With a total of 300,000 employees, Ford operates in 50 countries around the world. It sells a huge array of products, and offers an equally widespread range of services — from financing to distributing and dealer support.

VENTURING INTO THE BADLANDS

When system and social complexity are high, the organization enters the realm of “the Badlands.”

Like any large organization, it’s also peopled by individuals who come from all walks of life — and who have the different outlooks to prove it. Engineers, accountants, human-resource folks — they all have unique backgrounds and view their work through unique perspectives. Add Ford’s various stakeholders to the mix, and you’ve got even more complexity. There are media stakeholders, shareholders, customers, the families of employees — all of them with different expectations and hopes for the company.

System and Social Complexity: “The Badlands”

Now let’s look even more deeply inside Ford to see what complexity really consists of. If you think about it, the complexity that Ford and other large organizations grapple with comes in two “flavors”: system complexity and social complexity. System complexity derives from the infrastructure of the company — the business model it uses, the way the company organizes its various functions and processes, the selection of products and services it offers. Social complexity comes from the different outlooks of the many people associated with Ford — workers, customers, families, and other stakeholders from every single country and culture that Ford operates in.

Why is it important to distinguish between these two kinds of complexity? The reason is that, if we put them on a basic graph, we get a disturbing picture of the kinds of problems that complexity can cause for an organization (see “Venturing into the Badlands”). We can think of these problems as falling into four categories:

“Tame” Problems. If an organization has low system and social complexity — for example, a mom-and-pop fruit market in a small Midwestern town — it experiences what we can think of as “tame” problems, such as figuring out when to order more inventory.

“Messy” Problems. If a company has low social complexity but high system complexity, it encounters “messy” problems. A good illustration might be the highly competitive network of tool-and-die shops in Michigan. These shops deal with intricate, precisely gauged devices that have to be delivered quickly. However, the workforce consists almost entirely of guys, all of whom root for the Detroit Lions football team — so there’s little social tension.

“Wicked” Problems. If a company has high social complexity but low system complexity, it suffers “wicked” problems. For instance, a newspaper publisher works in a relatively simple system, with clear goals and one product. However, the place is probably staffed with highly creative, culturally diverse employees — with all the accompanying differences in viewpoint and values.

The Winner: “Wicked messes,” or “The Badlands.” When an organization has high system and social complexity — like Ford and other large, globalized companies have — it enters “the Badlands.” Singer-songwriter Bruce Springsteen graphically captured that unique region in South Dakota characterized by dangerous temperature swings, ravenous carnivores, and uncertain survival in his song “Badlands.” But the area and the song also represent optimism and possibilities. More vegetation and wildlife inhabit the Badlands than anyplace else in the United States, and Springsteen’s voice and lyrics offer a sense of hope despite the song’s painful and angry chords.

What’s So Bad About the Badlands?

A company that’s operating in the Badlands faces a highly challenging brand of problems. The complexity is so extreme, and the number of interconnections among the various parts of the system so numerous, that the organization can barely control anything. Solutions take time, patience, and profound empathy on the part of everyone involved.

In Ford’s case, a number of especially daunting challenges have arisen recently. For one thing, the Firestone tires tragedy has left the entire Ford community reeling. Ford faces an immense struggle to make sure this kind of fiasco never happens again. The bonds of trust between company and supplier, and between company and customer, will take a long time to rebuild. In addition, Ford and other automotive manufacturers have come under fire not only for safety issues but also for environmental and human-rights concerns.

Clearly, Ford’s business environment keeps getting tougher. The company is held accountable for parts it buys from suppliers and for labor practices in the various parts of the world where it does business. It’s also accountable for resolving baffling patterns — for example, the demand for

All of these challenges come from a single error in thinking: the assumption that human beings can control a complex, living system like a large organization.

SUVs is rising, along with cries for environmentally friendly vehicles. The majority of Ford’s profits come from sales of SUVs; how will the company reconcile these conflicting demands? Ford’s newly launched initiative — to not only offer excellent products and services but to also make the world a better place through environmentally and socially responsible manufacturing — will probably be its toughest effort ever.

But here’s where the big lesson comes in. All of these challenges come from a single error in thinking: the assumption that human beings can control a complex, living system like a large organization. Systems thinker Meg Wheatley compares the complexity of large companies to that of the world. The world, she points out, existed for billions of years before we humans came along, but we have the nerve to think that it needs us to control it! Likewise, what makes us think that we can control a big, complex organization?

Yet attempt to control we do — often with disastrous results.

Our All-Too-Common Controls . . .

We human beings try to control the complexity of our work lives through lots of different means:

System Fixes. When we attempt to manage system complexity, we haul out a jumble of established tools and processes that seem to have worked for companies in the past. For example, we use something we blithely call “strategic planning.” Our assumption is simple: If we just write down the strategy we want to follow, and plan accordingly, everything will turn out the way we want. We even call in consultants to help us clarify our strategy — and pay them big bucks for it. The problem is that this approach to planning has long outlived its usefulness. The world has become a much more complicated place than it was back when organizations like General Motors and the MIT Sloan School of Management first devised this approach to strategy.

We also use financial analysis and reporting models that were probably invented as far back as the 1950s. These models don’t take into account all the real costs associated with doing business — such as social and environmental impacts. Nor do they recognize the value of “soft” assets, such as employee morale and commitment.

In addition, we all keep throwing the phrase “business case” around — “What’s the business case for that new HR program you want to launch?” “What’s the business case for that product modification?” In other words, what returns can we expect from a proposed change of any kind? Again, this focus on returns ignores the bigger picture: the long-term costs and benefits of the change.

Finally, we try to manage system complexity by making things as simple as possible through standardization — no matter how complicated the business is. Standardization is appropriate at times. For example, the Toyota Camry, Ford’s number-one competitor in that class of car, has just seven kinds of fuel pump applications. The Ford Taurus has more than 40! You can imagine how much simpler and cheaper it is to manufacture, sell, and service the Camry pump. But when we carry our fondness for standardization into areas of strategy — unthinkingly accepting methods and models that worked best during a simpler age — we run into trouble.

Social Fixes. Our attempts to manage social complexity get even more prickly. In many large companies, the human-resources department engineers all such efforts. HR of course deals with personnel planning, education and training, labor relations, and so forth. But in numerous companies, it spearheads change programs as well — whether to address work-life balance, professional development, conflict and communications management, or other social workplace issues. Yet as we’ll see, this realm of complexity is probably even more difficult to control than systemic complexity is.

. . . and Their Confounding Consequences

Each of the above “fixes” might gain us some positive results: We have a strategic plan to work with; we have some way of measuring certain aspects of our business; we manage to get a few employees thinking differently about important social issues. However, these improvements often prove only incremental. More important, these fixes also have unintended consequences — many of them profound enough to eclipse any gains they may have earned us.

The Price of System Fixes. As one cost of trying to control system complexity, we end up “micromanaging the metrics,” mainly because it’s the only thing we can do. This micromanaging in turn creates conflicts of interests. For example, when Ford decided to redesign one of its 40 fuel pumps to make it cheaper to build, it unwittingly pitted employees from different functions against each other. Engineering people felt pressured to reduce the design cost of the part, manufacturing staff felt compelled to shave off labor and overhead costs, and the purchasing department felt driven to find cheaper suppliers. Caught up in the crosscurrents of these conflicting objectives, none of these competing parties wanted to approve the change plan unless they got credit for its success. As you can imagine, the plan languished in people’s in-boxes as the various parties jockeyed for position as “the winner.”

Micromanaging the metrics can also create a “Tragedy of the Commons” situation — that archetypal dilemma in which all the parties in a system try to maximize their own gains, only to ruin things for everyone. For instance, at Ford (and probably at many other large companies), there’s only so much money available to support a new product or service idea. People know this, so when they build their annual budgets, they ask for the money they need for the new ideas — plus another 10 percent as a cushion (because they know the budget office would never give them what they originally asked for!). At the end of the year, everyone’s out of funds because they beefed up their budgets too much. And great, innovative ideas end up going unfunded.

The Price of Social Fixes. The biggest consequence of social fixes is probably a “Shifting the Burden” archetypal situation. Upper management, along with HR, tries to address a problem by applying a short-term, “bandage” solution rather than a longer-term, fundamental solution. The side effect of that bandage solution only makes the workforce dependent on management, thus preventing the organization from learning how to identify and implement a fundamental solution.

What does this look like in action? Usually, it takes the form of upper management’s decision to “roll out” a change initiative to address a problem. For instance, employees might be complaining about something — work-life tensions, conflicts over cultural differences, and so forth. Rather than letting people take responsibility for addressing their problems — that is, get involved in coming up with a shared solution — management force-feeds the company a new program (B1 in “Shifting the Burden to Management”). This might reduce complaints for a time, and managers might even capture a few hearts and minds. But these gains won’t stick. Worse, this approach makes employees passive, as they come to depend more and more on management to solve their problems and “take care of them.” The more dependent they become, the less able they are to feel a sense of responsibility and get involved in grappling with their problems (R3 in the diagram).

This “sheep-dip” approach to change — standardized for the masses — completely ignores employees’ true potential for making their own decisions and managing their own issues. For example, consider the difference between a company that legislates rigid work hours and one that trusts its employees to pull an all-nighter when the work demands it—and to head out to spend time with their kids

on a Friday afternoon because the work is in good shape. People can’t learn how to make these kinds of judgments wisely for themselves if their employer treats them like children.

“Sheep dipping” has another consequence as well: Because it makes employees passive, it discourages the fluid transfer of knowledge that occurs when people feel involved in and responsible for their work. Instead of looking to one another, anticipating needs, and collaborating as a team, employees have their eyes on management, waiting to be taken care of. Knowledge remains trapped in individuals’ minds and in separate functions in the organization, and the firm never leverages its true potential.

From Control to Soul

So, if we can’t control complexity, how do we go to work every day with some semblance of our sanity? Should we just give up hoping that our organizations can navigate skillfully enough through the Badlands to survive the competition and maybe even achieve their vision? What are we to do if we can’t control our work, our employees, and our organization? How can we take our organizations to places they’ve never been — scary, dangerous places, but places that also hold out opportunities for unimagined achievement?

The answer lies in one word: soul. “Soul” is a funny word. It means different things to different people, and for some it has a strong spiritual element. But in the context we’re discussing now — organizational health, values, and change — its meaning has to do with entirely new, radical perspectives on work and life.

To cross the Badlands successfully, all of us — from senior executives to middle managers to individual contributors — need to adopt these “soulful” perspectives:

Understand the system; don’t control it. As we saw above, we can’t manage, manipulate, or avoid problems in our organizations without spawning some unintended — and often undesirable — consequences. Understanding the organizational and social systems we live and work in makes us far more able to work within those systems in a healthy, successful way.

Know the relationships in the system. Understanding a system means grasping the nature of the relationships among its parts — whether those parts are business functions, individuals, external forces acting on the organization, etc. By knowing how the parts all influence each other, we can avoid taking actions that ripple through the system in ways that we never intended.

Strengthen human relationships. Success doesn’t come from dead-on metrics or a seemingly bulletproof business model; it comes from one thing only: strong, positive relationships among human beings. When you really think about it, nothing good in the world happens until people get together, talk, understand one another’s perspectives and assumptions, and work together toward a compelling goal or a vision. Even the most brilliant individual working alone can achieve only so much without connecting and collaborating with other people.

Understand others’ perspectives. This can take guts. People’s mental models — their assumptions about how the world works — derive from a complicated process of having experiences, drawing conclusions from those experiences, and then approaching their lives from those premises. Understanding where another person is “coming from” means being able to set aside our own mental models and earn enough of that other person’s trust so that he or she feels comfortable sharing those unique perspectives.

Determine what we stand for. Why do you work, really? Forget the easy answers — “I want to make money” or “I want to buy a nice house.” What lies beneath those easy answers? Around the world, people work for the same handful of profound reasons: They want their lives to have meaning, they want to create something worthwhile and wonderful, they want to see their families thrive in safe surroundings, they want to contribute to their communities, they want to leave this Earth knowing that they made it better. All these reasons define what we stand for. By clarifying what we stand for — that is, knowing in our souls why we go to work every day — we learn that we all are striving for similar and important things. That realization alone can build community and commitment a lot faster than any “rolled-out” management initiative can.

Determine our trust and our trustworthiness. Strong relationships stem from bonds of trust between people. To trust others, we have to assume the best in them — until and unless they prove themselves otherwise. But equally important, we also need to ask ourselves how trustworthy we are. We must realize that others are looking to us to prove our trustworthiness as well. By carefully and slowly building mutual trust, we create a network of robust relationships that will support us as we move forward together.

Be humble, courageous, and vulnerable. Understanding ourselves and others in ways that strengthen our relationships takes enormous courage — and a major dose of humility. It also takes a willingness to say “I don’t know” at times — something that many companies certainly don’t encourage. And finally, it takes a willingness to make ourselves vulnerable — to explain to others why we think and act the way we do, and why we value the things we value.

Find “soul heroes.” We need to keep an eye out for people whom we sense we can learn from — people who live and embody these soulful perspectives. These individuals can be colleagues, family members, friends, customers, or neighbors. If we find someone like this at work — no matter what their position — we must not be afraid to approach them, to talk with them about these questions of values, trust, and soul.

Tools for Your Badlands Backpack

So, to venture into the Badlands, we need soul — whole new ways of looking at our lives and work. But soul alone won’t get us safely through to the other side. We wouldn’t approach the real Badlands without also bringing along a backpack filled with water, food, first-aid materials, and other tools for survival and comfort. Likewise, we shouldn’t tackle the Badlands of organizational complexity without the proper tools.

These five tools are especially crucial:

Systems Thinking Tools.The field of systems thinking provides some powerful devices for understanding the systems in which we live and work, and for communicating our understanding about those systems to the other people who inhabit them. Causal loop diagrams, like the one in “Shifting the Burden to Management,” let us graphically depict our assumptions about how the system works. When we build such a diagram with others, we especially enrich that understanding, because we pull all our isolated perspectives into one shared picture. From there, we can explore possible ways to work with the system to get the results we want. These diagrams also powerfully demonstrate the folly in trying to manhandle a system: When we draw them, we can better see the long-term, undesirable consequences of our attempts to control the system.

Dialogue. The field of dialogue has grown in recent years to include specific approaches to talking with one other. For example, dialogue emphasizes patience in exploring mutual understanding and in arriving at potential solutions to problems. It also encourages us to suspend our judgments about others during verbal exchanges — that is, to temporarily hold our judgments aside in order to grasp others’ reasons for acting or thinking as they do. Dialogue lets a group tap into its collective intelligence — a powerful way of transferring and leveraging knowledge.

Ladder of Inference. This tool offers a potent way to understand why we think and respond to our world as we do. It helps us see how we construct our mental models from our life experiences — and how those mental models can ossify if we don’t keep testing them to see whether they’re still relevant. In the workplace, we all make decisions, say things, and take actions based on our mental models. By using the Ladder of Inference to examine where those models came from, we can revise them as necessary — and reap much more shared understanding with colleagues. (For information about the Ladder of Inference, see The Fifth Discipline Fieldbook published by Currency/ Doubleday).

Scenario Planning. This field has also grown in recent years. Numerous organizations, notably Royal Dutch/Shell, have used scenario planning to remarkable effect. This tool reflects the fact that we can’t control systems. Scenario planning encourages us to instead imagine a broad array of possible futures for our organization or even our entire industry — and to make the best possible arrangements we can to prepare for and benefit from those potential outcomes. This approach thus acknowledges the complexities inherent in any system; after all, there’s no way to easily determine the many different directions a system’s impact may take.

Managing by Means. New methodologies are emerging that can help us assess the true costs of running our businesses — costs to human society, to the environment, and to the business itself. And costs in the short run as well as the long run. We must grapple with these methodologies if we hope to achieve the only long-term business goal that really makes sense: business that doesn’t destroy the very means on which it depends.

Traditional change management methods build things to stick. They do not build things to last and are thus ineffective because well-intentioned people create the strategy, solution, and problem sets based on a narrow set of assumptions. To create a sustainable organization, we must work to understand the complex system dynamics of the environment and experiment with multidimensional strategies. We must also work to understand diverse social dynamics and allow multiple perspectives and behaviors to emerge. Finally, we must trust ourselves, hold true to our core convictions, and have courage, humility, and soul. In these ways, we can navigate through — and even prosper in — the most desolate and challenging of Badlands.

David Berdish is the corporate governance manager at Ford Motor Company. He is leading the development of sustainable business principles that will integrate the “triple bottom line” of economics, environmental, and societal performance and global human-rights processes. He is also supporting the organizational learning efforts at the renovation of the historic Rouge Assembly site.

The post Learning and Leading Through the Badlands appeared first on The Systems Thinker.

JAY FORRESTER: I think we should start by realizing that system dynamics is a profession like learning engineering or medicine. The idea that it is quick and easy to acquire is fallacious. We’ve had the experience of running a basic training program in system dynamics here at MIT the last three years by e-mail for professionals around the world; about 20 took it each year. It was a very intensive program in which participants received an assignment each week that took them about 15 hours to complete. That is a big load on top of their normal activities. The program ran for 30 weeks. Thirty weeks at 15 hours a week is 450 hours of work on their part. At the end, many said, “I’m now beginning to see enough of this field to know that I need to go further.”

We have seen people going to three-day conferences and thinking they’re experts in system dynamics. They set themselves up as consultants or to bring the ideas into a corporation when, in fact, they don’t have enough insight to know how to approach the subject. You can draw an analogy to medicine. I think a one-day first-aid course is useful. It will help you with simple things in medicine, but it does not prepare you to do heart transplants. System dynamics covers fully that wide a range.

The activity called “systems thinking,” which is talking about systems, recognizing there are systems, and agreeing that systems are important, is really at the level of the one-day first-aid course. It is not sufficient for understanding the dynamics of an organization. I have no doubt that a brief introduction can be useful; it just isn’t sufficient. The introduction from systems thinking is not strong enough and not persuasive enough to reverse detrimental policies that are strongly held, because there’s no solid basis for the argument to change. A systems thinker cannot, I believe, achieve the kind of position that one can have working from a good system dynamics simulation model.

With a solid, thoroughly studied system dynamics model, you know the assumptions that are in the model, you know the behavior those assumptions lead to, and you know how the behavior will change from a wide variety of different policies. If everything you say at the level of policies, at the level of structure, and at the level of behavior is correct in the eyes of participants who know various parts of the real system, it becomes persuasive. And that’s what the expert system dynamics practitioner should aspire to.

I would say that any attempt to introduce a deep understanding of systems on a broad sweep through the organization by simply talking about it probably will not be effective. The right way is to go deeply into some specific issues, do serious computer simulation modeling, and show how the troubles of the organization are being generated, how problems evolved out of past policies, and how alternative policies would improve behavior. To effectively create and use a model requires skill. People will spend tens of millions of dollars over a period of five years or more to develop a new product, but are reluctant to spend anything like that amount in preparing themselves to make the corporation more successful.

I think the way to introduce system dynamics is to find colleagues, build a grassroots understanding, develop skills, and get help from people who understand system dynamics very well. Engaging an expert consultant in system dynamics can accelerate the launching of a program. System dynamics is for solving problems. An effort should start by selecting an important problem. Decide what difficulty to work on and model its causes, rather than starting to model the entire system.

Most people believe their problems are created from outside. In system dynamics modeling, we usually find that the problems are being created on the inside. A corporation that is having problems and is being overtaken by other organizations is operating in the same outside world as those other corporations. Therefore, it must be something they themselves are doing that is causing them to be different and less effective.

Beyond the “Quick Fix” Mindset

DC: In some of my meetings with management teams, something seems to be missing in terms of the way that problems or issues are approached. The thinking somehow doesn’t encompass what you just talked about.

JWF: People expect a quick fix in a year. A company’s problems take years to develop and the fixes take years to repair the damage. If you look carefully at the difficulties of many major corporations, you find the cause of troubles began 10, 15, or 20 years before symptoms are recognized by management or the public.

It’s a mindset of the whole society that’s standing in the way — the mindset on short-term results. In complex systems, we usually see that policies that are good in the short run produce troubles in the long run and vice versa. Therefore, to do something good in the long run probably imposes some pain in the short run. With hired managers who are in their positions only one to five years, their personal interests tend to be in the short run. They are not committed to the long-run good of their organizations. The financial markets also tend to impose that same detrimental short-run view.

People will spend tens of millions of dollars to develop a new product, but are reluctant to spend anything like that amount to make the corporation more successful.

The attitude of founder owner managers is substantially different. Those who found a company, who are significant owners, and who are managing without expectation of going to some other corporation can have a 20 year view or more. I think many of today’s corporations that are being run by short view point managers will disappear in favor of a new wave of founder-owner-manager companies.

DC: Compare the current state of the field of system dynamics its development and acceptance with your own hopes and expectations.

JWF: It’s probably developing faster than I would have expected. The growth rate in the field number of people interested in it is probably doubling every four years or so, which is a very rapid growth rate. We are arriving now at the point where it really can’t be ignored. The consulting companies are looking more and more for people with system dynamics backgrounds. And, of course, my own work is helping to in filtrate system dynamics into the kindergarten through 12th-grade educational levels. I think it’s going very, very well.

A lot of people in the field express disappointment. They say, “Why isn’t it developing faster?” Well, it can’t because one of the great dangers is running ahead of the number of people who can practice it effectively and correctly.

I think one can argue that great frontiers don’t stay as frontiers; they become a part of everyday life. The most recent frontier has been exploring science and technology. I think the next great frontier is to truly understand and be able to improve the behavior of our social, economic, and managerial systems. The understanding of those systems has not improved markedly since the time of the ancient Greeks. My wife and I were taking a tour through the Alhambra, the great Moorish castle above Granada, Spain. Our guide stopped at one point to show us the room where the Moors around the year 1300 met to discuss their problems of inflation and balance of trade problems that are still with us.

It’s clear why the understanding has not advanced until recently there has not been any effective means to understand dynamic complexity of social systems. Mathematics is a weak science when it comes to dealing with dynamics. It can deal with extremely simple systems, but in realistic social systems, there is no possibility of getting mathematical solutions. Therefore, simulation is the only known approach. System dynamics modeling is like doing experiments in the laboratory instead of trying new policies on a corporation. The simulation experiment is much clearer than trying policy changes in real life because you know the circumstances under which you did the experiment, you know the policy changes that were made, and you know nothing else has changed. If you carry on those same experiments in real life, results are very ambiguous, because you’re never quite sure what other things affected the results.

Are We Doomed?

DC: In my work, I keep running into deep frustration that employees lower within an organization experience, and the high levels of burn out, cynicism, and turnover that result. I believe that this is linked to not using system dynamics more effectively in running organizations.

JWF: Well, you find a lot of reasons for frustration. Demands are put on people that they cannot possibly achieve, because they aren’t given the resources and authority to produce what is demanded. Further more, people haven’t been educated in what they need to know to succeed. Those lower-level people are squeezed by demands for impossible performance. That’s very frustrating.

DC: My sense is that people tend to blame upper management for the problem.

JWF: I suppose it’s fair enough from the viewpoint of the middle level to blame upper management. But upper managers are in the same situation; they also do not know what to do and are themselves under pressures from the outside world. Everybody is operating under the pressure of growth. Why should they be? Why not just run a successful business? It is not possible for everybody to grow beyond the capability of the system. We have great pleading to allow people to immigrate into this country because we think we need more labor. Why should we want to do more than we are able to do? The attitudes that society has drifted into create pressures not only at the middle levels, but also at the top of corporations. Many top managers are coping with problems created by predecessors who focused on the short run.

DC: Are we doomed?

JWF: A lot of large corporations are doomed, yes, and properly they should be. It is good for society to have decaying organizations eliminated. Great depressions like in the 1930s have traditionally helped solve such decay and inefficiency. Severe economic downturns wipe out a lot of dead wood incorporations and open the door for new, vital growth.

DC: What do you see in the future as potential breakthrough areas in the field of system dynamics?

JWF: We need a different approach from the one followed in the early days of system dynamics. The result of a system dynamics study will almost always show that the serious problem at hand arises from policies people know they are following but believe are the solution to their problems. You often have to say to people, “Your problems are because of what you’re doing that you’re proud of, and you must reverse your course.” It takes three or four years for them to accept that point.

We’ve often worked many years to introduce system dynamics into corporations from the top down. It takes three or four years with even a receptive top management before they fully understand. Then the people you’re dealing with retire or die, and you have to start over with another group. This is one of the main reasons why I shifted over to system dynamics in kindergarten through 12th grade, to bring up a society that has a better understanding of the nature of the systems within which we live.

It is much easier to teach system dynamics to fifth graders than it is to CEOs or parents. As children ask questions that people can’t answer, they learn it’s politically incorrect to ask questions that embarrass people. So they finally stop addressing the big issues. However, at age 10, children have much less to unlearn and they have more open minds. They are more inquisitive; they have not yet had stamped out of them the desire to understand what is difficult.

The Linking of People and Modeling Skills

DC: I have found a lot of fear in people trusting that there might be a different way to do things.

JWF: That’s right. There are two big hurdles in system dynamics: having enough people with enough competence, and finding out what to do about people being afraid to take the steps necessary to improve their situations. There are great challenges in implementing policies that are opposite to what people have been doing and what they believe is successful, even though those policies are getting them into worse and worse difficulty.

DC: Does it mean that system dynamics professionals also need to be fairly skillful in dealing with people? They can’t just be good modelers?

JWF: To be successful, yes. Sometimes we see a team where several people have different roles, with one doing dynamic modeling work and other spaying attention to how to get people to understand it, why are they balking, and why they find it so difficult.

DC: What career advice would you give young system dynamics practitioners?

JWF: I suppose the main thing would be to keep building skills. Very few have read all of the available good system dynamics literature, and probably very few are trying to establish an apprenticeship with an expert. Just as in medicine, one needs to go through an internship. One does not just go to medical school and then do major operations or deal with the most serious illnesses most learning comes from experience. You don’t learn system dynamics by just going to conferences; you must have working experience. System dynamics is not a spectator sport. Like learning to ride a bicycle, listening to lectures is not sufficient.

I would say that a young system dynamicist who goes by himself into a company and is doing simulations will have great difficulty in building acceptance. The best choice would be to go into a place where there is already some level of acceptance, but also to be careful not to be subverted by bad system dynamics that may already be going on there. There’s a lot of so called system dynamics work that is very bad practice. People who are not yet competent are trying to do things well beyond their ability because system dynamics seems deceptively simple. The major books in the field can be read by almost anyone. Urban Dynamics was, I think, on the list of books for discussion by the League of Women Voters and PTAs. People can read those books and understand them, and the process looks very straight forward. Then, when the person closes the book and says, “I’ll do some of that for myself,” there isn’t the slightest idea of what to do next. Also, the accessibility of system dynamics software allows people to build things that look like system dynamics models but may not be useful. There is a great need for processes for developing high levels of skill.

DC: If you were going to design a corporation, how would you introduce system dynamics?

JWF: It’s like introducing system dynamics into K–12 education. InK–12, very few places have a way to learn system dynamics. System dynamics needs to become a part of everything else that’s going on. It has to be widespread to be most effective. In a corporation, suppose we have a top management that has some serious problems, and the long-term dynamic solution requires reversing cherished policies. Assume top management accepts the reversed policies, they believe in the new policies, they are willing to act, and they issue instructions to do so. Below the top will be several levels of managers who see it as their duty to protect the organization from the idiosyncrasies of the top. The understanding of policy design must extend down through many levels.

DC: So even if you had a group of executives who decide to change policies, they may still be in trouble.

JWF: As an example, take one of the early studies in system dynamics done by a couple of graduate students. It dealt with a two terminal trucking company between Boston and Philadelphia. Their big problem was that trucks tended to be at the wrong end of the route. When they needed to ship things from Boston to Philadelphia, they had too many trucks in Philadelphia and vice versa.

The modeling showed how the terminal with extra trucks could provide prompt service, and business there would increase until trucks were concentrated at the opposite end, resulting in poor service and decline of business at the first terminal. Then service would improve and business would pick up at the second terminal. Business would swing back and forth as the stock of trucks shifted.

“The high-school teachers who know what’s going on here are terrified. They see the day coming when the elementary schools and the middle schools will be delivering to them little monsters who can think!”

The solution then became relatively obvious: They needed to keep their trucks balanced, even if they sometimes had to send empty trucks from one end to the other. Management understood and issued orders but nothing happened, because the people in the dispatching office and on the shipping dock knew the company didn’t make money driving empty trucks around. Nothing happened until the model was explained on the shipping room platform and in the dispatchers’ offices. I was told that one could hear truck loaders on the dock discussing the model. At that point, management could get the policy implemented, because now it made sense and everyone understood why. Previously, the lower level employees, who were making day-by-day decisions, saw the policies as totally irrational and believed they should resist in the best interests of doing a good job.

“Delivering Little Monsters Who Can Think!”

DC: Is your K–12 initiative developing as you had anticipated? What have you been learning from it?

JWF: Yes, I think it’s developing as rapidly as is reasonable. Moving to system dynamics is a difficult transition. A particular school may start with one enthusiast but, even in a receptive environment, it may take 10 years to get to a self-sustaining, school wide activity.

There are now conferences for teachers interested in system dynamics in K–12 education. My wife and I went to one at the end of June 2000. There were nearly 200 teachers present. Never before in any field have I gone to professional meetings where the excitement is so high and the enthusiasm about the future so great. Teachers come up to me and say, “I had no idea these students could do so much.” One teacher reported that in the junior high, the students in detention hall for misbehavior dropped from an average of 50 to an average of 5. It’s the first time they’ve seen students who want to come in before school starts and stay after it ends. My favorite sound bite was from the teacher who said, “The high school teachers who know what’s going on here are terrified. They see the day coming when the elementary schools and the middle schools will be delivering to them little monsters who can think!”.

DC: Jay, what are they doing in high schools around system dynamics?

JWF: Most of what’s going on so far is very elementary. Furthermore, there is not yet any continuous program that builds on itself from kindergarten through 12th grade, to say nothing about going on through undergraduate college and graduate schools. There’s no organized developmental path yet. Eighth, ninth, or tenth graders should be able to move well head of what is now being taught in the graduate schools. There’s the challenge of developing new material for high school, and for four years of undergraduate and three years of graduate school. That would be some 12 years of material not yet on the books. The system dynamics challenge for the future lies in developing such additional depth and breadth.

Worcester Polytechnic Institute is the first school to organize a four year undergraduate program leading to a bachelor’s degree in system dynamics. It will take a long time to get system dynamics introduced widely into teachers’ colleges. The teachers that are coming into system dynamics now are doing so through knowing others who have become enthusiastic and by reading the limited amount of available material. They become intrigued, they introduce a little into a class, and then it begins to evolve. You hear stories like a teacher begins to introduce system dynamics in biology, and other teachers find that their students are taking notes in system dynamics stock and flow diagrams. Then the other teachers go to find out what is happening.

System dynamics runs across all disciplines. The application to physics is fairly obvious because of the dynamics involved, but it’s probably not one of the most active areas. In social studies, students can use system dynamics to explore the economic and social forces causing various things to unfold in history. There are English teachers doing computer simulation modeling of the psychological dynamics in various pieces of literature. System dynamics provides a foundation that underlies most of the subjects. A student discovers a new mobility between subjects. If one understands a particular dynamic structure in one setting, the behavior is the same in all settings.

DC: So it seems as though for children who experience feedback dynamics over a number of years, there’s a deep difference in the way they perceive things.

JWF: Entirely different. One father of a junior high boy told me his son had gone on a tour of Europe. He came back with descriptions of the way things are interrelated far beyond what you see in the newspapers, because he looked at things differently. Another boy, when asked what all this has meant to him, said, “I’m much better able to deal with my mother.” It gets down to things that matter. After all, that’s a very complicated interacting feedback system.

The system dynamics mentor to the schools in Glynn County, Georgia, has written that some of her most interesting experiences come when she is talking with teachers and students about modeling discipline problems. As she develops a diagram of the processes and interactions going on, the students suddenly see why what they’re doing gets the teachers so frustrated. The teachers also see that the discipline system they’ve set up is preordained to create trouble.

On the Cliff’s Edge

DC: When you wrote Urban Dynamics, you bumped up against people’s cherished beliefs by putting out something very different. What allows you to continue to work when you stir up a lot of controversy or receive a lot of criticism?

JWF: Pioneers always find that. The very definition of pioneering is that you’re doing something that people don’t already know and don’t already believe. I have been a pioneer in several different fields. In the early days of digital computers, we were building a computer using the binary system of calculation. Many people said it would be useless unless we did decimal calculations. Of course, all modern digital computers are binary.

Before that, I’d been in the pioneering of feedback control systems for the military in World War II. I graduated in electrical engineering, electronics, and we found ourselves working on systems to control Army gun mounts. The Army wouldn’t trust anything made out of electronics except their radios. So my first professional job was to design high performance controls using hydraulic oil pressure, with an emphasis on reliability. We were doing one of these for the Navy, and the question naturally arose, what will happen with the equipment in an ocean environment? So I thought I’d better know. I went down to the beach and brought back a gallon of genuine Atlantic Ocean water, mixed it half and half with the oil, and ran the equipment in it all winter. Everything still worked.

DC: So part of the success of moving the field of system dynamics forward has to do with your own comfort in being a pioneer?

JWF: Yes.

DC: And knowing what that entails as you’re moving things forward.

JWF: Knowing the opposition, knowing a little bit about how you bridge the gap. But it takes time. And, of course, being very much in touch with the real world. I grew up on a cattle ranch in Nebraska. And there, if things didn’t work, you found out fast. In my senior year in high school, I built a wind driven electric plant that provided the first electricity we had on our ranch. And it worked. So I think you develop a feeling for where the edge of the cliff is. If you step out too far, you’re a crackpot and you fall off. If you stay back too far, you’re just part of the crowd.

The post A Pioneer on the Next Frontier: An Interview with Jay Forrester appeared first on The Systems Thinker.

I had good teachers in organizational development, but none of them, except Chris Argyris, could articulate his or her practice theory. When I began to work with teams and organizations using Peter Senge’s The Fifth Discipline as a point of departure, I realized that the disciplines Senge describes are useful approaches, but that the approach lacked a practice theory — I couldn’t tell which discipline to use when. So, I took some bits and pieces of ideas from colleagues and I made one up. And since I’m a visual person, it’s a practice theory as a picture (see “The Learning Action Matrix”). I call it the Learning Action Matrix, though the name isn’t important.

What is important is that the Learning Action Matrix knits Senge’s learning disciplines into a system that provides a logical “map” to guide practitioners through a process that produces real results and continuous learning. It helps identify where you are in any given process, suggests what to do at any given point, and indicates where to go next.

Learning Action Matrix

Level of Reasoning

The vertical axis “Levels of Reasoning” is borrowed from Daniel Kim’s “Vision Deployment Matrix” (see “Levels of Understanding” in The Systems Thinker, June/July 1993). His work, in turn, owes a debt to the “Iceberg Model” from Innovation Associates’ Systems Thinking curriculum.

What is a matrix? A matrix is a grid with different elements on the horizontal and vertical axes. Each cell combines the attributes of the vertical and horizontal axes to create a unique meaning.

The Learning Action Matrix is a five by four (5 x 4) grid. Let’s understand each axis of the grid, and then see what happens when we combine these axes into a matrix.

On the vertical axis is listed “Level of Reasoning.” Each of these five levels represents different ways of seeing, frames through which situations can be viewed at increasing levels of complexity. The more complexity that can be brought into the conversation, the more potential for change.

All of these levels are informed by vision. The key question at this level is “What do we want to create?” or, taken retrospectively, “What do we seem to be creating?” These aspirations, stated or unstated, exert a powerful influence on the events, patterns, systemic structures, and mental models working in any given situation. Systemic structures, in turn, are frequently held in place by mental models — assumptions that may be undiscussable theories on what constitutes quality, good service, or an acceptable return on investment. These “theories in use” may also treat interpersonal dynamics, for example, approaches toward conflict or the correct way to interact with senior leaders. Once a pattern has been identified and described, it is possible to document the systemic dynamics that maintain it. The level of systemic structures marks the boundary between what can be easily observed in the objective world (events and patterns) and what must be assessed, often laboriously, from the data (mental models and vision). Systemic dynamics are abstractions, but they stay close to the data. The causal loop language is an example of this kind of thinking. There is nothing wrong in understanding the world as a series of events. It’s just not a very high-leverage way to approach problems. Leverage begins with pattern recognition, with the basic insight that “this has happened before.” Most discussions begin at the events level, with some version of “this is what happened.” Discussions on this level usually assign a single cause to each effect: “This happened because that happened.” Listen to an explanation of stock market behavior on any given day for a good example of reasoning at the events level. The horizontal axis of the matrix describes a four-phase iterative learning cycle: observe, assess, develop, and implement.

Learning begins with observation

Learning begins with observation, with seeing what has occurred. An assessment or diagnosis is made about what one has observed — one develops a theory about what is going on. This theory influences the development of a response, which leads to the implementation of certain actions. These actions are observed, initiating a second trip through the cycle. When we combine the two axes described in the last section, we get the Learning Action Matrix (below).

Notice how the terms on the horizontal axis are verbs (“Observe”) and the terms on the vertical axis are nouns (“Events”). When we combine the two, we get a series of imperative sentences that we can group into four “Zones of Work.”

THE LEARNING ACTION MATRIX

The Learning Action Matrix knits the learning disciplines into a system that provides a logical “map” to guide practitioners through a process that produces real results and continuous learning.

The four zones on the matrix are:

• Zone 1:Observe Current Events and Patterns
• Zone 2:Assess Current Systemic Structures, Mental Models, and Vision
• Zone 3:Develop New Systemic Structures, Mental Models, and Vision
• Zone 4:Implement New Events and Patterns

The arrows in the Learning Action Matrix show the logical progression through the four zones.

Progressing Through the Zones

Learning begins with observing events and patterns (Zone 1).

People make assessments about the underlying structures that drive the behavior they have observed (Zone 2).

They then work to develop new structures, based on that assessment (Zone 3).

They implement the new patterns of behavior suggested from the changed structures (Zone 4) and observe the results of these actions, initiating a second iteration of the learning cycle.

While the boundaries between the zones are not hard and fast (rarely does a group say “O. K. — done with Zone 2; let’s move on to 3!”), the zones are helpful for a number of reasons: There are different kinds of work that one must to do integrate reflection and action, and the zones do a good job describing these differing kinds of work. Observing what is (Zone 1) is different from developing ideas about what could be (Zone 3). The differences are “different enough” to be useful.

Knowing where you are can help you get to where you want to go. If you’re leaping from seeing something (Zone 1) to doing something (Zone 4) without reflecting (Zones 3 and 4), chances are you’ll create unwanted conditions. The matrix helps to direct careful, learning-oriented work by suggesting what to do next.

Finally, the zones provide a way for groups to quickly self-assess what type of work they’re doing now. My clients use the vocabulary of the zones as “sound bites” to describe what they see themselves doing. It’s a vocabulary that carries over beyond my work with them, which I really like.

The work that takes place in the different zones is discussed in more detail below.

Zones 1 and 2 in Detail

Here’s a detailed tour through the first two zones of the matrix.

Zone 1: Observing Events and Patterns.

In Zone 1, team members observe and report on events in the workplace; they tell stories that focus on “what happened” in a given situation. These organizational war stories are like potato chips — no one can tell just one.

But to gain leverage, storytelling must move up the axis from “Observing Events” to “Observing Patterns.” Recognizing a pattern begins with the simple insight that “this has happened before.”

Having teams identify the patterns in their work is useful for lifting conversation out of the Events level.

For example, one group was considering rolling out an update to a product development method when I asked, “How do you usually do this, and what usually happens?” One member responded immediately that their pattern was to announce changes through a large meeting like the one they were planning, and that very little usually happened as a result. (Notice how this constitutes Zone 1 work of “Observing Patterns.”) Others laughed in agreement. The moment was an important one, as they realized the truth of the cliché “If we do what we’ve always done, we’ll get what we’ve always gotten.”

Many of the best tools for Zone 1 work come from Total Quality. Statistical process control, with it’s ability to distinguish normal from special variation, supports a rigorous analysis of production patterns. Group process practices like multi-voting and affinity diagramming make clear patterns of opinion that a group holds but cannot articulate. Stripped of its elaborate architecture, Process Reengineering reveals itself as a process of replacing one work pattern with another more rational one, here moving from Zone 1 of the matrix to Zone 4.

Zone 2: Assessing Current Systemic Structures, Mental Models, and Vision.

Once group members have identified and described a pattern, they can begin to document the underlying systemic structure that maintains that pattern. This zone is usually the first one teams experiment with when they begin to practice the five disciplines. They try to draw causal loop diagrams to explain the patterns they identify and eagerly point out each other’s mental models. As individuals become more experienced in this practice, they recognize that they need to examine their own beliefs as well.

New practitioners frequently strive to create the “right” causal loop diagram to describe a pattern. More experienced practitioners learn to tolerate more complexity and thrive in the intricacies of contradiction. Eventually, deep and sustained work with causal loop diagramming and mental models leads to a vision-oriented understanding of “what we seem to be creating here.” Vision is the foundation for all of the levels below and exerts a powerful influence on the events, patterns, systemic structures, and mental models working in any given situation. The simple question “What do we seem to be creating here?” can often lead a group to state the obvious.

Loop B1 describes a balancing structure where pressure to improve leads to change initiatives, such as new teaching methods, sexuality education, anti-gang programs, and state-mandated curriculums. These initiatives lead to actual improvements and a perception that things are improving, but only after delays. Reinforcing loop R1 illustrates how new change initiatives actually increase impatience for improvements, which increases the pressure for improvements. R2 is a reinforcing loop, where each new initiative reduces the ability to focus on any single initiative, reducing the work and slowing the rate of actual improvement.

The group also identified mental models supporting a few of the key links in this system. These are indicated by the “thought bubbles” drifting off the links. In addition, they identified the highest level of “what we are creating here,” namely, a system in which the stereotype that schools resist change will lead to behavior (more and more initiatives), which will then reinforce this very perception.

I see groups working with “chaotic purpose” in this zone, jumping from working on causal loops to speculating on mental models to reflecting on the present culture (an “assessing vision” discussion) without resolving any of these issues. Teams in this zone, especially teams new to the disciplines, are like student archeologists wandering over an area they are convinced is an important historical site. The process of learning is iterative. They will need to dig in one spot several times before they become skilled enough to understand what’s there.

Zones 3 and 4 in Detail

Zone 3: Developing New Systemic Structures, Mental Models, and Vision.

While the work of Zone 2 is like an excavation, the work of Zone 3 is more creative, like the work of an architect or artist. Like all activities that relay on inspiration, it follows its own pace, oblivious to deadlines and urgency

Teams that skip this zone imperil their ability to implement in Zone 4. Without Zone 3 work, the actions of Zone 4 are just different versions of “what we’ve always done.” They have to be, because the team lacks the cognitive infrastructure (mental models), the causal infrastructure (systemic structures), and the aspiration (vision) to create anything else.

Teams sometimes begin work in Zone 3 by literally making something up that serves as a provisional vision of the way they want things to be. In fact, I find many groups already have reflected on their vision for the future, inspired by the fact that, as one manager told me, “Vision is hot right now.” However, their visions have remained castles in the air, with little hope of informing action directly. The development of new beliefs and systemic structures are needed to link these castles to the “ground” of Zone 4 implementation.

The work of Zone 2 is a necessary point of departure for the work of Zone 3, especially in the development of new systemic structures. These structures can be creatively recast by:

• Linking existing variables in a new way
• Breaking existing links between variables
• Reducing delays in the system. (Thanks to Innovation Associates for first putting this so clearly.)

Using these as redesign principles, groups can reconfigure the structures in which they find themselves.

Extending the example of the educators and their challenge managing change, let’s look at how this team developed a new systemic structure in response to their original loop (see “Zone 3 Loop and Its Strategies”). Their Zone 3 strategies are:

1. Break the link between “Impatience for Improvements” and “Pressure to Improve.”

2. Add a link between “Impatience for Improvements” and “Ability to Focus on Any One Initiative.”

3. Reduce the delays in B1 between “Change Initiatives” and “Actual Improvements” and between this variable and “Perception of Improvements.”

In Zone 4, they make these theoretical changes concrete.

Zone 4: Implementing New Events and Patterns.

Obviously, drawing or crossing out a link on paper changes nothing in the material world (other than the paper, of course). Zone 4 work demands that these paper changes be translated into actual actions.

For most groups, Zone 4 work is familiar territory. They are comfortable with the methods that make sense in this zone. After all, planning actions is what most traditional managers do most of the time. Especially useful are those simple methods that support team planning, such as making public commitments through action plans and accountability charting.

To return to our example, reducing the two delays in the balancing loop might involve some or all of the following actions:

In “Example of Zone 2 Work,” a group of public school administrators impatient with the pace of change in their schools built the above causal loop diagram to describe what they saw.

Reduce these delays

• Designing an initiative for early successes
• Improving something simple and visible early
• Starting work before announcing the initiative to have some successes in-hand (an old fund-raising trick)
• Lowering expectations regarding the speed of change

Obviously, the mental models identified in the original loop will need to be addressed along with the systemic dynamics. For example, the assumption that “In X weeks I should see some improvement. If not, something’s wrong” needs to yield to a belief more consistent with the actual pace of change.

The educators will need to determine how best to influence this belief, possibly choosing different approaches for different constituencies; i.e., one influences a governor differently than one influences a parents’ committee. In the case above, both constituencies will need to be influenced, since both are sources of change initiatives.

How might the educators accomplish their second strategy, breaking the link between “Impatience for Improvements” and “Pressure to Improve”?

A strategy might include:

• Testing whether or not people believe that the causal loop diagram makes sense, and then
• Seeking their agreement to shift their impatience to increasing the focus on present initiatives

This last point represents an implementation of the strategy “Add a link between ‘Impatience for Improvements’ and ‘Ability to Focus on Any One Initiative.’”

In addition, the educators could establish a pattern of having senior people visit the sites of present initiatives and publishing these visits in the school-system paper, along with statements that changes take time.

Typical Group Patterns

In moving through the four zones of work, groups often follow a similar developmental course as they becomes better able to integrate reflection (Zones 2 & 3) with action (Zones 1 & 4) in the service of learning and results.

Leaping to Action

Most teams initially move from Zone 1 directly to Zone 4 (see “Leaping to Action”). They see something happening (Observe) and they do something about it (Implement), without passing through the zones where they assess and develop new systemic structures, mental models, and vision.

Lost in Space As teams begin to learn the disciplines of organizational learning, they add Zone 2 work to their “Leaping to Action” habits, developing a “Zone 1/Zone 2/Zone 4” dance step, which one group called “Lost in Space” (see above).

Teams at this stage are able to use systems thinking and mental model disciplines to assess current reality in increasingly complex ways, yet they have difficulty using much of what they learn to implement new actions. They have usually learned just enough to see how the solutions they might have used in the past will not serve them in the long term, but have not learned enough to create new approaches. The result can be “analysis paralysis.”

Alternatively, when groups at this stage do take action, they can get into trouble. They haven’t yet developed the systemic structures or beliefs to underpin a desired future based on a new vision of what the team wants to create (Zone 3 work).

For example, one executive team I worked with used the matrix structure to redesign an organization. Working through Zones 1 and 2, they did a good job of describing current reality. However, once the outlines of a new organization began to emerge, they moved quickly to draw up the new pattern for the organization (Zone 4 work).

They presented this new organizational chart to their boss a few days later. Intrigued, he asked them to put some names on the positions on the chart. When they tried to assign the executive positions — their own slots — their agreement broke down, and part of the group went to the boss to retract the new design.

I now wonder what would have happened if they had developed a deeper understanding of the future they desired by working through Zone 3 in a disciplined manner, articulating the different beliefs they would have needed to function in this organization and developing the systemic structures to support these beliefs. At least, they might have confronted their own resistance to changing responsibilities.

Acknowledgments

As I mentioned earlier, the vertical axis “Levels of Reasoning” is borrowed from Daniel Kim’s “Vision Deployment Matrix” (see “Vision Deployment Matrix:A Framework for Large-Scale Change,” The Systems Thinker V6N1). His work, in turn, owes a debt to the “Iceberg Model” from Innovation Associates Systems Thinking curriculum, as do several other concepts from this article.

This piece benefited from early readings by Marty Castleberg, Peter Senge, and Janice Molloy. Several clients have advanced my understanding of how to apply the Matrix, most notably the Product Development Leadership and Learning Team at Harley-Davidson.

The post A Practice Theory for Organizational Learning appeared first on The Systems Thinker.

RIGOR VS. SUPPORT

The Facilitative Modeling approach for making important decisions combines high levels of analytical rigor with high levels of stakeholder support.

Common Decision-Making Approaches

Because of this level of complexity in all aspects of organizational life, organizations usually rely on what I refer to as the “shoot from-the-hip” approach for making important decisions. You’ve seen this technique if you’ve ever been in a team meeting in which a decision must be made today. Some members of the group toss out their ideas; most participants stay silent. Eventually, the team leader contributes his or her opinion, and everyone agrees. Decision made! Most meeting participants later bemoan the “poor” decision, claiming they won’t support it. The result? The new policy dies on the vine prior to implementation, leaving the organization the same as it was before.

In analyzing “shoot-from-the-hip” decisions, we observe that they lack strength in at least two major areas: analytical rigor and stakeholder support (see “Rigor vs. Support”). This isn’t a novel observation: Organizations have struggled with these two shortcomings for years and have devised various ways to overcome them.

1. The Technological Approach Before making a major decision, in order to increase the level of analytical rigor (or understanding of the issues), managers often rely on analysts and their toolkit — what I call the Technological Approach. Organizations adopting the Technological Approach generally do so because they’ve fallen victim to the mindset that they must find the perfect answer. The idea is that if you throw enough analysis at an issue, you can completely understand everything and uncover an ideal solution. These organizations think the answer must be found in the numbers.

To process the data they generate, organizations subscribing to the Technological Approach employ spreadsheets and statistical techniques. Some even build large simulation models to test nearly infinite possible scenarios. However, these tools can obscure the assumptions underlying the analysis. And because decision-makers aren’t privy to these hidden assumptions, they cannot compare them to their own mental models — so they do not trust the resulting recommendations. This lack of trust in the analysis is a major factor in why, although usually carefully applied, the Technological Approach rarely generates the support needed to lead to effective policy-making.

2. The Stakeholder Approach In contrast, proponents of a Stakeholder Approach often put technology aside and instead try to build knowledge and support through stakeholder involvement. Well-known techniques that follow this approach include Future Search, Open Space Technology, the World Café, various forms of dialogue — even some facilitated mapping sessions using causal loop diagrams and systems archetypes. These methodologies share an underlying mindset — by getting representation from different players in “the system,” everyone will gain a broader view of the problem at hand. Further, by allowing participants to express divergent perspectives in an unconstrained fashion, the Stakeholder Approach lets them formulate creative, systemic recommendations.

Whether trying to define the problem or to generate solutions, people applying these processes (if only implicitly) tend to follow a model of interaction described by Interaction Associates as the Open-Narrow-Close model. During the Open phase, participants get all of the data on the table while defining the problem; if they’re generating solutions, this is the stage in which creative solutions spring forth from the group’s collective wisdom. During the Narrow phase, contributors take an overwhelming list of choices (problems or solutions) and narrow them down to a few to consider further. During the Close phase, they actually choose which problems to tackle or solutions to implement and how to do so. Managers then often assign groups to each of the major action items identified during this stage and give them their blessing to “go forth and implement.”

The Stakeholder Approach includes processes that build broad support — unlike what often occurs in the Technological Approach. Plus, it helps those involved to see the system from a broad spatial and sometimes temporal perspective. These results are necessary and important for creating effective changes in any system.

A major weakness of the Stakeholder Approach, however, is that the processes used to narrow and choose

APPROACHES FOR IMPLEMENTING SYSTEMS THINKING

Facilitative Modeling serves as a middle ground between the Technological Approach and the Stakeholder Approach.

among the resulting divergent issues/strategies lack rigor and usually

rely on the assumption that, simply by having enough stakeholder representation, the group will make excellent decisions. But as Irving Janis learned by studying extremely poor decisions (such as the Bay of Pigs fiasco and the escalation of the Vietnam War, which he described in his book Groupthink), groups with very high average IQs can function well below expectations.

Barry Richmond of High Performance Systems, Inc. created a simple example called the Rookie-Pro exercise that also illustrates this point. Despite working with a much simpler human. resource system than that found in most organizations, only 10 to 15 percent of individuals can guess the system’s future behavior — even after lengthy discussion! So the assumption that the collective wisdom of the group will surface in a way that leads to optimal decision-making is tenuous at best.

In addition, the framework employed to guide team members in narrowing and choosing among different options doesn’t help to determine if elements of the proposed solutions need to be implemented at different times and in varying degrees. The result is that the organization often chooses to put the same amount of resources and effort into each action item. Nor does the Stakeholder Approach determine if the issues are interconnected — different groups may be separately implementing policies that should be done together or, even worse, are mutually exclusive.

Facilitative Modeling

The good news is that there is a way to both rigorously understand (or

even reduce) complexity and improve stakeholder support! Practitioners are often drawn to the field of systems thinking because of its promise to build collective understanding — to get everyone on the same page. Even so, these managers can be pulled between the Technological Approach (big simulation models created by experts) or the Stakeholder Approach (facilitated sessions using causal loop diagrams or systems archetypes). But there’s a middle ground — a large range of activities that I refer to as “Facilitative Modeling” — where tremendous power resides (see “Approaches for Implementing Systems Thinking”).

Facilitative Modeling is a Technological Approach, because it uses computer simulation and the scientific method to build understanding. It is also a Stakeholder Approach, because it requires the input of the important stakeholder groups, uses a common language so everyone can get on the same page, and creates small, simple, and easy-to-understand models. The models don’t generate the answer; rather they facilitate rigorous discussion. Facilitative Modeling usually culminates in a facilitated multi-stake-holder session in which the participants generate common understanding and make well-informed decisions.

Overview of the Process

In the Facilitative Modeling process, a group of stakeholders identifies and addresses an issue critical to their collective success. The issue is often one that has been resistant to organizational efforts to “fix” it. After choosing the area for exploration, the group sets the agenda for a facilitate

session. In preparation for that meeting, several individuals in the group serve as a modeling team and develop (alone or working with a modeler) a series of simple systems thinking simulation models that clearly articulate important components of the issue. These components may include the historical trend for that issue, the future implications if the trend continues, possible interventions, and the unintended consequences of some of these solutions. The models are deliberately kept small so that stakeholders will understand them and the development process remains manageable.

However, it’s not enough just to make models! In fact, building useful models is probably less than half of what makes a Facilitative Modeling initiative successful. The process requires the modeling team and perhaps others to create additional materials for the facilitated session, such as workbooks for tracking experiments and writing reflections, as well as CDs of the models for after the session. A facilitator and/or design team needs to carefully plan various aspects of the session, such as appropriate questions, suggested experiments to run on the model, and a mix of small and large group discussion.

The facilitated session represents the culmination of the process. During the gathering, teams of two to four people explore the models on computers. The session includes large group interludes and debriefs between exercises. And at the end of the session, participants discuss and agree on

next steps based on the insights that emerged during the event (see “The Facilitative Modeling Process”).

Facilitative Modeling in Action

Using the Facilitative Modeling Process outlined above, a nonprofit organization recently explored potential issues associated with implementing new funding policies. This organization was responsible for improving the health and welfare of the poor population in a community by giving funds to other local nonprofits to provide services. Originally, the organization had determined which organizations to fund and how much funding to supply by analyzing the services that the target organization would provide; in recent years, it had settled into just increasing the amount of funding incrementally over the previous year’s figure. To create more accountability among the local organizations and improve outcomes in the community, the nonprofit had decided to apply a performance driven approach to funding (that is, base funding on projected improvements to performance indicators and then renew the funding if the community experienced noticeable improvement in those areas).

Some members of the organization, as well as members of an important partner group, were concerned about the potential barriers to implementing this updated approach and were eager to understand possible unintended consequences that might result from the change. They agreed that a Facilitative Modeling approach would be an excellent way to surface and discuss these issues in a way that would give all stakeholders shared insight. In little more than five days of working with a facilitator and a few representatives from the organization and its partner, the team developed three small “conversational” models for a one-day facilitated session.

At the beginning of the session, the group adopted a set of ground rules to guide their interactions. Once participants agreed to the guidelines, they began by experimenting with the first model. The purpose of this initial simulation was to surface and discuss the potential dynamics associated with implementing the new funding approach. Allowing “sub groups” to work with the models at their own speed often increases their level of understanding. However, even those with some skill at reading stock and flow diagrams similar to the one shown here can be quickly overwhelmed by maps. The simulation included a function that let the sub groups slowly unfurl pieces of the map so that they more easily followed its logic (see “The First Map” on p. 5).

The map shown here represents one way to look at the different organizations affected by the nonprofit’s funding decisions. The language of stocks and flows is ideally suited for looking at this issue. The three stocks at the top of the diagram (the rectangles labeled “Resistant,” “Not Committed,” and “Committed”) represent groups of organizations. Currently, because the new approach has yet to be implemented, all organizations would belong in the “Not Committed” stock. Eventually, as the new funding approach is made into policy, organizations would begin to move into the “Committed” or “Resistant” stocks. Obviously, if possible, the funding group wanted to avoid any organizations becoming “Resistant.”

At the session, the individual groups discussed the meaning of each of the stocks. What does it mean to be “Committed”? “Resistant”? They mulled over the question, What number of “Resistant” organizations would pose a problem for the program as a whole? Can “Committed” organizations become “Resistant”? Is it realistic to assume (as the model does) that “Resistant” organizations never become “Committed”?

Talking about the diagram helped he sub groups, and eventually the entire group, reach consensus about how organizations might become committed or resistant to the changed funding policies. For many of the participants, it was the first time they had discussed the potential that some of their client organizations might resist the changes! By working with the model, the group was able to surface an unpleasant concept in a way that allowed them to grapple with its implications for their changed strategy.

They then entered different values into the model to experiment with how the funding organization might allocate its resources in the coming months. How much effort should they put into developing the performance-driven funding program? How much into explaining the program to the funded organizations? And how much of each should they do prior to officially announcing the program? After announcing it? In short, the group wrestled with the systemic or “chestration” (a concept developed by Barry Richmond) of resources the magnitude and timing of efforts required to successfully implement the strategy.

The group concluded that, in the first phase of development, they should apply most of their efforts to designing the new policy. Doing so builds the “Clarity of the Program,” which is useful in preventing “Doubts About the New Approach” down the road. They realized that they would need to allocate at least some resources in the first phase to working with the client groups and addressing their doubts about the change. This process would also help them to refine the approach (see “Implementation Timetable” on page 6). The next phase would require additional work with the other stakeholder groups to explain the program prior to release. The third and fourth phases would involve implementation; this is when the nonprofit’s staff members would spend most of their time addressing the doubts of the affected organizations.
The group realized that the exact numbers of organizations in each category wouldn’t be the same in real life as in the simulation, but that the stories described by the model were consistent with what they now expected might happen when overhauling their approach to funding. In keeping with the need for systemic orchestration the group concluded that their allocation of strategic resources must shift over time, depending on which phase they were in (for example, in the second phase, they would need to apply some resources to program development and even more to working with stakeholders).

Working with Subsequent Models

In Facilitative Modeling, each model tends to add to the understanding generated by previous ones. Because the performance-based funding approach would require implementing a new IT system, the second model helped participants explore how a funded organization would need to allocate resources in order to develop a new IT system and build its staff ’s capacity to use it. The third model served as the capstone exercise, because it required participants to explore how client organizations might allocate their resources across the following needs: providing services, building and maintaining the IT system, investing in staff skill development, and collaborating with partner organizations.

THE FIRST MAP

The three stocks at the top of the diagram (the rectangles labeled “Resistant,” “Not Committed,” and “Committed”) represent groups of organizations. As the new funding approach is made into policy, organizations would begin to move from the “Not Committed” stock into the “Committed” or “Resistant” stocks.

During the large-group debrief of the third model, the nonprofit’s senior director said that he didn’t like one dynamic that he experienced with the model. In all cases, after the funding change, the youth population’s sense of disconnection from the community initially worsened, even when the simulated strategies encouraged a majority of client agencies to be committed to the shift and to effectively implement performance-based approaches to providing services. When he experimented with the model, the director kept trying to avoid this “worse-before-better” dynamic. Through probing questions, the group learned that it wasn’t that he didn’t expect this behavior to happen, he just wished it wouldn’t!

IMPLEMENTATION TIMETABLE

By using the model to explore the magnitude and timing of efforts required to successfully implement the strategy, the group concluded that, in the first phase of development, they should focus on designing the new policy.

This revelation led to an interesting discussion of what is often an undiscussable in the public sector: that policies designed to improve social systems often take time before they lead to noticeable improvements and that there is often conspicuous degradation of performance in the interim. The director expressed that it was political suicide to admit that things might actually get worse before improving. Ultimately, through the facilitated discussion, he came to understand that regardless of whether he wanted to admit that such a dynamic might occur, it was inevitable, given the long delays before activities such as IT development and skill-building would have a positive effect on services. Through this admission, he and his staff were then able to explore options for mitigating the effects of this unavoidable dynamic.

Ultimately, the nonprofit’s staff left the session with useful insight in several areas. First, they all understood that some of their client organizations might resist the new approach. Second, they realized that it would be helpful for them to include those organizations in developing the program. Third, the group agreed that building staff skills was likely to be a more challenging impediment to successful implementation of the changed approach than developing the IT infrastructure. Finally, they accepted that systemwide implementation would require orchestrating a series of activities that, even in the best of circumstances, would cause a “worse-before-better” dynamic. All of these insights were just the beginnings of an ongoing dialogue, and all were facilitated by using small models to focus the conversation.

The Value of Facilitative Modeling

As shown in the example above, there is a powerful place for small models in a facilitated environment. The process used for developing good systems thinking models increases the rigor of the analysis and captures the benefits of a Technological Approach. At the same time, by keeping models small, Facilitative Modeling improves on the benefits of a Stakeholder Approach and increases the likelihood that all participants end up in alignment. Moreover, the Facilitative Modeling approach uses a language — stocks and flows — that is more representative of reality than other visual mapping languages. For this reason, the participants are able to discuss and come to a novel understanding of the assumptions built into the model. Running the simulation provides an essential test of the group’s understanding and facilitates further conversations about the likelihood of different results. The computer-generated “microworld” creates a safe environment for experimentation.

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These and other metaphors are often used to help explain systems theory, and they do so effectively — to a point. Many people can intellectually grasp the idea of interconnections in our world and the importance of taking a holistic perspective. But for some, the concept seems so easy to understand that they miss its value. For them, having a metaphorical understanding of systems thinking does not necessarily lead to action or to an integration of the concepts into everyday practice.

Nevertheless, it’s not necessary to have a deep understanding of systems theory in order to use it to influence institutional behavior. What is crucial is to connect some of the elements of systems thinking directly to proposed actions. In this article, I suggest how organizations might apply four models to make the transition from thinking to action. The iceberg metaphor helps to probe the underlying causes of events and patterns. The force field analysis provides a visual means of understanding the factors that keep organizations in “quasi-equilibrium” and the issues involved in any change process. The spidergram emphasizes linkages within a given system. Finally, behavior over time graphs draw attention to the long-range effects of organizational efforts.

The Iceberg (It’s bigger than you think!)

The iceberg is one of the most frequently used models to explain systems thinking (see “The Iceberg”). Thanks to movies like “Titanic,” many people recognize that most of an iceberg sits hidden beneath the water; that is, out of sight.

Different authors present the iceberg model as having from three to six levels; we’ll use a four-level model here.

In the iceberg model, the piece of the structure that appears above the surface represents a single “event.” A young woman arrives an hour late for work after dropping off her young child at a nursery. Her supervisor is understanding — this time. Just below the surface, a deeper level of examination reveals patterns of events, or “trends.” The young mother is late on the same day a week later. We might ask, in this case or any similar situation, whether these two events are unique or if a pattern of behavior is beginning to emerge.

It’s not necessary to have a deep understanding of systems theory in order to use it to influence institutional behavior.

Submerged below the level of the trend is the “structure,” the foundation that supports and creates the behaviors higher up in the pyramid. In the case of the working mother, is she late every week because the organization has strict policies about when staffers need to be in the office — policies that don’t take into account when daycare facilities open their doors in the morning? Would a more effective policy be one that allows employees to work flexible hours or dial in from home on some days? In organizations, the structure is often determined by its policies and procedures.

THE ICEBERG

Each level down the iceberg offers a deeper understanding of the system being examined as well as increased leverage for changing it.

At the next level down, our “mental models” — and those of the people who came before us — affect the structures we put in place and the way we understand the top parts of the iceberg. Is the company founded on a sense of trust for its employees, or does management view itself as needing to monitor workers’ hours to make sure they put in what they’re being paid for? Is “face time” more important than productivity? These attitudes affect the company’s policies and ultimately how it treats all employees, including those with small children.

Each level down the iceberg offers a deeper understanding of the system being examined as well as increased leverage for changing it. Consider, for example, the response of many communities across the U. S. to the events of September 11. Immediately following the tragedy, various groups sponsored events embracing immigrants, with participants singing “We Are the World” and taking part in other heart-warming efforts to reach out to others in a time of national pain and anguish. These events were nice, but of little long-term significance. If the planners had applied the iceberg model to the process, they might have begun by asking simply, “Will we do this again? Should it become an annual event?”

Other questions lead deeper into the model. How do we keep this issue in people’s vision throughout the year? Are there other ways that we might integrate new immigrants into our community? How might we link “native” families to those who are new? And, ultimately, what can we do to open the minds of Americans to see the benefits of the diversity provided by the influx of immigrants? Such exploration might lead to a revival of workshops in cross-cultural understanding such as those brought forth by local ecumenical councils during desegregation.

As shown here, groups can use the iceberg model to improve program planning and to integrate systems thinking into the process. Next time you are involved in event planning, ask yourself whether you are planning an event or a whole movement!

Force Field Analysis (I’m losing my balance!)

Another useful approach to getting deeper into a systems mode of thinking is the force field analysis attributed to Kurt Lewin (, “Resolving Social Conflicts,” Selected Papers on Group Dynamics, 1948). Force field analysis (FFA) is a well-known tool for examining change (see “Force Field Analysis”). It asks, “What forces are at play to increase the odds of a given change taking hold, and what are the elements hindering that change?” This framework provides a rich systems perspective on an issue.

The concept is simple. At any given moment, an organization is in equilibrium; that is, there’s a balance between opposing forces. Without this balance, operations couldn’t move along at their normal pace. When a new idea to change the way the organization operates comes along, it threatens to disrupt the balance. But the forces that maintain the status quo usually make it difficult for change initiatives to take root. The FFA offers a useful way to illustrate this dynamic.

As an example, consider the issue of organizational paperwork. When the academic vice president in an institution of higher education proclaims, “We must simplify operations and eliminate as much unnecessary paperwork as possible,” you can hear the roar of approval from the faculty. But then the change does not happen.

Why? The FFA analysis can provide an understanding of the system as it exists and why there is resistance to change.

Imagine the forces that oppose such a change. For instance, in an attempt to ensure that departments spend certain funds properly, the institutional effectiveness office creates a form requiring that someone from its staff sign off on expenditures of more than $100 from those funds. The graduate college believes that another college in the university is not following standards, so they insist on receiving duplicates of all paperwork that involves graduate students. Department chairs, who have not received any training regarding institutional procedures, fail to follow some of the mandatory processes and lose the trust of the vice president, who then insists on signing off on all travel forms. And on it goes.

In these situations, the top manager often tries to force the change with further declarations and threats. Predictably, the use of strong-arm tactics frequently results in greater resistance.

A more productive way to approach the problem is by listing and examining the balancing forces that prevent the change from taking root (see the table below). Is an individual’s status within the university determined by how many decisions he or she must sign off on? If so, how can we change this reality? Are new faculty members adequately trained on proper completion of paperwork? If not, why? In what ways do various policies reinforce the status quo? How did those forces come about? What can be done to eliminate the forces of resistance or to redirect them in such a manner that they support the proposed change? Each question expands our understanding of the system and opens up possible methods of supporting the initiative.

Spidergram (Not Spider Man!)

Another metaphor for explaining systems thinking is that of a spider web. In The Web of Life (Anchor Books, 1996), Fritjof Capra uses the spider web as the central metaphor to describe the interconnections of all life on Earth. A disruption at one point in the web has an impact that reaches to all points, as it also does in human institutions.

Applying this systems metaphor to organizational issues is easy through the spidergram (see “Spidergram”). First, place the initiative, change, or process to be modified in the center of the web. Then draw threads outward, with blocks at the ends that represent anchoring points for the web. Identify, at each anchor, a unit or process within the organization that might be affected by the change. Stretch your mind to identify all possible anchors. Then, along each line connecting the center to an anchor, indicate the potential impact that the action might have on the anchor.

Consider, for example, an admissions unit in a hospital. The CEO believes that no one should have to stand in line for anything. The admissions staff is aware of and agrees with this perspective. They would also like to reduce their workload, so when budget time comes around, they ask for two additional positions to be created. From their perspective, this is the right thing to do.

Applying the spidergram to this issue involves placing the admissions unit’s request in the center of the web. What then are the anchor points? They might include the hospital budget; the other departments that would be affected by adding expense and capacity to the admissions unit, such as the records office and human resources; and customer satisfaction.

The next step is to note anticipated side effects of funding two more positions in admission on the anchor points. Will other departments requesting positions go without? Will the workload in the records office increase to the point where it begins to cause delays in patient services? Are there other means of resolving the issue, such as sending patients paperwork in advance to complete before coming to the hospital?

The spidergram will not provide an answer as to whether or not the hospital should support the admissions office’s request. It will, however, help identify the interconnections that exist and the potential impact of the proposal beyond the single unit or process involved. It is an extremely useful systems thinking strategy to help an organization see the “big picture” and to avoid sub-optimizing the whole in order to fulfill requests by units with strong and persistent advocates.

Behavior over Time Graphs (The long view)

Short-term thinking leads to event-level actions (as shown in the iceberg model). The number of surgeries in a given month, students enrolled in the fall semester, and quarterly profits are all examples of short-term thinking. If people do view those bits of data historically, they often do so only in relationship to the previous year’s numbers, and begin and end the examination with the question “Are we up?” And often, closely examining the numbers is a guise for searching for someone to blame for a decline!

A systems perspective encourages looking at more data points over a longer period and within a larger context than we’re used to doing. It involves analyzing relevant trends and other patterns that may be acting on the numbers we’re examining at the moment. The graphs may include both historical data and anticipated or desired future trends after a particular intervention. These graphs do not have to be precise, though they should be representative of actual or projected trends in order to be of value. If taken seriously, so-called behavior over time graphs can provide a means for understanding the flow of events and enhance discussion both of the past and the future (see “Behavior over Time Graph” on p. 9).

Take the example of a decline in enrollment numbers in a given department within a large university. The president sees the drop and, with great frustration, calls the provost: “What’s going on over there? Why aren’t the faculty doing their jobs?” The provost calls the dean, who phones the department chair. The chair reminds the dean that they agreed to raise standards for admission to the program in order to meet increasing state employment standards for graduates. Looking at long-term student enrollment patterns in similar situations might have led the administrators to understand that numbers frequently decline at first before enrollment begins to rise again. And doing so might have kept everyone’s blood pressure in check.

“Behavior over Time Graph” represents a small local business that had a tremendous launch, but then experienced lagging sales. When top managers considered the demographics of the individuals they catered to, they recognized that many of the older retirees who had created their initial success had left the state or died. To boost sales, they would need to consider marketing to a slightly younger crowd or even altering their product. Graphing trends in the rise or fall of multiple variables (enrollment and the local economy in higher education, sales and new product introductions in manufacturing, and so on) helps generate discussion, leading to hypotheses and deeper understanding of the trends as part of creating an overall strategy.

Back to Start

Busy executives who think that systems thinking is interesting but of limited value are missing an important tool for change. The best-laid plans can go astray if the whole system has not been considered. Administrators in every kind of organization can benefit from the use of these and other metaphors and models that build a deep understanding of the systems within which they work and live, and strengthen their actions toward continuous improvement.

Ed Cunliff is assistant vice president for academic affairs at the University of Central Oklahoma, with major responsibilities in institutional research, assessment, continuous improvement, and the Academic Support Center. He is active in the pursuit of quality concepts on and off campus, and serves on the board of the National Consortium for Continuous Improvement in Higher Education. Ed’s interest in systems theory has led him to become involved with environmental issues, and he serves on several related boards.

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People don’t become systems thinkers because systems thinking is so cool; they do so because they discover that linear thinking won’t answer their questions. Linear thinking is cause-and-effect thinking: One cause has one effect. Sometimes it works adequately, as when you run out of gas and your car stops. Your car stopped (effect) because it had no gas (cause). If you put gas in again, your car will run. Linear thinking is quite effective in solving this kind of problem.

However, our world is made of many complex relationships and interrelationships. Systems thinking provides a perspective that, most of the time, various components affect each other in various, and often unexpected, ways. So, for example, the use of the pesticide DDT to kill mosquitoes led to a number of unanticipated side effects. These included the decimation of several species of mosquito-eating birds and the rise of DDT resistant mosquitoes. Over time in some places, this dynamic made the mosquito problem worse (see “Unintended Consequences of DDT”). In organizations, systems thinking brings powerful tools and enlightened perspectives to organizational diagnosis, problem solving, strategy, and leadership (see “Linear vs. Systems Thinking”).

The Road to Becoming a Systems Thinker

Adopting a systems approach takes persistence and curiosity. Being the sole systems thinker in a linear thinking organization can be a lonely place. People will not understand you. You’ll feel like you’re walking around with two heads… whenever you talk, people will stare at you, confused.

Of course, many people have thought systemically all their lives. Many of them don’t even know that what they are doing is labeled “systems.” But for the vast majority of us, the jump to systems thinking requires time, practice, curiosity, and intentionality (see “Making the Shift”).

Is It a Problem or a Symptom?

One way to start to shift from linear to systems thinking is to practice identifying whether something is the problem or merely a symptom of something deeper. Linear thinking tends to focus on addressing surface-level behaviors – or symptoms. Unfortunately, making a symptom go away won’t solve the problem. In fact, it may make things worse and cause effects in other parts of the organization. A manager taking a systems thinking approach will work to understand the underlying problem before addressing any of the symptoms. Usually, if the true problem is solved, the symptoms will be eliminated as well.

How do you know if you’re seeing the real, underlying problem or simply a symptom of something deeper? Below are eight clues that what you are experiencing is an indicator of a larger problem rather than the problem itself:

1. 1. The Size of the Problem Isn’t Commensurate with the Discussion Around It.

Is the problem too small in comparison to the time and energy it is taking? If people are spending all their time, for example, complaining about the color of the carpet or the shape of their offices, you can assume that their reaction is a symptom of another problem.

• People Don’t Solve a Solvable Problem. Is it within the power of the people in your organization to solve the problem, but they don’t? For example, people complain there is no decaffeinated coffee, but no one does anything about it. Why don’t they feel empowered to change the status quo?
• The Problem Won’t Go Away. What has the history of the problem been? Is it something that won’t go away? Have you tried to solve it and have been unsuccessful? Does it keep coming back, like a monster in a horror movie? Does the problem morph into a related issue once you “solve” the original issue? Generally speaking, if you “solve it” and it comes back, then you haven’t addressed the underlying problem.
• The Problem Involves Emotional Barriers. In the middle ages, prior to Christopher Columbus, mariners were afraid to sail south of the equator. Contrary to popular belief, they weren’t afraid of falling off the edge of the world. (The ancient Greeks had proven that the world was round in about 500 B. C.) They were unwilling to do it because it hadn’t been done before. Sailors never even considered it a possibility. As such, it was an emotional barrier, a product of stunted imagination. The same kinds of emotional barriers are present in today’s organizations. What are the things that are never talked about? What are the things that, if someone mentions them, people laugh them off? Where is the imagination stunted in your organization?
• The Problem Has a Pattern. Does the problem have an annual cycle? Is it predictable? If so, it may be a symptom of something deeper.
• The Organization Has Kept the Problem Around, like a Pet. In a healthy organization, if a problem arises, people solve it once and for all. Unhealthy organizations need problems because they give people something to focus on and fuss about. No one consciously tries to keep the problem, and everyone says they want to solve it. However, even though we may not be aware of it, we manage to keep the challenges we like!
• Other Stresses and Anxieties Are Present in the Organization. The more anxiety in an organization, the more likely it is that real problems are hidden, manifested only in symptoms. For example, in companies with a domineering culture, employees can feel victimized by management. Most people, when feeling victimized, will complain about other things rather than reveal their true feelings. The more stresses that are present, the more likely there will be a variety of seemingly unrelated symptoms.
• As One Problem Is “Solved,” Another Crops Up. In an organization that relies on reactive, quick-fix, cause-and-effect management, once one problem is solved, another tends to crop up. Most linear thinkers won’t realize that the two issues are related. Meanwhile, the underlying dynamics fueling the problems fail to be addressed.

Ten Enemies of Systems Thinking

The ten statements below are usually evidence of linear thinking and, thus, enemies of systems thinking. Hearing them is not always a sure-fire guarantee that linear thinking is coming, but they should set off warning bells.

1. We’ve got to fix it quick! This is the proverbial “quick-fix” mentality. We see a problem, and we react to fix it before we really understand it. There is nothing wrong with quick, assertive action, and a systems response to a problem is not necessarily slow. But doing the fix before grasping the problem is a recipe for disaster.
2. “Oh, let’s just put a bandage on it.” The bandage solution is often a half-hearted attempt to fix a problem. The danger is that it can cover up the worst of the symptoms while allowing the problem to continue to fester.
3. “We must make the budget by the end of the fiscal year!” Budgets are notoriously linear. They force us to make decisions based on money rather than on whether the idea is good. In particular, making a decision to fix something so we are “in the black” by an arbitrary deadline is problematic. While being profitable is desirable, last-minute Herculean efforts to reach monetary targets are the antithesis of systemic thinking. Short-term quick fixes almost always harm long-term sustainability.
4. “We need to respond immediately!” Knee-jerk reactions and panic attacks, borne out of anxiety and learned helplessness, create linear solutions. A calm, reasoned strategy offers a more systemic way to address a situation. This does not mean acting slowly; it means taking a moment to consider the different variables that contribute to a situation.
5. “Who cares?” An apathetic approach, or a plain lack of curiosity, is a barrier to effective problem solving. Curiosity, play, imagination, and adventure are the antidotes to stuck organizations.
6. “We need more information.” There is nothing wrong with seeking more information, unless we believe it will solve the problem for us. Additional data is good when we know its place. We – not information -have the power to act. And we – not information – must have the courage to do so.
7. “Oh, you’re just thinking too much.” Shallow and superficial thinking is everywhere – just watch the nightly news. All of the complex problems of the world are boiled down to a few sound bytes. The accusation of “thinking too much” usually means “Stop thinking differently from me.” The reality is that systems thinking is a new kind of thinking, and not everyone likes to stretch in new ways.
8. “To hell with the rest of the organization; we must get our own needs met.” Many people in organizations hold this kind of fortress mentality. In our companies and schools, we live in bunkers, protecting our own needs and the resources of our unit. Consequently, we end up thinking of win-lose strategies and strategizing about how to get more for ourselves. This approach is classic linear thinking.
9. “We can’t have any conflict.” Some of us will do anything to keep the peace in our organizations. Edwin Friedman calls this “peace-mongering.” Peace-mongers will avoid, suppress, and mask conflict, at the expense of discussing and addressing real issues.
10. “You will do it this way, and you will enjoy it!” Authoritarian managers who force their will on the workforce are prime examples of linear thinkers. Wisdom is collaborative, and domineering interventions undermine innovation, collective problem solving, and creativity.

Systems thinking is easy for some and difficult for others. Some people intuitively think in systems terms and have done so their entire lives. However, most people today think in linear, reductionistic, and mechanistic terms.

At first when people start thinking in systems, they can find things to be a bit chaotic. They become overwhelmed by the number of variables and think, “How can I do anything if I don’t know what effect my intervention will have?” This kind of thinking is normal and usually gives way to a sense of deeper insight as an individual begins to learn various principles of systems behavior. We hope the ideas in this article offer a first step toward that kind of understanding.

Jim Ollhoff (jim@ollhoff.com) is a college professor, with an academic background that includes training in education, family studies, developmental psychology, social psychology, and systems theory. His academic interests are the process of discovery in anxious systems, effective management from a complexity perspective, leadership, strategy, and adult learning. Jim teaches courses in the areas of family studies and in management.

Michael Walcheski is the chair of the Department of Family Studies at Concordia University, St. Paul, Minnesota. He has a PhD in Marriage and Family Therapy and is a licensed marriage and family therapist.

The post Making the Jump to Systems Thinking appeared first on The Systems Thinker.

That’s the challenge Al Gore has faced each of the more than 1,200 times he has personally delivered his presentation on global warming depicted in the film, An Inconvenient Truth. As an educator, I am fascinated by how elegantly he communicates complex systems thinking concepts — without ever actually mentioning systems thinking. By any measure, he has been successful: He has been nominated for the Nobel Peace Prize, the film has won an Academy Award, and many believe that Gore’s work has caused a sea change in U. S. attitudes toward climate change. How did he do this?

What follows is an analysis of how Gore met this challenge, as well as ideas for how the rest of us might apply these techniques in our own work. Some of these observations have come from my participation in a training session with Gore in Nashville in support of his non-profit organization, The Climate Project, which is funded by proceeds from the film. While these ideas may not work for all speakers and all audiences, I think there is wisdom here for all of us.

Tips for Presenting Complex Concepts

Use Everyday Analogies to Reduce Complexity.

• Gore makes the case for why we should be concerned about the bleaching of coral reefs from higher ocean temperatures by calling them “the rainforests of the oceans.” “Rainforest” instantly evokes a rich, colorful, and complex habitat that serves as a linchpin of the environment. Coral reefs are equally full of life — and equally threatened.
• In describing moulins, streams that tunnel down through the middle of glaciers, Gore describes them as behaving “like termites.” This analogy elegantly communicates the idea that such melting will eventually cause ice sheets to break apart, just as termite damage can cause a house to collapse.

Avoid Technical Jargon Like the Plague, and if You Do Use It, Make Fun of It.

• After explaining the greenhouse effect in terms of solar radiation, Gore introduces a cartoon version by saying, “That’s the traditional explanation. Here’s what I think is a better explanation.”
• At another part in the film, he says, “Scientists tell us that the earth is a ‘non-linear system. ’That’s just a fancy way they have of saying that the changes are not all just gradual. Some of them come in big jumps.”In this way, Gore connects with the audience. He’s implicitly saying, “I’m just like you. If I can understand this, so can you.”

Explain Reinforcing and Balancing Loops in Plain Language.

• Gore never uses the word “exponential” to describe population growth. Standing next to a graph showing the level of population growth in just the last generation, he simply says, “In one human lifetime, something profoundly different is going on.”
• In describing why melting of the polar ice cap is accelerating, Gore explains, “As the surrounding water gets warmer, it speeds up the melting of the ice.”
• In describing how warmer ocean temperatures make hurricanes stronger, he states, “If you add energy to a system, it becomes more energetic.”
• Gore describes the Earth’s atmosphere as “a big engine for redistributing heat” from the warmer equator to other latitudes—one big balancing loop.

Don’t Take Yourself Too Seriously.

• Use self-deprecating humor. When Gore uses a worker’s lift in the film, he says, “. . . if I don’t kill myself here.”
• Risk using a few constructions that would get points off from your English teacher, such as “Communicate this real clearly.”
• And yes, even use a folksy accent if it comes naturally to you: New “Orlens” instead of New “Orleens.” I am certainly not saying that we should all talk with a Southern accent; I just noted that Gore doesn’t hide his.

As the actor Peter Ustinov once said, “It is our responsibilities, not ourselves, that we should take seriously.”

Tie Your Message to Personal Stories. Throughout the film, Gore traces his personal learning journey about the Earth from growing up on a farm, to college, to traveling around the world in support of continually learning.

• The death of his only sister to lung cancer forced Gore and his family to confront the mental models of tobacco use. His father finally stopped being a life-long tobacco farmer as a result of her death.
• Gore’s son almost died in an automobile accident. Gore learned from this experience that it is possible to lose what is most precious to you. He reports that this realization changed “my way of being in the world,” a shift that enabled him to confront the reality that we could also lose the Earth. This personal experience is the source of the passion that has sustained him in telling the story of global warming for 30 years.

When I first heard how long Gore had been advocating on this issue, I reflected on the fact that I’ve been trying to tell the story of organizational learning for two years and feel as though nobody’s listening. If Al Gore can tell his story for three decades, then maybe I can keep at it a little longer, too.

Don’t Vilify Your Opponents (but Some Good-Natured Poking Fun Might Be O. K.)

• Regarding some in the petroleum industry, Gore quotes Upton Sinclair as saying, “It is difficult to get a man to understand something when his salary depends upon his not understanding it.”
• Regarding skeptics, he cites a lyric from the band Dire Straits: “Denial ain’t just a river in Egypt.”
• Gore implores us to rise above party lines in order to respond to this challenge: “We must remove global warming from the partisan framework.”

Sometimes, through their anger, activists end up recruiting the half of the audience who already agrees with them at the expense of alienating the other half who does not. We cannot afford such an outcome with an issue like global warming. This problem will require all of us.

Confronting Mental Models

“It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.” — Mark Twain

In designing his presentation, Gore invested the most time trying to understand the mental models of skeptics: “I guess the thing I’ve spent more time on than anything else in this slide show is trying to identify all those things in people’s minds that serve as obstacles to them understanding this. And whenever I feel like I’ve identified an obstacle, I try to take it apart, roll it away, move it, demolish it, blow it up.”

• One technique he uses to try to win converts is to draw parallels with history. Gore relates denial of global warming to the rise of Hitler in the 1930s: “How do we react when we hear warnings from scientists” about something awful but that has never happened before?
• In one section of the film, he explores old habits that are hard to change through technology, such as nuclear technology: “New technology brings a responsibility to think about its consequences.” This is an unassuming way of addressing the systems thinking adage of asking, “And then what?”
• To prompt the audience to examine the inertia of the status quo, he invokes the story of the frog in the pot of boiling water—that is, if you place a frog in a pot of boiling water, it will jump right out, but if you put it in a pot of lukewarm water and slowly raise the temperature, it will stay in and boil to death.
• In an aside during training, he offered this additional thought on why elected officials can be slow to change:, “If an issue is not on the tips of their constituents’ tongues, it’s very easy for them to ignore it.”

Rhetoric As a System

Gore crafts his presentations by managing three stocks or, as he calls them, “budgets”:

A Time Budget: How long will the audience stay interested? Gore operates under the premise that if he periodically throws in an interesting aside or an arresting image, he “buys” more time from the crowd.

A Complexity Budget: Is the information too complex? By simplifying concepts, he buys more capacity to learn from the audience.

A Hope Budget: Is the graphic depiction of what will happen if we don’t act soon balanced by concrete actions people can take? Fear leads to paralysis. If we replace fear with concern, we motivate action, and in action there is hope.

The main thing that surprised me about Mr. Gore in person was how funny he is. I laughed throughout the training with him. As one of his asides, he then shared this fourth budget:

• A Humor Budget: Show a cartoon or share a funny quotation, and you make deposits in pretty much all three “accounts” above simultaneously.

Sharing a Vision via Affect

Gore also connects through emotion. Here are a few examples that relate to the genesis of his personal vision and his efforts to inspire that vision in others.

• Gore conceives of collective will as a stock: “We have everything we need — with the possible exception of political will. But in America, political will is a renewable resource.”
• “I set myself a goal: Communicate this real clearly. The only way I know how to do it is city by city, person by person, family by family.”
• “Are we capable of doing great things even if they are difficult? The historical record says that we can. . . . It is our time to rise again to secure our future.”
• “There’s nothing that unusual about what I’m doing with this. What is unusual is that I had the privilege to be shown it as a young man. It’s almost as if a window was opened through which the future was very clearly visible.‘See that?’ he said.‘See that? That’s the future in which you are going to live your life.’”

Peter Pruyn is an Organizational Development and Training Consultant at Tufts University. A member of the Society for Organizational Learning and graduate of Rick Karash’s Systems Thinking Development Program, he lives contentedly in Cambridge, MA. He can be reached at pwp [at] airmail.net.

The post What I Learned About Teaching Systems Thinking from Al Gore appeared first on The Systems Thinker.

First, relax and take a deep breath. (You probably need it, if you think a stock and flow diagram is cute!) Then consider some lessons I’ve learned, as I’ve tried to advance the use of systems thinking in many different organizations over the past 15 or more years:

Lesson 1: Except in rare circumstances, don’t tell your managers that they must adopt systems thinking. Most senior managers are eminent pragmatists, focused on their goals (or the goals they’ve been given). To them, as good as it is, systems thinking is just a means to an end. Your bosses will be more likely to hear you if you help them achieve their goals than if you ask them to adopt your tools.

Listen to them, and discover what their problems and goals are in their words. Ask questions. Be curious. Don’t fake curiosity so they’ll open up; instead, really be curious (people can often tell the difference, and taking this approach also affects your levels of perception). When they’ve stated a clear problem that systems thinking can address, ask them if they’d be interested in finding a solution. Then show them the way forward, perhaps without ever mentioning the words “systems thinking.”

Your bosses will be more likely to hear you if you help them achieve their goals than if you ask them to adopt your tools.

As an analogy, think about the times you’ve called the help desk to solve a problem with your personal computer. You don’t want the technician to tell you all the gory details about the technology you’re using; you just want her to solve your problem now. That’s the way your manager will likely regard systems thinking.

If you work for an innovative manager who sees the strategic advantage in simulation, you may again be tempted to start talking about systems thinking. Careful! I had a manager like that when I was starting in organizational simulation, and the situation initially seemed great. What I forgot was that the other managers I was serving, his peers, didn’t share his enthusiasm, and I needed to work on solving their problems, not talking about my technology.

Lesson 2: Don’t do your work in a vacuum. When I first started out, I’d ask managers what their biggest problem was. They’d tell me, and then I’d head back to my desk and computer to start working on it. A week or so later, I’d drop by the managers’ offices again to get more data, only to hear that they had solved the problem two days earlier! When I would ask what they did, it was clear they had found an acceptable but often quite mediocre bandage to apply. That is, they fixed the problem well enough so that they could turn to another area of concern that was crying out for help, but they hadn’t necessarily fixed it for good.

It took me a few loops through this process before I discovered that, if I didn’t change my approach, I would always be working on a problem someone had declared was their biggest bugbear one day and that they had “solved” two days later — not a way to feel good about my contribution or to ensure my long-term job security!

If a manager presents you with a problem, work with him to solve it. Solicit the information you need while you’re sitting with him, and capture the key aspects of the situation on paper in front of him. Scribble down statements, data, and fragments of stock and flow diagrams. Accept the manager’s input about the diagram. If it’s the sort of issue and situation where it’s appropriate to pull together a group, do so and use any of the facilitation techniques created to help with such work.

You’ll probably need to do some of the more detailed modeling on your own, but don’t stray long from involving the others in giving you data or reviewing and guiding your progress. You’ll have to judge how long you can stay apart, but in most cases, you should be interacting several times a week.

To maintain that openness and pace, you’ll need to be good at modeling. If you don’t feel comfortable working in front of your managers or internal customers, and if you have to spend more time studying than doing, get some support, whether it means taking a course, bringing in outside consultants to help, or allying yourself with others in your company who can help you deliver the services your internal customers expect. You might find a consultant who will collaborate with you so that you deliver the value together while you simultaneously increase your skills.

Lesson 3: Respect the data. As I was listening to an explanation of a problem recently, I developed an intriguing hypothesis regarding the cause of the behavior being described. Back at the office, I started working on a simple model to explore that hypothesis. The harder I looked, the less I could find quantitative evidence that my theory was true. After a bit of struggle, I managed to let go of my intriguing idea, focused on the data, and ultimately discovered what I think is an even more important story.

Remember that data comes in many forms, not all of which are quantitative.

Lesson 4: Develop a knack for seeing patterns and recognizing likely underlying structures. One of the key mantras of systems thinking is that events are part of patterns, and patterns are created by structures. Most people look at events and see events. When you see a notable happening, see if it’s part of a pattern. If it is, think about the type of structure that might create such a pattern — such as exponential growth or cyclical behavior — and look at the organizational system to see if it has such a structure. Then think about modifications to the structure that might fix the recurring events. Finally, test your hypothesis by creating a simple simulation model.

This approach will help you offer effective services faster, and your managers will appreciate that you can help them solve their problems well and quickly. Of course, you get better at recognizing the structures that create specific patterns by doing lots of simulation.

Some years ago, I watched a manager talk about bouts of overspending followed by bouts of underspending. To him, it was an event of overspending that lasted several months, then a pause, then another event of several months of overspending. I saw this as a type of simple oscillation, and I began to look for a structure that could create this kind of behavior. Knowing what to look for expedited my search for a structure in the organization that could generate such a pattern. It wasn’t too far from discovering the structural problem to proposing the cure, and then testing it, submitting it for approval, and implementing it. Incidentally, out-of-control spending dropped by 95 percent when we installed the new process in the real world.

Lesson 5: Remember that systems thinking is ultimately about helping people. No matter how ironclad your model seems to be, you’re doing this to make the world (or your piece of it) better for people. Most of us don’t want to be told what to do; we prefer being involved in the process of deciding what to do. When you keep others involved and make it clear that your goal is to help them, not simply to create a technological marvel, people are more likely to provide insights you need and help the implementation succeed. Besides, it’s the right thing to do.

In the out-of-control spending case, I created a simulation model and persuaded the manager to try the approach. As we implemented the solution, we created a team that met weekly to discuss progress and to guide mid-course corrections. Even though I had created the model and implemented some necessary software, I made sure my influence was only equal to that of the others. To keep that message of equality in the forefront, we rotated responsibility for leading our meetings so no one appeared to be the de facto leader.

Involving the entire group was key to our success, for everyone involved knew that they had a say in the matter and that we’d do what worked in the real world, not just what worked in my model. Everyone, from the administrative assistants to the finance department representative to the managers, understood that this system was in place to help them do their work more effectively and to help the organization be more successful, and they knew by example that their insights could and would be adopted to further refine our process. I credit the project’s success half to the insights from modeling and half to the way we involved the people doing the work.

Lesson 6: Plan on course corrections; systems thinking doesn’t end when you’ve got a model. Your model was only a model; you’ll probably discover unforeseen problems as you implement the solution. Because models produce hard numbers, while life often seems messy, it’s sometimes tempting to hold on tightly to the lessons of the model when the two seem to diverge.

Remember that you’ve just sold your organization on the importance of a systems view and on the importance of understanding feedback. Now it’s your turn to deal with feedback — feedback from the real world. Listen, observe, and reflect, and be willing to incorporate what you learn into the implementation.

Now, take another deep breath, stand up, and go make your organization and the world better! Don’t sell systems thinking; be a systems thinker!

The post Introducing Systems Thinking into Your Organization appeared first on The Systems Thinker.

We’ll use paper and pencil (the only items you’ll have to pay for, assuming you own a fairly up-to-date computer) to sketch out the initial model, a simulator called SimPack to code the model, a compiler called gcc to compile the model into an executable program, gnuplot for the graphics, and Dia for producing stock and flow diagrams and other documentation (see “Shoestring Resources”).

The Process, Briefly

Let’s start with model building. I still find paper and pencil the best way to get started — it’s easy to use, there is no syntax checking to constrain creativity, and editing is quick and satisfying — erase small mistakes or, for bigger changes, ball up the paper and throw it in the recycling bin.

Once you have sketched a model, it’s time to convert it into something the computer can understand. While it’s not too hard to write a basic system dynamics simulator from scratch, SimPack, a collection of simulation programs produced by Paul Fishwick at the University of Florida, makes life easier.

SimPack provides two system dynamics simulator programs that you’ll find in the constraint/differential/integrate subdirectory of SimPack: conte.c for Euler integration and contrk.c for Runge-Kutta integration. You’ll need to enter your model equations as statements in the C programming language.

Once you’ve coded the model in C, you’ll need to compile it to turn the C program into an executable program for your computer. If you’re running on Linux or Mac OS X, you probably have ready access to the compiler gcc. If you’re running Windows, Cygwin offers a free environment that includes gcc and other tools you might use.

After you compile and run the program, you’ll get a file full of numbers, representing the value of each variable of interest at each point of simulated time. Gnuplot can graph that data.

What’s left? Perhaps you want to communicate your thinking about the relationship between stocks and flows in the system to others. Use Dia to create traditional or creative stock and flow diagrams. Both Dia and gnuplot can produce results suitable for casual viewing on the screen, incorporation into a Web site, or publication in a report or journal.

Taking the Next Step

If you haven’t programmed much, you may be a bit overwhelmed. Move forward in small steps. Start by installing and exploring gnuplot and Dia; you’ll likely find many uses for them, including plotting data and drawing diagrams.

Then install Cygwin, if you’re on Windows. While it can be a massive download, all you really need is the basic installation plus gcc. You’ll probably want the man (manual) pages, too.

Even if you decide you prefer to use a commercial simulator, you might find that some of these tools can augment your normal processes. For example, I’ve used gnuplot to produce publication-quality graphics from data generated using a commercial simulator.

Who knows? You might enjoy systems thinking on a shoestring!

Bill Harris (bill_harris@facilitatedsystems.com) is principal and founder of Facilitated Systems, a company dedicated to helping organizations address complex problems, work more productively in meetings and groups, and learn more effectively from experience.

this is a continuation…

Making It Concrete

The Model. To illustrate, I’ll carry a simple model about the spread of infection through a population through the entire process. If you need more information, refer to “Shoestring Resources” in the main article.

The SI model is a simple model of disease. It divides a population into two groups: Susceptible (S) and Infected (I) people (thus the SI moniker). There’s only one flow, from S to I. The number of susceptibles becoming infected per day, ipd, is the product of the number of susceptible people S, the number of contacts a susceptible person has per day c, the probability of any one contact being with an infectious person, and the probability of getting infected from contact with an infected person p:

ipd = S * c * (I / (S + I)) * p

For more information, see chapter 9 of John Sterman’s Business Dynamics (McGraw-Hill/Irwin, 2000).

To create the simulation program, open the SimPack file conte.c in a text editor (e.g., Notepad; I use GNU Emacs) and save it as si.c in a convenient directory. Then set the number of initial susceptibles S to 9999, the number of initial infecteds I to 1, the probability of getting infected from one contact p to 10% (0.1), and the number of contacts per day c to 4 by editing the initialization function init_conditions in si.c:

init_conditions() { out[1] = 9999.0; /* Susceptibles */ out[2] = 1.0; /* Infecteds */ p = 0.1; c = 4.0 time = 0.0; delta_time = 0.125; } Note that we don’t refer to S and I by those names; rather, we use elements of the array in and out to represent values of stocks. out[1] holds S, the number of susceptible people just calculated by the model, while in[1] holds the value of S to be used at the start of the next iteration. The function init_conditions also sets the initial time to 0 and the simulation time increment (often referred to as DT in system dynamics models) to 0.125.

We need one more SimPack function to calculate the results:

state() { /* Calculate flows */ ipd = out[1] * c * (out[2] / (out[1] + out[2])) * p; /* Update stocks */ /* Susceptibles */ in[1] = 0.0 – ipd; /* Infecteds */ in[2] = ipd – 0.0; }

We have a bit of housekeeping to attend to, as well; we’ll need this declaration at the start of the program:

double d, c, ipd;

In the function main, we’ll set the program to run when time (in days) is less than 50.0, and we’ll add a statement to print out all the results. To speed experimentation, I print all the stocks and flows and let gnuplot select the values to plot:

printf( “%f %f %f %f n”,time, out[1], out[2], ipd);

If you’re not a C programmer, some of this may look like gobbledygook; you can just try it, or you can read some of the “Shoestring Resources.”

Compile this program by typing two simple commands in a Cygwin command shell window:

gcc –o si.exe si.c ./si.exe > si.dat

The first line compiles the program si.c, creating si.exe, and the second runs si.exe, putting its results in the file si.dat. Si.dat has four columns: the time, S, I, and ipd. You can look at si.dat with your favorite text editor to see the results. If you’ve made it this far, pat yourself on the back; you’ve created a system dynamics model!

Plotting the Output

Few of us are satisfied looking at such a long list of numbers. Start gnuplot, and enter the command

cd “/Documents and Settings/My Documents/My Name/”

if that’s where you put your program. Then the command

plot “si.dat” using 1:2

will plot the number of susceptible people over time.

plot “si.dat” using 1:3

will plot the number of infectious people over time.

plot “si.dat” using 2:4

will create a phase plot showing the number of people getting sick per day for different values of the susceptible population. In each case, the numbers in the plot statement refer to columns in the data file you wrote when you ran si.exe.

Gnuplot can plot multiple graphs on the same sheet and can format the output for the screen or publication.

Making Life Simpler and More Powerful

As you advance, you’ll likely need a table function to represent nonlinearities. With basic C programming skills, it isn’t hard to create. You might also want to be able to give your model new parameter values without recompiling the program; the getopt C library function can help. If you want to reduce the typing required for this work, check out gnuplot mode for the Emacs text editor in the “Shoestring Resources” section of the main article.

Stock and Flow Diagrams. Those of us accustomed to using commercial simulators expect to see computer-generated stock and flow diagrams. We’ll use Dia. While you can draw straightforward stock and flow diagrams easily with Dia, you can also exercise a bit of creativity, using a symbol for stocks that suggests the type of object being accumulated and a symbol for flows that matches the symbol for stocks.

Now that you’ve seen that you can do system dynamics on a shoestring, remember all the good practices you’ve learned elsewhere. Happy modeling!

Bill Harris (bill_harris@facilitatedsystems.com) is principal and founder of Facilitated Systems, a company dedicated to helping organizations address complex problems, work more productively in meetings and groups, and learn more effectively from experience.

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How many times have we felt the same way, bumping along as always and wondering whether there is a better way to do things? Each time we are faced with a familiar problem, we swear to ourselves that we will look deeper into the situation and really solve it once and for all. But then something else comes up, causing us to push the question to the back burner until it surfaces again.

Events, Events, Events…

We live in the world of events:, “The stock market dropped 15 points today… A five-car pileup occurred on interstate 95…Our copy machine broke down at 3 o’clock…Our first quarter earnings were down by 20%…Our latest product launch was 10 weeks late…” and on it goes. When events (like a car breakdown) have a direct impact on our lives, we have to react as quickly as possible to them. But there is no long-term leverage for creating change in an organization if we only stay at the level of events (see “Levels of Understanding: ‘Fire-fighting’ at Multiple Levels,” June/July 1993).

For example, managers at A-to-Z Corp., a semiconductor company, have been puzzling over a series of events that occurred in their most recent quarter. They posted record sales for the quarter, with the majority of the sales force meeting or exceeding sales quotas. All products scheduled for release were launched, with additional products ready for early release in the next quarter. At the same time, however, profits actually declined for the first time in company history, as overhead costs as a percent of sales reached an all-time high.

Interrelated Patterns of Behavior

The frenetic pace at A-to-Z made it easy for its employees to get caught up in the daily demands of the semiconductor business. Until their profits declined, A-to-Z’s managers had no idea that there might be underlying financial problems. To address the issue of falling profits, they decided to collect data about their past performance, looking back over a period of time to identify important patterns of behavior. What, for example, was the pattern of product launches over the last two years? Or the number of new products in the pipeline? The number of product engineers? The average experience level of engineers?

The data they found was as follows: Sales revenue had risen every quarter for the past 10 years, but profit growth had been falling for the last several quarters and had actually declined in the most recent quarter. Because the company’s past success was based on new products, there was a continued commitment to launching many new products each year. Each quarter they added new sales people to meet more aggressive sales targets.

An initial plot of these events over a period of several years is shown in “A-to-Z’s Performance OverTime.” Just plotting the data, however, provided little insight about why the trends have occurred.

Data Analysis and Theory Building

There are many tools and methods available for analyzing such time series data as the A-to-Z managers collected. The quality improvement arena, for example, offers run charts, scatter diagrams, and statistical process control methods for analyzing trends, interrelationships, and system capability. Various regression or trend analysis tools are also available for identifying correlations between variables. But there are limitations to the use of these tools.

A-TO-Z’S PERFORMANCE OVER TIME

Sales revenue at A-to-Z has risen every quarter for the past 10 years, but profit growth has been falling for the last several quarters. Meanwhile, new product launches and the size of the sales staff have been increasing every year.

One obvious limitation is that regression or any other data analysis tool is useless without data. However, there is often a paucity of data available for analyzing a new problem — and therein lies the dilemma. If we are only using data analysis tools, we run the risk of just focusing on those variables for which we have data. On the other hand, it is unrealistic to try to track data for everything in advance. Data analysis tools and methods are most useful when they are used as part of a theory-building process.

Drawing behavior over time (BOT) graphs (also called “reference modes”) can help break the data availability dilemma by building causal theories before we gather the necessary data. The BOTs can be used to connect past observed behavior with future behavior in a way that offers insight into the causal structures underlying the case. Developing such causal theories reduces the risk of becoming straight-jacketed by the limitations of the data that is readily available. In short, BOTs guide the use of data, but are not data-bound.

Building a Theory

The A-to-Z managers began working with their initial behavior over time charts by putting together a cross-functional team to try to understand what was happening. This team decided to look at a time horizon of five years.

To begin to understand why profits were falling even as revenues were growing and new product introductions were running smoothly, the A-to-Z team hypothesized about the relationship between total number of new products and the unit cost of carrying products. Although the number of products in their catalogs had been growing steadily, they wondered whether the cost of carrying the products was growing at an even faster rate. One person inferred that the number of new products with revenues of less than $10K was probably increasing and that the average selling price was decreasing.

This possibility would help explain how they could have record unit sales and dollar volume and still have falling profits. Another person suggested that increasing revenue pressures might be putting pressure on new product development to keep pumping out even more new products. These pressures might cause people to work on creating products that were easier to develop and launch, rather than on more innovative and potentially more profitable ones. This emerging causal theory is shown in “Pressure on New Product Development.”

Guidelines for Using BOTs

As the A-to-Z team members continue to work with and build confidence in their causal theory, they can begin to gather the appropriate data to see whether it supports what they have theorized using the BOTs and the accompanying causal loop diagram. Through an iterative process of going back and forth between theory-building and data analysis, they can build a better understanding of what is happening.

When you begin using BOTs and causal loop diagrams to build causal theories of specific issues, some general suggestions can help guide the process:

1. PRESSURE ON NEW PRODUCT DEVELOPMENT

1. 1. Select Time Horizon. Identify the desired time horizon for the problem at hand. The length of time will provide a guide for determining which variables to select and study further. Having a time horizon of two years, for example, will have different critical variables than those associated with a time horizon of 20 years.
2. 2. Define the Problem Dynamically. Draw behavior over time charts of key variables. These charts can serve as reference points throughout the theory-building process, helping to define the problem, focus the conceptualization, and validate the emerging theory.
3. 3. Conduct Thought Experiments. Conduct thought experiments by hypothesizing about the time behavior of different variables and inferring the behavior of other related variables. Do “what-if” experiments of possible future scenarios and draw out the implications of those events on other variables.
4. 4. Build Causal Theories. Use causal loop diagrams to build causal theories that draw out the interrelated behavior of variables over time.
5. 5. Validate with Data. Use data analysis tools to help validate the BOTs and causal relationships.

If we don’t want to be like Edward the Bear — forever bumping our heads down the stairs — we need to be able to step out of the day-to-day stream of events and see the larger context in which we operate. Drawing behavior over time charts and a corresponding set of causal loop diagrams can not only show us what happened, but can also help us build a better understanding of why something happened.

The post Behavior Over Time Diagrams: Seeing Dynamic Interrelationships appeared first on The Systems Thinker.