When errors such as these surface, blaming seems to be a natural reflex in many organizations. Even those individuals who wish to learn from mistakes fall into naming culprits. Once we figure out who’s at fault, we then try to find out what is wrong with the supposed offenders. Only when we discover what is wrong with them do we feel we have grasped the problem. Clearly they are the problem, and changing or getting rid of them (or simply being angry at them) is the solution.

There’s a problem with this common scenario, however: Where there is blame, there is no learning. Where there is blame, open minds close, inquiry tends to cease, and the desire to understand the whole system diminishes. When people work in an atmosphere of blame, they naturally cover up their errors and hide their real concerns. And when energy goes into finger pointing, scapegoating, and denying responsibility, productivity suffers because the organization lacks information about the real state of affairs. It’s impossible to make good decisions with poor information.

In fact, blame costs money. When the vice president of marketing and the vice president of R&D are blaming each other for quality problems in product development, they can’t focus on working together to bring the best products to market. Their finger pointing results in lost sales potential.

Blame rarely enhances our understanding of our situation and often hampers effective problem solving. So how do we avoid the tendency to blame and create organizational environments where we turn less frequently to blame? Clarifying accountability is one option. This process of assigning responsibilities for a situation in advance can help create a culture of real learning.

Accountability comes from clear contracting, ongoing conversations, and an organizational commitment to support accountability rather than blame. The contracting focuses on tasks to be accomplished, roles to be taken, processes to be used, standards sought, and expected results. Periodic conversations over time review both explicit and tacit contracts in order to verify shared understanding. This communication becomes most useful when people are willing and able to discuss their common difficulties within a larger setting that values accountability.

The Differences Between Accountability and Blame

The dictionary helps clarify the differences between accountability and blame. To be accountable is “to be counted on or reckoned on.” To blame is “to find fault with, to censure, revile, reproach.” Accountability emphasizes keeping agreements and performing jobs in a respectful atmosphere; blaming is an emotional process that discredits the blamed.

A focus on accountability recognizes that everyone may make mistakes or fall short of commitments. Becoming aware of our own errors or shortfalls and viewing them as opportunities for learning and growth enable us to be more successful in the future. Accountability therefore creates conditions for ongoing, constructive conversations in which our awareness of current reality is sharpened and in which we work to seek root causes, understand the system better, and identify new actions and agreements. The qualities of accountability are respect, trust, inquiry, moderation, curiosity, and mutuality.

Blaming, on the other hand, is more than just a process of allocating fault. It is often a process of shaming others and searching for something wrong with them. Blaming provides an early and artificial solution to a complex problem. It provides a simplistic view of a complex reality: I know what the problem is, and you’re it. Blame thus makes inquiry difficult and reduces the chances of getting to the real root of a problem. Blame also generates fear and destroys trust. When we blame, we often believe that other people have bad intentions or lack ability. We tend to excuse our own actions, however, because we know firsthand the challenges we face. The qualities of blame are judgment, anger, fear, punishment, and self-righteousness.

The Organizational Consequences of Blame

Blame Slows Information Flow and Reduces Innovation. People sometimes use blame as a strategy to get others to take ownership of problems. But this approach often backfires because people begin to equate acknowledging mistakes and surfacing bad news with punishment. When this happens, two reinforcing sets of behaviors may emerge: one by managers who are ostensibly seeking information and then punishing those who bring bad news, and the other by groups of employees who hide information and try either to protect each other or to blame each other. People who feel compelled to protect themselves can’t admit mistakes-and therefore can’t learn from them. Under these conditions, individuals spend time denying problems rather than solving them, and

The Reinforcing Cycles of Blame

Blame causes fear, which increases cover-ups and reduces the flow of information. The lack of information hinders problem solving, creating more errors (R1). Fear also stifles risk taking and discourages innovation (R2).

As shown in “The Reinforcing Cycles of Blame,” blaming leads to fear, which increases cover-ups and reduces the flow of information by stopping productive conversation. The lack of timely and accurate information about an organization’s current reality hinders problem solving, leading to more errors and more blame (R1).

Blaming and the fear it generates also discourage innovation and creative solutions. Frightened people don’t take risks, which are essential for innovation. Lack of innovation, in turn, leads to an inability to solve problems effectively and an increase in errors (R2).

Blame “Shifts the Burden.” In a “Shifting the Burden” situation, a problem has multiple solutions. People often grab onto the most obvious, short-term fix rather than search for the fundamental source of the problem. The lack of a permanent, long-term solution reinforces the need for additional quick fixes. Blame is a fix that actually diverts the blamers’ attention away from long-term interpersonal or structural solutions to problems (see B1 in “The Addiction to Blame” on p. 3).  Although blame provides some immediate relief and a sense of having solved a problem (“It’s their fault”), it also erodes communication (R3) and shifts the focus even further from accountability (B2), the more fundamental solution.

Blaming can also be addictive, because it makes us feel powerful and keeps us from having to examine our own role in a situation. For example, Jim, a brewery manager, got word that things were slowing down on line 10, a new canning line. He left his office and headed to the plant floor. “Grady, you’ve got to get this line going. Get with it,” he told his line foreman. Grady replied, “Jim, you know those guys on the last shift always screw things up.”

This is a familiar conversation to both men. Each walks away thinking something is wrong with the other. Jim thinks, “That Grady, I give him responsibility and he just can’t get it together.” Grady thinks, “Why is he always on my case? Can’t he see this is a tough issue? He’s so simplistic and short-sighted.”

In this scenario, Jim can walk away feeling relieved because he knows what the problem is-Grady is a lousy supervisor and may need to be replaced. Grady, on the other hand, can blame Jim for being a shortsighted, run-the-plant-by-the-numbers manager. Both get some initial relief from blaming each other, but neither solves the ongoing problem.

Moving from Blame to Accountability

How, then, do we move from blame to accountability? Even within carefully designed systems, people may fail at their work. And even with a knowledge of system dynamics, we still often look for an individual’s failure as a way to explain a problem. One leverage point is to understand the organizational dynamics of blame as described above. There is also leverage in changing how we think about and conduct ourselves at work.

There are three levels of specific behavioral change in moving from blame to accountability-the individual level, the interpersonal level, and the group or organizational level. First, individuals must be willing to change their own thinking and feelings about blame. Second, people need to become skillful at making contracts with one another and holding each other accountable for results. Third, groups need to promote responsible and constructive conversations by developing norms for direct conflict resolution between individuals. These behavioral changes-and the use of systems thinking to focus on the structures involved and not the personalities-can help create a constructive organizational culture.

Individual Level

Below is a list of ways to start breaking the mental models we hold about blame. When you find yourself beginning to blame someone else for a chronic problem, refer to this list and to the sidebar “Distinctions Between Blame and Accountability” (see p. 4).

1. Remember that others are acting rationally from their own perspective. Given what they know, the pressures they are under, and the organizational structures that are influencing them, they are doing the best they can. Give others the benefit of the doubt.

2. Realize that you probably have a role in the situation.Your behavior may be influencing this person’s behavior and may be producing some unintended effects. Keep in mind that you will tend to justify your own actions and point of view and discount the other person’s perspective.

3. Remind yourself that judgment and criticism make it very difficult to see clearly. Judgments are mental models that limit the ability to take in new data. They tend to increase the likelihood of anger and make it difficult to learn. The following questions may help stretch your thinking and ease angry feelings. Ask yourself:

• What information am I missing that would help me understand this person’s behavior?
• How might this behavior make sense?
• What pressures is he or she under?
• What systems or structures might be influencing this behavior?

4. Use a systems thinking perspective to explore the pressures on the players involved. Notice that there are some larger forces at work that are probably having an impact on both of you. For example, when organizational goals, strategies, and values aren’t clear, groups will sometimes work toward different objectives. A group that values customer service over cost will conflict with a group that is trying to lower expenditures. Identify some key variables and their interrelationships, and ask, Is this situation an example of a vicious cycle, “Shifting the Burden,” or “Accidental Adversaries”?

5. Be willing to be held accountable. This means that, when an issue comes up, you are willing to consider whether you have lived up to your end of an agreement or expectation. Ask yourself:

• Did I have a role in this situation?
• Did I take some actions that seemed right at the time, but that had unintended consequences?

6.Work constructively with your anger. Sustained anger may point to personal issues that have been triggered by the current situation. Broken agreements, mistakes, and blame all have difficult associations for most people. However, in a learning environment, constructive resolution of conflict can also lead to significant personal growth. The guiding questions here are:

• What am I learning about myself in this situation?
• What does this remind me of?
• What new behaviors or thoughts does this situation call for that may be a stretch for me?

Interpersonal Level

Initial Contracting. At the beginning of any working relationship, it’s vital to come to some basic agreements defining the nature and scope of the work, specific and yet-to-be-defined tasks, deadlines and related outcomes, processes or methods to be used, interim checkpoints and expectations at those checkpoints, standards, and roles.

It’s also helpful to discuss what to do in the event of a misunderstanding, a lapse in communication, or a failure to keep an agreement. Imagine possible breakdowns and design a process for handling them. If breakdowns do occur, be prepared to remind others of the plan you had prepared.

When lapses do take place, they need to be brought to the collective attention as soon as possible. Misunderstandings and broken agreements often promote anger, frustration, and blame. Allowing unaddressed misunderstandings to fester can hamper productive conversations. By contrast, raising issues early can minimize escalation of problems.

Accountability Conversations. Once any project or working relationship is under way, it’s useful to check in periodically on the state of the partnership through accountability conversations. You may or may not have clear recollections of the initial contract regarding the task, roles, standards, processes, and expected results. Either way, it’s productive to establish or reestablish these agreements and explore what is working or not working as you take action together to create envisioned results.

Accountability conversations aren’t always easy. However, the skills they require can be applied and developed over time. Some of the basic tools of learning organizations come into play here-the ladder of inference, for example, can be used to create a conversation of inquiry rather than inquisition. The accountability conversation is also the perfect setting for practicing left-hand column skills to surface assumptions blocking honest and productive discourse. In addition, admitting the tendency to

Distinctions between blame and accountability

Here are steps for initiating an accountability conversation:

1. Find out whether the person you are working with is interested in seeing problems as learning opportunities. If so, when a problem occurs, include other people who are also interested in the situation. Other people’s perspectives can be helpful because often two people in conflict are actually mirroring the conflict of a larger system within the organization.

2. Create a setting that is conducive to learning.

• Allow plenty of time to address the issues.
• Reaffirm with each other that the goal is to learn, not blame.
• Establish confidentiality.
• Be truly open-minded.
• Listen hard to the other person’s perspective

3. Have a conversation in which the two (or more) of you

• Clarify your intention for the meeting.
• Identify the data and any assumptions or conclusions you have drawn based on that data.
• Identify the pressures each of you is experiencing in the situation.
• Identify any stated or unstated expectations. If implicit agreements were not jointly understood, this is a good time to clarify and reestablish shared agreements.
• Analyze the problem from a systems perspective. Clarify how your mutual beliefs and actions might be related and are perhaps reinforcing each other.
• Identify some new ways to address the problem.

Group Level

How people talk about one another in an organization affects the levels of accountability and trust. Often, because people are reluctant to discuss accountability issues directly, they go to a third party to relieve their discomfort and get support for their point of view. The complaint does not get resolved this way, however, although the person with the complaint gains some relief. Bringing a complaint to a third party to clarify a situation can be a much more productive alternative.

To see how this works, let’s take a situation where Tony is angry with Lee because Lee wasn’t fully supportive in a meeting. Tony complains to Robin that Lee is unreliable. Robin sympathizes with Tony and agrees that Lee is unreliable. Tony and Robin now feel closer because they share this point of view. Lee does not yet know that Tony has a complaint. Later, though, Robin, busy with other projects, puts off one of Tony’s requests. Now Tony complains about Robin to Lee, and Robin doesn’t get the necessary feedback. Over time, all of these relationships will erode.

What is the alternative to this kind of dysfunctional blaming and resentment? The solution is a deep commitment on the part of all these people to work through their reluctance to give and receive difficult feedback. In addition, they need to learn how to hold one another accountable in an ongoing way. Now, when Tony is angry with Lee and goes to Robin, the purpose is to get coaching on how to raise the issue with Lee, not to get Robin’s agreement on what is wrong with Lee. In addition, Robin’s role is to make sure that Tony follows through on raising the concern directly with Lee.

To resolve conflict directly:

1.Bring your complaints about someone else to a third person to get coaching on how to raise your concerns.
Valuable questions from the coach include:

• Tell me about the situation.
• What results do you want?
• What’s another way of explaining the other person’s actions?
• How might the other person describe the situation?
• What was your role in creating the situation?
• What requests or complaints do you need to bring to the other person?
• How will you state them in order to get the results you want?
• What do you think your learning is in this situation?

2. Raise your concerns directly with the other person. Reaffirm your commitment to maintaining a good working relationship and find a way to express your fundamental respect for the person. The ladder of inference can be a helpful tool for focusing on the problem. Start by identifying the data that is the source of your concern. Then spell out the assumptions you made as you observed the data and any feelings you have about the situation. Finally, articulate your requests for change. During the conversation, remind the other person that reviewing the concern is part of learning to work together better

3. Let the coach know what happened.

4. Outside of this framework, refrain from making negative comments about people

5. For listeners who frequently hear complaints about a third party and want to create a learning setting, it can be helpful to say something like: “I’d like to help, but only if you want to create a constructive situation. We can explore these questions; otherwise, I prefer not to listen to your complaints.”

Organizational Accountability: The IS Story

Systems thinking provides useful tools for surfacing and breaking reinforcing cycles of blame within an organization. In the story below, a group was able to use causal loop diagrams to help them move beyond blame and craft a constructive, long-term solution.

The Information Systems group of a manufacturing plant was meeting to discuss their lack of progress on a large project to overhaul the department. Initially, the IS group decided that top management’s actions caused the group’s ineffectiveness. The plant management team (PMT) kept adding projects to the group’s already full plate. Members of the PMT responded to “squeaky wheels” by giving otherwise low-priority projects the force of their support. Also, the PMT didn’t reinforce plant wide policies the IS group had developed. Most important, the team didn’t give group members the support they needed to stick to the IS overhaul they had committed to, and wouldn’t give them the budget to hire the additional staff they sorely needed.

But when the group mapped out their current situation in a causal loop diagram, they gained a new perspective on the problem. They found that the situation resembled a “Success to the Successful” story, in which two or more projects or groups compete for limited resources.

The diagram “Success to the Squeaky Wheel” shows how, in this case, the IS group’s attention to urgent requests diverted resources away from prioritized items. Because rewards for completing urgent requests were heightened, the urgent tasks continued to receive greater attention (R2).  At the same time, the rewards for and focus on prioritized tasks decreased (R1). Finally, as people realized that urgent requests received greater attention than prioritized items, the number of “squeaky wheels”-or people promoting their own agenda items to management-proliferated. This development was followed by an increase in management’s efforts to get action on those agenda items, which further promoted urgent items over prioritized ones (R3).

After examining the causal loop diagrams, the group realized that they had played a role in the stalled progress on the overhaul project. Although IS team members encouraged each other to blame the PMT, no one in the group had given the PMT feedback concerning the impact of their requests and lack of support.

Armed with a systems view, the group identified several actions they could take to shift these unproductive dynamics. They decided to tell the PMT that they recognized that the IS overhaul was a top priority for the plant as a whole. They would point out that they couldn’t make progress on the overhaul if they continued to respond to “squeaky wheels. “The group would also let the PMT know that when they received additional requests, they would ask:

• How much of a priority is this request for you?
• Are you aware that there is a tradeoff in priorities?

The group concluded that they would issue a memo to the PMT describing their priorities and soliciting the PMT’s support of those priorities. They would also request that the PMT clearly communicate the priorities to the rest of the plant. In the memo, they would indicate the tradeoffs they were making and identify how their choices would help the company as a whole. The group felt that, with the PMT’s support, they would have the authority to focus on the prioritized project instead of responding to urgent requests.

Conclusion

Developing accountability skills is challenging; it takes courage and the willingness to learn new ways of thinking and acting. So why is moving from blame to accountability worthwhile? Because blame is like sugar – it produces a brief boost and then a let-down. It doesn’t serve the system’s long-term needs and can actually prevent it from functioning effectively. On the other hand, developing accountability skills and habits on every level of your organization can be an important element in maintaining your organization’s long-term health.

Marilyn Paul, PhD, is an independent organizational consultant affiliated with Innovation Associates, an Arthur D. Little company. She has sixteen years of experience facilitating organizational change. One focus of her work is peer mentoring and capacity development.

The post Moving from Blame to Accountability appeared first on The Systems Thinker.

From my work with both business and education professionals over the last 15 years, I have come to believe that systems thinking’s steep learning curve is related to the fact that the discipline requires mastering a whole package of thinking skills.

STEPS IN THE SYSTEMS THINKING METHOD

Begin by specifying the problem you want to address. Then construct hypotheses to explain the problem and test them using models. Only when you have a sufficient understanding of the situation should you begin to implement change.

Much like the accomplished basketball player who is unaware of the many separate skills needed to execute a lay-up under game conditions – such as dribbling while running and without looking at the ball, timing and positioning the take-off, extending the ball toward the rim with one hand while avoiding the blocking efforts of defenders – veteran systems thinkers are unaware of the full set of thinking skills that they deploy while executing their craft. By identifying these separate competencies, both new hoop legends and systems thinking wannabes can practice each skill in isolation. This approach can help you master each of the skills before you try to put them all together in an actual game situation.

The Systems Thinking Method

Before exploring these critical thinking skills, it’s important to have a clear picture of the iterative, four-step process used in applying systems thinking (see “Steps in the Systems Thinking Method”). In using this approach, you first specify the problem or issue you wish to explore or resolve. You then begin to construct hypotheses to explain the problem and test them using models whether mental models, pencil and paper models, or computer simulation models. When you are content that you have developed a workable hypothesis, you can then communicate your new found clarity to others and begin to implement change.

When we use the term “models” in this article, we are referring to something that represents a specifically defined set of assumptions about how the world works. We start from a premise that all models are wrong because they are incomplete representations of reality, but that some models are more useful than others (they help us understand reality better than others).  There is a tendency in the business world, however, to view models (especially computer-based models) as “answer generators;” we plug in a bunch of numbers and get out a set of answers. From a systems thinking perspective, however, we view models more as “assumptions and theory testers” we formulate our understanding and then rigorously test it. The bottom line is that all models are only as good as the quality of the thinking that went into creating them. Systems thinking, and its ensemble of seven critical thinking skills, plays an important role in improving the quality of our thinking.

The Seven Critical Thinking Skills

As you undertake a systems thinking process, you will find that the use of certain skills predominates in each step. I believe there are at least seven separate but interdependent thinking skills that seasoned systems thinkers master. The seven unfold in the following sequence when you apply a systems thinking approach: Dynamic Thinking, System-as-Cause Thinking, Forest Thinking, Operational Thinking, Closed-Loop Thinking, Quantitative Thinking, and Scientific Thinking.

The first of these skills, Dynamic Thinking, helps you define the problem you want to tackle. The next two, System-as-Cause Thinking and Forest Thinking, are invaluable in helping you to determine what aspects of the problem to include, and how detailed to be in representing each. The fourth through sixth skills, Operational Thinking, Closed-Loop Thinking, and Quantitative Thinking, are vital for representing the hypotheses (or mental models) that you are going to test. The final skill, Scientific Thinking, is useful in testing your models.

Each of these critical thinking skills serves a different purpose and brings something unique to a systems thinking analysis. Let’s explore these skills, identify how you can develop them, and determine what their “non-systems thinking” counterparts (which dominate in traditional thinking) look like.

Dynamic Thinking: Dynamic Thinking is essential for framing a problem or issue in terms of a pattern of behavior over time. Dynamic Thinking contrasts with Static Thinking, which leads people to focus on particular events. Problems or issues that unfold over time as opposed to one-time occurrences are most suitable for a systems thinking approach.

You can strengthen your Dynamic Thinking skills by practicing constructing graphs of behavior overtime. For example, take the columns of data in your company’s annual report and graph a few of the key variables over time. Divide one key variable by another (such as revenue or profit by number of employees), and then graph the results. Or pick up today’s news-paper and scan the head-lines for any attention-grabbing events. Then think about how you might see those events as merely one interesting point in a variable’s overall trajectory over time. The next time someone suggests that doing this-and-that will fix such-and-such, ask, “Over what time frame? How long will it take? What will happen to key variables over time?”

System-as-Cause Thinking: Dynamic Thinking positions your issue as a pattern of behavior over time. The next step is to construct a model to explain how the behavior arises, and then suggest ways to improve that behavior. System-as-Cause Thinking can help you determine the extensive boundary of your model, that is, what to include in your model and what to leave out (see “Extensive and Intensive Model Boundaries”). From a System-as-Cause Thinking approach, you should include only the elements and inter-relationships that are within the control of managers in the system and are capable of generating the behavior you seek to explain.

By contrast, the more common System-as-Effect Thinking views behavior generated by a system as “driven” by external forces. This perspective can lead you to include more variables in your model than are really necessary. System-as-Cause Thinking thus focuses your model more sharply, because it places the responsibility for the behavior on those who manage the policies and plumbing of the system itself.

To develop System-as-Cause Thinking, try turning each “They did it” or “It’s their fault” you encounter into a “How could we have been responsible?” It is always possible to see a situation as caused by “outside forces.” But it is also always possible to ask, “What did we do to make ourselves vulnerable to those forces that we could not control?”

EXTENSIVE AND INTENSIVE MODEL BOUNDARIES

The extensive boundary is the breadth or scope of what’s included in the model. The intensive boundary is the depth or level of detail at which the items included in the model are represented.

Forest Thinking: In many organizations, people assume that to really know something, they must focus on the details. This assumption is reinforced by day-to-day existence—we experience life as a sequence of detailed events. We can also think of this as Tree-by-Tree Thinking. Models that we create by applying Tree-by-Tree Thinking tend to be large and overly detailed; their intensive boundaries run deep. In using such models, we would want to know whether that particular red truck broke down on Tuesday before noon, as opposed to being interested in how frequently, on average, trucks break down. Forest Thinking–inspired models, by contrast, group the details to give us an “on average” picture of the system. To hone your Forest Thinking skills, practice focusing on similarities rather than differences. For example, although everyone in your organization is unique, each also shares some characteristics with others. While some are highly motivated to perform and others are not, all have the potential to make a contribution. Regardless of the individual, realizing potential within an organization comes from the same generic structure. For example, what is the relationship among factors that tends to govern an individual’s motivation?

Operational Thinking :Operational Thinking tries to get at causality—how is behavior actually generated? This thinking skill contrasts with Correlational or Factors Thinking. Steven Covey’s The Seven Habits of Highly Effective People, one of the most popular nonfiction books of all time, is a product of Factors Thinking. So are the multitude of lists of “Critical Success Factors” or “Key Drivers of the Business” that decorate the office walls (and mental models) of so many senior executives. We like to think in terms of lists of factors that influence or drive some result.

There are several problems with mental models bearing such list structures, however. For one thing, lists do not explain how each causal factor actually works its magic. They merely imply that each factor “influences,” or is “correlated with,” the corresponding result. But influence or correlation is not the same as causality.

For example, if you use Factors Thinking to analyze what influences learning, you can easily come up with a whole “laundry list” of factors (see “Two Representations of the Learning Process”). But if you use Operational Thinking, you might depict learning as a process that coincides with the building of experience. Operational Thinking captures the nature of the learning process by describing its structure, while Factors Thinking merely enumerates a set of factors that in some way “influence” the process.

To develop your Operational Thinking skills, you need to work your way through various activities that define how a business works examine phenomena such as hiring, producing, learning, motivating, quitting, and setting price. In each case, ask, “What is the nature of the process at work?” as opposed to “What are all of the factors that influence the process?”

Closed-Loop Thinking :Imagine discussing your company’s profitability situation with some of your coworkers. In most companies, the group would likely list things such as product quality, leadership, or competition as influences on profitability (see “A Straight-Line vs. a Closed-Loop View of Causality”). This tendency to list factors stems from Straight-Line Thinking. The assumptions behind this way of thinking are 1) that causality runs only one way—from “this set of causes” to “that effect,” and 2) that each cause is independent of all other causes. In reality, however, as the closed-loop part of the illustration shows, the “effect” usually feeds back to influence one or more of the “causes,” and the causes themselves affect each other. Closed-Loop Thinking skills therefore lead you to see causality as an ongoing process, rather than a one-time event.
To sharpen your Closed-Loop Thinking skills, take any laundry list that you encounter and think through the ways in which the driven drives and in which the drivers drive each other. Instead of viewing one variable as the most important driver and another one as the second most important, seek to understand how the dominance among the variables might shift over time.

TWO REPRESENTATIONS OF THE LEARNING PROCESS

Factors Thinking merely enumerates a set of factors that in some way “influence” the learning process. Operational Thinking captures the nature of the learning process by describing its structure.

Quantitative Thinking: In this phrase, “quantitative” is not synonymous with “measurable.” The two terms are often confused in practice, perhaps because of the presumption in the Western scientific world that “to know, one must measure precisely.” Although Heisenberg’s Uncertainty Principle caused physicists to back off a bit in their quest for numerical exactitude, business folk continue unabated in their search for perfectly measured data. There are many instances of analysis getting bogged down because of an obsession with “getting the numbers right.” Measurement Thinking continues to dominate!

There are a whole lot of things, however, that we will never be able to measure very precisely. These include “squishy,” or “soft,” variables, such as motivation, self-esteem, commitment, and resistance to change. Many so-called “hard” variables are also difficult to measure accurately, given the speed of change and the delays and imperfections in information systems.

A STRAIGHT-LINE VS.A CLOSED-LOOP VIEW OF CAUSALITY

The assumptions behind Straight-Line Thinking are that causality runs only one way and that each cause is independent of all other causes. Closed-Loop Thinking shows that the “effect” usually feeds back to influence one or more of the “causes,” and the causes themselves affect each other.

But let’s return to our “squishy” variables. Would anyone want to argue that an employee’s self-esteem is irrelevant to her performance? Who would propose that commitment is unimportant to a company’s success? Although few of us would subscribe to either argument, things like self-esteem and commitment rarely make it into the spreadsheets and other analytical tools that we use to drive analysis. Why? Because such variables can’t be measured. However, they can be quantified. If zero means a total absence of commitment, 100 means being as committed as possible. Are these numbers arbitrary? Yes. But are they ambiguous? Absolutely not! If you want your model to shed light on how to increase strength of commitment as opposed to predicting what value commitment will take on in the third-quarter of 1997—you can include strength of commitment as a variable with no apologies. You can always quantify, though you can’t always measure.

To improve your Quantitative Thinking skills, take any analysis that your company has crunched through over the last year and ask what key “soft” variables were omitted, such as employee motivation. Then, ruminate about the possible implications of including them systems thinking gives you the power to ascribe full-citizen status to such variables. You’ll give up the ability to achieve perfect measurement. But if you’re honest, you’ll see that you never really had that anyway.

Scientific Thinking: The final systems thinking skill is Scientific Thinking. I call its opposite Proving Truth Thinking. To understand Scientific Thinking, it is important to acknowledge that progress in science is measured by the discarding of falsehoods. The current prevailing wisdom is always regarded as merely an “entertainable hypothesis,” just waiting to be thrown out the window. On the other hand, too many business models are unscientific; yet business leaders revere them as truth and defend them to the death. Analysts make unrelenting efforts to show that their models track history and therefore must be “true.”

Seasoned systems thinkers continually resist the pressure to “validate” their models (that is, prove truth) by tracking history. Instead, they work hard to become aware of the falsehoods in their models and to communicate these to their team or clients. “All models are wrong,”” said W. Edwards Deming. “Some models are useful.” Deming was a smart guy, and clearly a systems thinker.

In using Scientific Thinking, systems thinkers worry less about outfitting their models with exact numbers and instead focus on choosing numbers that are simple, easy to understand, and make sense relative to one another. Systems thinkers also pay lots of attention to robustness they torture-test their models to death! They want to know under what circumstances their model “breaks down.” They also want to know, does it break down in a realistic fashion? What are the limits to my confidence that this model will be useful?

The easiest way to sharpen your Scientific Thinking skills is to start with a computer model that is “in balance” and then shock it. For example, transfer 90% of the sales force into manufacturing. Set price at 10 times competitor price. Triple the customer base in an instant. Then see how the model performs. Not only will you learn a lot about the range of utility of the model, but you also will likely gain insight into the location of that most holy of grails: high-leverage intervention points.

A Divide and Conquer Strategy

As the success of Peter Senge’s The Fifth Discipline: The Art & Practice of the Learning Organization has shown, systems thinking is both sexy and seductive. But applying it effectively is not so easy. One reason for this difficulty is that the thinking skills needed to do so are many in number and stand in stark contrast to the skill set that most of us currently use when we grapple with business issues (see “Traditional Business Thinking vs. Systems Thinking Skills”).

By separating and examining the seven skills required to apply systems thinking effectively, you can practice them one at a time. If you master the individual skills first, you stand a much better chance of being able to put them together in a game situation. So, practice . . . then take it to the hoop!

“Barry Richmond is the managing director and founder of High Performance Systems, Inc. He has a PhD in system dynamics from the MIT Sloan School of Management, an MS from Case Western Reserve, and an MBA from Columbia University”

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What Does Systems Thinking Involve?

Why Use Systems Thinking?

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

When Should We Use Systems Thinking?

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

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

Where Should We Start?

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

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

How Do We Use Systems Thinking Tools?

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

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

THE ICEBERG

How Do We Know That We’ve “Got It”?

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

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

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

Michael Goodman is principal at Innovation Associates Organizational Learning

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The Paradox of KSFs

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

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

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

Beyond Factors to Loops

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

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

Launching a New Venture

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

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

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

Benefits of KSLs

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

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

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As a process leader or facilitator, how can you use systems thinking as part of an effective group process? The following are some overall considerations that should be addressed.

Engage, Don’t Convince

If learning is the objective, then you want everyone to be thinking hard about the problem at hand. To be engaged, people need to feel that their ideas are being heard, examined, and tested. Whether you are presenting a diagram, or facilitating the development of one, it is important to get everyone engaged in creating a shared understanding of the problem. This approach may generate more debate, but it is much better to finish a meeting with strongly felt, irreconcilable differences in the group than to finish with weak acquiescence to an analysis that no one truly believes.

Presume that every view has merit. Whenever anyone makes a suggestion or offers a fragmentary theory, listen to it, inquire into it, and draw out the assumptions. If necessary, help articulate the conditions under which it would be valid. This will draw out more ideas and create a sense of shared problem-solving.

Pursue differences. Areas of conflict often provide the greatest opportunities for learning. One of the most common sources of disagreement in systems thinking diagrams is fuzzy or changing definitions of variables (see “Clarifying Variables”). Work through these issues to gain clarity about what each variable means, and add variables if needed. This process will ensure that the finished diagram represents the collective understanding of the group.

CLARIFYING VARIABLES

Listen for the frequent mistake of changing the interpretation of a variable in a loop.

Treat Theory as Theory

Every causal loop diagram represents a theory (or model) of the way things work. When we create systems diagrams, we are trying to ensure that our solutions are well grounded in a theory of what caused the problem in the first place. In this way, we reduce the possibility that we will end up with solutions that address only the symptoms of the problem. Because each loop diagram is a theory:

• It is important to know who is advocating the theory. If it’s yours, say so. If it’s unclear, ask. A danger signal comes when no one is willing to take ownership of a particular theory. Some groups believe (or hope) that data will point the way to a theory independent of the personal commitment of any person. This rarely happens. Encourage people to suggest a hypothesis, a mechanism, or theory about how things are happening.
• Every theory should be tested vigorously. Since theories are by definition never complete or universally true, it is important to clarify under what conditions or assumptions the diagram will be valid and helpful (see “Testing Theory”). When a model fails a test, ask, “If that theory doesn’t work, what explanation might work better?”If testing a diagram becomes an issue of right vs. wrong, the discussion can quickly deteriorate into a win-lose situation and learning will suffer. Be careful when presenting your own diagrams—if challenged, it is easy to become defensive and lose the openness which is necessary for real inquiry.
• You can facilitate inquiry by asking, “As you see it, how does X cause Y? What’s your rationale? What is the data? Can you give me an example?” (Or just make sure someone asks questions like these.) Once you have heard the answers, state your point of view (“Well, that doesn’t quite work for me.. ..”), but share your own line of reasoning as well.

Remember that an effective group process brings out several alternatives before closing in on one. Without some guidance, most groups will settle for the first reasonable suggestion without investigating other possibilities.

Be Clear About Process

It is usually helpful for a group to have a “road map” for the process. Make sure that all participants have a clear understanding of the overall systems thinking process—if necessary, post a chart of the systems thinking steps (see “Six Steps to Thinking Systemically,” March 1995). From time to time, make sure the group stops to note where it is situated in the process.

Use the Diagram as a Learning Tool

Groups are often reluctant to add variables and links to their diagram until they’re sure that the line of thinking is sound. But the group may need to see an idea in the diagram in order to respond. To avoid this “chicken-and-egg” situation, encourage the group to use the causal loop diagram to support group thinking, not just to record finished, tested thoughts.

Show every suggestion or idea in the causal loop diagram. If someone says, “Longer hours will cause more turnover:’ then add that to the diagram. If someone responds, “I think the improved spirit will keep turnover low,” show this as well. If the ideas don’t work out, then change the diagram back to its original configuration.

The key to making this technique practical is to use self-adhesive notes (such as Post-Its). Put each variable on its own self-adhesive note, using a size large enough to be visible to the whole group. Arrange the notes to illustrate a chain of cause and effect. If the chain seems accurate, then ink in the arrows between variables. Magnetic vinyl tiles and a white board are another good alternative.

Being a Systems Thinker

Being a systems thinker yourself is perhaps the most important single factor for supporting systems thinking in your group. If people see that you model the behaviors and skills you are trying to encourage, it will provide a powerful example. If they hear you say one thing, but see you do another (not “walking the talk”), it can have a negative impact on the work. The actions and bearing of a single individual can be a strong force in setting the overall tone for an approach, regardless of that individual’s level or position in the organization.

Richard Karash (Boston, MA) is a consultant, facilitator, and trainer in the disciplines of the learning organization.

Editorial support for this article was provided by Colleen P Lannon.

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

The Storytelling Trap

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

FROM EVENTS TO VISION: STRUCTURED PROBLEM-SOLVING

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

Storytelling at Multiple Levels

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

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

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

Using the Matrix

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

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

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

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

Guiding Questions

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

Current Reality

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

Desired Future Reality

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

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

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

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To respond to this changing paradigm, what is needed may not be a change of action, but a change in perception. How we think, act, and value are all associated with our particular view of reality. In order to create a new “reality,” we must discover how our current worldview affects the way we perceive and respond to problems. The leverage lies in going to a more fundamental level — to look beyond the problems themselves and re-examine the paradigm that gave rise to them.

The Problem-Solving Model of Managing

The prevailing model of management can be described as a “problem-solution” model: we encounter problems, and as managers, we are expected to solve them as quickly as possible (see “Problem-Solution Model”). In this model, we attack each problem individually, apply an appropriate solution, and then move on to the next one. The problems rarely remain “solved,” however. From a systems thinking perspective, we can see how solutions often feedback to create other problems, or even a repeat of the same problem. By the time this happens, it often appears to be a brand new problem because we either have forgotten about the previous round of solutions, or the same person is no longer in that position (the average tenure in a position is 18 months or less in some companies). This creates a series of problem-solution cycles that can keep an organization continually busy fighting fires instead of taking more fundamental action.

How we think, act, and value are all associated with our particular view of reality. In order to adapt to and create a new “reality,” we must discover how our current worldview affects the way we perceive and respond to problems.

At its worst, the problem-solution paradigm leads us to see problems in terms of pre-determined solutions. Statements such as, “The problem is we need a better information system,” or “The problem is we need the latest flexible manufacturing system,” are examples of solution statements at work. The danger of this habit is that once we begin to frame problems in terms of solution statements, we exclude other possibilities — including the possibility that our original statement of the problem may be wrong.

Even when we don’t resort to our favorite solution, we often don’t challenge the problem statement itself. Problems are nothing more than a formal statement of a set of assumptions about the world. Those assumptions, however, are often not made explicit. By conversing and making decisions at the level of tacit assumptions, we can get very good at defending our point of view at the expense of learning. This can lead to what Chris Argyris of Harvard University calls “skilled incompetence.” Rather than looking at the real data and real issues — which may prompt a re-articulation of the problem — we become very skilled at dancing around the issues.

Problem Articulation

To re-examine the way we think about problems and solutions, we need to understand more fundamentally what a problem is. In reality, there are no problems “out there” in the world — nature just is. Whether we see an event or situation as a problem depends on our view of the world. For example, if oil prices double, is that a problem? Our response would be a resounding “Yes!” since our economy is heavily dependent on petroleum products. If we lived in an OPEC nation, however, we would not see it as a problem at all. If we lived in an undeveloped country with no dependence on oil, we probably would not even be interested.

PROBLEM ARTICULATION

To an extent, we create the problems we see by the way we view reality, and how we articulate those problems can determine the future direction of our reality. To break out of the “problem-solution” model of reality, we need to go back one step further to re-examine the question,“How did we distill out of this vast pool of life a particular problem which led us to act a certain way?”

Problems do not exist independently of the person who sees them Out of the pool of life we “construct” problems in our minds (or in our organizations) by the way we view reality (see “Problem Articulation”). Fred Kofman of the M.I.T. Sloan School of Management suggests that deconstructing a problem and finding a way to re-articulate it can provide much more leverage than trying to just double our efforts to solve the problem as it is currently stated. One of the clear challenges is to explore more explicitly how we articulate problems. Why do we consider something a problem? The “why” is what leads us to surface the deeper set of assumptions that may give insight into reformulating an entirely different problem.

Paradigm-Creating Loops

How can we break out of the problem-solving straitjacket and begin reframing issues in new ways? One tool that can help is the “Ladder of Inference,” developed by Chris Argyris. The “Ladder of Inference” provides a framework for exploring mental models. It graphically depicts the process we use to draw conclusive opinions and judgments from data, showing that individual evaluations are, in reality, highly abstract and inferential.

At the bottom of the “Ladder of Inference” is directly observable data: those things that can be objectively observed (see “The Reflexive Loop”). From that data, we add culturally shared meaning — that is, we interpret and make sense of an event by the norms of our culture. For example, suppose Bob, a colleague, walked into a 9:00 meeting at 9:15. The directly observable data is that Bob physically entered the room 15 minutes after the scheduled start time. What do we say to ourselves when we notice this?

When managers are asked this question, typical responses are:

“He’s late.” “He doesn’t care.” “His previous meeting ran late.” “He’s not a team player.” “He’s disorganized.”

If we locate the responses on the “Ladder of Inference,” we see that most of them are on the higher rungs of the ladder, reflecting judgments and values based on the observable data.

There is nothing inherently wrong about drawing inferences and conclusions from the events we observe. In fact, the ability to move quickly up the ladder is what enables us to make sense of the incredibly complex, infinitely detailed world in which we live. It is impossible for us to see and absorb everything — we are constantly selecting out a narrow slice of life to focus on and understand. What we don’t often realize, however, is that our set of beliefs and assumptions directly affect the selection process by which we receive new observable data. Argyris calls this process the reflexive loop because it happens subconsciously and involuntarily.

For example, if we have concluded that Bob doesn’t really care about meetings and is not a team player, what do we begin to notice about Bob? We take note of all the times he shows up late and we ignore or aren’t aware of all the times he is on time. We notice that Bob does not say much at meetings, but don’t register the fact that a few people always dominate the conversation and that there are others who say even less than Bob. We continually filter out any information that doesn’t fit in with the mental model we have created about Bob. In fact, all the data we see confirm our beliefs and assumptions about Bob. We have leaped from data up to beliefs and assumptions, and then operated as if the assumptions are the reality.

The reflexive loop can also be called the paradigm-creating loop, because it is the process through which, over time, we develop a shared set of corporate assumptions and beliefs about reality. In The Machine That Changed The World (New York: Rawson Associates), there is a striking example of how this paradigm-creating process literally affects our ability to see. The book describes a new system of manufacturing invented by Toyota called “lean production” that uses less material, requires smaller inventories, has a shorter design time, and produces fewer defects than the traditional mass production system (See “Lean Production: From the Machine Age to the Systems Age,” August 1991). The authors tell the story of a General Motors plant manager’s reaction after seeing a lean production plant in Japan: He “reported that secret repair areas and secret inventories had to exist behind the plant, because he hadn’t seen enough of either for a ‘real’ plant.” In actuality, there is no rework area in that plant — they drive the cars right off the assembly line and onto the ships. The GM manager’s paradigm of a “real” plant kept him from seeing that there might be an alternative way to produce cars.

Mistaking the Map for the Territory

Comedian Steven Wright tells this joke: “Last summer my wife and I were planning our summer vacation. We bought a map of the United States. It was life-sized. One mile equals one mile. We never went on the vacation because it took the whole summer to fold the map.”

Of course, buying a life-sized map is ridiculous — it would be no more useful than reality itself. A map is useful precisely because it is a simplification of reality. We would never mistake the map for the territory and plan a trip as if California is only three feet away from New York. And yet we are prone to make such errors of perception whenever we mistake our mental models for the real world.

Marcel Proust once said,“The real voyage of discovery consists not in seeking new landscapes but in having new eyes.” Becoming aware of how our view of the world is continually being constructed through the reflexive loop can prevent us from mistaking the map for the territory. Seeing problems as a product of our own thinking and not a product of nature can open our eyes to a whole new world of possibilities.

THE REFLEXIVE LOOP

The reflexive loop illustrates how our mental models can influence the way we view reality. We make leaps up the “Ladder of Inference” from data to values and assumptions, and then operate based on those assumptions as if they are reality. It can also be called the paradigm-creating loop, because it is the process through which, over time, we develop a shared set of cultural assumptions and values about how we view reality.

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Articulating Reality

Causal loop diagrams provide a language for articulating our understanding of the dynamic, interconnected nature of our world. We can think of them as sentences which are constructed by linking together key variables and indicating the causal relationships between them. By stringing together several loops, we can create a coherent story about a particular problem or issue.

The next page includes some suggestions on the mechanics of creating causal loop diagrams. Below are some more general guidelines that should help lead you through the process:

• Theme Selection. Creating causal loop diagrams is not an end unto itself, but part of a process of articulating and communicating deeper insights about complex issues. It is pointless to begin creating a causal loop diagram without having selected a theme or issue that you wish to understand better. “To understand the implications of changing from a technology-driven to a marketing-oriented strategy,” for example, is a better theme than “To better understand our strategic planning process.”
• Time Horizon. It is also helpful to determine an appropriate time horizon for the issue — one long enough to see the dynamics play out. For a change in corporate strategy the time horizon may span several years, while a change in advertising campaigns may be on the order of months.

Time itself should not be included as a causal agent, however. After a heavy rainfall a river level steadily rises overtime, but we would not attribute it to the passage of time. You need to identify what is actual driving the change. In computer chips, $/MIPS million instructions per second) have been decreasing in a straight line over the past decade. It would be incorrect, however, to draw a causal connection between time and $/MIPS. Instead, increasing investments and learning curve effects are likely causal forces.

• Behavior Over Time Charts. Identifying and drawing out the behavior over time of key variables is an important first step toward articulating the current understanding of the system. Drawing out future behavior means taking a risk — the risk of being wrong. The fact is, any projection of the future will be wrong, but by making it explicit, we can test our assumptions and uncover inconsistencies that may otherwise never get surfaced. For example, drawing projections of steady productivity growth while training dollars are shrinking raises the question “If training is not driving our growth, what will?” The behavior over time diagram also points out key variables that should be included in the diagram, such as Training Budget and Productivity. Your diagram should try to capture the structure that will produce the projected behavior.
• Boundary Issue. How do you know when to stop adding to your diagram? If you don’t stay focused on the issue, you may quickly find yourself overwhelmed by the number of connections possible. Remember, you are not trying to draw out the whole system – only what is critical to the theme being addressed. When in doubt about including something, ask “If I were to double or halve this variable, would it have a significant effect on the issue I am mapping?” If not, it probably can be omitted.
• Level of Aggregation. How detailed should the diagram be? Again, the level should be determined by the issue itself. The time horizon also can help determine how detailed the variables need to be. If the time horizon is on the order of weeks (fluctuations on the production line), variables that change slowly over a period of many years may be assumed to be constant(such as building new factories). As a rule of thumb, the variables should not describe specific events (a broken pump); they should represent patterns of behavior (pump breakdowns throughout the plant).
• Significant Delays. Make sure to identify which (if any) links have significant delays relative to the rest of the diagram. Delays are important because they are often the source of imbalances that accumulate in the system. It may help to visualize pressures building up in the system by viewing the delay connection as a relief valve that either opens slowly as pressure builds or opens abruptly when the pressure hits a critical value. An example of this might be a delay between long work hours and burnout: after sustained periods of working 60+ hours per week, a sudden collapse might occur in the form of burnout.
  

  TOOL BOX: GUIDELINES FOR DRAWING CAUSAL LOOP DIAGRAMS

  

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Senge, the director of the Systems Thinking and Organizational Learning Program at MIT’s Sloan School of Management, describes The Fifth Discipline as a compilation of the work of many people in the systems thinking field. It also draws on the experience of a core group of organizations — including Ford, Digital, Hanover Insurance, Herman Miller, and Analog Devices — who, under the auspices of the MIT program, have become “experimental laboratories” for developing and testing new tools and ideas.

A learning organization, explains Senge, “is an organization where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning how to learn together.” He distinguishes his definition of organizational learning from the contemporary meaning it has acquired. A learning organization is often described as one that is “fast on its feet,” and able to adapt quickly to a changing marketplace. But Senge feels that the idea of learning as adaptation is very inadequate. “Learning is really about evolving the capacity to create. It is very action-oriented.”

From Invention to Innovation

In terms of actually creating such an organization, Senge believes we are still on the road from invention to innovation. “A new idea has been invented when it is proven to work in a laboratory,” he explains. “Only when it can be replicated reliably on a meaningful scale at a practical cost can it be considered an ‘innovation.'” In these terms, the learning organization has been invented, but it has not yet been innovated.

Senge likens the development of the learning organization to the creation of the commercial airline industry. The Wright brothers proved powered flight was possible, but it took thirty years and the synthesis of five component technologies to create a viable commercial aviation industry.

In the learning organization, the “component technologies” are the five disciplines: personal mastery, mental models, building shared vision, team learning, and systems thinking. Only when these five disciplines are used together will the learning organization become an “innovation” — predictable, stable, and functional.

Learning Disabilities

The book begins by identifying several core “learning disabilities” which, Senge argues, afflict all organizations to a certain extent, not just the ones that fail. In fact, he suggests that perhaps even successful companies are underperformers, never living up to their potential. “What if,” he muses, “in light of what organizations could be, ‘excellence’ is actually ‘mediocrity?'”

“But the learning disabilities really just set the stage,” says Senge. “What I think potentially could be the enduring contribution of the book is the idea that it’s possible to build a different sort of organization, and I’ve proposed a method for doing that in the form of the five disciplines.”

The Five Disciplines

According to Senge, the indivisible unit of the learning organization is the individual. “Organizations learn only through individuals who learn. Individual learning does not guarantee organizational learning. But without it no organizational learning occurs.” Therefore, personal mastery — the discipline of personal growth and learning — is the cornerstone of the learning organization, its spiritual foundation.

“I think in many ways the discipline of personal mastery is the most radical in the book,” comments Senge. “It seems to me that the idea of what it means for an organization to be fully committed to the development of each individual’s personal mastery is still pretty far ahead of us. I also think that one of the reasons shared visions are not more common in the world is that very few corporations have any idea of the sort of commitment you have to make to the individual for this sort of vision to operate.”

Mental models, the constructions and internal pictures we use to interpret the world and take appropriate action, comprise the second discipline. Transferring the learning from the individual to the organizational level requires shared understanding of mental models, so that shared visions can evolve. Senge emphasizes that working with mental models requires the ability to carry on “learningful” conversations, where individual assumptions can be exposed and held up to scrutiny.

Shared vision emerges from personal visions. “If people don’t have their own vision, all they can do is ‘sign up’ for someone else’s.” Shared vision, Senge cautions, cannot be dictated by the head of a company or even by a “vision statement.” Instead, it emerges over time as a by-product of the interactions of individual visions.

Building on the discipline of mental models is team learning, which emphasizes that the mental models that really matter in an organization are the shared, implicit assumptions that “this is the way the world is.” Team learning consists of three critical dimensions: the need to think insightfully about complex issues; the need for innovative, coordinated action; and the continual fostering of learning through team members’ roles on other teams. Although it can be very difficult to achieve, team learning, when effective, can become a microcosm for learning throughout the organization.

Systems Thinking

Systems thinking is the “fifth discipline,” the one that fuses the others into a coherent body of theory and practice. “By enhancing each of the other disciplines, it continually reminds us that the whole can exceed the sum of its parts,” explains Senge. If we don’t understand how our actions create our current reality, there is no fundamental reason to have a personal vision and practice personal mastery. Systems thinking also strengthens mental models because it shows how to restructure assumptions to reveal the causes of significant problems and expose high-leverage solutions. Similarly, while shared vision paints a picture of what we want to create, systems thinking reveals how we have created our current reality and gives us a sense of empowerment over the future reality we strive to create.

Without a shared language for dealing with complexity, team learning is limited. Systems thinking is such a language — it provides a way for teams to begin learning about the issues that are most important for the long-term health of the company

Senge cautions that mastering a discipline is a never-ending process. “No matter how much you learn, you realize how much more there is to learn.” The same can be said about the process of creating a learning organization. “When the five component technologies converged to create the DC-3 the commercial airline industry began. But the DC-3 was not the end of the process. Rather, it was the precursor of a new industry. Similarly, as the five component learning disciplines converge they will not create the learning organization but rather a new wave of experimentation and advancement.”

The Fifth Discipline is published by Doubleday, 384 pages, $19.95 hardcover. Innovation Associates offers a substantial discount for orders of 10 or more. Contact: Innovation Associates, P.O. Box 2008, Framingham, MA 01701. Phone (508) 879-8301.

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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.

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