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”

The post The “Thinking” in Systems Thinking: How Can We Make It Easier to Master? appeared first on The Systems Thinker.

At Boeing, a major aerospace company, a team leader and his R&D group recently found themselves in uncharted territory as they faced a new project. They needed to create a leadership infrastructure to bridge the learning that happens in the workplace with more structured classroom learning. The framework would span multiple organizations, missions, locations, and personnel. The temptation to leap into action was hard to resist. But the project team realized that taking the time to develop an implementation strategy would help them to be more effective in the long run. In order to do so in a systematic way, they chose to develop an Operational Strategy Map to guide their efforts.

The Operational Mapping Methodology

Developing a map of strategy isn’t a new idea. Most organizational improvement methodologies (such as total quality management, reengineering, and the balanced scorecard) recommend some form of mapping in order to facilitate understanding of an organization and its processes. All mapping methodologies have benefits as well as limitations. Because maps are necessarily a representation of reality — and not the reality itself — it’s important to choose a framework that captures the essence of the system in a way that helps the organization most effectively navigate through the unfolding strategy.

The Operational Strategy Mapping (OSM) framework synthesizes elements from three disciplines — system dynamics, skilled facilitation, and balanced scorecard—to create a process and product that can enhance the creation and implementation of organizational change efforts (see “Operational Strategy Mapping”). Using OSM, a strategic planning and implementation team clearly articulates what the strategy should accomplish, how it works, and what unintended consequences might result. In the process of developing the map, team members generate understanding of, and commitment to, the overall plan.

System Dynamics. OSM uses system dynamics mapping and its underlying paradigm of the world. System dynamics incorporates two different visual languages: causal loop diagrams and stock and flow maps. In order to quickly get up to speed on the terminology and launch into the mapping process, groups may begin with causal loop diagrams. Causal loops can be extremely useful for eliciting important interdependencies that will impact and be impacted by the strategy.

Because OSM requires exploring questions such as “How does/will it work?” the strategy team will eventually need to build stock and flow maps to generate this “operational” focus. Although doing so may initially require a little more effort than creating causal loops, the value derived from this additional effort of differentiating between conditions and activities that change those conditions will dramatically increase the rigor and quality of any strategy discussions. Using stock and flow maps, groups can look at the factors inherent in the strategy that may contribute to unintended consequences during implementation.

OPERATIONAL STRATEGY MAPPING

The Operational Strategy Mapping (OSM) framework synthesizes elements from three disciplines — system dynamics, skilled facilitation, and balanced scorecard—to create a process and product that can enhance the creation and implementation of organizational change efforts.

The paradigm of system dynamics asks us to move from thinking about our organizations in terms of one-time events and isolated functions to considering them in terms of continuous, dynamic, integrated processes. To implement OSM, a team needs to look at the strategy as something that will unfold over time, with natural ebbs and flows, and will likely require adjusting in terms of the magnitude and timing of different elements. The system dynamics approach also suggests the need to identify forces that might slow or impede implementation. It offers guidance in predicting natural delays in the system; knowing about these delays is vital to generating an effective implementation plan.

Skilled Facilitation. Skilled facilitation, based on the work of Roger Schwarz, provides the framework for the process of building OSMs. It offers tools for assessing if the appropriate stakeholders are involved, how effective the group dynamics are, and how to facilitate conversations around building and testing the usefulness of the map. Because skilled facilitation applies an explicit approach to developing shared mental models (both about the content of the project and the group’s process), it is a natural fit with the system dynamics approach to mapping.

The Balanced Scorecard. The third discipline built into the OSM methodology, Kaplan and Norton’s Balanced Scorecard (BSC), has become popular for helping businesses and public-policy organizations build and revise visual strategic “bubble maps” as part of an ongoing, iterative learning process. The BSC’s four quadrant perspective — Financial, Customer, Internal Processes, and Learning — provides a useful guide for ensuring that the strategy map covers the organization’s different facets. (Although not all OSMs cover the four quadrants, groups should be conscious about choosing to eliminate one or more quadrants from the map.) However, the stock and flow language is better able to depict how processes work than “bubble maps” and can serve as the basis for computer simulation at a point in the future if the team finds this additional step helpful.

The steps for building an OSM are the same as those described for the BSC. In their book, The Strategy Focused Organization (Harvard Business School Press, 2000), Kaplan and Norton describe strategy management as following four principles:

1. Translate the Strategy to Operational Terms
2. Align the Organization to the Strategy
3. Make Strategy Everyone’s Everyday Job
4. Make Strategy a Continual Process

As you’ll see, the distributed learning team at The Boeing Company followed these steps as they developed and used an OSM.

Building an OSM at Boeing

The Boeing Company is an organization widely distributed across geographies, business segments, and product lines; it also includes several engineering disciplines. The decision to sponsor a leadership initiative in the company reflected an understanding that, although the culture focused primarily on formal learning events, more than 80 percent of learning and leadership development occurred on the job. The “Workplace Leadership Initiative” would integrate formal and informal learning and would support participants in pursuing their individual learning agendas on their own time. In turn, employees would contribute their own content/expertise through a personalized web site and a community space that would be integrated into the leadership program’s learning experience. Putting together the various pieces of the program was a challenging opportunity. The development team decided to create an Operational Strategy Map to help them “mentally simulate” how they might execute the initiative.

Translating the Strategy to Operational Terms. The first phase of developing the OSM was to get background information on the project and develop a “strawman” map of the strategy. Getting background information usually requires phone interviews with a few stakeholders/experts. This interviewing process serves two purposes: (1) Gathering information from throughout the system of interest, and

(2) Generating understanding and commitment from the stakeholders for the process and subsequent map.

For this project, the team leader possessed the knowledge to provide enough input for the initial map.

The team leader was concerned about the following areas of execution: creating the initial workplace leadership system, generating enthusiasm among potential users, and building support among senior managers (who might not be users, but who would likely encourage or discourage the use of the system among their staff). He had several hypotheses about how the system might work, but felt that the OSM process would force him to better articulate those assumptions, integrate the team’s assumptions more effectively, test the accuracy of the combined assumptions, and ultimately communicate them to management.

Based on initial conversations, the group chose to focus the core structure of the map on the system’s end users. In this case, the core structure (often referred to as the spinal cord or main chain of the model) assumes that users can move from being Unaware of the WL (abbreviation for “Workplace Leadership System”) to being Aware of and May Use WL. (See the section labeled “Core Structure” in the diagram “A Virtuous Cycle” on p. 4.) After experiencing the Workplace Leadership System, they might become an Advocate for WL — or they might become Resistant to WL.

The stocks and flows visually represent the movement of people from one state to another. The stocks (boxes) are the accumulation of people (how many in each state at any point in time), and the flows (circles) are the processes that advance people through the various stocks. The initiative would need to carefully manage the movement from Unaware to Aware and then ensure Advocates were generated while simultaneously limiting the flow into Resistant to WL. The team spent hours further defining attributes associated with the stocks: What type of person was in each stock? Is there a better name for the stock? Is there anything missing in the main chain?

After focusing on the stocks, the team was ready to begin thinking through strategic implications by analyzing what might drive each of the flows. They quickly realized that they couldn’t directly affect the stocks — they needed to design policies directed toward the processes that move people from one state to another. The group determined that they could have a direct impact on awareness by having focus groups and other public relations-type events. People would move into the Advocates stock through word-of-mouth; their experience with the WL system would influence the level of Advocates and Resistant folks, because the more positive the experience, the faster the rate of acquiring new Advocates.

As always happens, the team identified weaknesses in the draft map’s assumptions. Foremost among these was the map’s aggregation of the learning initiative’s attributes into a single stock. The team suggested three categories of attributes: Useful Content, Features, and Ease of Use. The discussion around the development of these features was heated. Through it, the team found an appreciation for the level of precision that OSMs bring to what’s often a fuzzy process.

As a result of the conversations to improve the assumptions in the map, the team identified a virtuous cycle they wanted to set in motion. An important element of the Workplace Leadership System is users’ ability to add their own content, wisdom, and expertise—and Advocates would likely contribute the most. The greater the content that the program has to offer, the greater participants’ overall satisfaction will be (the team called this the “Wow!” effect). High levels of satisfaction in turn create more Advocates. A nice loop to get going! The team realized, however, that a limit to growth for this loop would be the ease of use. If it’s not easy to add content, then Advocates probably will not do so, making it difficult to set the cycle into motion.

The team found that the mapping process surfaced a dark side of implementation that they hadn’t consciously discussed before: the buildup of folks resistant to the initiative. At first, the group was dismayed to think about the potential for Resisters to develop in

A VIRTUOUS CYCLE

An important element of the Workplace Leadership System is users’ ability to add their own content, wisdom, and expertise. The greater the content that the program has to offer, the greater participants’ overall satisfaction will be. High levels of satisfaction in turn will create more Advocates.

the organization. But after some discussion, they realized that because they now knew the possibility existed, they could look out for it.

Further, they decided that if budding Resisters were identified early enough and were listened to, two things would happen. First, they would likely have feedback that would improve the overall system. More importantly, they might move over into the stock of Advocates. The team believed that people who cared enough to be Resisters could become strong Advocates — the energy would just be directed differently. The team referred to this as an aikido approach to resistance: Rather than push directly back against critical feedback (the natural tendency of a design team), they would redirect the energy behind the criticism — and apply it to improving the product. The team also strongly believed that the process of listening would generate Advocates.

The group developed a large wall hanging with crisp high-resolution graphics. Over the course of a couple of weeks, they used the map in their meetings and presented it to managers and other stakeholder groups within Boeing. In discussions and presentations, team members were able to walk up to the map, point directly at the area of strategy they were describing, and quickly get everyone’s reactions.

As a result of these meetings, the map was modified slightly — yet the core structure remained the same. The team found they could present the map without the aid of the project consultant. In that sense, they owned the map, its assumptions, and the implications it had for their strategy — it provided a common framework that guided their discussions.

Aligning the Organization to the Strategy. The second step in the process is to align the organization to the strategy. The team did so by using the map to develop a team project plan. They focused on the flows in the map and assigned tasks to different individuals. Although the group could have used sophisticated project planning software, for this effort they imported snapshots of map segments into Excel worksheets and added roles and responsibilities (see “The Project Plan”).

Results from the Initiative

The project is still underway, but the team has already reaped several benefits from developing the OSM. The most significant impact is that the team focused their early effort on a seven-day process to set in motion a virtuous cycle around the project. The goal of this experiment was to learn as quickly as possible about potential Advocates and Resisters. The team tested the initiative’s ease of use, features, and useful content in order to assess the “Wow!” factor, identify the number of individuals in various categories, and analyze the quality of their experience in moving to being an Advocate or a Resister.

As a result of this exploration, the team reconceptualized the project’s web interface. If they hadn’t learned from this experiment with setting a virtuous cycle in motion, they might have wasted a large portion of their 2005 budget in trying to implement a system without thoughtful consideration of Advocates and Resisters.

The team was pleased to find that the map was still valid even after the shift in emphasis. This process confirmed that the level of aggregation was sufficiently useful, that is, it allowed them to examine the implications of their implementation strategy at a high level, without becoming so specific that they needed to modify the map every time they made minor modifications to the actual program.

Making Strategy Everyone’s Everyday Job. Another result of the OSM process was that the team developed a shared language. This terminology improved the quality of conversations, because it made implicit assumptions about the strategy explicit. It created an environment for making

THE PROJECT PLAN

The team developed a project plan by focusing on the flows in the map and assigning tasks to different individuals. They imported snapshots of map segments into Excel worksheets and added roles and responsibilities.

strategy everyone’s everyday job. When people pointed to a piece of the map to describe the impact of a certain proposal, everyone understood what they were referring to. Having a shared language also had the unintended benefit of increasing camaraderie.

In most cases of strategy development, management knows the underlying assumptions, but the implementation team is left in the dark. The OSM process integrates assumptions from the entire team. The group as a whole owns the strategy, the implementation, and of course, the results. Talk about empowerment!

Another benefit of the process was that the team found it easier to be brutally honest during implementation. For example, as word of the Workplace Leadership Initiative spread during the development of the map, the team not only heard from folks with a favorable impression of the project but also from those with an unfavorable view. In other circumstances, the group might have filtered out the negative input. But because the map suggested that they pay attention to potential resisters, and that by doing so they could generate a positive trend, the team accepted the early criticism and incorporated some of the constructive comments in their implementation plan.

Making Strategy a Continual Process. As part of continual learning, the Boeing team may choose to go into more detail in some areas of the map. They are exploring the potential benefits of developing simulation models of certain aspects. Further, the group may build additional maps or revise the current one. Even so, they will continue to use the OSM they’ve developed in building and implementing strategy for months to come.

Using the Methodology in Your Organization

If you’d like to use an Operational Strategy Map to help guide your strategic planning and implementation, here are a few things we’ve learned:

• You won’t get the map perfect the first time. The process of building the map is where the learning is. Create a prototype (what we’ve called the “strawman map”) as quickly as you can. Then let the strategy development team critique, modify, and ultimately own it. The process of their owning it will make it better. Trust us!
• Identify as quickly as possible the “main chain” of the map. Use the main chain to ask questions about how the system in question works and what might be some unintended consequences of any activities.
• Focus on analyzing the major dynamics in the map. In the case described here, the team focused on the major virtuous cycle for a week. They asked questions about it, tested its usefulness and likelihood of occurrence — and in the end, they developed a whole new approach to the overall project.
• Fit the map on one page if you can. The Boeing team struggled on occasion as it tried to add nuances to the map that added complexity. The understanding generated from these incremental add-ons was usually minimal. You can always create separate maps of more detailed processes at a later date.
• Once the strawman map has been developed, modify it only in the presence of the whole team. Otherwise, you will not have the buy in needed to implement any new insights. Plus, you’ll likely miss something important when making the change.
• Develop simulation models only to the point where doing so provides an adequate return for the time and money invested. The process of simulation modeling is often a laborious one; it may take months to develop a reasonably sophisticated computer model of the strategy. The siren call of “We’ll find the answer” often tempts teams to try to develop the Mother of All Models. But this quest can become a journey of diminishing returns, in that simulation modeling may not generate enough additional insight to be worth the investment. The team in this article will develop a few small models to deepen and refine their understanding of implementation dynamics.

The OSM methodology holds potential for all organizations. The process of developing a simple, one page stock and flow map of the organization’s strategy generates strategic insight and commitment to implementation. If your organization has been struggling to execute its strategy — or even to develop a good one — you will find building an OSM useful. It’s a perfect tool to get everyone on the same page so that when you come to a fork in the road, you’ll be more likely to take the better path.

Chris Soderquist (chris.soderquist@pontifexconsulting.com) is the founder of Pontifex Consulting. He consults to organizations and communities in order to build their capacity to create and implement sustainable, high-leverage solutions to their most strategic challenges. Mark Shimada (mark.s.shimada@boeing.com) is a program manager in The Boeing Company’s Leadership Development and Functional Excellence Group. He supports his peers to accelerate business results through extraordinary leadership development programs.

The post Operational Strategy Mapping: Learning and Executing at The Boeing Company appeared first on The Systems Thinker.

Barry’s death left a gap in the field of system dynamics as well. As the founder of High Performance Systems (now isee systems) and the driving force behind the popular ithink® and STELLA® systems thinking–based software products, he made computer modeling accessible to people in business and education. At his memorial service, several speakers commented on what Barry’s life had meant to them. Peter Senge spoke about both the importance and the incompleteness of Barry’s work, noting that it was “up to us” to continue this important effort.

Since Barry’s death, I have spent a lot of time reflecting on his life and contribution to the field of system dynamics. In this article, I identify five operating principles that guided Barry’s work, especially in the realm of public policy. These principles are also applicable in business, education, and other areas of inquiry. By way of summary, I also offer a few thoughts about the nature of Barry’s legacy and how we might build on that legacy.

A Broad-Brush Conceptual Framework

To gain a deep understanding of Barry’s work, it is first necessary to have some sense for where he was coming from. What motivated his activities? What were his ideas regarding the real value of system dynamics?

The framework, tools, and language of system dynamics should be accessible to all. Anyone can do this at some level, and everyone should try!

Fortunately, Barry left a good paper trail that documents his thinking. For example, the STELLA and ithink user guides (HPS, 2003) do an excellent job of presenting Barry’s view on how to “do” system dynamics. In The “Thinking” in Systems Thinking: Seven Essential Skills (Pegasus Communications, 2000), Barry identified the key competencies behind the effective practice of systems thinking.

These resources shed light on Barry’s fundamental belief, which provided the motivating force for many of his professional endeavors. I like to phrase it this way:

“The framework, tools, and language of system dynamics should be accessible to all. Anyone can do this at some level, and everyone should try!”

This belief is an assertion that the primary value of system dynamics comes from the process not the products of that process (although Barry would readily agree that products were important, too!). It’s also an assertion that as more people use the framework, language, and tools of systems thinking and system dynamics to generate insight—and act accordingly —the more likely we will be to solve the big problems facing the world today.

Over the time that I collaborated with Barry, this deeply held assumption was never very far out of sight. It would often come to the surface in the context of a formal presentation, essay, or paper. Consider, for example, Barry’s contribution to the 1985 System Dynamics conference in Keystone, Colorado, in which he introduced the STELLA software. The paper he presented was entitled “STELLA: Software for Bringing System Dynamics to the Other 98%.” The title clearly reflects Barry’s fundamental belief that everyone should be using these tools.

Or consider the paper Barry presented at the 1994 conference in Sterling, Scotland, provocatively titled, “System Dynamics/Systems Thinking: Let’s Just Get On With It.” In the paper, Barry asserts that system dynamics is “quite unique, quite powerful, and quite broadly useful as a way of thinking and/or learning. It’s also capable of being quite transparent —leveraging the way we learn biology, manage our businesses, or run our personal lives.”

Barry devoted a huge part of his life to turning this deeply held belief into reality, through a variety of products and services, including software, learning environments, workshops, and specific client deliverables. The common theme in these efforts was increasing the base of people who could partake in the process of gaining value by doing system dynamics.

A simple graphic that Barry and I developed for use in our workshops gives a clear picture of what he saw as the relative value of investing in various levels of analysis (see “The Return on Investment of System Dynamics”).

It relates effort or time expended to the value or utility that one can expect to derive from that effort. As the curve shows, there is significant value to be gained from simple “conversational” uses of the fundamental thinking skills. Examples would include drawing a behavior over time graph to cast a problem in dynamic terms, characterizing an issue in generic terms in order to recognize patterns over time, or asking operational questions such as “how does this work?” (For details about the different systems thinking and system dynamics tools referenced in this article, go to www.pegasuscom.com/lrnmore.html and click on a term or topic.)

Another jump in value/utility can come at relatively low cost from creating a simple stock and flow map. A third increase in value can be added, again at relatively low cost in terms of time or effort, by transforming a map into a computer-based simulation model, perhaps with a simple interface to facilitate controlled experimentation.

Note that, once you move past simpler applications, diminishing returns can quickly begin to set in. In our experience, as the complexity of the model increases, the amount of effort, skill, and time required to underwrite that complexity increases disproportionately relative to the amount of value derived! Out at the end of the curve, adding complexity may well result in negative returns. The implication: You don’t need to build huge, complex models in order to derive value. Simple, straightforward uses of the framework, language and tools can add significant value at relatively low investment!

Five Principles

This section distills what I believe are key principles that guided Barry’s public policy efforts. The principles fall into three broad categories, associated with the three activities that Barry viewed as fundamental to any modeling effort:

THE RETURN ON INVESTMENT OF SYSTEM DYNAMICS

There is significant value to be gained at relatively low cost from the application of basic system dynamics skills. Once you move past simpler applications, diminishing returns can quickly set in. As the complexity of the model increases, the amount of effort, skill, and time required to underwrite that complexity increases disproportionately relative to the amount of value derived!

Building

1. The Principle of Operational Thinking
2. The Principle of Irreducible Essence

Simulating

3. The Principle of Controlled Experimentation

Communicating

4. The Principle of Mental Model Confrontation
5. The Principle of Controversial Topics

1. The Principle of Operational Thinking This principle was at the bedrock of Barry’s work. Barry himself viewed operational thinking as the key thinking skill required for the effective application of system dynamics.

Operational thinking entails getting to the essence of how a process works. It involves asking questions about key accumulations, or stocks, and flows in the system. For example, “What is being produced?”, “How is this activity generated?”, “What resources are consumed in the process of generating the flow?” These are questions about the physical relationships among different parts of a dynamics system that work together to determine its dynamic behavior. The effort is one of building understanding of how it works rather than simply listing the factors that influence the process.

The benefit of operational thinking is that it facilitates the identification of levers for changing system performance. If you have a clear picture of how the process works, you are in a solid position to ask focused questions about alternate proposed policy interventions and more accurately think through the implications of a proposed initiative. If, on the other hand, your thinking simply results in a laundry list of factors that influence the process, your efforts to identify levers for actually changing performance may well be limited.

Barry used an excellent illustration of operational thinking in his presentation at the 2001 Pegasus Conference. This event took place shortly after the September 11 terrorist attacks. Issues associated with international terrorism were very much on the minds of participants at the conference. One part of a storytelling progression within Barry’s presentation is shown in “The Inflows and Outflows of Terrorism” on p. 4.

This stock and flow map nicely captures the essence of the processes through which people become terrorists, and through which terrorist activity is generated. Note the salient features:

• The number of terrorists is represented by a stock; terrorist activity is represented as a flow. From this map, you can identify two fundamental ways to reduce terrorist activity: Either reduce the number of terrorists or make terrorists less productive.
• The options for directly attacking the problem are clearly mapped (eliminating terrorists, eliminating supporters, and implementing defensive initiatives).
• The diagram captures both the inflows and the outflows to the terrorist stock; that is, the factors that lead people to become terrorists as well as those that cause them to stop their activities. In so doing, it identifies the levers for long-term improvement in the performance of the system.

THE INFLOWS AND OUTFLOWS OF TERRORISM

The diagram captures both the inflows and the outflows to the terrorist stock; that is, the factors that lead people to become terrorists as well as those that cause them to stop their activities. In so doing, it identifies the levers for long-term improvement in the performance of the system.

2. The Principle of Irreducible Essence This principle is a variation of “Keep it simple, stupid.” Einstein worded this tenet as:, “A good explanation is one that is as simple as possible, but not simpler.” Occam’s razor is another version:, “A simple explanation is to be favored over a more complex one.” These views, along with the principle of irreducible essence, recognize that we must simplify in order to make sense of the world—it’s impossible to hold all the relationships that exist in our heads. The challenge is to preserve the relevant essence of that part of the world upon which we wish to act in our models.

The usefulness of this principle is twofold. First, it enforces a mental discipline that can lead to improved clarity about an issue. Second, irreducible essence leads to explanations that are accessible to both experts and nonexperts on a given topic. As a result, following this principle can lead to a significantly larger audience of people who can derive value from the effort.

Barry’s “Stories of the Month,” published on the HPS web site 2001–2003, provided many examples of the principle of irreducible essence in practice. These stories typically used a simple stock and flow map or a small simulation model to provide a systems perspective on current events in the news. A story that Barry was working on at the time of his death, entitled “Hot Air and Greenhouse Gases,” was motivated by some sloppy statements about global warming coming out of the White House in the summer of 2002. Among other things, these statements contended that the president had a plan that would reduce greenhouse emissions while sustaining economic growth. The implicit claim was that this plan would result in a reversal of global warming trends.

In response to these statements, Barry could have developed an elaborate model of greenhouse gases, or he could have pointed people to large, detailed models produced by others on the topic. Instead, he began working on a simple model and story (see “Growth, Gases, and Warming”).

This diagram is stark in its simplicity. It provides just enough of the relevant essence of the issue to get at the dynamics of the greenhouse effect. It includes just enough structure to facilitate investigation of the interaction between reduced greenhouse emissions (for example, through “green technology”) and increases in the level of economic activity that serves as the base for generating greenhouse emissions.

3. The Principle of Controlled Experimentation The principle of controlled experimentation entails making changes in a model one at a time to learn why it behaves in a particular way under particular conditions. Through such controlled experiments, users build understanding of the connections between structure (how the process is put together) and behavior (how it performs over time). They can compare their assumptions about the situation to the computer simulation and modify their mental models in response to what they learn.

Simple, controlled experiments can also create the activity basis for building shared understanding. A sequence of controlled experiments can yield extremely productive conversations, particularly when participants compare the results of the experiments to what they had predicted would happen. They can then discuss differences of opinion, identify commonalities of thought, and surface tacit assumptions.

Less directly, controlled experiments build an individual’s capacity to accurately trace dynamics and to make structural/behavioral connections. Barry was a firm believer that humans aren’t very good at doing mental simulations of anything except the simplest of systems. Nevertheless, he believed that people could build their capacity to play out dynamics in their heads through sustained practice. Indeed, this was one of the motivations behind the “Story of the Month” concept.

Many of the stories reflected the principle of controlled experimentation, including the first one that HPS produced. This story came about because Barry was in California at the time of the run-up in energy prices that took place in April 2001. Everywhere he went, he read news articles about organizations that planned to pass on increased energy prices to consumers. This practice raised an interesting systems question: Is it possible for everyone to pass on costs? Or is there some self-limiting process at work?

We developed a simple story to address the issue. The first part of the story looks at what producers do in response to a step-increase in energy costs. In the model, a simple balancing process is at work. In an experiment with a step-increase in energy costs, producer profits initially decrease. Producers then raise prices in order to bring profitability back to desired levels. When taken in isolation, this balancing process keeps profits at desired levels by passing on increased energy costs to consumers.

The next part of the story involves expanding the model boundary just a bit, to consider what consumers do in response. For consumers, an increase in prices means a decrease in purchasing power. This in turn can lead to upward pressure on wages. It’s another balancing process. This loop works to keep purchasing power in line with desired levels by driving wages upward.

It’s important to note, however, that wages are a cost to producers, and so an increase in wages can undermine producer profitability. In an experiment with the expanded model, a step-increase in energy costs leads to price increases, which causes wages to increase, which creates a further round of price increases! A reinforcing feedback process, latent within the structure of the system, underwrites a wage-price spiral!

By using controlled experiments in a simple progression, it’s possible to build understanding, stimulate good conversations, and strengthen mental simulation muscles.

GROWTH, GASES, AND WARMING

This diagram facilitates investigation of the interaction between greenhouse emissions and the level of economic activity that serves as the base for generating those emissions.

4. The Principle of Mental Model Confrontation Like the principle of controlled experimentation, the principle of mental model confrontation is simple but powerful. The premise? Whenever possible, bring the prevailing mental model to the surface of the discussion. Explore the dynamic implications of that mental model. Then, provide an alternative mental model (often in the form of a stock and flow diagram) that offers richer explanations, more robust policy propositions, or improved insight into the issue at hand.

The process of confronting the default mental model is a key part of creating a compelling case for changed behavior—often the desired outcome of work in public policy. When there are multiple, conflicting mental models, the principle of mental model confrontation can be used to facilitate communication among key stakeholders. There’s learning to be had from systematically comparing, testing, and evaluating underlying assumptions!

In late September 2001, Barry put together a “Story of the Month” on terrorism. This story nicely illustrates the principle of mental model confrontation. In it, Barry begins by “surfacing the mental model underly- ing [the rhetoric of the Bush administration in response to the September 11 attacks, for example, ‘leading the world to victory in a war against terrorism’] so you can critically examine its implicit assumptions.”

Next, Barry builds upon this simple mental model to offer a critique of the prevailing thinking. This richer structure—very similar to the one he developed for the 2001 Pegasus Conference—sheds light on longer-term difficulties for the “war on terrorism.” Over the long haul, a reinforcing loop associated with the terrorist recruiting process, as turbocharged by increasing anger at US-led actions, can lead to a rapid growth in both the number of terrorists and the frequency of terrorist acts.

Later in this story, Barry offers a systems thinking–based alternative to looking at the situation. The alternative consists of two components: a defensive component that minimizes current threats, and an offensive component that gets to what Barry sees as the root cause of terrorism. Building it up a piece at a time, Barry ends up with a map that shifts from a focus on “winning the war” to building tolerance of another’s viewpoint, managing anger, defusing hatred, and maybe even adjusting one’s position. By initially confronting the mental model that appeared to be prevalent in the Bush administration, Barry presents a systems thinking– based alternative.

5. The Principle of Controversial Topics This principle flows directly out of Barry’s deeply held view that anyone could (and should be able to) use the language, framework, and tools of system dynamics in a productive way. He believed strongly that an informed layperson could generate insight into any topic of interest. For Barry, controversial or “hot” topics were especially important to pursue, because they’re often the most confusing or perplexing, and therefore have the most potential for benefiting from the use of system dynamics!

I’ve interspersed several of these controversial topics through this paper. To make the point very clearly, I’ll introduce one more issue that Barry tackled in his “Story of the Month” series. In response to the tragedy at Columbine High School and at other schools in the United States, Barry put together the “Guns at School” story. He wrote, “Until we have a solid grip on the relationships responsible for producing and maintaining this scary phenomenon, we have scant hope of doing much to effectively address it.” His story was an effort to come to grips with these relationships.

The story begins with a brief history of gun-related school violence and then incrementally develops a stock and flow map that seeks to explain the phenomenon. The map depicts the progressive build-up of alienation and rage, relating these emotions to the acquisition and use of guns within a student population.

Against this backdrop, Barry developed a set of policy-based experiments around three kinds of potential actions: gun-related initiatives (such as improved screening of gun purchasers, disarming students with guns, and restricting student access to guns), media initiatives (anti-copycat practices that limit news about school shootings), and student coping skills initiatives (trainings in rage, alienation, and humiliation management).

Barry’s real legacy in public policy work resides in the mindset along with the principles that he employed.

Readers are prompted first to conduct one-at-a-time controlled experiments with different interventions. Then, in a second round, they are encouraged to create a “policy cocktail” to find the most effective set of interventions. The intent of these experiments is to provoke thought and stimulate discussion by exploring the relationships that drive this pressing social issue. Is the topic controversial? Yes! Is the story helpful in shedding light? Absolutely!

Barry’s Legacy

Barry did not have a huge publication record in the realm of public policy. Most of his work was done in the context of client work or, more recently, in presentations of the “Story of the Month” column. I do not think that Barry’s work, by itself, is where his legacy resides. Rather, as befitting the teacher that he was, Barry’s real legacy in public policy work resides in the mindset along with the principles that he employed.

For those of us who wish to carry on the work, I believe that there is much to glean from this legacy. For me, the primary lessons are:

• Maybe not everyone can apply system dynamics to public policy issues, but there is a large population of people who could derive value, at some level, who currently are not. Those people need access to systems tools, concepts, and frameworks.
• Most people/organizations are on the steep part of the effort/value curve. They therefore can derive significant value from conversational uses of system dynamics, simple stock and flow maps, and simple models with interfaces.
• The five principles aren’t rocket science—although there is some art associated with their application. I have found them helpful guideposts for my own work. You may find them useful as you seek to apply systems thinking in practical ways in your own context.

While it is beyond my ken to consider how one might replace someone like Barry, I believe that it is possible to carry on his work. It will require sustained effort and application, but it can be achievable. The world will be better for our efforts to do so.

Steve Peterson (steve@evans-peterson.com) is an independent consultant based in West Lebanon, NH, where his work focuses on the practical application of system dynamics across a broad range of application areas. Before starting his own practice, he worked closely with Barry Richmond, both at Dartmouth College and at High Performance Systems, Inc., where he was an integral part of the development team responsible for the ithink® and STELLA® software products.

The post Applying System Dynamics to Public Policy: The Legacy of Barry Richmond appeared first on The Systems Thinker.