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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Learning infrastructures create a process through which the assumptions of an organization are continually surfaced, challenged, and (if necessary) changed. Such structures are places in which corporate sacred cows are subject to scrutiny rather than accepted as truth, and where multiple future scenarios are developed and explored rather than focusing on a single” plan.

Parallel Learning Process

The O-A-D-I (Observe-Assess-Design-Implement) learning cycle links the practice and performance fields together in a continuous process of theory building and experimentation.

For most organizations, such learning infrastructures do not exist. Yet they may be the single most important factor for creating sustained competitive advantage because they can provide an organization with the ability to continuously learn about itself. Learning infrastructures provide the means for an organization to develop its own theory (or set of principles) of how it works in a way that is comprehensible and actionable to its members.

An Infrastructure for Working “on” the System

Building infrastructures for learning requires a parallel process that takes us out of the day-to-day pressures into a different kind of space in which we can practice and learn. With learning infrastructures, we are able to step out of the system so that we can work “on” it and not just “in” it. There is an ongoing learning cycle that creates a bridge between the performance field (working in the system) and practice fields (working on the system) (see “Parallel Learning Process” for example of this learning cycle applied to product development process). The learning cycle of Observe-Assess-Design-Implement (O-A-D-I) links the two processes together: “Assess” and “Design” are more emphasized in the practice field and “Implement” and “Observe” are more emphasized in the performance field.

Perhaps the most important link in the learning cycle lies in the “Observe-Assess” step, because our designs can only be as good as the assessments on which they are based. In turn, if our assessments are not grounded in actual observations, but in previously-held assessments, then we are on shaky ground. The 0-A-D-I learning cycle thus helps us continually reflect on what we think we know and how we know it — in essence, to challenge our prevailing mental models.

This parallel process can be likened to a manager’s equivalent of a practice field, which enhances his or her ability to perform online by creating an environment that is safe for experimentation and failures. Like a sports team, the practice field provides the tools and the appropriate arena for trying out new “plays” or strategies that may be a radical departure from standard procedure.

A management flight simulator, for example, can be most useful for understanding situations in which causality is distant in time and space, or when the inherent time lag is particularly long (on the order of months or years) and organizational complexity is high (see “Management Flight Simulators: Flight Training for Managers,” Parts I and II, Nov. 1992 and Dec. 1992/Jan. 1993). Management flight simulators are one of many tools that can be used in a practice field. Causal loop diagrams, systems archetypes, action maps, dialogue, and the Ladder of Inference are among the many other tools and frameworks that can also be utilized to enhance learning.

Creating learning infrastructures such as practice fields or learning laboratories is an important part of becoming a learning organization, but alone it is inadequate. It is too easy for such structures to become “training” infrastructures. There is nothing wrong with training per se. But training involves teaching a new twist on a well-established body of knowledge or disseminating that body of knowledge itself. Learning, on the other hand, requires a shift in the understanding of the base of knowledge itself. It is the difference between acquiring new information that fits into a current theory and developing a new theory. Learning infrastructures should help organizations build their own ongoing theories about how they work as a system.

Theory-Building Process

Because individuals are continually learning in organizations, one can argue that organizations are very supportive of learning. In most cases, however, the learning is done at an individual, not organizational, level. Oftentimes, there is no coherent process for integrating the learnings of many individuals into a form that can benefit the whole organization. In short, there is no theory-building process.

The word theory is too often viewed as an esoteric word that has no practical meaning. In fact, theory is of utmost practical importance because theories are distillations of our knowledge and understanding of the world. Theories represent the general principles drawn from a body of facts and observations. Without them, we could not learn because we would have no means to provide a coherent structure to our observations.

Given today’s pace of change and organizational complexity, managers need to be competent in applying the research skills of a scientist to better develop theories about how their organizations work as a system. The old paradigm of feeding experiments from organizations into research institutions that then feed the results back is no longer adequate.

In Beyond the Stable State, Donald Schon points out that a major disruption in this paradigm occurred when the pace of change crossed into the intra-generational state — when lessons learned became obsolete within the same generation. Given this pact of change, the research cycle must be compressed, otherwise solutions (in the form of research results) will be stillborn — the problems that they addressed will no longer be relevant.

Managers’ New Roles: Researcher and Theory-Builder

In order to keep pace with intra-generational change, managers need to become theory-builders within their own organizations. It is no longer sufficient to apply generic theories and frame-works like Band-Aids to one’s own specific issues. As theory-builders, managers must have an intimate knowledge of how their organization works as a whole — but they also require some guiding theory and methodology to make sense of their experience and learning.

There is no “golden formula” that will hold for all time. Companies that lived by the learning curve theory almost died by it (as in the case of Texas Instruments and the personal computer debacle). Others who followed the BCG business portfolio theory also had their share of problems. Theory building should therefore not be done as an academic exercise but as a process grounded in reality that continually helps provide a framework for interpreting one’s competitive environment.

Theory-Building loops

There are several projects being conducted at the MIT Organizational Learning Center which attempt to design and embed a theory-building process within an organization. By conducting parallel “experiments” at multiple company sites, we hope to accumulate learnings across organizations that will allow each individual organization to accelerate its own learning. We are trying to integrate a variety of research methods that build theory at various levels (see “Organizational Theory-Building Cycle”). Although a lot of the Learning Center work lies in the (virtual) world of ideas, model formulation, and design of flight simulators and learning labs, an important aspect of the Learning Center’s theory-building process is its close integration with active experimentation in several company sites.

The Learning Center research efforts can be viewed in terms of four interrelated learning loops which guide all projects — grounded theory building, dynamic theory building, behavioral decision theory building, and managerial practice field theory building:

Grounded Theory Building (Loop L1): This loop represents the field research tradition of building theory based on observable data. It is rooted in direct observations, but instead of bringing pre-formulated frameworks that are then applied to the data, we try to hear what the facts themselves have to say.

Grounded theory building is an inductive process of suspending prior assumptions in order to view observable data through fresh eyes. Action science, clinical research, and ethnography are probably the most relevant research approaches. Mapping tools such as systems archetypes, causal loop diagrams, and action maps can play an important role in building grounded theory.

Dynamic Theory Building (Loop L2): Static models can provide illuminating frameworks to better understand our observations (e.g., supply and demand curves of economics), but they don’t provide an opportunity to explore the rich set of dynamics that are possible over time. In dynamic theory building, we are interested in understanding how our grounded theories play out over time. This loop includes the traditional system dynamics model-building process of data collection, model formulation, testing, revising, and validation. It includes some of the work represented by loop L1, but builds on it in a more rigorous fashion.

Behavioral Decision Theory Building (Loop L3): People do not always behave rationally or in their best interests, especially in complex dynamic environments where causality is separated in space and time. This theory loop attempts to understand why people make the decisions they do in order to improve their decision making in the future. MIT Professor John Sterman’s work on dynamic decision making is a good representation of behavioral decision theory studies. Using interactive computer simulators to study how managers make decisions in a laboratory setting is one part of the work; linking the impact of those studies to actions in the workplace is another.

Managerial Practice Field Theory Building (Loop L4): Creating meaningful practice fields for managers requires an understanding of what makes a practice field “real” enough to be taken seriously and yet “playful” enough to provide a learning environment.

Experiments can be conducted in the practice field that would not be possible in the actual work environment, and successive rounds of experiments can help an organization begin to develop its own organizational theory.

All four learning loops are important to organizational theory building. In the short term, no single project is likely to adequately address all four loops at once. But over time, the collection of various projects across many companies will help us build a rich set of theories about how organizations learn at multiple levels. The hope is that as more organizations engage in theory building, it will become such an embedded part of doing business that the alternation between practice and performance will be a seamless process of integrated learning.

Organizational Theory-Building Cycle

The four theory-budding loops integrate a variety of research methods to build theory at various levels.

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A Starting Point for Theory-Building

Quality pioneer Dr. Edwards Deming once said, “No theory, no learning.” In order to make sense of our experience of the world, we must be able to relate that experience to some coherent explanatory story. Without a working theory, we have no means to integrate our differing experiences into a common picture. In the absence of full knowledge about a system, we must create a theory about what we don’t know, based on what we currently do know.

Each systems archetype embodies a particular theory about dynamic behavior that can serve as a starting point for selecting and formulating raw data into a coherent set of interrelationships. Once those relationships are made explicit and precise, the “theory” of the archetype can then further guide us in our data-gathering process to test the causal relationships through direct observation, data analysis, or group deliberation.

Each systems archetype also offers prescriptions for effective action. When we recognize a specific archetype at work, we can use the theory of that archetype to begin exploring that particular system or problem and work toward an intervention.

For example, if we are looking at a potential “Limits to Success” situation, the theory of that archetype suggests eliminating the potential balancing processes that are constraining growth, rather than pushing harder on the growth processes. Similarly, the “Shifting the Burden” theory warns against the possibility of a short-term fix becoming entrenched as an addictive pattern (see “Archetypes as Dynamic Theories” on pp. 9–10 for a list of each archetype and its corresponding theory).

Systems archetypes thus provide a good starting theory from which we can develop further insights into the nature of a particular system. The diagram that results from working with an archetype should not be viewed as the “truth,” however, but rather a good working model of what we know at any point in time. As an illustration, let’s look at how the “Success to the Successful” archetype can be used to create a working theory of an issue of technology transfer.

, “Success to the Successful” Example

An information systems (IS) group inside a large organization was having problems introducing a new email system to enhance company communications. Although the new system was much more efficient and reliable, very few people in the company were willing to switch from their existing email systems. The situation sounded like a “Success to the Successful” structure, so the group chose that archetype as its starting point.

'SUCCESS TO SUCCESSFUL' EMAIL

Starting with the “Success to the Successful” storyline (top), the IS team created a core dynamic theory linking the success of the old email systems with the success of the new system (middle). They then identified structural interventions they could make to use the success of the old systems to fuel the acceptance of the new one (loops B5 and B6, bottom).

The theory of this archetype (see “‘Success to the Successful’ Email” on p. 8) is that if one person, group, or idea (, “A”) is given more attention, resources, time, or practice than an alternative (, “B”), A will have a higher likelihood of succeeding than B (assuming that the two are more or less equal). The reason is that the initial success of A justifies devoting more of whatever is needed to keep A successful, usually at the expense of B (loop R1). As B gets fewer resources, B’s success continues to diminish, which further justifies allocating more resources to A (loop R2). The predicted outcome of this structure is that A will succeed and B will most likely fail.

When the IS team members mapped out their issue into this archetype, their experience corroborated the relationships identified in the loops (see “Core Dynamic Theory”). The archetype helped paint a common picture of the larger “elephant” that the group was dealing with, and clearly stated the problem: given that the existing email systems had such a head start in this structure, the attempts to convince people to use the new system were likely to fail.

Furthermore, the more time that passed, the harder it would be to ever shift from the existing systems to the new one.

Using the “Core Dynamic Theory” diagram as a common starting point, group members then explored how to use the success of the existing system to somehow drive the success of the new one (see “Extended Dynamic Theory”). They hypothesized that creating a link between “Usefulness of Existing Email” and “Usefulness of New Email” (loop B5) and/or a link between “Use of Existing Email” and “Usefulness of New Email” (loop B6) could create counterbalancing forces that would fuel the success loop of the new system. Their challenge thus became to find ways in which the current system could be used to help people appreciate the utility of the new system, rather than just trying to change their perceptions by pointing out the limitations of the existing system.

Managers As Researchers and Theory Builders

Total Quality tools such as statistical process control, Pareto charts, and check sheets enable frontline workers to become much more systematic in their problem solving and learning. With these tools, they become researchers and theory builders of their own production process, gaining insight into how the current systems work.

Similarly, systems archetypes can enable managers to become theory builders of the policy- and decision-making processes in their organizations, exploring why the systems behave the way they do. As the IS story illustrates, these archetypes can be used to create rich frameworks for continually testing strategies, policies, and decisions that then inform managers of improvements in the organization. Rather than simply applying generic theories and frameworks like Band-Aids on a company’s own specific issues, managers must take the best of the new ideas available and then build a workable theory for their own organization. Through an ongoing process of theory building, managers can develop an intuitive knowledge of why their organizations work the way they do, leading to more effective, coordinated action.

ARCHETYPES AS DYNAMIC THEORIES

Limits to success dynamic theory

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