. A simple description might be enough to stimulate dialogue and provide a new way to see a problem. In other situations, you may need more loops to clarify the causal relationships you are surfacing.

Also keep in mind that people often think that a diagram has to incorporate all possible variables from a story; this is not necessarily true. In some cases, there are external elements that don’t change, change very slowly, or whose changes are irrelevant to the problem at hand. You can unnecessarily complicate things by including such details, especially those over which you have little or no control. Some of the most effective loops reveal connections or relationships between parts of the organization or system that the group may not have noticed before.
And last, don’t worry about whether a loop is “right”; instead, ask yourself whether the loop accurately reflects the story your group is trying to depict. Loops are shorthand descriptions of what we perceive as current reality; if they reflect that perspective, they are “right” enough.

THE ICEBERG

How Do We Know That We’ve “Got It”?

Here’s how you can tell you’ve gotten a handle on systems thinking:

• You’re asking different kinds of questions than you asked before.
• You’re hearing “catchphrases” that raise cautionary flags. For example, you find yourself refocusing the discussion when someone says, “The problem is we need more (sales staff, revenue).”
• You’re beginning to detect the archetypes and balancing and reinforcing processes in stories you hear or read.
• You’re surfacing mental models (both your own and those of others).
• You’re recognizing the leverage points for the classic systems stories.

Once you’ve started to use systems thinking for inquiry and diagnosis, you may want to move on to more complex ways to model systems-accumulator and flow diagrams, management flight simulators, or simulation software. Or you may find that adopting a systems thinking perspective and using causal loop diagrams provide enough insights to help you tackle problems. However you proceed, systems thinking will forever change the way you think about the world and approach issues. Keep in mind the tips we’ve listed here, and you’re on your way!

Michael Goodman is principal at Innovation Associates Organizational Learning

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As we will see, most organizations and people have mastered the ability to adapt to new situations and challenges. They can learn and improve, as long as the basic causes of their success do not change. But sometimes managers and enterprises become addicted to old ways of operating and making decisions, and thus fail to function well in a new environment. The result is decline. To understand the powerful dynamics that cause this turn of events, we must investigate the systems within which these organizations and managers operate.

Adaptation Versus Addiction

Adaptation and addiction differ in subtle ways. Adaptation takes place when we observe the symptoms of a problem and then take an action that counteracts the problem. Addiction occurs when we observe the symptoms of a problem and then take an action that suppresses the symptoms of the problem but makes the actual problem worse.

For example, lei’s say that you have just moved to a new area and find yourself spending a great deal of time alone. The number and quality of your social relationships are important indicators of the health of your personal system. Moving causes a decline in your system’s health when it leads to loneliness. An adaptive response to your loneliness could be to get involved with activities in your new community, to make connections with people at your new workplace, or to join a few clubs with members you find compatible.

The cause-effect mechanisms at work in this process are illustrated in the diagram “Adaptation” (p. 2). If the quality of your social life is important to you, then any change that causes loneliness in effect decreases the health of the system. After a delay, perceived health also goes down. When perceived health declines, the gap between perceived and desired health—between where you think your health is and where you want it to be—increases. So you take action to close the gap. In an adaptive system, the consequence of an action counteracts the problem and restores the health of the system. The whole process is a balancing loop that holds perceived health close to the level of health you actually desire.

But let’s look at another scenario, one of addiction. Say that when you find yourself feeling lonely, rather than trying to meet people, you have a few drinks. Drinking alcohol depresses the emotional center in your brain that causes you to experience loneliness. Thus, over the short term, the alcohol suppresses the symptoms of loneliness (sadness, self-pity, and so forth). But when you drink to an extreme, the quality of your social life deteriorates even further, making you even more lonely. So the action you took to ease the problem eventually only worsens it.

The cause-effect relations involved in addiction have two subtle differences from those associated with adaptation (see “Addiction” on p. 3). First, we take an action whose consequence raises our perceptions of the health of the system, but not the actual health. Second, our action actually damages the system’s real health.

Addiction, therefore, is a process by which an external problem can send us into a damaging cycle that quickly feeds on itself. Eventually, we don’t even need an external problem to spur us to take action; we simply generate our own internal problems through our addictive behavior—like someone who drinks salt water to quench his or her thirst.

Unfortunately, it is fairly easy to slide from adaptation into addiction, because it is usually difficult to measure the true health of any system. We often rely on symptoms—indirect measures—to determine the perceived health of the system. But information about symptoms typically comes to us only after a delay. The information also may contain deliberate biases or random errors. As a result, we take an action – that will eventually damage our true health, because the short-term symptoms cause us to feel better than we did before. A classic example of this pattern is smoking cigarettes, which can bring us immediate pleasure, but will also damage our health in the long run.

An Addictive Response in Organizations

Enterprises often become addicted to patterns of behavior that have brought them success in the past. They persist in pursuing policies that are no longer productive, until there is some sort of collapse within the organization, such as excessive outsourcing of technology until there is virtually no internal capacity left. This failure can happen when the feedback loops governing the firm’s success manifest a phenomenon called shifting dominance.

The “dominant” loop in a system is the one that principally controls the system’s behavior over a certain, often extended, period of time. When one loop dominates for a decade or more, a whole generation of managers, a set of control systems, and even a mythology grow up around the lever points that activate the loop governing the enterprise’s success; for example, “Marketing promotions are always the answer to a sales slump.” The company leaders see these lever points as the keys to their prosperity and act in ways that reinforce them.

But eventually, any loop will lose its dominance; another set of causal mechanisms will become more important. Then the usual lever points no longer lead to success, and the managers are left with a heritage of ineffective policies and irrelevant myths. At this point, the firm should drastically revise its policies. But often it simply redefines its measures of success so that the old policies still appear attractive. Why does this occur, and what can we do to prevent it from happening?

The Market Growth Model: Shifting Dominance at Ace Electronics

The concept of shifting dominance first became real to me in the 1960s when I encountered a model created by David Packer, an early member of the Industrial Dynamics Group at the Massachusetts Institute of Technology’s Sloan School of Management. Out of the group’s investigations evolved an elegant theory, later called the Market Growth Model, that illustrates the mechanics and importance of shifting dominance.

Packer and his colleagues applied system dynamics to a firm I will call Ace Electronics. In its earliest days, Ace had an enormously superior product. Its sales were limited only by the company’s capacity to market and sell the product. The dominant loop governing the firm’s profits was composed of its expanding sales force, growing orders and backlogs, swelling production capacity, and increasing deliveries (R4 in “Market Growth”). Because the budget for the marketing and sales department was a percentage of sales income, its budgets expanded, and the sales force grew even more. This loop produced rapid growth.

For a long time at Ace, the market growth loop was dominant, and a group of people who knew how to make this loop operate moved up through the firm’s ranks. However, eventually the dominance shifted within the system (B5 in “Market Growth”). The sales force booked far more orders than the factory could produce, so the order backlog started to increase. When the sales force could not promise timely delivery in a technologically sophisticated and rapidly changing market, its effectiveness in booking new orders declined. Sales began to drop. Before, expanding the sales force increased profits; now it cut into them.

When we find ourselves unknowingly caught up in a situation of shifting dominance, we often blame each other for our faltering fortunes. Ace is a perfect example of this phenomenon. We can imagine that the company leaders agonized over why the sales staff wasn’t as good as it used to be, what kind of new incentives were needed to whip the sales staff back into shape, and so forth. But in shifting dominance, the problem actually originates within the system in the form of an addiction to the old ways of doing things. Managers can push a sales force as hard as they like and still fail to revive sales—the system simply doesn’t respond to this kind of force when the control has shifted to a different loop.

As one particularly destructive result of Ace’s failure to adapt to change, the company eventually developed an addiction to a new, short-term “solution”: downsizing. Many companies fall into the trap of firing people in order to make the bottom line look good on the next quarterly report. Downsizing lowers costs and temporarily kicks up profits. But if it’s not done well—and often it isn’t—downsizing also drastically reduces the quality and size of the staff and dulls a company’s competitive edge. As its niche shrinks, the company has to fire even more people in order to boost its profits. The addictive cycle of downsizing takes over.

The Difficulties of Breaking Addiction

If the pitfalls of addiction seem so obvious, why is it so difficult to break out of addictive processes? There are three main forces that work against an individual or organization seeking to break the cycle of addiction.

The Pain of Withdrawal. One reason is that withdrawal is extremely painful. Remember that perceived health, which drives our actions in the addictive system, is affected by two factors: actual health and the consequences of the actions we take (see “Addiction” on p. 3). These addictive consequences progressively damage actual health, which means that we have to take more and more of the addictive action to offset the consequences. The process becomes a spiral of increasing use.

Codependency. When we get ourselves into the trap of addiction, it’s astonishing how the various components of the system work in collusion to sustain the addictive behavior. This subtle reorganization of the system to support the addictive action is called codependency and is another reason that breaking an addiction is so difficult.

Drifting Goals. Addiction has many forms. One interesting variant of the addictive structure occurs with the addition of a causal link that produces what is commonly known as “Drifting Goals.” If we don’t get what we want, we start to want what we get. When we lower our aspirations, the addiction causes progressive deterioration of our goal.

If we don’t get what we want, we start to want what we get.

For example, imagine a firm that borrows more and more in order to finance its operations. One symptom of a company’s health is its debt-equity ratio; there are industry standards that indicate the appropriate ratio of debt to equity in a healthy firm. When debt rises above this level, a company will undertake efforts to increase profitability or sell off assets to reduce debt. But if these efforts fail and the debt-equity ratio remains high, management may get used to the higher levels of debt and stop trying to reduce them. Spokespeople for the firm may even develop elaborate rationalizations indicating why the higher levels are acceptable. Of course, over the long term, high levels of debt can be fatal to an organization.

Understanding and Changing Systemic Structure

Addictive behaviors, with their self-perpetuating, destructive cycles, can seem particularly stubborn. But cycles of addiction can be broken, allowing us to respond more adaptively to situations of shifting dominance.

What is the key to breaking addictive responses in organizations? One place to begin is to familiarize ourselves with the laws of systemic behavior and learn to work with these laws (see The Fifth Discipline by Peter Senge). Most of the principles of systemic behavior apply directly to the process of addiction and contain the seeds of a solution (see “Moving Beyond Organizational Addictions” on p. 4).

The most effective way to combat organizational addiction is to learn to understand the system. When we do that, we can anticipate an imminent shift in dominance and prepare ourselves for it; in other words, we can design an adaptive instead of an addictive response. We can also identify opportunities to create new feedback loops that let us catalyze a desirable shift in dominance. But beware of spending too much time creating loops that aren’t going to dominate. The key is to make a change that will grip the system and take it down a different path.

To beat personal addictions, we often must place our trust in the potential of the system to change. Likewise, in organizations, if we build up confidence in a group’s ability to work together, to stay committed to each other, and to cope with problems in a way that will produce satisfactory results in the long run, we can get through withdrawal together. With the high turnover rates the business world is experiencing under downsizing, it has become harder for workers to place their faith in anyone or to adopt long-term perspectives. However, only trust can help an organization establish a sense of stability. Despite all the pressures to do otherwise, we must work to cultivate a culture of trust.

Herman Daly, a leader among economists in analyzing sustainable development, once made a statement that is profoundly applicable to the challenges discussed in this article: “The paths to sustainability are unknown, not because they’re hard to find, but because we never looked.” Let’s start looking for long-term solutions to organizational addictions.

Dennis Meadows is director of the Institute for Policy and Social Science at the University of New Hampshire. He directed the system dynamics graduate program at Dartmouth College for 16 years. He has written eight books that apply systems thinking to social and corporate issues.

Editorial support for this article was provided by the editorial staff and Joy Sobeck.

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The potential for measurement error is therefore an important modeling consideration. Traditional analytical approaches often leave out qualitative factors because they are hard to measure and reduce the precision of a model’s results. But the importance of measurement error diminishes when the investigative focus shifts from concern over the system’s current state to understanding the system’s behavior over time, which is often the purpose of a system dynamics model.

Measurement Error

In traditional business analysis, conceptual (pen-and-paper) models might contain a mix of quantitative and qualitative factors, but such models rarely advance past the theoretical stage. Traditional formal (computer) models usually either bury qualitative factors within more quantitative assumptions or leave them out entirely. As a result, organizations over the years have focused much more of their analytical attention on easily measurable “hard” factors (for example, production output, lines of code, or cash flow) than on “soft” variables (for example, employee morale, efficiency of code, or customer satisfaction). But these soft factors are important components of the system structure: They can strongly influence the performance of the system. So one of the key steps to understanding dynamic social systems is crafting and using simple but explicit and sensible measures for qualitative variables.

It is important to keep in mind that any measurement will contain some degree of error. For variables that have well-established units—feet, pounds, liters, volts—the measurement error is usually a function of the accuracy and precision of the measuring device. For example, if the smallest gradation on a ruler is 1/32nd of an inch, then any measurement taken with that tool may be off by as much as 1/64th of an inch. Whether this fundamental type of error is significant depends on what is being measured and the purpose of the measurement.

For soft variables that don’t have well-established units of measure, measurement error arises from two additional sources: the definition of a unit of measure and the creation of a measurement tool. For instance, when trying to measure customer satisfaction, we might invent a unit of measure, such as the customer satisfaction index. Through survey instruments, focus groups, and other tools, we could then come up with a number to represent our best estimate of current, actual customer satisfaction. Both of these steps introduce the potential for error, in addition to the fundamental error described above. And people often cite these additional opportunities for error as justification for excluding qualitative variables from a computer modeling effort.

The Dangers of Excluding Qualitative Variables

Although qualitative factors are generally more prone to measurement error than quantitative variables, we shouldn’t exclude them on that basis alone. How well a model recreates the system’s performance—and thereby the model’s usefulness—depends on much more than measurement precision.

Another perspective is that measurement error is an important but usually static source of error in models. For that reason, the measurement error in one time period does not affect (or has a limited effect on) the measurement error in the next. For instance, the measurement error associated with this month’s plant utilization, operating hours divided by total hours in the month, is not affected by last month’s measurement error, nor will it affect next month’s. Also, well-designed measurement standards are unbiased: They tend to overestimate values as often as they underestimate them. A static and unbiased measurement error will have a relatively small impact on the depiction of a system’s dynamic behavior (behavior over time). Leaving out a qualitative factor entirely, on the other hand, means potentially omitting an influential feedback loop, and thereby creating a dynamic source of model error. Dynamic errors, unlike measurement errors, compound over time, causing the model to lose validity very quickly.

For example, consider the variable “Employee Morale” (see “Interacting Hard and Soft Variables”). As profitability drops, management intervention increases. In response to greater management controls, employee morale decreases, leading to a decline in productivity, quality, and, ultimately, profitability. Leaving this variable out of the model ignores serious reinforcing processes and quickly leads to unacceptable levels of total model error. Can we precisely measure employee morale and its impact on related variables? No. Are the processes described real? Absolutely. Although we can worry about whether a system dynamics model, with all its qualitative factors, is generating precise output, one thing is certain: A model that leaves soft variables out entirely is definitely off the mark.

Quantitative Scales for Qualitative Variables

If qualitative factors are so important, how do we incorporate them into a computer model? Although most managers can give a ballpark estimate of qualitative variables such as market focus, they often feel uncomfortable about encoding this kind of estimate in a computer model. But for many qualitative factors, a ballpark estimate by an experienced management team is the only data available and is usually a pretty good reflection of the system’s state. At the very least, this data is important because it represents the mental models of the managers involved in the model-building process.

Indexed Variables. The most straightforward way to capture qualitative variables in a model is to create an indexed variable. To do this, we typically set the value of the variable equal to “1” at some given point in time, usually the start of the simulation. We can then identify the factors that affect the indexed variable and establish mathematical or graphical relationships to cause the indexed variable to change over time.

For example, suppose we create an index for customer satisfaction that has a value of “1” at the outset of the simulation. Notice that we are not attempting to say that the current level of satisfaction is high or low; we are simply establishing a starting point. Next, we determine that the ratio of customers to telephone representatives is a key driver of customer satisfaction. Third, we ask what ratio (everything else being equal) would maintain customer satisfaction at “1” and what would happen if the ratio changed? For instance, if the “steady state” ratio were 200 customers per telephone representative, the management team could estimate the impact of letting the ratio slip to 300: satisfaction might fall by 20 percent. When we run the model, we will then know whether satisfaction goes up, down, oscillates, or remains constant, based on the behavior of the indexed variable at any given time and its value relative to “1.”

Formulating an explicit equation or graphical relationship between a qualitative variable and its drivers provides a management team with the opportunity to share mental models about the business and to try to achieve a mutual understanding. Through modeling, differing assumptions about the strength of such relationships can be tested.

Assessing Models

Interacting Hard and Soft Variables

The qualitative variable “Employee Morale” Is a key component of these reinforcing loops. As profitability drops, management intervention increases. In response to greater management controls, employee morale decreases, leading to a decline in productivity, quality, and, ultimately, profitability.

If you are responsible for building and managing models, present the decision-maker with alternatives: the old way of model-building or a new way that captures the impact of qualitative variables. Use both kinds of models concurrently to explore the thinking and assumptions that went into each one, and to uncover new insights about the organization and business. See if you can move senior management from using modeling as a forecasting tool to using modeling as a way to test ideas, explore strategies, and learn how the system works.

If you are the decision-maker, ask tough questions about the assumptions going into the models you use, especially with respect to qualitative factors. For instance, ask whether employee morale and its impact on productivity are addressed in your business plan. If not, why not? Last but not least, figure out ways to free your team from the tyranny of quantitative spreadsheet thinking. Spreadsheets are an important and helpful tool, but today’s management teams need to have a variety of tools at their disposal and must know how to include qualitative factors in their thinking.

Gregory Hennessy Is co-founder and managing director of Dynamic Strategies, a collaboration of advisors working with clients to Improve organizational effectiveness, apply system dynamics, and develop organizational learning capabilities.

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But if we are not going to define “leanness” in financial terms, how should we define it? I believe we need to expand our thinking to include the application of employee competency to achieve leanness. I strongly believe that people are a company’s only long-term competitive advantage. As such, we should view them as assets and resources to be developed, rather than as line-item expenses to be controlled. By taking this approach, we might discover value-added activities that would enable us to keep employees on the payroll even during tight times.

Business Process

Within Harley-Davidson’s motorcycle operations, we are trying to establish a business process that will accommodate such thinking. At the top of our business process diagram is an umbrella that sets the context for our work (see “Business Process: Setting the Context”). Under this umbrella, we identify the values, issues, and stakeholders that are the basis for our vision statement, which is to be “a leader of continuous improvement in the quality of mutually beneficial relationships with all of our stakeholders.” We measure our progress in achieving that vision against the following statement: “The key to our success is to balance stakeholder interests through empowered employees focused on value-added activities.”

These statements could be viewed as esoteric rhetoric. But we hope they will operate instead as a guiding light toward effective leanness. If we adopt this view, then we can start to utilize the workforce as a resource, creating an environment in which all employees seek to apply their competencies to value-added activities that can result in employment security.

In this context, “employment security” is dramatically different from conventionally stated job security. In employment security, the employee’s focus is on ensuring that the company survives, while job security centers on ensuring that he or she continues to do the same thing day in and day out. If all employees focus on creating employment security by providing value-added activities (in conjunction with others with complementary competencies), the result will be a lean organization. In addition, their work will generate additional resources to develop the company further, enabling the company to become more externally and future oriented.

The Role of Financial Measurement

Defining leanness in terms of value-added activities does not eliminate the need for financial measures. In order for the company to survive over the long term, it must be financially viable, and all of the employees must understand this. A primary measure of employee effectiveness is the company’s financial results. Those results come only when employees deliver value-added activities that are recognized as such by the customers. Therefore, if customers are not purchasing our products, it is up to all employees to seek ways to apply their competencies toward creating new products or services that will ensure the long-term financial viability of the company. If this strategy is not recognized and adopted by all employees, it is likely that leanness will have to be associated with meanness in the form of down-sizing efforts that have cost reduction as their only objective.

In order to survive, Harley-Davidson had to experience such a downsizing. In 1982, we reduced our workforce by 40%. It was not an easy decision, but we did it as humanely as possible—far more humanely than our bankers thought necessary. However, this approach put us in good stead with the people inside the company, because they knew that we were in crisis and they put forth the extra effort to help the company recover.

While that result sounds great, I can’t help but speculate that if we had consciously worked on having all employees focus on value-added activities, the solutions to our problems could have been identified much earlier. By redefining our approach to leanness, we are hopefully putting ourselves on the right path to prevent a recurrence of that difficult experience.

Rich Teerlink is president and chief executive officer of Harley-Davidson. Inc.

Reprinted with permission from Collective Intelligence (Vol. 1 . No.1) May 1995. ©MIT Center for Organizational Learning. All rights reserved.

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The Paradox of KSFs

Most of us approach a large, complex issue by breaking it down into manageable parts. By focusing on a few aspects at a time, we sometimes succeed in improving the parts, but we often fail to address the problem as a whole. In the long run, this approach robs us of resources that we could have used to look at an issue from a systemic perspective.

We can find ample evidence of the limits to a factors approach in medical literature. In Sweden, for example, researchers tried to reduce cardiovascular risk factors in 3,490 business executives. After five years of intervention and 11 years of follow-up, the executives had reduced their risk factors by an average of 46 percent, yet they had a higher death rate than members of a control group. A similar study in the U.S. produced comparable results.

We might dismiss these studies as statistical flukes if the consequences weren’t so serious. The sad reality is that these results probably reflect many of our efforts, not just in healthcare but in virtually every facet of our organizations. Although we focus time and again on improving single factors, we fail to acknowledge that the health of most individuals—and most systems—is greatly determined by the relationships among critical loops. The line “the operation was successful, but the patient died” sums up the pitfalls of the factors approach to complex systems.

Beyond Factors to Loops

To create long-lasting success, we need to extend our factors approach and identify the interrelationships among the factors that drive the dynamics of the system—in short, to identify the Key Success Loops (KSLs).When we take a systemic approach, we realize that the lowest meaningful units of analysis are loops, not individual factors—and we no longer initiate actions on any factors until we distinguish the critical loop or loops involved.

Now, imagine being given the same charge as before from corporate (see “Key Success Loop Approach”). We begin in the same way, by brainstorming and then prioritizing KSFs (Step 1). But instead of leaping into action by assigning the factors to teams, we take each of the high-priority factors and identify at least one reinforcing loop that will make the factor self-sustaining without continued external investments (Steps 2 and 3). We integrate all of the loops into a single diagram, in which the individual loops are connected by the factors they have in common (for example, B and D in Step 4).We then look at the diagram as a whole and decide where to make the investments that would help support the success of the entire system (Step 5). Only after we have developed a sufficient understanding of the system will we assign teams to implement specific success loops. Each team then collaborate closely with those teams whose loops are directly connected to theirs (Step 6).

Launching a New Venture

Let’s walk through a simplified example of a Key Success Loop approach. Suppose we want to launch a new business venture in our organization (see “New Business Venture Success Loops”).We begin by brainstorming a list of KSFs that we believe are important to our success, such as number of new products, skilled people, profit, and ability to meet customer needs (Step 1).

We then focus on the first factor and try to identify a key loop that would make it self-reinforcing. We can ask either “What would an increase in the number of new products cause?” or “What would be an important driver of growth in the number of new products? ”The first question leads us downstream in the arrow flow to “Revenues,” while the second takes us in the upstream direction to “Acquisitions.” Either way, we try to create a reinforcing loop around the original factor (Step 2).We then repeat the process with the remaining factors (Step 3).

After we have created a loop for each KSF, we look for common variables in the individual loops. In this example, loops R1 and R2 can be linked through “Revenues” and “# of New Products” (Step 4). Once we have a diagram that maps the key linkages, we can begin to identify the best places to make high-leverage investments (Step 5). Now we are ready to assign teams to focus on each of the loops through a collaborative effort in which each team understands its loop in the context of the larger system (Step 6).

Benefits of KSLs

Moving beyond Key Success Factors to Key Success Loops offers a number of advantages. First, because the loop approach links you to a broader set of variables, you reduce the risk of focusing on the wrong factors. Even if you initially pick the wrong factors, the process of mapping the loops increases the likelihood that you will include the most important ones. Also, identifying the loops decreases competition for limited resources. When everyone can see the interconnections, teams are less likely to “pump up” their own factors without regard for the effect on others. Loops can also provide a clearer picture of where investing in one point could positively affect multiple factors. Finally, rather than being stuck in the “Ready, Fire, Aim” syndrome that many organizations experience, emphasizing KSLs can actually give you a viable “Ready, Aim, Fire” approach.

Daniel H. Kim is a co-founder of Pegasus Communications, Inc., and publisher of The Systems Thinker.

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The first meeting begins with a “post-mortem” on the latest launch crisis. The team members tackle the issue with enthusiasm, jumping in with their own perspectives of what went wrong and why. At first the meeting seems to be going well, since everyone is obviously engaged in solving the problem. But as the meeting progresses, you start to feel like the group is spinning its wheels. The stories begin to resemble a jumble of personal anecdotes that share no common elements: “Well, on project X, we tried doing something new, and this is what happened…” or “This reminds me of the time when we implemented process Y and we were carrying spare parts in brown paper bags…” Lots of interesting stories are being exchanged, but they do not seem to be leading to a common understanding of the root causes.

The Storytelling Trap

Stories can be a powerful tool for engaging a group’s interest in a problem or issue. The specific details about people and events make it easy for most people to relate to stories, and they often provide a firm grounding in the day-to-day reality of the situation. But storytelling’s strength is also its Achilles heel: when we remain at event-level storytelling, it is difficult to generalize the insights to other situations, and so the solutions are often situation-specific. Without a deeper understanding of why something happened, the most we can do is find ways to react faster to similar events in the future.

FROM EVENTS TO VISION: STRUCTURED PROBLEM-SOLVING

By using a modified version of the “Vision Deployment Matrix,” a team can look at a particular problem under study from different perspectives. The “Current Reality” and “Desired Future Reality” columns allow you to differentiate between diagnosis of the current situation and proposed solutions for the future

Storytelling at Multiple Levels

One way that managers can move beyond event-level storytelling to a deeper understanding of an issue is to use a modified version of the Vision Deployment Matrix (see “Vision Deployment Matrix: A Framework for Large-Scale Change,” February 1995). In particular, applying the first two columns of the matrix (“current reality” and “desired future reality”) to a particular problem can provide a framework for both analyzing the current situation and designing an effective, long-term solution (see “From Events to Vision: Structured Problem-Solving”).

The matrix distinguishes between different levels of seeing and understanding a situation. The “Events” level captures stories about specific incidents or events that indicate a problem. The next level,“ Patterns,” expands the time horizon. At this stage, the team might ask, “Are these individual events or stories part of a larger pattern that has been unfolding over time?” Next, the “Systemic Structures” level looks at the structures that might be producing the observed pattern of behavior. Since those systemic structures are usually physical manifestations of deeply held mental models in the organization, the “Mental Models” level prompts the team to surface them. Finally, at the “Vision” level, the group considers how the vision of what the organization is creating might be influencing those mental models.

Analyzing a problem or situation from multiple levels can be useful in several ways. First, it forces us to go beyond event-level storytelling, where our ability to affect the future is low, to a perspective that offers greater leverage for creating systemic change. Second, the matrix provides a way to distinguish between different ideas and experiences (e.g., “Does this story illustrate a problem situation or a prevalent mental model?”). Finally, when the conversation does jump from events to specific systems to assumptions and so on, the matrix can provide a coherent framework for mapping everyone’s contribution in real time.

Using the Matrix

By filling in the matrix around a particular problem or issue, the team members can work together to raise their understanding from the level of events to patterns, systemic structures, mental models, and vision. For example, in the product launch situation, the team started with stories of a particular launch failure. After some discussion, the team discovered that the proper tests for verification were never conducted. But instead of going further into the details of why that process was neglected, the team can ask questions designed to draw the stories up to the patterns level, such as, “Was this indicative of a pattern that happens on all products?” Additional stories can then be used to establish whether that is indeed a pattern.

The next step is to identify the underlying structures that may currently be responsible for such behavior. In this example, the test and verification efforts all relied on a central group of people who were chronically overused by all the products under development, hence verifications were rarely done to the level specified. When the group tried to understand how engineers could justify skipping such an important step, they revealed an implicit mental model: “not knowing there is a problem and moving forward is better than knowing there is a problem and moving forward.” In short, the division had been operating according to an “ignorance is bliss” strategy.

To understand where this assumption came from, the group asked, “What is the implicit vision driving the process?” The most common answer was “to minimize unwanted senior management attention.” In other words, no one in product development wanted to have problems surface on their “watch.”

Although this team focused on the “Current Reality” column, they could also fill out the “Desired Future Reality” column by asking what kinds of new structures might be needed to prevent these problems from happening in the future.

Guiding Questions

The following set of questions can be used to guide conversations as a team moves among the different levels of perspective. In looking at current reality, it may be easier to start at the level of events (since that is where stories usually begin) and work your way up the levels. When mapping out the desired future reality, however, it may be better to begin at the level of vision and go down to the other levels so that your desired future reality is not limited by the current reality. Having said that, it is likely that in actual meetings the conversation will bounce all over the place. The main point is to use the matrix to capture the conversation in a coherent framework.

Current Reality

• What are some specific events that characterize the current reality?
• Are those specific events indicative of a pattern over time? Do other stories corroborate this repeated pattern?
• Are there systemic structures in place that are responsible for the pattern? Which specific structures are producing the most dominant pattern of behavior behind the current results?
• What mental models do we hold that led us to put such structures in place? What are the prevailing assumptions, beliefs, and values that sustain those structures?
• What kind of vision are we operating out of that explains the mental models we hold? What is the current vision-in-use?

Desired Future Reality

• What is the espoused vision of the future?
• What sets of assumptions, beliefs, and values will help realize the vision?
• What kinds of systemic structures are required (either invented or redesigned) to operationalize the new mental models and achieve that vision?
• What would be the behavior over time of key indicators if the desired vision became a reality?
• What specific events would illustrate how the vision is operating on a day-to-day basis?

By elevating the conversation from events to systems structure and beyond, this simple tool can help managers make clearer sense of their own experiences, and use those experiences to formulate more effective solutions to the problems at hand.

Daniel H. Kim is co-founder of the MIT Center for Organizational Learning, and of Pegasus Communications, Inc. He is a public speaker and teacher of systems thinking and organizational learning.

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To answer this question, Shell’s planners set out to study other companies that had weathered significant changes and survived with their corporate identity intact. In particular, they were looking for companies that were older than Shell (100 years or more) and that were as important in their own industries. After some research, a few examples started trickling in: Dupont, the Hudson Bay Company, W.R. Grace, Kodak, Mitsui, Sumitomo, Daimaru. Forty companies were eventually identified, of which 27 were studied in detail.

Keys to Longevity

Of the tens of thousands of companies that had existed at the beginning of the 19th century, why did so few remain by 1980? And what had these few done to survive? Shell’s planners found that, in general, the 27 long-established companies shared a history of adaptation to changing social, economic, and political conditions. The changes within those companies appeared to have occurred gradually, either in response to opportunity or in anticipation of customer demand. The companies shared some additional characteristics that could explain their durability:

• Conservative Financing. These companies had an old-fashioned appreciation of money. They did not make business decisions based on intricate financial deals using other people’s money. Rather, they understood that money-in-hand gave them the flexibility to take advantage of opportunities as they arose.
• Sensitivity to the Environment. The leaders of these companies were outward looking, and the companies were connected to their external environment in ways that promoted intelligence and learning. As a result, they were sensitive to changes and developments in the world. They saw changes early, drew conclusions quickly, and took action swiftly.
• A Sense of Cohesion and Company Identity. In numerous cases, the Shell researchers found a deep concern and interest in the human element of the company–a quality that was somewhat surprising for the times. Employees and management seemed to have a good understanding of what the company stood for, and they personally identified with it. Quite often, this value system had been brought in by the founder, and was occasionally formalized in a kind of company constitution.
• Tolerance. The companies had made full use of what we would call in modern terms “decentralized structures and delegated authorities.” They did not insist on relevance to the original business as a criterion for selecting new business possibilities, nor did they value central control over moves to diversify. In other words, they had high tolerance for “activities in the margin.”

Businesses: Economic Entities or Organisms?

The Shell planners summed up their profile of these corporate survivors as follows: “They are financially conservative, with a staff that identifies with the company and a management which is tolerant and sensitive to the world in which they live.” This definition of a successful enterprise is quite different from the one I was taught in college, which portrayed businesses as rational, calculable, and controllable. Production, we learned, is a matter of costs and price. Costs are associated mostly with labor and capital—production factors that are interchangeable. If you have trouble with labor or if it is too expensive, you simply replace it with capital assets. For aspiring corporate leaders, this description of their future workplace painted a reassuring and comforting picture.

The real world, we discovered, was quite different. The economic theories offered at school made no mention of people, and yet the real workplace seemed to be full of them. And because the workplace teemed with people, it looked suspiciously as if companies were not always rational, calculable, and controllable.

The Shell study, which described within these companies a “struggle for survival, maintaining the institution in the face of a constantly changing world,” supports this view that companies are perhaps more organic than economic in nature. Of course, the long-term survivors had to control costs, market their product, and update their technology, but they tended to see these basic functions as secondary to the more important considerations of life and death. These companies not only employed people who sometimes proved uncontrollable or irrational; the companies themselves behaved as if they were alive.

What if we were to look at companies as “living systems,” rather than mere economic instruments created to produce goods and services? Would that viewpoint change our ideas about how to manage a business, or perhaps offer an explanation of why some companies endure and so many die young?

Though this hypothesis certainly does not apply to all companies—many do operate as if the production of goods and services is a purely economic problem—it may offer new insights into some corporate phenomena. In particular, I’d like to explore how “living” versus “economic” companies—and the management of them—differ in three basic respects:

• the role of profits and assets
• the amount of steering and control from the top (in decisions such as diversification, downsizing, or expansion)
• the way the company creates and shapes its human community

Role of Profits and Assets

In the 27 companies Shell studied, the main driving force seemed to be the firm’s own survival and the development of its potential. History shows that these companies engaged in a business—any business—so long as doing so sustained them as viable work communities. In fact, over their long lifetimes, each one changed its business portfolio at least once.

For example, Stora, a company that was not included in the original Shell study, began as a copper mine in central Sweden around the year 1288. During the next 700 years, new activities replaced the old “core” business: the company moved from copper to forest exploitation, to iron smelting, to hydro • power, and, more recently, to paper and wood pulp and then chemicals.

Dupont de Nemours started out as a gunpowder manufacturer, became the largest shareholder of General Motors in the 1930s, and now focuses mostly on specialty chemicals. Mitsui’s founder opened a drapery shop in Edo (Tokyo) in 1673, went into money-changing, and then converted the company into a bank after the Meiji Restoration in the 19th century. The company later added coal mining, and toward the end of the 19th century it ventured into manufacturing.

In retrospect, each one of these portfolio changes might seem Herculean. But for the people running these enterprises at the time, the shift may have been imperceptible at the outset. At some stage, these companies may have thought of themselves as bankers, while a later generation of their leaders viewed themselves as manufacturers. Such changes cannot come about if a company regards its assets as the essence of its existence.

This fluidity demonstrates an important attitude toward whatever “core” business the company happens to be doing at any moment. All businesses need to make a profit in order to stay alive, but neither the core business—nor the profits from it—must be the driving force. Businesses need profits in the same way that any living being needs oxygen: we need to breathe in order to live, but we do not live in order to breathe.

This attitude is quite different from the “economic” company, which engages in a particular business to make profits or to maximize shareholder value. For such a company, the core business is the essence of life, and profits are its purpose. This position can lead to the belief that the present asset base represents the essence of the company—that the company’s purpose in life is to exploit this particular set of assets. In a crisis, such a business will scuttle people rather than assets to save its “balance sheet” (which quite appropriately records only physical assets).

Businesses need profits in the same way that any living being needs oxygen: we need to breathe in order to live, but we do not live in order to breathe.

The logical endpoint of this thinking would be: “We will liquidate the company and return the remaining value to the shareholder whenever the oil runs out.” Such “corporate suicide” is uncommon among “living” companies, however. Because their main purpose is their survival and the development of their potential, they would sooner shift the asset base than allow the current assets to determine the death of the institution.

Steering and Control from the Top

The long-term survivors shared two ways of handling a shift in their core business: the new business was not required to be relevant to the original business, and the diversifications were not initiated from a central control point. This pattern suggests that the companies’ managers were highly tolerant of “activities in the margin.”

Tolerance levels—toward new people, ideas, or practices—differ from company to company. Both a low-tolerance and a high-tolerance approach have a place in business, but which strategy a company should pursue depends on the amount of control that company has over its environment.

A management policy of low tolerance can be very efficient, but it needs two conditions to be fulfilled: the company should have some control over the world in which it is operating, and this world should be relatively stable. In such a world, a company can aim for maximum results with minimum resources. To achieve its goal of minimum resources, however, management will have to exercise not only some control over its surrounding world, but also a high degree of control over all internal operations. In these companies, little room exists for delegated authority and freedom of action.

A company may be lucky enough to live in a world that happens to be stable. However, any business that endures for more than a few score years will inevitably face changes in the external world. In a shifting and uncontrollable world, any company with the desire to survive over the long term would be ill advised to rely on a management policy of high internal and external controls. The Shell study showed that the survivors did, in fact, follow a high-tolerance strategy by creating the internal space and freedom to cope with external changes.

High tolerance is inefficient and wasteful of resources, but it enables a company to adapt to a changing environment over which the company has no control. Moreover, high tolerance provides a means for gradually renewing the business portfolio without having to resort to diversification by top-down “diktat.”

The spring ritual of pruning roses provides a good illustration of the different implications of a high-tolerance versus a low-tolerance strategy. If a gardener wants to have the largest and most glorious roses in the neighborhood, he or she will take a “low-tolerance” approach and prune hard—reducing each rose plant to one to three stems, each of which is in turn limited to two or three buds. Because the plant is forced to put all its available resources into its “core business,” it will likely produce some sizable, dazzling flowers by June.

However, if a severe night frost were to strike in late April or early May, the plant could well suffer serious damage to the limited number of shoots that remain. Worse, if the frost (or hungry deer, or a sudden invasion of green flies) is very serious, the gardener may not get any roses at all. In fact, he or she risks losing the main stems or even the entire plant.

Pruning hard is a dangerous policy in a volatile environment. If a gardener lives in an unpredictable climate, he or she may instead want to try a “high-tolerance” approach, leaving more stems on the plant and more buds per stem. This gardener may not grow the biggest roses in the neighborhood, but he or she will have increased the likelihood of producing roses not only this year, but also in future years.

Living companies, by contrast, are more like rivers. The river may swell or it may shrink, but it takes a long and severe drought for it to disappear altogether.

This policy of high tolerance offers yet another benefit—in companies as well as gardens. “Pruning long” achieves a gradual renewal of the “portfolio.” Leaving young, weaker shoots on the plant gives them the chance to grow and to strengthen, so that they can take over the task of the main shoots in a few years. Thus, a tolerant pruning policy achieves two ends: it makes it easier to cope with unexpected environmental changes, and it works toward a gradual restructuring of the plant.

Although this policy is not as efficient as hard pruning in its use of resources—since the marginal activities take resources away from the main stem—it is better suited to an unpredictable environment or one in which we have little control. And as the success of the long-term survivors indicates, diversifying by creating tolerance for activities in the margin has a better track record than diversification by dictum.

Creating and Shaping the Human Community

The way a company views its human community is the third area of distinction between economic companies and self-perpetuating organic companies. The fact that living companies want to survive far beyond the lifetime of any individual employee requires a different managerial attitude toward the shaping of its human community.

Economic companies are like puddles of rainwater—a collection of raindrops that have run together into a suitable hollow. From time to time, more drops are added, and from time to time (when the temperature heats up), the puddle starts to evaporate. But overall, puddles are relatively static. The drops stay in the same position most of the time, and some of the drops never seem to leave the puddle. In fact, the drops are the puddle.

“Living” companies, by contrast, are more like rivers. The river may swell or it may shrink, but it takes a long and severe drought for it to disappear altogether. Unlike a puddle, the drops of water that form the river change at every moment in time, and its activity is far more turbulent. The river lasts many times longer than the drops of water that shaped it originally.

A company can become more like a river by introducing “continuity rules”—personnel policies that ensure a regular influx of new human talent. Continuity rules also stipulate a fixed moment of retirement for every member, without exception. These strict exit rules remind the incumbent management that they are only one link in a chain. Within this expanded perspective, leadership becomes more like stewardship. A leader takes over from someone else, and eventually hands the enterprise over to yet another person. In the meantime, the current leader tries to keep the shop as healthy as he or she received it, if not a bit healthier than before.

Companies that are seen as teaming, living beings demand different thinking, not only about recruitment, but also about other aspects of human relations. This rethinking begins with a definition of self: Who are we? Who belongs to the institution, and whom shall we let in? Clarity on these points is essential for a living work community. Without it, there is no continuity. Without continuity, there is no basis for mutual trust between the community and its individual members. And without trust, there is no cohesion and therefore no community.

This thinking varies dramatically from the human-relations practices required in an economic company, where the HR function is expected to fit people to the asset base of the company. People are seen as cogs to fit a wheel, “hands” to serve the machines, or “brain? To make the right type of calculation or do the most promising research. Recruitment numbers are determined by the need for capacity to satisfy the foreseen demand for the company’s products. If the company has more demand than capacity to fulfill the demand, it adds new people and machines. When it has less demand, it reduces capacity by letting people go.

The type of people the company will admit or fire is defined mostly in terms of “skills”: “We need 250 metal bashers,” or “We have a surplus of paper pushers.” Within this framework, “people” are not hired or fired, only “skills” are. The mutual obligation between company and individual is that of “delivering a skill against the payment of a remuneration,” an agreement usually concluded under the umbrella of the country’s social legislation or some collective labor agreement.

In the living institution, criteria for admitting or dismissing people more closely parallels those methods used in clubs, trade unions, or professional bodies. Good care is taken that the new members carry the right professional qualifications, but the company also strives for a kind of harmony between the individual and the company. The members and the institution share certain values and purposes, and they aim to harmonize their respective long-term goals.

In the “living” company, admission is not determined solely by capacity. Capacity issues are addressed via the outside world, not by increasing or decreasing the internal membership. A shortage of capacity therefore leads to more subcontracting. In Italy, for example, Benetton does only a minor part of its manufacturing (recently, only 20%) with its own people. Benetton admits relatively few members to the inner core of its work community. In this case, the use of subcontractors has proven effective for acquiring capacity in a competitive industry with fluctuating demand.

The Choice

Many people in the business world may not want to create a living work community, and simply to manage a corporate machine with the sole purpose of earning a living. However, the latter choice has important consequences.

People in economic companies enjoy fewer options in their managerial practices. In those companies, only a small group of people qualify to be “one of us,” while the rest of the recruits become attachments to somebody else’s money machine. The company culture will consequently reflect this relationship. Non-managers will be viewed—and will view themselves—as “outsiders” hired for their skills rather than members with full rights and obligations. Their loyalty to the company will never extend beyond performing the tasks necessary to earn a paycheck. The lack of common goals and low levels of trust will require a strengthening of hierarchical controls in order to make the money machine work effectively and efficiently. As a result, the ability to mobilize all of the company’s human potential will be severely limited.

For such a company, a critical point comes when the succession of the inner community needs to be addressed. The absence of continuity rules or the reliance on the next generation of the family for corporate continuity will turn many of these money machines into “ships that pass in the night.” In short, economic companies not only face difficulties trying to operate effectively within a changing environment, but they also have to overcome considerable obstacles in their internal management practices just to make it to the next generation.

This paper was originally presented at the Royal Society of Arts in London on January 25. 1995.

Arie de Geus was appointed executive vice president at the Royal Dutch/Shell Group In 1978 and was with the company for 38 years. He served as head of an advisory group to the World Bank from 1990 to 1993, and is a visiting fellow at London Business School. Editorial support for this article was provided by Colleen P. Lannon.

Further Resources: Many of the ideas in this article are discussed further In the video infrastructure and Its Impact on Organizational Success” by Me de Geus which is available through Pegasus Communications, Inc.

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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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