It is the farmers’ fault. . . . They have neglected to plant new oaks. It takes ten years for truffles to appear under them in edible size. Truffles have dwindled. The price, in 30 years, has tripled. . . . Now the French taxpayer is paying for research into just how the truffle is born.”

–Ruffling France’s Truffles,’ The Economist, May 4, 1996

France’s Truffle Crisis

Why should anyone other than gourmets care about the fate of the black truffle? French government officials are concerned because the declining truffle harvest is opening the way for foreign competition. Though France dismisses the truffles grown by other countries as being of “dreadfully inferior quality,” some restaurateurs say that you cannot tell the difference—which could mean a big difference in terms of France’s hold on the worldwide truffle market.

But systems thinkers can also find something of interest in France’s “truffle crisis.” The issue—complete with long time delays and interesting behavior over time—lends itself well to a systemic perspective, and can provide a good opportunity for practicing drawing casual theories of a problem. Since most news articles are event oriented, drawing causal diagrams of news stories provides excellent practice in moving from events to patterns over time to systemic structure.

Creating a Causal Theory

The first step in creating a causal theory is to identify the problem and map key behaviors over time. In this case, the Economist article described the “problem” as a declining truffle harvest and a tripling of the price of truffles over the last 30 years (see “Declining Truffle Harvest”).

We know from the article that the truffle harvest is dependent on the truffle population, which in turn is based on the number of appropriately aged oak trees under which the truffles grow. The dynamics suggested by the Economist is that farmers are planting fewer oak trees, leading to less nurturing oak trees, a fall in the truffle population, lower truffle harvest, and finally, climbing prices (see “Simple Explanation”).

We can expand on this rather linear worldview by looking for plausible feedback loops. For example, a simple balancing loop governs the relationship between population and harvest—increasing population allows for a greater harvest, but each year the harvest reduces the live population (B1 in “Closing Feedback Loops” on p. 8). Based on general commodities theory, as the price goes up, we would expect people to put more effort into gathering truffles, which would lead to an increase in the truffle harvest and an eventual decrease in the price (B2). Notice, however, that the two balancing loops could act as a reinforcing loop—the higher price leading to a greater harvest, potentially lowering the population beyond its ability to regenerate, which would lower the harvest and raise the price even further in the future.

Exploring Solutions

To close the gap between the actual truffle harvest and the desired truffle harvest, the French government is investing in research to find ways to increase the truffle harvest without relying on oak trees. The implicit thinking behind this strategy is that putting more money into research will (after a time delay) result in effective alternatives for increasing the truffle harvest, and thus reduce the price to reasonable levels (B3 in “Looking for ‘Solutions’ “).

Technological Solutions

Investing in research can be described as a technological solution—an attempt to solve a problem by developing alternatives that bypass the cause of the problem. This is often faster and cheaper than finding a more fundamental structural solution. Without a clear understanding of the root causes, however, this approach risks creating unintended consequences that could set off a cascade of additional problems.

While the Economist article focused on potential technological solutions that would bypass the need for oak trees, other solutions could also be found by examining why the oak tree population itself is declining, and what can be done about it. Traditionally, oak trees in France have been planted by farmers in the course of their normal farm maintenance. Since most farmers lived on their farm for life, the 10-year delay between planting and truffle harvest was negligible. Over the last century, however, more farmers have been seeking employment in the city, as the attractiveness of city jobs relative to working on the farm has increased.

The question this raises for the French government is whether the oak tree population can be increased without relying on the farmers, or whether the farmers can be encouraged to take up farming (and oak planting) again. Because of the 10-year time delay between planting an oak tree and harvesting the truffles, it would be difficult to rely on short-term market forces to encourage the planting of trees. Through public programs, the French government could (and actually is) encouraging children to plant trees—but this is not likely to be a sustainable long-term solution, because it will likely stop as soon as the government push ends.

To ensure the long-term oak tree supply, the French government might therefore need to examine the forces that have made it so attractive to leave the farm for the city, and potentially create incentives to encourage more domestic farming (B4). Since the dynamics around this migration is complex and the delays long, it is not hard to imagine why the government is hoping for a technological solution rather than trying to influence a major social dynamic.

Using Articles for Practice

Using the truffle example, we have tried to illustrate how one might practice developing causal theories using stories found in magazine or newspaper articles. In summary, the process would be to:

1. Look for articles that talk about a problem over time. Avoid specific cases (Joe lost his job today) and hunt for trends (more and more people are losing their jobs).

2. Draw out the behavior over time. This provides a reference point of behavior that the causal theory should be able to explain.

3. Map out the problem as described in the article, first limiting yourself to the data directly mentioned. Then add other variables or feedback loops that you would hypothesize are driving forces behind the problem.

4. Map out any proposed solutions, and then look for unintended consequences or other alternatives.

Peter Senge has said, “We only learn what we want to learn.” By using real-life news items as the starting point for developing theories, the practice of systems thinking becomes more than an academic exercise. It can serve as a true exploration of issues that are important to us.

Linda Booth Sweeney is an educator consultant, and associate of the MR Center for Organizational Learning.

Don Seville is an associate with GKA Incorporated and is affiliated with Sustainable Solutions.

Editorial support for this article was provided by Colleen Lannon.

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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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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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By following a systems thinking-based graphical facilitation process using hexagons, we can surface and focus on the issues that are most important in our organizations.This process can help shorten the amount of time it takes teams to move from ideas to action steps and can give us a more systemic view of the issues our organizations face.

The Hexagon Technique

The hexagon technique for brainstorming was created by Tony Hodgson and Gary Chicoine-Piper, British creativity and organizational development consultants. Unlike other brainstorming techniques, which focus on generating ideas, hexagons can also help us surface underlying assumptions. By writing people’s thoughts and ideas on hexagons and posting them in front of the entire team, we make those thoughts visible and separate the idea from the person. Because of their unique shape, hexagons can easily be grouped in a honeycomb structure; we can then move the hexagons into various configurations and combine ideas in different ways.

The following steps describe a brainstorming process using hexagons.

Unlike other brainstorming techniques, which focus on generating ideas, hexagons can also help us surface underlying assumptions.

Step One: Identifying Issues

Hexagon maps capture the event level—the world of who, what, when, where, and why. You want to start here, because you first have to connect with people’s understanding of their world. So begin by talking in everyday language. Surface team members’ concerns and mental models by asking questions such as: “What is really important to you?” “What issues do you feel are absolutely critical for success?” “What are your strongest opinions?” “What do you feel is holding us back?”

Summarize each response in three to six words and write it on a hexagon. Place the hexagons on the board in sequence, with one point at the top; don’t attempt to arrange the ideas at first. Number the hexagons sequentially for easy/reference. You can use color-coded hexagons (see “Color-Coding Hexagons”); for example, if you or someone else has a strong opinion, put it on a red hexagon.

But because your goal is to build a shared understanding, you have to go beyond simple brainstorming. You want to explore the reasoning—and the emotions—behind people’s statements. So, if someone says, “We need to raise prices,” you would ask, “Can you tell me more about that?” And they may respond, “If we don’t raise prices, this company is going to go under, because we won’t have enough revenues to support R&D!” The challenge is to capture of each person’s position in just a few words, so that the hexagon can serve as a vivid reminder for the entire group of that individual’s perspective. Separating an idea from the person who articulated it and creating a symbol for the idea that can be understood by the whole group is an important step in the process.

Step Two: Identifying Clusters

From this divergent step, move to convergence. Zero in on the key issues by asking, “Which hexagons seem to go together?” Find the hexagons that seem related, and then move them the same general area on the board. Once you have reviewed the positioning with the team, draw a circle around each grouping and give each cluster a name (see “Identifying Clusters”).

You may start by writing one title, and someone might say, “Let’s change it; that’s not quite right.” Remember, it’s an organic process through which the team starts to develop a common language. The titles of the most important clusters become the emergent agenda; these are the hot spots, according to the group.

Step Three: Identifying Variables

In this step, you begin to distinguish the most important trends and patterns of behavior over time within your organization. When you look for key variables, you’re really asking, “Can you tell me how something in this system might change over time?” Surface the key variables by asking a set of transition questions about the most important clusters on the board: “What do you really want?” “How would you know if you got it?” “Who are the key players?” “What do they want?” “How would they know if they got it?” “What are the key uncertainties?” You’re trying to shift to the systems point of view, and it takes some skill to navigate into that domain.

A variable is something that can increase or decrease over time. So, if you were concerned about the economy, you might say, “We might have a depression!” A depression, however, is not a variable; a variable is something that can go up or down, something you can measure. However, once you define a depression as eight consecutive quarters of declining GNP, you’ve found your variable. GNP is something that can go up or down. You can also identify “soft” variables— “morale” or “quality” can go up or down over time.

When identifying variables, choose brief, one- to two-word descriptions for each. Try not to use adverbs or lengthy adjectives. Write the variables on orange hexagons for easy identification.

IDENTIFYING CLUSTERS

After writing the issues on hexagons and numbering the hexagons sequentially for easy reference, cluster related issues. Draw a circle around each grouping and give each cluster a name. Then, surface the key variables by asking a set of transition questions about the most important clusters.

Next Steps

Once you’ve identified the trends and the variables, you’ll be amazed at how quickly you can move to a causal loop diagram by arranging the key variables. But for real breakthroughs, the maps must focus on the group’s most important problems and objectives. Otherwise, they can easily degenerate into meaningless “spaghetti” diagrams, or pictures of things that are connected but don’t necessarily have a cause-and-effect relationship. The steps outlined above should help your team make the transition from ideas to key variables.

Be sure to document your learning process for future reference. Take photographs of your hexagon maps, clusters, variables, and causal loops.

Beyond Hexagons

Using hexagons for brainstorming can be an engaging, dynamic way to move a group toward taking a systemic perspective. By allowing you to capture various viewpoints, hexagons provide a spring board for creative brainstorming and can help you elicit mental models. Finally, by helping you identify key issues, the hexagon technique enables teams to move from ideas to variables, and then on to causal loop and flow diagrams.

David Kreutzer is founder and president of GKA Incorporated, an international management consulting firm. The process described in this article is based on the initial steps of FASTBreak, a systems thinking-based facilitation methodology for moving from ideas to action designed by GKA Incorporated.

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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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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.

The post The “Living” Company: Extending the Corporate Lifeline appeared first on The Systems Thinker.

One may be tempted to conclude that substituting new people would be easier than replacing all the information and systems. But even in the most bureaucratic organization, with all its standard operating procedures and established protocols, there is much more about the firm that is unsaid and unwritten. In fact, numerical and verbal databases only capture a small fraction of the information that is in mental “databases.”

The essence of an organization is embodied in its people, not its systems. The intangible assets of a company reside in the individual mental models that contribute to the organization’s memory. Without these mental models—which include the subtle interconnections that have been developed among the members—an organization will be incapacitated in both learning and action. Yet in most organizations, individual mental databases are not “backed up,” nor is the transfer from individual to organizational learning well managed. A critical challenge for a learning organization is understanding the transfer process through which individual learning and knowledge (mental models) become embedded in an organization’s memory and structure. Once we have a clear understanding of this transfer process, we can actively manage organizational learning to be consistent with an organization’s goals, vision, and values.

“The essence of an organization is embodied in its people, not its systems. The intangible assets of a company reside in individual mental models…”

From Individual Learning…

In order to develop a framework for organizational learning, we must begin by understanding how individuals learn. The “Individual Learning Cycle” diagram shows a simplified model of individual learning. The diagram traces the process through which the brain assimilates some new data (environmental response), takes into account the memories of past experiences, comes to some conclusion about the new piece of information (individual learning), and then stores it away (individual mental models). After processing the new learning, one may choose to act or simply do nothing (individual action).

The processing stage has been labeled “individual mental models” because it represents much more than the traditional concept of memory. Memory connotes a rather static repository for knowledge, whereas mental models involve the active creation of new knowledge. Mental models represent a person’s view of the world, including both explicit and implicit understandings. They also provide the context in which to view and interpret new material, and they determine how stored information will be applied to a given situation.

…To Organizational Learning

In the early stages of an organization’s existence, organizational learning is often synonymous with individual learning since it usually involves a very small group of people and the organization has minimal structure. As an organization grows, however, a distinction between the two levels of learning emerges. Somewhere in that process, a system evolves for capturing learnings from its individual members.

There is little agreement on what constitutes “appropriate” learning—those individual actions or learnings that should be transferred from the individual into the organization’s memory. Standard operating procedures (SOP’s), for example, are viewed as an important part of an organization’s memory—a repository of past learning. But SOP’s can also be a roadblock to learning if an organization becomes locked into old procedures and avoids searching for entirely new modes of behavior. How does an organization decide when once-appropriate routines are no longer valid? Can an organizational anticipate obsolescence of its SOPs or must it always learn by first making inappropriate decisions in the face of changing conditions? These are the types of issues which a model of organizational learning must address.

Organizational Learning Cycles

By extending our model of individual learning to include organizational learning, we can begin to explore the transfer process between the two (see “A Simple Model of Organizational Learning”). This model represents the organizational learning cycle as a four-stage process, with organizational learning composed of three distinct sub-stages: individual learning, individual mental models, and organizational memory. Individual actions are taken based on individual mental models. These actions, in turn, translate into organizational action, and both actions produce some environmental response. The cycle is complete when the environmental response, in turn, leads to individual learning and affects individual mental models and organizational memory.

This simple model captures the transfer of individual learning to organizational memory via changes in individual mental models. Thus, organizational learning is separated from action (because all learning does not translate into taking new actions) and from environmental response (because all learning is not precipitated by the environment). The complete learning cycle, however, does include both the actions of the individual and the organization as well as the environmental response to those actions.

An Integrated Model

There are at least two fundamentally different levels of learning at which an organization must be equally adept—operational and conceptual. Operational learning deals with the changes in the way we actually do things–filling out entry forms, operating a piece of machinery, handling a switchboard, retooling a machine, etc. While operational learning emphasizes the how of doing things, conceptual learning, emphasizes the why of doing things—that is, it has do with the thinking behind why things are done in the first place. Conceptual learning deals with issues that challenge the very nature or existence of prevailing conditions or procedures. In order for organizational learning to be effective, however, conceptual learning must be operationalized into specific skills that can be learned and executed.

Individual Mental Models: Frameworks and Routines. Individual learning is captured in mental models through two different paths (see “Organizational Learning: An Integrated Model”). Operational learning produces new or revised routines that replace old or outworn ones. Conceptual learning leads to changes in frameworks, leading to new ways of looking at the world and new actions. For example, a design engineer may follow a six-step process for getting her drawings ready for a program review meeting. Through experience, she may learn to improve the process by stream-lining some of the steps involved (operational learning). As she rethinks the framework of her work—the context in which the drawings are being produced and what their use is—she may question the production of the drawings themselves and identify situations when the drawings may not be necessary (conceptual learning). Her revised mental models will contain both the new frameworks and routines as well as the knowledge about how the routines fit within the new framework.

Organizational Memory: Weltanschauung and SOP’s. The dual pathway continues from mental models to organizational memory. Over time, individual mental frameworks become embedded into the organization’s own weltanschauung, or worldview. An organization’s view of the world, in turn, affects how the individual interprets changes in the environment and how she translates her mental models into action. It also influences how the organization translates its organizational memory into action. For example, if an organization believes its ability to affect the environment is low, it will rely on standard routines and reactive behaviors. If, on the other hand, an organization assumes that it can take an active role in affecting its environment, this organization may approach everything in the spirit of experimentation, testing, and inventing.

In similar fashion, individual routines that are proven sound over time become a company’s standard operating procedures. The strength of the link between individual mental models and organizational memory depends how influential an individual or group is. In the case of a CEO or upper management, influence can be high due to the power inherent in the positions. Similarly, a united group of hourly workers can have a high degree of influence due to their size.

Incomplete Learning Cycles

Organizational learning requires completing the entire loop. If any of the links are either weak or broken, learning can be impaired. Situational learning, for example, occurs when the link between individual learning and individual mental models is severed: that is, the learning is situation-specific and does not change mental models. Crisis management is one example of situational learning in which each problem is solved but no learning is carried over to the next case.

When the link between individual models and organizational memory is broken, fragmented learning occurs. Individual mental models may change, but those changes are not reflected in the organization’s memory. When organizational learning is fragmented among isolated individuals (or groups), the loss of the individuals (through turnover or layoffs) means loss of knowledge as well.

The link between organizational memory and organizational action, if broken, can lead to opportunistic learning. This occurs when organizational actions are pursued without taking into account organizational memory or the organization’s values, culture, and SOP’s. Sometimes this is done purposely, when one wishes to bypass the features of an organization that may impede progress on a specific front. The use of “skunk works” to develop the IBM personal computer is a good example, as is General Motors’ creation of an entirely new car division, Saturn.

Managing the Whole Learning Cycle

Managing organizational learning means managing the complete cycle—explicitly. Improving each of the pieces is not enough—the links between the pieces must also be managed. This requires addressing each of the incomplete learning cycles described above.

Beyond Situational Learning.

Mental models are the critical pathway between individual learning and organizational memory. Mental models are the manager and arbiter of how new information will be acquired, retained, used, and deleted. Although a company can try to manage the flow of information, control the environment, or manipulate peoples’ learning environment in various ways, if a person’s view of the world remains unchanged, it is unlikely that any such actions will affect the quality of learning.

Therefore, closing the loop on situational learning—the link between individual learning and individual mental models—requires developing individuals’ ability to transfer specific insights into more general maps that will guide them in the future. In order to make mental models explicit, we nerd appropriate tools to capture the type of knowledge that is being mapped.

Dynamic systems, in particular, require a different set of tools for making mental models explicit. Systems archetypes (systemic structures that recur repeatedly in diverse settings) such as “Shifting the Burden” and “Tragedy of the Commons” can be very helpful for eliciting and capturing managers’ intuitive understanding of complex dynamic issues. Action maps are also useful for capturing the behavioral dynamics of a team or organization over time. They help managers see the larger patterns of behavior in which their specific actions are embedded. Together, these two methods can help surface and capture a great deal of tacit individual knowledge in a way in which it can be shared, challenged, and subject to change—thus transferring it to organizational memory.

From Fragmented to Organizational Learning. Capturing individual mental models alone is not sufficient to achieve organizational learning, however. There also needs to be a way to prevent fragmented learning among individuals and to spread the learning throughout the organization. One way to accomplish this is through the design and implementation of learning laboratories—managerial practice fields where teams of managers can practice and learn together (see page 5).

Learning laboratories can be designed, in part, around the learnings captured in systems archetypes and action maps. The spirit of the learning lab is one of active experimentation and inquiry, where everyone participates in surfacing and testing each other’s mental models. Through this process, a shared understanding of the key assumptions and inter-relationships of the organization can emerge. The use of an interactive computer management flight simulator (see “Flying People Express Again,” V IN6) offers the participants an opportunity to test their assumptions and to viscerally experience the consequences of their actions. The learning laboratory can be the vehicle through which organizational memory—via its weltanschauung and SOP’s—can be enriched over time.

Harnessing Opportunistic Learning. If the organization’s own culture and ways of doing things get in the way of learning, scenario planning and idealized designs can provide a way to break out of the norms. Royal Dutch Shell uses scenario planning to create alternative realities that stretch beyond what most managers in the company are likely to envision. By carefully constructing a multiple set of possible scenarios, Shell has been successful in anticipating and adapting to extremely volatile environments (see “Scenario Planning: Managing by Foresight,” V IN7).

Idealized designs, used by Russell Ackoff and his colleagues at Interact (Bala Cynwood, PA), can also minimize the amount of influence an organization’s current state has in determining its future. The principle idea is to start by crystallizing an ideal future without considering the current capabilities or organizational limitations. Thus, the planning process is “pulled” by where you want to be instead of “anchored” by where you are.

The Learning Challenge

The old model of a hierarchical corporation where the top thinks and the bottom acts is giving way to a new model where thinking and acting must occur at all levels. As organizations push for flatter structures and reduced bureaucracy, there will be increased reliance on the individuals to be the carriers of the organization’s knowledge. Instead of codifying rules and procedures in handbooks and policy manuals, the new challenge is to continually capture the emerging understanding of the organization wherever it unfolds. At the heart of it all is understanding the role individual mental models play in the organizational learning cycle and continually finding ways to manage the transfer from individual to organizational learning.

Further reading: Daniel H. Kim, “Individual and Organizational Learning: Where the Twain Shall Meet?” System Dynamics Group Working Paper #D-4114 (MIT Sloan School of Management, Cambridge, MA) 1989.

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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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—Colleen P. Lannon

Peter Block—Stewardship: A Governance Strategy for the Learning Organization

As we begin to develop new infrastructures for organizational learning, at some point we must address the ineffectiveness of our current governance systems. Peter Block argues that nothing short of political reform at the institutional level will provide us with the systems and structures needed to stew-ard the learning organization into the future. His exploration of the concept of stewardship provides a foundation for creating institutional structures that engage each individual in the process of moving a company toward its desired future.

—CPL

Over the years, we have tried to humanize and soften our organizational structures. But all we have learned to do is adapt more effectively to what is essentially a corrupt and autocratic system. What we really need is political reform at the level of institutional structure that addresses the larger issue of power—who is “in charge.” Ultimately, we must ask how we can create institutions where citizens and citizenship are rediscovered. How can we create a culture where we are all accountable for what is happening?

Accountability and Patriarchy

To be accountable means to carry the well-being of an institution in one’s hands. Such a change in thinking demands a redistribution of power. But given the political structures in which we now live, such redistribution is almost impossible. Our current structures are highly controlling and deeply patriarchal. Unfortunately, we all collude in maintaining that structure. We treat top management as if it is more important than other areas of the company, and we continue to express the belief that learning must start at the top (e.g., “leadership sets the vision”).

In fact, most of our management practices are “colonial” strategies designed to maintain consistency, control, and predictability. If we are serious about creating learning organizations—places where surprise, discovery, and genuine contact have meaning—then we have to do something about these artifacts of sovereignty and colonialism.

The economic motivation for change is driven by customers. They are demanding a unique response to their needs, which our current structures are incapable of providing. For example, look at the difference between Federal Express and the U.S. Post Office. At Federal Express, if I give them my last name and zip code, they know exactly who 1 am. More importantly, they know my needs and preferences as a customer. The post office, on the other hand, identifies me as “Current Resident.” Even though they come to my house every day, they do not know me as a unique customer. It’s not that the people in the post office care less about their customers than Federal Express does, it is just that Federal Express is organized to allow the customer to control the relationship. In order to make that happen in all organizations, we need to redesign our structures so that everyone feels responsible and accountable for meeting the customer’s needs.

Social Architecture

So how can we design new social architecture to support accountability and responsibility? Our task is to build the capacity of local units to redesign and reconfigure themselves—whether it is a neighborhood, school, or department. That redesign should focus on five areas: job design, staff roles, human resource practices, pay practices, and financial practices.

Redesigning Jobs. How do we engage people in restructuring their jobs to ensure that they meet the needs of a market?

Staff Roles. Many of our staff functions—finance, human resources, training and development, etc.—still operate as if top management is their customer. But we cannot have an empowered workforce if we still have staff groups that serve in a policing role. By allowing line management a choice of staff services, we can remove the power from the hands of staff groups and have them serve local units.

Human Resource Practices. How can we redesign our human resource practices to promote partnership? One way is to put power and choice in the hands of those doing the actual work by enabling peers to do the hiring, the scheduling, and the feedback of each other.

Pay Practices. Most institutions have two pay systems: executive compensation and regular compensation. The goal for executive compensation is to pay the people at the top as much as possible, while regular compensation is targeted at suppressing labor costs. How can we create a partnership when we have a system as divisive as that?

Pay should be based on success or failure in the marketplace. If a supervisor determines pay increases, that insulates individuals from the marketplace. We need to pay according to real business outcomes, rather than approval ratings.

Financial Practices. How can our financial practices create ownership at the center and at the bottom of the organization? The problem with high-control systems is that they steal accountability away from people. If management decides our pay, if others organize our efforts, if we look to “the top” to define the future, we are simply reinforcing the notion that we are not responsible. By creating a culture of accountability, and by redistributing choice and power throughout the organization, we can create large, whole systems change.

—Edited by Elisabeth Bowman

Danah Zohar—A Quantum Vision for Building the Learning Organization

The top-down control that has characterized traditional management structures is no longer effective in an age of accelerating uncertainty and rapid change. The new physics of the 20th century–particularly quantum physics—offers a new model for creating the integrative, cooperative, and constantly inventive infrastructures necessary for the learning organization. In her presentation, Danah Zohar explores the implications of the Newtonian paradigm for our society and our organizations, and describes the new possibilities that present themselves when we begin to view our organizations through the lens of quantum physics.

—CPL

Our paradigm—our deeply held set of unconscious assumptions—structures our experiences without us even realizing it. Our environment shapes this paradigm, and the paradigm, in turn, focuses our attention. It determines the questions we will ask, the expectations we will have, and the experiments we will do in our lives and in our organizations.

In fact, our brains can’t help making mental models based on our paradigms. The purpose of the self-organizing system in the brain is to make patterns out of our experience. Without this pattern-making process, we would be completely scattered. The downside, however, is that our paradigms can trap us. We can get “paradigm paralysis,” where we only know how to ask the questions that our paradigm allows us to ask.

Part of breaking out of paradigm paralysis is learning to ask new questions. In complexity and chaos physics today, there is this idea of being “at the edge,” meaning that we are poised like a tightrope walker between too much order and too much chaos. If we can learn to poise ourselves at the edge, that is where we can be most creative and begin to ask new questions that will lead to new mental models and patterns.

Newtonian Physics

All of the concepts, language, expectations, and images of our culture have come down to us filtered through the lens of Newtonian physics. Newton said that the physical world consists ultimately of atoms. Each atom is impenetrable and is related to every other by way of forces of action and reaction. When one atom touches another, it knocks the other off its path. If it doesn’t want the other off its path, the best it can do is avoid the other atom—it can “compromise.”

Freud modeled his psychology of object relations after Newtonian atomism. He said, “You’re an object to me, and I’m an object to you. When we meet, all we can do is bounce into each other, conflict, and go our separate ways. Or we find avoidance strategies.” This idea is the basis of our notion that the individual is the primary unit of society. It has led, unfortunately, to an emphasis on fragmentation. We divide our organizations into units, and these units compete and bounce against each other.

The quantum model, on the other hand, tells us that everything in the universe is interwoven with everything else. The quantum universe says that the world doesn’t consist of separate interacting parts; it consists of sets of systems that are so interwoven that they take their identity from their relationship. For example, the way I relate to you changes me. The environment in which your organization operates changes the potentiality and the whole agenda for your organization.

Uncertainty in the Quantum Organization

A quantum organization therefore stresses dynamic integration—cooperation rather than competition. In quantum physics, C always equals more than A+B. You have to bring A and B into interrelationship to get that larger C. For example, I am an individual, and I make decisions as an individual. But I am also in relationship to others, and part of me is being evoked by participation in that field. By engaging with another person in relationship, I realize an aspect of myself to which I did not have access before.

If you have a Newtonian particle at A, and it wants to get to location B, there’s one best path for that particle—it will follow the path of a straight line and go directly to B. Now in quantum systems, if you have a particle at A, you don’t even know where B is or what B is. It’s only eventually, when B comes into focus, that we see retroactively the particular path A rook to get to B. Quantum physics thus says we can’t predict anything, and that there’s no single “best path.”

Thus, the leading principle of 20th-century science is this idea of uncertainty. For our organizations, this means that we need to develop infrastructures that will allow us to surface all our potentiality and actually thrive on uncertainty. If I come into a situation with the belief that I know what I want to do, I will just get the result I am looking for. But if I come to a situation with an attitude of inquiry—questioning what might be the best way forward or what insights others can offer—then new possibilities will slowly evolve and I will get a result I never imagined possible.

Dialogue

The larger question we need to address as individuals and organizations is, “How can we dip into that rich field of potentiality and develop a whole that is greater than the sum of the parts?” Dialogue is one way to do this, because we come to a dialogue with a willingness to share our uncertainty, our pain, and our expectations. Through that process, something rather magical happens. Suddenly, everything comes together, and new ideas emerge. With those new ideas, our present position evolves—not through a Newtonian perspective, but through questioning and uncertainty. And from that experience, we arrive at a new way of thinking.

—Edited by Kellie Wardman O’Reilly

Karl-Henrik Robert—The Natural Step: A Framework for Large-Scale Change

Moving from fragmentation to wholeness means expanding our perspective to include the larger system. In his talk, Karl-Henrik Robert describes The Natural Step, a large-scale social and environmental movement that is based on the following premise: “If you want a large number of people to work together in a coordinated way, they must share an image of the system of which they are a part.” His story provides an illustration of how a common shared vision can become the catalyst for effecting large-scale change.

—CPI..

The Natural Step is a federation of professional associations in Sweden—economists, doctors, business leaders, lawyers, entertainers, etc.—that are working toward developing a sustainable society. There are approximately 10,000 people participating in The Natural Step, working together on cooperative projects. What binds our group together is a collective under-standing of the larger system of which we are a part.

A system is like a tree—the trunk and the branches are the underlying principles that give form and structure to the system, while the leaves represent the various efforts we can take to meet the principles. If we look at our work in The Natural Step from this perspective, we can see that the various associations—the engineers and scientists, doctors and lawyers—are each operating as the leaves, providing input from their background, while the trunk provides an overarching unity to our work. Because we are operating out of a shared mental model of the system as a whole, we are able to operate effectively as a team, rather than simply a collection of individuals. By working cooperatively toward the same overall principles of sustainability, we believe we can create large-scale change.

There Is No “Away”

We know from physics—from the principal of the conservation of matter—that the Earth cannot expand in volume or size to support its inhabitants. Matter doesn’t disappear on Earth, but it does change forms. That is the core of our dilemma: we are systematically turning our natural resources into garbage. We are consuming resources and turning them into dispersed waste faster than they can be reconstituted back into resources.

Our whole biosphere operates as a system of natural cycles. For over two million years, the human species took part in those cycles, utilizing resources in a manner that was sustainable. Then we identified concentrated energy, such as fossil fuels and nuclear power, which gave us access to tremendous flows of matter. Now that we have the power to utilize these resources, we are flooding our own ecosystem. We are turning back the evolutionary clock and making our species extinct. This is the global challenge that we face.

Toward Sustainability

So what are some overall principles for sustainability? Clearly, a sustainable society must integrate itself into the natural cycles of the Earth. Since matter cannot disappear, the sum of the living resources must equal the waste that is emitted back into the system. With this in mind, it is not difficult to identify the overall principle for sustainability in our whole ecosphere: there must be a balance in these flows. The basic principles can be summarized in four system conditions:

1. Extracted substances from the Earth’s crust must not systematically increase in nature. Nature cannot sustain a systematic increase of dispersed junk from the Earth’s crust. Why? Because substances disperse, but they do not disappear. Every substance becomes a toxin if its concentration is too high.

2. Substances produced by society must not systematically increase in nature. For the same reason as above, we must not produce unnatural, persistent substances such as DDT, PCB, or freons, which contribute to a systematic increase of man-made compounds. When we produce more compounds than can be handled in the system, they naturally increase in concentration and become deleterious to the system as a whole.

3. The physical basis for the productivity and diversity of nature must not be systematically deteriorated. This principle refers to the Earth’s system itself—its physical needs. We cannot keep digging up the earth, eliminating forests, and destroying the species that coexist in this system.

4. We must have a fair and efficient use of energy and other resources. If one billion people starve while another billion have a definitive over-production of goods, this cannot be perceived as a fair and efficient use of resources to meet human needs.

Creating a Sustainable Society

Thus, the four system conditions make up the trunk of the tree—the absolute, bottom-line conditions for the entire system. If we want to create a sustain-able society, we must live in agreement with these basic principles. For businesses, operating according to these basic principles is also a way of saving money and becoming more efficient.

As part of our work in The Natural Step, we work with businesses to identify the systemic consequences of their actions. By referring to the four basic system conditions, we identify the consequences of current practices, and offer professional advice on how to operate within those principles as well as pros-per from them. We train businesses to make investments that help them improve their image in the short term and set the stage for greater profitability in the long term. For example, if we continually convert non-renewable resources into garbage, the prices of those resources will inevitably go up.

We also prompt businesses to ask themselves this critical question: “Are we systematically making ourselves less economically dependent on resources or practices that have no futures’ For example, suppose we are trying to decide if we should rely more or less on mining a particular substance. If there is very little room for more mining in the system because it will violate a system condition, it is not a good long-term strategy. Any smart team understands that you will be hit by the future market or by future legislation if you systematically depend on something that has no future.

So the rules of the game for the future involve making ourselves economically independent of violating the four system conditions. If we do not succeed in this effort, the consequences are obvious—we are our own Titanic. If we go down, we all die together. The laws of nature supersede manmade laws, and they will impose themselves on us whether we want it or not—it’s just a matter of time. In realizing this, we can make a choice—to continue to follow unsustainable practices that we will pay for in the long term, or begin to profit now from smart investments that take into account the natural infrastructure of which we are a part.

—Edited by Diane J. Reed

Peter M. Senge—Building Learning Infrastructures

Sustaining large-scale change requires more than a one-time shift in structures and habits—it requires deeply embedded infrastructures that enable the continued creation and dissemination of new knowledge. Peter Senge discusses the recent innovations in infrastructure that are snaking the learning organization a sustainable phenomenon. His discussion of infrastructure then becomes a springboard for exploring the role of storytelling in creating a larger context and meaning for our work.

—CPL

There has been a lot of emphasis in business lately on the importance of infrastructure. Reengineering, business process redesign, and rethinking performance measures all have to do with the infrastructure of organizations—what wires things together. I believe that fundamental innovations in infrastructure are important in order to create an environment where the work we are doing can continue. These innovations in infrastructure fall into two categories: (1) rethinking and redesigning existing infrastructures; and (2) creating new infrastructures to support learning.

Redesigning Existing Infrastructure. One area of potential leverage involves redesigning existing organizational infrastructures—the process that currently hold together organizations. For example, Shell International Petroleum Company’s rise from a mediocre position in the world oil industry to preeminence was the redesign of a critical infrastructure—its planning process. Shell’s planners discovered that having a single plan was becoming irrelevant in a world of unpredictability and change. But the planning process itself—the act of bringing people together to develop strategies in response to various scenarios—was increasingly important. Shell’s scenario planning process, which was eventually named “planning as learning,” represents an extraordinarily elegant strategy for creating new learning capabilities in organizations.

Creating New Infrastructures. In addition to rethinking the elements of infrastructure that have always existed, over the last few years a whole host of new innovations in learning infrastructure have emerged. For example, coaching networks have become an important part of team development. Coaching can take the form of educational initiatives, diagnosis, intervention design, facilitation, and core process consultation. At EDS there are now about 100 “transformational coaches” who have gone through a one-year training program in these skills, and several other companies are developing similar networks of internal coaches.

Another area of infrastructure development centers around redesigning the work environment so that working and learning become inseparable. This includes innovations such as learning laboratories and applied practice fields. For example, at Ford Motor Company, the 1995 Lincoln Continental team created a new car development learning laboratory. Federal Express has also developed a global sales learning laboratory, and there are many other learning laboratories being used in other companies.

These individual learning experiences have had some well-documented successes. But the next challenge is how to share the insights from individual teams throughout the respective companies. We are gradually coming to realize that there is no infrastructure in our organizations to enable serious analysis and reflection on what is being learned. One possible way to do this is through learning histories—a formal process that is being developed for capturing data on critical learning incidents. As one example, for 150 years the U.S. Army has had learning historians who provide it with a rich sense of its own history and its ability to learn from the past.

Why Talk about Infrastructure?

We can get very excited about the new infrastructures that are being developed, but building infrastructure is not an end in and of itself. Organizational learning infrastructures are part of a larger group of elements that are essential for designing a learning organization—what I have termed “organizational architecture” (see “Framework for the Learning Organization”). And organizational architecture really functions in the service of a larger purpose, which is to create an environment in which the “deep learning cycle” can be initiated, energized, and sustained. The deep learning cycle involves developing fundamental new skills and capabilities, which lead people to see the world differently and then to develop fundamental new attitudes and beliefs.

Essentially, we need to develop sufficient organizational architecture in order to begin to sustain this deep learning cycle—to be able to create some degree of critical mass of new collective capacity. As this capacity develops, it further expands our collective ability to listen to the larger pattern of what is emerging—the “implicate order” that I referred to in my original presentation of this framework at the 1993 Systems Thinking in Action”‘ Conference. This brings us to a new point in the cycle, as we reflect on the emerging story—a new, deeper set of “guiding ideas.”

Framework for the Learning Organization

Innovations in infrastructure are part of a larger group of elements–organizational architecture–that are essential for designing a learning organization. Organizational architecture really functions in the service of a larger purpose. which is to create an environment in which the “deep learning cycle” can be initiated, energized, and sustained. The deep learning cycle involves developing fundamental new skills and capabilities, which lead people to see the world differently and to develop fundamental new attitudes and beliefs.

What Is Our Story?

I think this brings us to the question, “What is our new cultural story?” Cultures ultimately need a story in order to be vital. But as a society and as a culture, we have lost our story. The old story—the account of how the world came to be and how we fit into it—sustained us for a long period of time. It shaped our emotional attitudes, provided us with life purpose, and energized our actions. But it is no longer functioning properly, and we have not learned a new one.

Dee Hock, the founder of VISA International, says that “we are living in an era of massive institutional failure on every front.” The mismatch between our large institutions and the deeply complex interdependent world we live in is evident in our current environmental crises, in the chaos and perpetual crises of businesses, in our paralysis in confronting national political issues, in the breakdown of our societal infrastructure and civic spirit, etc. There is not a single critical institution that is not failing in the eyes of the public.

As the cycle moves another turn, it’s time for a new set of guiding ideas. It’s time for a new story of how human beings and human institutions can rediscover our place in a larger natural order. As Sarita Chawla asked, “What is the story our grandchildren would want us to be telling today?”

—Edited by Colleen P. Lannon

Peter Block is a consultant and speaker whose work focuses on ways to create empowering organizations. He is the author of Stewardship and The Empowered Manager

Danah Zohar is a physicist and philosopher who teaches at Oxford Brooks University in England. She is the author of The Quantum Self and The Quantum Society.

Karl-Henrik Robert is the founder and working chairman of The Natural Step, a federation of professional associations in Sweden that cooperate on projects to benefit the environment.
Peter M. Senge is the director of the MIT Center for Organizational Learning, and author of The Fifth Discipline: The Art and Practice of the Learning Organization.

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