This integration also shows you how to build the foundation for a new kind of organization – a learning organization, where front-line people work in self-managed groups, managers develop their research skills and take on the role of theory-builders, and leaders become more like philosophers who inspire the human spirit. At the core of any learning organization lie learning systems and processes firmly rooted in the two disciplines of TQC and systems thinking. Read this volume in our “Innovations in Management Series” to see how – together – these disciplines provide a powerful method for change.

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This volume explores these questions and introduces the principles and practice of a quietly growing field: systems thinking. With roots in disciplines as varied as biology, cybernetics, and ecology, systems thinking provides a way of looking at how the world works that differs markedly from the traditional reductionistic, analytic view. Why is a systemic perspective an important complement to analytic thinking? One reason is that understanding how systems work – and how we play a role in them – lets us function more effectively and proactively within them. The more we understand systemic behavior, the more we can anticipate that behavior and work with systems (rather than being controlled by them) to shape the quality of our lives.

It’s been said that systems thinking is one of the key management competencies for the 21st century. As our world becomes ever more tightly interwoven globally and as the pace of change continues to increase, we will all need to become increasingly “system-wise.” This volume gives you the language and tools you need to start applying systems thinking principles and practices in your own organization.

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According to project manager Janet Gould, the research will address three basic questions:

• What does it mean to be competent in systems thinking?
• What skills must people acquire in order to become competent in systems thinking?
• What additional skills are necessary to become an active facilitator of systems thinking within an organization?

Much of the initial work in the project has been devoted to defining what should be included in a list of systems thinking competencies. The diagram at the right shows a proposed framework for addressing the issue. Deciding what specific skills fall under each matrix cell is a crucial aspect of the research and will re-main fluid for some time. Even the current definition of the axes is a tentative selection.

Although dialog about the course content continues, a few formats for delivery of the course have been suggested. One possibility is to conduct an intensive, five-day course which would immerse the participants in the principles of systems thinking. Such an experience, explains Tom Grimes of Hanover Insurance Company, a sponsoring company, might help participants retain the lessons from the course. “We have such a capacity to think linearly in our lives,” he explains, “that it’s going to take a major learning experience to turn it around.”

Another possible format would be to have three days of instruction followed by “refresher courses” held every few months. In between, participants would keep logs describing how systems thinking is affecting their work. The iterative process could continue for a year or more, notes Gould.

Regardless of its final format, an essential element of the course will be team learning. Groups of people from the same division of a company will be encouraged to go through the course together and to continue using the skills they have learned back in the workplace. Explains Gould, “We think the learning might last longer with this method, because the participants would be working with a group of people with whom they can continue talking about systems thinking, rather than being isolated.”

Initially, the content of the course will be modeled after two courses already available—the MIT Summer Session, a week-long introduction to systems thinking, and a five-day course designed by consultant David Kreutzer for his clients. Both courses teach participants simple feedback loops and how to build simple computer models of complex systems. A limitation of both course designs, however, is that the skills covered do not fully address all the cells of the research matrix.

Grimes hopes to address four main objectives with the course:

1) To raise awareness of the limits and some of the potential dangers of linear thinking.

2) To use systems thinking as a way of identifying the assumptions we make underlying our decisions.

3) To develop a common language for talking about systemic issues.

4) To critique and expand our view of reality without getting into issues of personality or emotionality.

A prototype course should be ready in a few months. At that point, the researchers will begin to implement it in four or five participating companies. But Gould emphasizes that the course design is only part of the research project. “We also need to know from a research standpoint whether this course is going to do anything for a company. Are people actually learning what we’re expecting?”

…an essential element of the course will be team learning.

In order to evaluate the course, participants will answer questionnaires that test how well they have assimilated key concepts. Not only will their answers help the researchers gauge the success of the course, but Gould notes that the participants will also be able to track their own progress.

Internal facilitators will also play a crucial role in implementing systems thinking in a company. “Essentially you need to build up internal expertise in systems thinking,” explains Dan Simpson, Director of Planning at The Clorox Company. “Without that internal expertise, it’s unlikely any new thinking mentality will infiltrate the organization very well.” Simpson adds that a separate, more intensive course may be necessary to train the facilitators who will continue the systems thinking learning process inside their companies. “These people will continually make the translation from what is an academic field of study into operational action inside an organization.”

Despite the questions on how well the course might implement systems thinking in companies, there is no doubt among the course planners that systems thinking is a valuable tool for organizations. As Simpson describes it, “Systems thinking helps practicing managers begin to think through the ‘ripple effects’ of their decisions. It’s often not clear when you make a decision as a practicing manager in one area that there are interactions with other areas, intended or not. Systems thinking offers a way to control—or at least consciously manage—the ripple effect, as opposed to just letting things happen.”

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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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One of the reasons for this wide-spread institutional failure is that the knowledge-creating system, the method by which human beings collectively learn and by which society’s institutions improve and revitalize themselves, is deeply fragmented. This fragmentation has developed so gradually that few of us have noticed it; we take the disconnections between the branches of knowledge and between knowledge and practice as a given

A Knowledge-Creating System

Before we can address the issue of fragmentation, we need to establish what has been fragmented. In other words, what do we mean by a knowledge-creating system, and what does it mean to say it is fragmented?

THE CYCLE OF KNOWLEDGE-CREATION

Like theories, the tree’s roots are invisible, and yet the health of the root system determines the health of the tree. The branches are the methods and tools, which enable translation of theories into new capabilities and practical results. The fruit is that practical knowledge. The tree as a whole is a system.

We believe that human communities have always attempted to organize themselves to maximize the production, transmittal, and application of knowledge. In these activities, different individuals fulfill different roles, with varying degrees of success. For example, in indigenous cultures, elders articulate timeless principles grounded in their experience to guide their tribes’ future actions. “Doers, “whether warriors, growers, hunters, or nannies, try to learn how to do things better than before and continually improve their craft. And coaches and teachers help people develop their capacities to both perform their roles and grow as human beings. These three activities-which we can term theory-building, practice, and capacity-building-are intertwined and woven into the fabric of the community in a seamless process that restores and advances the knowledge of the tribe. One could argue that this interdependent knowledge-creating system is the only way that human beings collectively learn, generate new knowledge, and change their world.

We can view this system for producing knowledge as a cycle. People apply available knowledge to accomplish their goals. This practical application in turn provides experiential data from which new theories can be formulated to guide future action. New theories and principles then lead to new methods and tools that translate theory into practical know-how, the pursuit of new goals, and new experience-and the cycle continues.

Imagine that this cycle of knowledge-creation is a tree (see “The Cycle of Knowledge-Creation” on p.1). The tree’s roots are the theories. Like theories, the roots are invisible to most of the world, and yet the health of the root system to a large extent determines the health of the tree. The branches are the methods and tools, which enable translation of theories into new capabilities and practical results. The fruit is that practical knowledge. In a way, the whole system seems designed to produce the fruit. But, if you harvest and eat all the fruit from the tree, eventually there will be no more trees. So, some of the fruit must be used to provide the seeds for more trees. The tree as a whole is a system.

The tree is a wonderful metaphor, because it functions through a profound, amazing transformational process called photosynthesis. The roots absorb nutrients from the soil. Eventually, the nutrients flow through the trunk and into the branches and leaves. In the leaves, the nutrients interact with sunlight to create complex carbohydrates, which serve as the basis for development of the fruit.

So, what are the metaphorical equivalents that allow us to create fruits of practical knowledge in our organizations? We can view research activities as expanding the root system to build better and richer theories. Capacity-building activities extend the branches by translating the theories into usable methods and tools. The use of these methods and tools enhances people’s capabilities. The art of practice in a particular line of work transforms the theories, methods, and tools into usable knowledge as people apply their capabilities to practical tasks, much as the process of photosynthesis converts the nutrients into leaves, flowers, and fruit. In our society,

• Research represents any disciplined approach to discovery and understanding with a commitment to share what’s being learned. We’re not referring to white-coated scientists performing laboratory experiments; we mean research in the same way that a child asks, “What’s going on here?” By pursuing such questions, research-whether performed by academics or thoughtful managers or consultants reflecting on their experiences-continually generates new theories about how our world works.
• Practice is anything that a group of people does to produce a result. It’s the application of energy, tools, and effort to achieve something practical. An example is a product development team that wants to build a better product more quickly at a lower cost. By directly applying the available theory, tools, and methods in our work, we generate practical knowledge
• Capacity-building links research and practice. It is equally committed to discovery and understanding and to practical know-how and results. Every learning community includes coaches, mentors, and teachers – people who help others build skills and capabilities through developing new methods and tools that help make theories practical.

“The Stocks and Flows of Knowledge-Creation” shows how the various elements are linked together in a knowledge-creating system.

THE STOCKS AND FLOWS OF KNOWLEDGE-CREATION

Research activities build better and richer theories. Capacity-building functions translate the theories into usable methods and tools. The use of these methods and tools enhances people’s capabilities. The art of practice transforms the theories, methods, and tools into practical knowledge, as people apply their capabilities to practical tasks.

Institutionalized Fragmentation

If knowledge is best created by this type of integrated system, how did our current systems and institutions become so fragmented? To answer that question, we need to look at how research, practice, and capacity-building are institutionalized in our culture (see “The Fragmentation of Institutions”).

For example, what institution do we most associate with research Universities? What does the world of practice encompass? Corporations, schools, hospitals, and nonprofits. And what institution do we most associate with capacity-building-people helping people in the practical world? Consulting, or the HR function within an organization. Each of these institutions has made that particular activity its defining core. And, because research, practice, and capacity-building each operate within the walls of separate institutions, it is easy for the people within these institutions to feel cut off from each other, leading to suspicion, stereo typing, and an “us” versus “them” mindset.

This isolation leads to severe communication breakdown. For example, many people have argued that the academic community has evolved into a private club. Nobody understands what’s going on but the club members. They talk in ways that only members can understand. And the members only let in others like themselves.

Consulting institutions have also undermined the knowledge-creating process, by making knowledge proprietary, and by not sharing what they’ve learned. Many senior consultants have an incredible amount of knowledge about organizational change, yet they have almost no incentive to share it, except at market prices.

Finally, corporations have contributed to the fragmentation by their bottom-line orientation, which places the greatest value on those things that produce immediate, practical results. They have little patience for investing in research that may have payoffs over the long term or where payoffs cannot be specifically quantified.

Technical Rationality: One Root of Fragmentation

How did we reach this state of fragmentation? Over hundreds of years, we have developed a notion that knowledge is the province of the expert, the researcher, the academic. Often, the very term science is used to connote this kind of knowledge, as if the words that come out of the mouths of scientists are somehow inherently more truthful than everyone else’s words.

Donald Schon has called this concept of knowledge “technical rationality.” First you develop the theory, then you apply it. Or, first the experts come in and figure out what’s wrong, and then you use their advice to fix the problem. Of course, although the advice may be brilliant, sometimes we just can’t figure out how to implement it.

But maybe the problem isn’t in the advice. Maybe it’s in the basic assumption that this method is how learning or knowledge-creation actually works. Maybe the problem is really in this very way of thinking: that first you must get “the answer,” then you must apply it.

THE FRAGMENTATION OF INSTITUTIONS

Because research, practice, and capacity-building each operate within the walls of separate institutions, the people within these institutions feel cut off from each other, leading to suspicion, stereotyping, and an “us” versus “them” mindset.

The implicit notion of technical rationality often leads to conflict between executives and the front-line people in organizations. Executives often operate by the notion of technical rationality: In Western culture, being a boss means having all the answers. However, front-line people know much more than they can ever say about their jobs and about the organization. They actually have the capability to do something, not just talk about something. Technical rationality is great if all you ever have to do is talk.

Organizing for Learning

If we let go of this notion of technical rationality, we can then start asking more valuable questions, such as:

• How does real learning occur?
• How do new capabilities develop?
• How do learning communities that interconnect theory and practice, concept and capability come into being?
• How do they sustain themselves and grow?
• What forces can destroy them, undermine them, or cause them to wither?

Clearly, we need a theory, method, and set of tools for organizing the learning efforts of groups of people.

Real learning is often far more complex and more interesting than the theory of technical rationality suggests. We often develop significant new capabilities with only an incomplete idea of how we do what we do. As in skiing or learning to ride a bicycle, we “do it” before we really understand the actual concept. Similarly, practical know how often precedes new principles and general methods in organizational learning. Yet, this pattern of learning can also be problematic.

For example, teams within a large institution can produce significant innovations, but this new knowledge often fails to spread. Modest improvements may spread quickly, but real breakthroughs are difficult to diffuse. Brilliant innovations won’t spread if there is no way for them to spread; in other words, if there is no way for an organization to extract the general lessons from such innovations and develop new methods and tools for sharing those lessons. The problem is that wide diffusion of learning requires the same commitment to research and capacity-building as it does to practical results. Yet few businesses foster such commitment. Put differently, organizational learning requires a community that enhances research, capacity-building, and practice (see “Society for Organizational Learning” on p. 4)

Learning Communities

We believe that the absence of effective learning communities limits our ability to learn from each other, from what goes on within the organization, and from our most clearly demonstrated breakthroughs. Imagine a learning community as a group of people that bridges the worlds of research, practice, and capacity-building to produce the kind of knowledge that has the power to transform the way we operate, not merely make incremental improvements. If we are interested in innovation and in the vitality of large institutions, then we are interested in creating learning communities that integrate knowledge instead of fragment it.

In a learning community, people view each of the three functions-research, capacity-building, practice-as vital to the whole (see “A Learning Community”). Practice is crucial because it produces tangible results that show that the community has learned something. Capacity-building is important because it makes improvement possible. Research is also key because it provides a way to share learning with people in other parts of the organization and with future generations within the organization. In a learning community, people assume responsibility for the knowledge creating process.

Learning Communities in Action

To commit to this knowledge-creating process, we must first understand what a learning community looks like in action in our organizations. Imagine a typical change initiative in an organization; for example, a product development team trying a new approach to the way they handle engineering changes. Traditionally, such a team would be primarily interested in improving the results on their own projects. Team members probably wouldn’t pay as much attention to deepening their understanding of why a new approach works better, or to creating new methods and tools for others to use. Nor would they necessarily attempt to share their learnings as widely as possible – they might well see disseminating the information as someone else’s responsibility.

In a learning community, however, from the outset, the team conceives of the initiative as a way to maximize learning for itself as well as for other teams in the organization. Those involved in the research process are integral members of the team, not outsiders who poke at the system from a disconnected and fragmented perspective. The knowledge creating process functions in real time within the organization, in a seamless cycle of practice, research, and capacity-building.

Imagine if this were the way in which we approached learning and change in all of our major institutions. What impact might this approach have on the health of any of our institutions, and on society as a whole? Given the problems we face within our organizations and within the larger culture, do we have any choice but to seek new ways to work together to face the challenges of the future? We believe the time has come or us to begin the journey back from fragmentation to wholeness and integration. The time has come for true learning communities to emerge.

Peter M. Senge, best-selling author of The Fifth Discipline: The Art and Practice of the Learning Organization, is an international leader in the area of creating learning organizations. He is a senior lecturer in the Organizational Learning and Change Group at MIT. Peter has lectured throughout the world and written extensively on systems thinking, institutional learning, and leadership.

Daniel H. Kim is a co-founder of Pegasus Communications, Inc., and publisher of The Systems Thinker. He is a prolific author as well as an international public speaker, facilitator, and teacher of systems thinking and organizational learning

Editorial support for this article was provided by Janice Molloy and Lauren Johnson

A LEARNING COMMUNITY

In a learning community, people view each of the three functions—research, capacity-building,practice—as vital to the whole

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