Causality

When we evaluate something, we typically are trying to understand and make claims about causal relationships. When we create a system dynamics model, we are mapping and modeling causal relationships. But how do we tell what relationships are causal and which are correlational?

Thanks to a recent pointer on the evaltalk mailing list, here's Sir Austin Bradford Hill's “The Environment and Disease: Association or Causation?” Hill gives nine considerations to ponder.

For a rather shorter read, see xkcd's take on causality. Be sure to see the alt tag.

System dynamics applied to music

One of the project teams from last year's system dynamics class in the Information School at the University of Washington will be presenting their work at the International System Dynamics Society Conference this summer in Albuquerque, New Mexico. Look on the tentative schedule for "Exploring the Dynamics of Music Piracy" by Trond Nilsen, Brian Houle, Douglas Kuzenski, and Arpan Sheth, or check out their abstract, paper, and models.

Congratulations Trond, Brian, Doug, and Arpan! For the rest of you, check out their work. Perhaps it will shed light on a subject you've talked about.

Creating sustainability in complex ecosystems

I recently had the privilege of teaching a course in system dynamic for Willamette University's Sustainable Enterprise certificate program. The course lasted two days, with a follow-up two-hour web seminar. We focused on qualitative system dynamics, but we treated it at a somewhat more rigorous level than many such courses, I think.

I'm writing because of one particular lesson I learned—we all learned. Early in the course, we used a simulation game to help people have a common, shared experience of interacting in a challenging system environment.

As with many such games, the expected result is that people fail in making the system work. Typically, the debrief is used to help people understand the ways of thinking that led them into trouble and to prepare them for the material that's to come.

Unexpectedly, this class managed their challenges quite sustainably. While their skill wrecked the planned flow of that part of the session, I was really pleased to see their skill in action. We spent some time talking about what made them successful and how that might carry over to real-world situations. Their insights were useful enough that I wanted to share them (with the students' permission) with a larger audience: you.

I first asked what made them succeed in the game and what provided the most challenges.

Goals were the first. While the game tells them the goal they should have, they rapidly realized that focusing on the stated goals would lead to ruin, and so they decided to set a much longer-term goal.

Communications was the second factor. After the first round, they began to spend most of their time huddled in the center of the room, talking animatedly through their decision-making processes instead of working in isolated teams.

They noted that delays provided a key challenge. As they worked to establish trust in the social system they had set up, they were both trusting other teams' commitments and verifying that they were indeed living up to their commitments. That takes time: commitments made today may not show up for quite a while.

Those delay effects were complicated by the natural delays in the system. Without revealing the game we used, I will say that the dynamics of the game included natural delays between actions and results that complicated decision making.

Some noted this seemed analogous to the situation OPEC finds itself in. They rely on mutual agreement to limit production as a way to manage prices. If anyone in OPEC breaks that agreement, the system can collapse. OPEC's problems are complicated by uncertain demand and uncertain prices, factors that had no analogy in our game.

Math skills created another success factor, which some may find surprising. A subset of the players rather immediatedly began developing quite a useful understanding of their system based on a mathematical model they developed. Once others saw that their results were accurate, everyone became driven by the data. Without some in the group being able to pull that off, they would likely not have succeeded.

Interestingly, trust and math worked together. At one point, the analyst team made a numerical error and then made an especial effort to communicate that they had made that error to others so that the others would be able to differentiate that error from a breaking of the trust relationship. Apologies were key. Information and the lack of information thus played a key role in the group's success. Even then, it took time for the others to regain their trust in the analysts' team.

Playing into this was the lack of external shareholders. Everyone on the teams had a serious take in the workings of the game; no one was in it just for the "money." Similarly, there were no new entrants into the field who might have upset the cartel relationship they had crafted.

I then asked them what they'd advise people in the real world.

Collaboration was the first clear answer. Work together across groups to align goals and actions.

They then said, "knowledge is power." After a bit of reflection and revision, they revised that to "timely, transferrable, actionable knowledge is power."

They felt it was important for everyone to be clear on a vision.

They would encourage people to watch their egos and to be visibly trustworthy.

At one point, in an attempt to test the strength of their commitment (okay, as an attempt to derail their commitment), I as facilitator announced I was the government and was giving them something they really didn't want. (To be accurate, that idea came from Anne Murray Allen, the executive director of the program, who was running the simulation computer.) For a while, I felt as if I were about to experience the French Revolution, as some rather emotionally argued for standing up to government and refusing my help, a bit of resistance I wasn't accepting.

As a result, their last bit of advice was to "Don't trust the wisdom of government, of the private sector, ... of either." In other words, test the data and the reasoning yourselves instead of blindly accepting what others say is good for you.

This was an intense and very exciting two-day workshop. I think those in the class learned a lot; I know I learned as they taught themselves and me (and now perhaps you) how to make sustainability work.

Perhaps I'll see some of you there next year.

Welcome to Pegasus Communications

Today I'm welcoming Pegasus Communications and their new Leverage Points Blog! They've done much to foster systems thinking over the years, from publishing The Systems Thinker, the free Leverage Points, and many of the major books at all levels of systems thinking and system dynamics to putting on the annual Systems Thinking in Action conference. Check them out.

And thanks, Janice and the others at Pegasus Communications, for listing Making Sense With Facilitated Systems among the august company in your "In the Loop" list.

The chicken or the egg?

Perhaps you've been wondering what in the world system dynamics is good for.

System dynamics can help you answer the question, "Which came first: the chicken or the egg?", which you can only do if you look at both the chicken and the egg at the same time.

I was reminded that I wrote that back in 2003 when I saw Tom Fiddaman's SD on Long Waves, Boom & Bust. Click on my name "Where are we in the long wave?" in that post to the the thread in which it occurs.

Literate modeling and neatness

Neatness and organization count for something, right?

That's what we were all told growing up, I imagine, and it is a pleasure to work in a neat environment.

Then why do (I suspect) so many of us who model have directories with files named model-2008-10-15.model, model-2008-10-15A.model, model-2008-10-16.model, etc.?

It's because we were also told that modeling is an iterative process, which it very much is (one student in one of my classes thought "Iterate" must be my name). If we iterate on models (writers do the same), and if we want to keep older versions around just in case we need to go back to one of them, we end up with heaps of models to keep track of.

Literate (and text-based) modeling can help. Instead of filling directories with files, I now have one model file per model, and I let bazaar, my revision control system, track the history of that file. If I want to see what it looked like last week (or last month), I simply check out the old version or compare it to the current version. Bazaar tracks comments by revision, too, so it's easy to find the model I created to address a particular issue (assuming I noted that issue in the comment for that revision).

Why do you care? Have you ever worked with someone who couldn't find an aspect of the work you needed to see? Have you ever "improved" something you're working on, only to find a prior version was better? Perhaps literate modeling, text-based modeling, and revision control are in your future!

Management Improvement Carnival: Annual Edition

John Hunter of Curious Cat has asked me to participate in the annual edition of the Management Improvement Carnival. I'm humbled to be invited and glad to participate.

The first station has to be Tom Peters' blog. I don't agree with everything he says, but I do find that he makes me think. Any of you who manage something are people, too. That's why my first link goes to his Christmas 2008. I share his sentiments, if not his bully pulpit. While I'm mentioning his blog, I'll also mention Repeat!.

The next station is MetaSD, the home of Tom Fiddaman and his Four Legs and a Tail. It's a good reminder of the leverage points we can seek in the systems in which we work as originally drafted by Dana Meadows, and it offers his notion that they don't necessarily compose an ordered list. Perhaps more importantly, it's a reminder that we need a mindset change to be successful in the world we're entering. Speaking of mindsets, Cynthia McEwen and John Schmidt of Avastone Consulting have published Leadership and the Corporate Sustainability Challenge: Mindsets in Action Report. While not a blog, that report does speak to mindset changes. Speaking of Tom Fiddaman, he has also posted My Bathtub is Nonlinear, an excellent reminder of the importance of grounding our assumptions in real data.

Times are tough, economically, and that's why I pick Paul Graham's Why to Start a Startup in a Bad Economy as the third stop. Don't do anything foolish, but don't think that the news from Wall Street necessarily predetermines your fate is the message, but he says it better than I. While I'm visiting non-conventional management sites, I'll stop at Elana Centor's Note to HR Folks: Hiring Over-Qualified People Is A Smart Strategy because you will need to hire again someday, if not today.

Speaking of saying things better, one of a manager's jobs is conveying information, and much of that information comes in the form of numbers and graphs. We do our organizations, our people, and ourselves a favor when we display such information clearly so others can make sense of it well. That's why the fourth stop in this carnival is at Andrew Gelman's An improved time-series graph instead of that notorious "spiraling down the drain" spiderweb. Follow the links, too, to see his earlier commentary. I'm a fan of Edward Tufte's approach to communicating information, and I'm a fan of the second graph in that posting. If you have to add drama, I like the third graph much better than the first, but I still think the second is the best of the three.

As important as data and statistics are, I'm reminded by xkcd's Decline that not everything we do, not even everything we do as managers, is best served by quantification and purely logical analysis. That brings me to Andrew Taylor's Not aloof and detached, but deeply, deeply human, a link to a Benjamin Zander TED presentation that, for me, brings together presentation skill and leadership in the service of his passion, music.

Finally, I'll take a view of another system we may not think of much, one that we very much need to be working well and one that may offer opportunities for some of us: food. Marilyn Holt's A Locavore Manifesto by Michael Pollan is a great education and reminder; click on the title of her post to get to the manifesto.

You may have thought I'd post about IT issues, about process improvement, or about systems or statistical analysis of management work. Those are indeed important, and I don't want to neglect them.

Yet I've found it helpful to start thinking at a high, systemic level to make sure I'm considering the important issues and to help me determine where I need more detailed information. While this, like most summaries of blog postings, can't claim to be as organized and logical as a book, I think it covers issues we need to concern ourselves about in business. From how we deal with people to the mindsets we bring to our work, from how to work in a tough economy to how to convey information, this covers a broad range. I closed with food systems because I wonder if we may be entering a period where the major systems we need for business—food, energy, the atmosphere and the overall environment—can no longer be safely taken for granted. That's why I think the desire and ability to view our challenges through a systems lens is particularly important as we enter 2009.

I'll conclude with with Tom Asacker's Nine Predictions for 2009, thanks to Tom Peters' Must Reading.

Follow-up:

To find the rest of the Management Improvement Carnival, check out these links:

• Management Improvement Carnival Best of 2008
  
• Got Boondoggle?
  
• Quality and Innovation parts 1, 2, 3, and 4
  
• Lean Blog
  
• Elegant Solutions
  
• Evolving Excellence
  

IMT 586: Information Dynamics at the University of Washington

If you are a University of Washington graduate student interested in understanding the impact of information feedback on the systems in which we live and work, check out this winter's IMT 586 (also offered as INSC 586). This is the second year it's been offered, and I'm looking forward to exploring this field with a whole new group of you. If there's enough demand, we hope to offer the follow-on IMT 587 in the spring this year, so there's even more potential this year than there was last year.

If you are not a UW graduate student, but you are an interested professional who lives within commuting distance of UW, consider signing up, too. For any of you, studying system dynamics (okay, it's offered in the Information School, so we call it Information Dynamics) offers a great opportunity to learn a new way to make sense of the challenges we face and to find and test solutions.

Last year, all of the students brought their laptops to class. That let us create and explore computer models and simulations in class, which seemed to make for faster, more solid, and much more interesting learning. I hope to do even more of that this year. If you sign up and can bring your laptop, great. If you can't because you have a desktop machine, that's okay. We'll be fine as long as at least half the class brings laptops.

I look forward to seeing many of you in January! Please ask if you have questions.

(Past) Time for a tip on managing budgets?

Twice in times past, I've been in business situations where it was explicitly important to get a better handle on managing expenses. In the second case, the organization was seeing expense cycles of perhaps six months duration and couldn't seem to fix them.

When I saw the oscillations, I saw that as possibly coming from a structural problem. I created a system dynamics model that matched the structure of managerial decision making and accounting in the organization; with very few tweaks, I was able to reproduce in the model the essential behavioral characteristics of the real situation.

Seeing the structure laid out simply made it relatively easy to think of possible solutions, and I was able to eliminate the problem in the simulation by changing the information flows to simulated managers.

After getting buy-off, we implemented the changes in the organization, and fluctuations in spending variance dropped by 95%. What's more, we were able to adjust spending levels rapidly and accurately as needed to meet changing expense targets. That was fairly convincing proof that the model had been useful in identifying the cause of the problem and in testing proposed solutions.

Given current economic times, perhaps it's time to bring out some of those lessons again—or perhaps it was already time for that a few years ago. You can read more in Applying System Dynamics to Business: An Expense Management Example, where you can also find links to a model and to a published article on the project.

Incidentally, one of the lessons is that managing our personal expenses with credit cards is riskier than managing with cash. Read the article for more!

Introducing literate modeling

Organizational modeling has much in common with programming. If you create or ask for organizational models in any one of a number of text-based systems, you likely realize that. If you use any one of a number of GUI-based systems, you may recognize what you're doing as visual programming.

In organizational modeling, the challenges are many:

• How to create a competent model
  
• How to make the process transparent so others can collaborate and still others can benefit
  
• How to organize the model in ways that are understandable both to people and the computer
  

It's both easier and harder than it sounds: it's easier to produce useful, insightful models than many might think, and it's harder to create solid models than some would have you believe.

Despite the claims of some, I don't think there's one right way: I think we need a diversity of approaches. To that end, I've been exploring text-based modeling and simulation for the last few years. Recently I've begun to merge the ideas of literate programming and organizational modeling into what you might call literate modeling. Strictly speaking, that's only doable with text-based modeling languages. It brings with it a few features that seem important:

• Thinking about the model and creating the model go hand-in-hand. I've already found that text-based modeling has helped me think in new and deeper ways about the problems I've addressed, and literate modeling strengthens that thinking by linking them even more tightly.
  
  Why is that so? Part of the reason has little to do with literate modeling and textual programming per se: I found that splitting up the work of modeling and simulation into different types of tasks (conceptualizing and modeling a problem, designing experiments to test theories of action, analyzing and thinking about experimental results, and communicating those results to others) helped me do a better job at each stage.
  
  Literate modeling adds a writing component, which may help us think more carefully about our modeling decisions, to the modeling process. Forcing the explanation of the model to go hand-in-hand with its creation seems to keep me from making assumptions I can't support. In fact, I tend to let the writing drive the modeling, which I think drives models even more from the aspect of hypothesized causality than from the aspect of what works technically. You can see what others have said about literate programming; I think those ideas apply to literate modeling, too.
  
  Of course, you can document normal models extensively, too. As others have said, literate approaches link the thinking required to explain a model (or a program) to other people tightly to the model (or program) itself; the model flows from the thinking and writing instead of the writing becoming partially a reverse engineering of the model code.
  



• Model consumers, collaborators, and even developers think most naturally about models in a sequence that doesn't necessarily match the sequence needed by the simulator. Literate modeling allows you to decouple those two sequences completely.
  



• To explain a model, you sometimes need graphs, diagrams, pictures, tables, or other non-textual components. A good literate modeling system can integrate all those components easily without being tied down to the features offered by a particular simulator. In a way, this is the old Unix philosophy: use a collection of smaller tools, each well-suited to the task at hand, and put them together flexibly as you need them.
  



• Literate modeling is one approach to applying some of the best of the lessons of software engineering to a related field in order to do better work.
  

Why do you care? Why should you care?

If you work with or use organizational simulation models to make better business or organizational decisions, perhaps literate modeling offers you a way to have more transparent, more collaborative, more understandable, and more well-thought-out models. Better models, applied appropriately to generate better insights, might just help you make better decisions. Better decisions, carried through with good implementation, might just lead to better results over the long haul.

Is literate modeling or, for that matter, text-based modeling the only way to go? By no means! By the rule of diversity, if nothing else, that would be wrong. Each of the graphical modeling tools I use has brought its unique strengths to the problem-solving process, and I continue to use them. "Horses for courses," as they say. Yet don't count out text-based tools for effectively engaging those with whom you're working, don't think that text-based modeling and literate modeling has to be ponderous, and don't count out the power of text and writing to help you think more effectively about the challenges you face.

What do you think?

A systems thinking tour de force

If you're interested in ways of making sense of situations systemically (or interested in making sense of situations that don't seem to lend themselves to the ways you've thought of things in the past), see Bobby Milstein's excellent Hygeia's Constellation: Navigating Health Futures in a Dynamic and Democratic World. Yes, it deals with public health issues. No, you don't have to be interested in or involved with public health to learn from it. Yes, you might get excited by some of the ideas presented there.

Thanks to Bob Williams for bringing it to my attention. To be honest, I'm only about half-way through it, but I thought you might want to get an early start reading it.

For an interesting lash-up between the US Centers for Disease Control and Prevention and Google.org for estimating the progress of flu in the USA, see Google.org Flu Trends.

Learning Through System Dynamics as Preparation for the 21st Century

Of what use is system dynamics? You might well ask of what use is systems thinking of any sort, but I'll save that for another day.

Jay Forrester has just published "Learning Through System Dynamics as Preparation for the 21st Century" in the October 2008 issue of The Systems Thinker (Volume 19, No. 8). It's a pretty comprehensive, five-page summary of what he thinks one should get from a system dynamics education. Each objective he lists falls into one of three categories:

1. Developing personal skills
   
2. Shaping an outlook and personality to fit the 21st century
   
3. Understanding the nature of systems in which we work and live
   

In the process, he touches on factors I've mentioned here, including its ability to provide us a more effective language for thinking, its ability to help us apply lessons from one set of experiences in another setting, its ability to help us test policies before we apply them, and its reminder that we often create our own problems by virtue of the way we respond to the environment in which we operate. That last sounded depressing when I first realized it until I also realized it meant we have a lot of ability to be able to fix those problems, too, if our policies are their cause.

He presents the case rather comprehensively. If you or your institution subscribes to The Systems Thinker, be sure to read this article. If you don't subscribe, you can purchase individual articles, too. I imagine they'll list this article on their Web site soon; I just got my subscription copy today. (Be sure to follow the terms of their licensing.)

Dealing with risk and uncertainty

Times are uncertain. Risks seem high. We may feel that the price of missteps is high; we know it's hard to decide what steps to take.

In situations such as this, how do you make decisions in and for your organization? How do you plan effective actions? How do you solve the inevitable problems that arise?

The German psychologist Dietrich Dörner, author of The Logic of Failure, has made a career of studying why people make mistakes and what we can do to improve. One of his key pieces of advice is to use computer simulation to get insight about the situations we face so that we can make better decisions in real life.

Perhaps today's uncertainties are your signal that the time is right to apply more systemic approaches in your work and to ground your planning, problem solving, and decision making with simulation that takes into account factors important to your business. Perhaps it's time to test and rehearse your plans before you implement them.

That's what we've been discussing here, and that's how I help others. If you're concerned that your standard approach to business may need augmentation in today's world, perhaps I can help you, too. Drop me an email or give me a call. There's no obligation—only opportunity.

System dynamics in Seattle

I just ordered texts for IMT 586, Information Dynamics I, in the Information School of the University of Washington, which reminds me to tell any of you at UW or within commuting distance who have been interested in system dynamics that we do plan on teaching system dynamics again this winter quarter. Registration starts November 7.

If there's enough interest, we hope to teach the follow-on IMT 587 in spring 2009. If you take IMT 586 this winter, consider leaving time in your spring schedule. If you took IMT 586 last year and would like to go further, think of IMT 587. If you've already got a system dynamics background (equivalent roughly to the first fourteen chapters of John Sterman's Business Dynamics) and would like to go straight to IMT 587, let's talk sometime before spring quarter enrollment.

I look forward to seeing you there!

The Age of Heretics: a review

I'm writing about a new book today, but first I have a disclaimer: I know the author, Art Kleiner, because I was on an extended panel discussion he led on organizational heresy that resulted in a small section of The Dance of Change: The Challenges to Sustaining Momentum in Learning Organizations. He and I have kept in touch from time to time since then, and he provided me a review copy of this book.

There. That's out of the way.

Art Kleiner has published a second edition of The Age of Heretics: A History of the Radical Thinkers Who Reinvented Corporate Management (J-B Warren Bennis Series). The executive summary: if you're in business, if you lead a business, if you consult to business, if you ever have thought of ways to make business work better, read this book!

Perhaps you read the first edition. So did I; I think I recommended it for the company library where I worked at the time and read it there. My recollection is that I liked that version, but I like this version so much more. Perhaps it's his new version; perhaps it's my added experience since I read that first edition (I no longer have easy access to check). Even if you read the first edition, read this one, too.

A heretic, in Art's view, is someone who simultaneously holds great loyalty to the organization to which they belong and a vision of a new truth the organization has yet to see. He has written about the evolution of organizational heresy by way of mini-biographies of archetypal heretics. There are too many for me to summarize, so let me simply refer to one as a way to whet your interest and to indicate what I think of the book.

I first discovered Chris Argyris's action science around 1992, about the time I began work with a group that eventually turned into a true high-performing work team. I had read The Fifth Discipline: The Art & Practice of The Learning Organization
and discovered reference to Argyris's work. As is often my custom when I read of new ideas, I like to find the original to learn more (perhaps I owe that to Dr. Malcolm R. MacPhail of Rice University, who would give extra credit in quantum mechanics for our reading related, primary research in its original language and writing summaries).

I picked up one of Argyris's books, probably about 400 pages long, and began to read. By the time I had read 50 pages, I had determined both that it was one of the most important books I had ever read and that I didn't have a clue how to apply its ideas. I kept reading.

At the same time, I was working with—managing—a team that had serious intra-group communications difficulties. I'd practice what I was discovering in meetings I held with them. Then I would come back to the book and try to discover where I had gone wrong. After a year or two of weekly meetings as experimental labs and after reading perhaps seven, eight, or more of Argyris's books, I discovered that the application of action science can facilitate breakthrough improvements in group productivity. I determined that action science has certain attributes:

• Action science requires great skills at discernment to see important incongruities in words that can help us improve our abilities to hold productive discussions in the presence of disagreements and even conflict. It also offers approaches to help us build our capabilities in discernment.
  
• Action science is a revolutionary approach that upends normal work cultures and offers the promise of real, revolutionary gains in productivity.
  
• There's an ethical principle that permeates action science. It's vitally important for each of us to find it and internalize what it means to us. That was, I think, central to my eventual understanding and use of action science.
  

Action science was perhaps the hardest material I've ever learned (even harder than some of the technical material I learned as an engineer). I think it was only the long, intense action research approach of reading, studying, reflecting, and doing (and often failing) that enabled me to comprehend and internalize it without a mentor or teacher.

Most books and articles I've read about action science (Bob Dick's and Tim Dalmau's Values in Action is a notable exception) attempt to make action science approachable, incremental, and easy to do. As important as some of those books are, I've come to the conclusion that those who see action science as anything but earthshakingly revolutionary and demanding of great personal courage and discernment have missed (or are hiding) the point.

Why this discussion? Because Art is the first writer I've seen who conveys that spirit in his description. He, like no other I've read, made that essence come alive. While you won't learn how to practice action science in the pages he devotes to Argyris's work, you may come away with a better impression of what it can do for you and for groups with which you work. Reading his words in conjunction with other material on action science may help you develop a deeper understanding and better practice of the approach.

Art did much the same for each of the heretics and their heresies throughout The Age of Heretics. He neither shied away from their warts nor downplayed the essence of their contributions. That has helped me put many past business and management developments into context, and that is why I recommend it so highly to you.

Now go read it!

The Marblehead Letter

I've written about my musings on growth a number of times, even as I worried that my ideas might be controversial.

Now I've seen the Marblehead Letter, written by executives at a SoL conference in 2001, and I think those of you reading this blog might find it worthy of your time. Read both the full letter—it's only two pages long, and I think it states its questions better—and the summary, which hints at some of the signatories.

Note that the letter has questions, not answers, and note that the letter comes from people high in the ranks of major organizations.

I discovered this letter by reading Presence: An Exploration of Profound Change in People, Organizations, and Society, courtesy of InBubbleWrap and 800ceoread. For various reasons, that's been a hard book for me to get through, but I'm persevering (and those of you who have a copy can tell the page I've reached by this blog posting). Perhaps I'll blog more about it when I finish it.

What do you think? It's comforting to know that others are considering similar questions to the ones I've been raising. Question 3 is exactly what I want to work on, but reading it brings two thoughts:

• You can't address that one question in a vacuum; you have to consider their other questions and still more (for example) in the process. It is a systems issue on multiple levels.
  
• I wonder if they didn't go far enough in question 3. They want to reconceive growth. I wonder if and how and under what conditions overall sustained growth is possible and good for us. If, in aggregate, it is not (and I have yet to see evidence that the systems mantra of "there are always limits to growth" is false), I want to help find a new and successful way forward. While we have to address the long-term situation, I'm more interested in helping us figure out how to make the transition from growth to sustainability, whether on an organizational, societal, or personal level.
  

Those of you acquainted with some of the literature on growth will realize that a stable system doesn't mean there is no growth. For example, in a business sense, some technologies, products, or services outlive their usefulness, and their companies shrink or perhaps go out of business. Other technologies, products, or services are needed in increasing amounts, and their companies grow. Equilibrium in the aggregate doesn't require equilibrium in the details.

While I'm optimistic we'll figure out a way to deal with this, I still think the issue of growth is an integral part of one of the two major problems we face as a people. From what I read, we may well have exceeded the carrying capacity of the planet. If that be true, then these are important times, for the way we respond can likely have a major effect on the response of the systems in which we live, and the recovery of a system from overshoot can be harsh.

I really would welcome your comments on this.

Stocks, flows, and the President's weight

I've noted before the importance of thinking appropriately about stocks and flows. Janice Molloy of Pegasus Communications just wrote "A Weighty Take on Stocks and Flows" for the August 2008 issue of The Systems Thinker, using stocks and flows to communicate the message of a New York Times column by Gail Collins. It's a good tale; if you subscribe to The Systems Thinker, check it out, or check out the original column.

It was fun talking through the implications of these ideas with Janice, creating a few simple models together to clarify Collins' message, and producing the diagrams that Janice used. There is a message hidden in the fun, though: be sure you understand what they really mean when someone says they'll reduce the rate at which something is growing. It may not be all that good a deal.

Prediction, system dynamics, and Future-Fusion

Recently, I made the claim that we're better off focusing on adapting to the present than predicting the future. I've made similar claims in the past, too. I've even given one example in which predictions serve a useful purpose.

That's all a bit simplistic, of course. Even system dynamicists could be said to predict the future in a way: we show behavior over time we feel is more likely to occur (although we may warn people away from point predictions based on a behavior over time graph). In other words, I might suggest that your current policies could produce a boom and bust effect in your business, but I wouldn't want you to draw the conclusion that your business will grow another 172.3% by June 15, 2009 before taking a tumble that afternoon.

Because we all would like to know the future, I've experimented with blending system dynamics and Bayesian analysis to quantify the probability of a particular behavior pattern, for example. Of course, that probability is conditioned on both the historical data and the model being correct, which is a loophole big enough for a good-sized locomotive to run through: models are always incorrect. Still, I think this approach may give more useful insight in certain cases.

Now Kshanti Greene of Stottler Henke Assocates, Inc. has shown me a Bayesian tool they've developed called Future-Fusion, and I've been exploring it a bit. They are using Bayesian networks and the power of groups to get a better handle on what the future holds. Much as Data360 looks at the past, Future-Fusion attempts to look at the future. As of this writing, they've created four test areas which you can explore: the 2008 US presidential election, the Iraq war, corporate strategy, and energy. Try it out: learn how to use the system, see current predictions, and add your own (I think you only have to create a free account if you want to add your own predictions). Perhaps you'll learn something, and perhaps they will, too.

Kshanti has pointed out a recent addition to Future-Fusion that may intrigue some of you: time. They've enhanced their technology to allow limited dynamic execution of a network model, which begins to narrow the gap between Bayesian networks and system dynamics from the Bayesian network side, much as what I've tried has narrowed it from the system dynamics side. To try that out, go to the energy model, select a prediction (e.g., "Reduced SUV sales"), click "view graph," note the numbers, and then click "Next Time Step."

I think this is all still experimental in many ways, but it's a good opportunity to learn a bit about this technology by trying it out on real-life issues. I'll be curious what you discover.

Bittersweet asphalt

No, it's not that I find asphalt bittersweet (I haven't tried tasting it). It's the news that I find bittersweet.

Five and a half years ago, I published Out of Gas: A Systems Perspective on Potential Petroleum-Fuel Depletion. In that column and in the accompanying simulation model, I suggested that delays due to debates over how to allocate shrinking petroleum stocks might hurt our ability to replace energy resources in a timely fashion.

Today, I read Asphalt shortage disrupts road projects. I'm sure you can find other examples, perhaps closer to your home, in which the imbalance in supply and demand of petroleum is leading companies to prioritize one usage over another, which can cause pain for the unfavored group.

Models such as this aren't designed to predict the future, at least in the sense that they tell you that a certain event will happen in a certain year. They're intended to give insights into the likely and potential ramifications of current and proposed policies, both formal and informal, that we've created. They're intended to help us test policies quickly, inexpensively, and at low risk, so that we can be more confident when we implement a policy in our organizations. They do not provide guarantees, but they can provide very useful and sometimes unexpected insights.

In which areas would you like to think more effectively about the effect your current policies could have on your organization's future?

Alternative energy: not as easy as it sounds?

Five and a half years ago, Pegasus Communications published my Out of Gas: A Systems Perspective on Potential Petroleum-Fuel Depletion. If you try out the downloadable model (see the column for instructions), you will discover my concern that we wouldn't start soon enough or be able to move fast enough to replace petroleum. Such delays could have a significant, perhaps massive, impact on society and on our economies.

Yesterday Forbes published America's Best Places For Alternative Energy and noted SRI's estimates that we need "[r]oughly 4.2 billion solar rooftops, 3 million wind turbines, 2,500 nuclear power plants or 200 Three Gorges Dams" to replace the amount of oil we use annually and that "no single category of renewable energy is growing anywhere near the speed it needs to bear the full brunt of displacing carbon-emitting fossil fuels anytime soon."

So my simple concept model identified a problem that's substantiated by more research at SRI (and by our daily experience, for if alternative energy sources were fully replacing petroleum, would we see overall energy price increases?).

That's part of the message of Is predicting the future really worthwhile?. My simple model didn't predict the future.

• It did identify past patterns of action that could credibly lead to a problem.
• It did use information that's known reasonably well (quantities of petroleum, even admitting that we don't know reserves as well as we'd like, as well as something about the dynamics of petroleum discovery and use) and apply simulation to explore what ramifications those factors might have over time.
  
• It did allow one to try different scenarios to see whether one's conclusions were sensitive to assumptions. For example, does it make a fundamental difference if petroleum reserves are 25% higher than assumed? (No, it just changes the timing of the problem.)
  
• It did provide a test bed for exploring strategies to see which might be more effective.
  

More research (in this case, in the form of the SRI study) substantiates the nature of the problem and helps us understand its magnitude and timing.

What systems are at work in your organization, your business, or your part of the world that might lead to consequences you don't want? How might you test your ideas? What can you change that might lead to better results? How might you test those ideas?

Is predicting the future really worthwhile?

Predicting the future, also called forecasting, is a popular business activity. Some managers want to know what the future holds so they can plan to accommodate it.

Yet I'm reminded by The Oil Drum: Europe's The Fantasy World of the UK Government that our record in forecasting isn't so great.

In that report, the U.K. government published a prediction on May 7, 2008 that gave four oil price scenarios. In the highest of the four, the "high high scenario," the price of oil hits $107 per barrel in 2010 and stabilizes at $150 per barrel by 2015.

As of my writing this, upstreamonline.com shows crude oil spot prices ranging from $138.96 to $152.58.

In 58 days, we've hit the prices they forecast for 7 years in the future.

Instead of predicting the future and then designing a business system to work well if the prediction is true, wouldn't it be better to design a business system that responds appropriately to whatever the future brings?

Isn't that hard? Yes, but so, apparently, is prediction.

That's one of the goals of system dynamics: to give us models which we can test against multiple futures to see if our modeled business systems work as well as we'd like independently of the outside environment. Once we are satisfied with the insights we've gained from modeling, we can implement our real business system with higher confidence it will work as we expect no matter what the future throws at it.

If you'd like to talk about such adaptive business systems, give me a call.

Sneak peak: Information Dynamics I / II

If you are a current University of Washington graduate student or you live within commuting distance of the University of Washington and if you are interested in learning about system dynamics in an academic setting, put IMT 586 and IMT 587 on your calendar for the coming winter and spring quarters.

If you took IMT 586 last year or if you have a solid background in the material of the first half of John Sterman's Business Dynamics, put IMT 587 on your calendar for the coming spring quarter (yes, that's nine months away). We plan to offer it, assuming we have sufficient enrollment.

I'll make a fuller announcement as we get closer. Ask if you have questions, and let me know if you think you're interested: I'm curious and interested.

Essential systems thinking for managers

This could be entitled "Lessons from teaching system dynamics."

As you may recall, I taught a graduate course in system dynamics at the University of Washington last winter, and I'm scheduled to repeat that course next winter.

While I won't write about that class nor about the systems thinking class I'm co-teaching at Bainbridge Graduate Institute, I wanted to note a few things I have come to think may be at the core of "systems thinking," at least in the system dynamics sense, as a result of thinking heavily about this in the process of teaching others:

• It's very important for people to understand that many of our problems are caused by the systems we create, not by externally-imposed actions. Understanding feedback ideas seems central to grokking that concept. Incidentally, grokking that concept should bring a bit of humility to each of us, and it also opens up possibilities: if we create our own problems, then we have some control over fixing those problems. That's a lesson worth remembering.
  
  
• Causal loop diagrams (CLDs) can be a key tool for making sense of the systems that create the problems we see. Better than that, their dialect, influence diagrams, as described by Geoff Coyle and others (for example, see SYSTEM DYNAMICS MODELLING: A PRACTICAL APPROACH), can be even more insightful and can replace stock and flow diagrams.
  
  
• While I'm not a fan of the "systems archetypes" you may have seen in The Fifth Discipline: The Art & Practice of The Learning Organization, there's a lot to be said for understanding what structures and what behavioral patterns are tied together. I don't mean understanding as in textbook knowledge; I mean understanding as in seeing the one and viscerally understanding the presence of the other. Can you look at data (for example, business results), find the pattern that contains the data, and use that to find the structure that likely caused the data? Can you see how to change the structure to make the data be like you wish? If you have the structure in front of you, can you work the other way to estimate the type of behavior you might expect to see? Can you test your theories through simulation or through comparison with real-life situations?
  
  
• Recognizing the difference between stocks and flows is every bit as important as I've written about before. Add to that being able to calculate mentally the changes you'll see in a stock, given the changes you're creating in a flow (mental integration, in other words), and you'll have a better understanding of the impact your actions may or may not have.
  

I came to the conclusion that understanding these ideas well would go a long ways towards helping anyone think more insightfully about tough challenges. Getting there isn't trivial: it seems to require a bit of math and a bit of simulation experience, and having a lot of both seem to help. By themselves, though, math and simulation aren't sufficient; this requires a lot of thinking.

What I'm coming to realize is that having people with these (and other) skills in the management meetings of our companies would be a great help. Instead of just arguing points based on best (unaided) intuition, someone might look at the data and draw some provisional inferences. Someone might think seriously about the type of structure that might have created that data pattern and look for evidence of it in the company and its environment, sketching and discarding diagrams as they go. People might understand the likely effect of interventions based on the current and proposed structure.

Many of you who read this may be able to do all of this already, and that's great! Is it helping you in your work? I hope so; it should.

Others of you may understand when you see others do this but not be able to do it yourself. That's okay; that's why Facilitated Systems is here. If you want to discuss whether your organization might benefit from these ideas, contact me today.

President Bush and greenhouse gases

I haven't been a political blogger, and I'm not about to start now. Yet the news of the past few days does offer ways to illustrate systems concepts I've mentioned before, and so I thought I'd point out what I hope is obvious to all here.

For but one example, take US President Bush's goal of having greenhouse gas (GHG) emissions stop growing by 2025, which is stirring up comment world-wide.

In system dynamics terms, GHG emissions (largely CO₂) are a flow, and the amount of CO₂ in the atmosphere is a stock. If you recall what I've written before on stocks and flows, you'll see that stopping the increase of a flow does not mean that the stock will decrease; it simply means that it will increase less rapidly.

In other words, even if we do meet this goal, things may well continue to get worse well after 2025, but they will at least get worse less rapidly after then.

I want to show you a little model that demonstrates that behavior, but, to publish it here, I'd like to get the numbers at least close to right, and that would take a bit of research time I don't have tonight. Let me try an analogy, instead; those of you who studied and remember the calculus can probably make a more elegant argument, and those who do system dynamics models can create one on your own in a few minutes (if you have the needed parameters, let me know, or post a pointer to your model).

In the real world, we are emitting CO₂ into the atmosphere by breathing, burning fossil fuels, and the like. That stock of CO₂ in the atmosphere is growing and threatening climate havoc.

Some of that CO₂ is taken out of the atmosphere each year through the action of photosynthesis and perhaps other mechanisms.

According to the science I read, we have too much CO₂ in the atmosphere at present, and our global CO₂ emissions per year, already above what the environment can naturally purge, are increasing. If that weren't the case, there would be little reason for President Bush's call to action.

Let's look at an analogous situation. For example, let's say you have a bathtub that's three-fourths full of water. The drain is open, but it's partially clogged, and so it's draining slowly.

In addition, the faucet is turned on, putting more water in the tub. It so happens that the water is currently coming into the tub faster than the partially-stopped drain can take it out, so the water level is rising, causing fears for the well-being of the bathroom floor.

The person controlling the faucet is opening the faucet as we speak, letting water come into the tub at an ever faster rate. That person, realizing the risk to the floor, promises to stop opening the faucet anymore in about 15 minutes.

What do you think will happen to the floor?

Even with the rough data I supplied, I hope you can see that the water will rise increasingly rapidly for the next 15 minutes. If the person takes their hand off the faucet in 15 minutes, the water will continue to rise until it overflows the tub (assuming it doesn't overflow sooner). The only way to save the floor is to reduce the flow of water from the faucet to below the flow of water out of the drain before the tub overflows. Even if they started reducing the flow of water out of the faucet now, the water in the tub would still rise until the inflow was less than the outflow.

Of course, this is a silly little example; the real world of GHG emissions is much more complex. Yet the general principle of stocks and flows holds: as long as the inflow exceeds the outflow, the stock will rise.

I'm not about to use this short, informal essay to argue for or against specific GHG or climate proposals or to try to balance climate stability against economic stability. I am suggesting that we all remember the lesson of stocks and flows when we are thinking about or evaluating policies such as these.

PS: Thanks to colleague Wayne Wakeland for, in a totally different situation, reminding me of the effectiveness of simple bathtub models (and I hope it worked here!).

System dynamics in practice: lessons learned

Drew Jones, Don Seville, and Dana Meadows of the Sustainability Institute wrote Resource Sustainability In Commodity Systems: The Sawmill Industry In The Northern Forest. That provides a good example of a way to use system dynamics models (it's of course not the only way).

I like that paper for several reasons. The model seemed good (at least from the explanation; I haven't explored the model yet), and the explanation of the model and its implications seemed good. What may be especially interesting to some is that they spent the last third of the paper talking about what they learned about the human side of the equation: how people responded to their work, and what they learned from that. The top of page 26 seems noteworthy, although you'll probably have to read the preceding 25 pages to make good sense of it.

Focusing on the symptom or the cure?

I recently read Jay Forrester's "Churches at the Transition Between Growth and World Equilibrium," a paper prepared for the National Council of Churches and published as part of Toward Global Equilibrium: Collected Papers, ed. Meadows and Meadows and published in 1973 (also available from Pegasus Communications).

Forrester emphasized two points that may be worthwhile today to some of you reading this:

• When fundamental changes happen in the environment in which we operate, old rules of thumb likely no longer appply.
  
• Trying to fix problems by focusing on symptoms is highly risky, for, even in static times, our intuitions don't always work as well as we need. In times of transition and turbulence, it's especially important to ensure one understands the dynamic causes of the problem being faced before engaging in actions that could be counterproductive.
  

Forrester was a bit more direct than I was in my paraphrase. "One should never attempt to find a solution without first establishing the dynamic causes," he wrote, and system dynamics was his tool of choice for testing whether one had found the underlying causes or not.

Today we face increasing energy costs, increasing population density, increasing effects on climate and on the inhabitants of the Earth from the by-products of our industrial and private activity, fundamental shifts in the distribution of production and wealth, a scarcity of resources that were abundant in the past, and the fall-out from overextended financial markets. No matter your type of organization, the complexity of these changes taxes our understanding.

In a time of such changes, how do you make sense of the challenges your organization faces? How do you determine which actions to take to achieve the sustainable successes you want?

If you'd like to discuss ways in which you might make more sense of those issues, ways you might understand the likely causes of the dynamics you face, and ways you might test your proposed actions faster and at less risk than by just trying them, get in touch. Perhaps I can be of help as you seek to fix problems and not just reduce symptoms. Of course, there's no charge or obligation from such an initial discussion.

More on LTG

I'll try to stop writing about LTG for a bit, but, before I do, I did find one other interesting paper that some of you might want to read. Matthew Simmons of Simmons & Company International wrote Revisiting The Limits to Growth: Could The Club of Rome Have Been Correct, After All?" back in October 2000. It appears to be a very readable, data-rich analysis of the changes in key parts of the world by someone who has been active in the energy business for decades. Check it out.

Simmons is a prolific writer; he has published a series of speeches and papers online (check the archives and the Oldies but Goodies, too). I'll have to come back and read more later.

Postscript: While I should be doing other things, I'm reading more of his articles. I encourage you to read his PEAK OIL: Is It Real? When Might It Occur? from February 25, 2008. While you need to start at the beginning to get context, check out his recommendations starting on slide 48:

Only viable solution that can work now:

• The solution: TRAVEL LESS
  
  
  
  • Less long distance commuting
    
  • Grow foods at home
    
  • Make goods locally
    
  
  

What do you think?

Cassandra's curse and LTG

Almost two years ago, I posted about Limits to Growth: The 30-Year Update. Whether you saw that posting or not, I suspect you know Limits to Growth, often referred to by its initials as LTG.

Now Ugo Bardi has written Cassandra's curse: how "The Limits to Growth" was demonized in The Oil Drum: Europe. It's his view how LTG started to stimulate true dialog about a major challenge for the planet and how it then became "everyone's laughing stock" (well, perhaps not everyone's).

That's changing. As Bargi notes,

Climate studies have also brought back the limits of resources to attention; in this case intended as the limited capability of the atmosphere to absorb the products of human activities. In this field, the LTG study can be seen as having taken the right approach from the beginning; modeling for the first time the interaction of the environment with the human industrial and agricultural system.

If you've not read LTG, I encourage you to read it now. If you'd like, you can buy Limits to Growth: The 30-Year Update online, or you can find it in your favorite library (you can change the country or specify the location more precisely).

Tipping points

A few years ago, thanks to a lead by John Sterman, I posted a note about a Proceedings of the National Academy of Sciences (PNAS) article that attempted to quantify the carrying capacity of this planet. The concept of carrying capacity is important; if you try to exceed the carrying capacity of an ecosystem, you will eventually be brought back. What's even more worrisome is the potential that you might eat up carrying capacity while you're in overshoot: if you do that, the equations suggest you'll eventually suffer a collapse.

There's another concept that's discussed both in the systems literature and the popular press: the tipping point. That's the claim (loosely) that systems may reach a point where a slight addititional change will lead to a qualitatively different state. Often the definition includes something about irreversibility (you can't go back) or at least about the difficulty of reversing a change due to the reaching of a tipping point.

Now John Schellnhuber and his colleagues have published Tipping elements in the Earth's climate system in the February 12, 2008 issue of PNAS. They've also published appendices, not in the printed version, that provide their formal definition of a tipping point, evaluate other potential tipping elements, and describe how they elicited the information for the main article.

Those of you interested in tying systems concepts to the real world (hopefully that's just about anyone doing systems work, although some may be more interested in some applications than others) might find this of real interest. Those of you wondering about the risks of climate change might find it informative.

For a report on Schellnhuber's lecture at the annual meeting of the AAAS, see John Schellnhuber’s Third Industrial Revolution, a New Approach to Addressing the Hazards of Global Warming by Julia Whitty in Mother Jones.

System dynamics, black swans, and the management of business

I'm currently reading Nassim Nicholas Taleb's The Black Swan: The Impact of the Highly Improbable. While I intend to tell you more of what I think when I'm finished, I have an early impression, based on stories such as what he calls "Hume's problem" (or the turkey problem). That's a problem in which everything seems to be getting better and better, only to change direction suddenly and drastically for the worse. In his example, the turkey sees life as a daily succession of friendly humans offering food, only to have it cut short in a manner seemingly quite out of character for life as the turkey has perceived it. (As Taleb points out, it all makes eminent sense to the butcher.)

I think that's part of the reason for system dynamics as yet another tool for thinking and working. As Geoff Coyle points out in his System Dynamics Modelling: A Practical Approach, top management is concerned about things such as the consequences of actions, the likely future, and robustness against uncertainty (p. 15). One of the basic parts of the system dynamics approach is to challenge preconceived notions of the extent of the system causing the current situation: are we looking over a broad enough time span, are we including enough of the actors and actions, and are we paying attention to feedback effects (what Taleb calls recursive effects on p. xxii), where something we do today might come back and affect the situation we face tomorrow?

While there are no guarantees, that unfortunate turkey, had she had good training in system dynamics (or a competent system dynamicist at her side), might have been inspired to look at life over a 5-10 year time span, not just the few months she had experienced. That might have surfaced the fate that led to her demise as part of a regular pattern (albeit one that occurred rarely compared to her lifespan). Had she looked not only at the friendly human feeding her and the other turkeys eating with her, she might have noticed the butcher looking eagerly over the fence from time to time and asked about his role in her life. Had she realized the implications of those observations, she might have decided not to become quite so friendly with her "caretaker," she might have decided not to eat nearly as much (if she were scrawny, might her fate have been different?), and she might even have encouraged the other turkeys to join her in an escape attempt.

Now I don't think that the use of system dynamics conveys infallibility; in fact, that's why I'm reading Taleb's work, to figure out more places my insights may be fallible so that I can make them more robust.

Taleb advocates tinkering as a way to make progress; I see system dynamics as a way to tinker faster and think more effectively in support of your (and my) goal of more effective action.

While my comments may be out of the main focus of Taleb's thesis (system dynamicists tend to focus on the deterministic, not the random, even as they seek to help you be able to respond better in the presence of the random), I don't yet see them in contradiction. I offer them to you in the hopes they are of use to you. Now it's my (and your) task to try to disconfirm them; the longer we can't, the greater the likelihood there's something worth attending to!

If you want to tinker faster with the situation you find yourself in but don't want to risk your business each time you tinker, let's talk.

Thanks to Andrew Gelman for his posts that led me to Taleb's work.

Looking from the outside in...in English

Realizing that the majority of those reading this blog may not read German, I put together a quick summary of Henrik Müller's arguments to which I pointed last Friday.

In his most recent article, he claims that, in a somewhat healthy economy, we have three feedback loops that would stabilize our economy and dampen out our current problems:

• People and the government would spend more to stabilize consumption.
  
  
• Government would borrow more in order to support its temporarily increased spending.
  
  
• The Fed would lower rates to encourage consumption (and, presumably, investment).

He claims all three are at their limits here. He quotes an OECD number that says our savings rate is -1.0%, and housing values are dropping, so we have nothing left to spend.

He says our Federal budget deficit is only 3% of the GDP, and our debt, at 60% of the GDP, is 60% beneath the norm in Europe, so we could increase the debt to try to pull us out. Unfortunately, because we save so little, the only people who can buy that debt are foreigners.

Finally, while the Fed has room to lower the rate, he sees banks as ready to absorb any excess cash rather than loan it out, and he worries about inflationary pressures that may present, thanks in part to an ever-weakening dollar.

In the current political scene, he sees candidates pushing protectionist agendas and hope, while he sees our real hope as lying in global product and capital markets. In fact, the only good news he sees is that the devalued dollar has increased exports and that foreign governments seem ready to invest huge sums in US banks, and he's worried that we don't see that for the good news it is.

What do you think? If you read German (especially if you read it natively), what important points do you think I missed from the two articles?

Looking from the outside in...

One of the things that doing enough system dynamics work teaches one is the benefit of perspective. Sometimes when you're in the middle of something, it's hard to see the forest for the trees. Standing back a ways and, just for a moment, trying to drop any emotions that are tied up in one's current situation can give one better insights.

That's what system dynamics modeling can often do: change a situation in which you're an intimate part to a situation you and your colleagues can look at with a bit of perspective. It also gives you the ability to test ideas on the model before you test them on the real situation.

When we can't get that perspective ourselves, either because of time limitations or because we can't figure out how to do it successfully, reading or hearing what others say about us can sometimes provide us similar perspective. Sure, those outsiders may not understand our situation as well as we do, at least in the details, but they may help us find a better perspective into which to place our more detailed understanding.

If you live and work in the USA, you've no doubt read much about our economic situation recently. I've suggested before that it's healthy to see how others see us. Recently Henrik Müller of the German business magazine manager magazin posted an article entitled Amerika steht mit dem Rücken zur Wand ("America stands with its back to the wall"), a follow-up to an earlier and more data-filled Nach der Orgie ("After the Orgy"). If you read German, or if Google Language Tools suffices, I encourage you to read these articles. He may not be correct in all his assessments, but he may give a better perspective than the headlines in the nightly news about sub-prime mortgages, foreclosures, and other problems. Certainly his earlier article does something I like to see: he gives graphs of at least some key data over a five-decade span, which is more useful for seeing patterns and gaining perspective than merely seeing what has happened this century.

How do your mental models compare with his? What are you doing in your company to adapt? What should you be doing?

IMT 586: Information Dynamics I

If you're in the Puget Sound area and have been thinking about enrolling in IMT 586 (Information Dynamics I, called system dynamics by most of the rest of the world) at the University of Washington, now's the time; the quarter starts next week.

For more on the course, see my two prior announcements.

Top postings of 2007

In the last 12 months (to be precise, from last December 28, the day after the Top postings of 2006 entry through December 26, 2007), you have chosen ten top postings on Making Sense With Facilitated Systems as ranked by unique pageviews in Google Analytics.

As I noted last year, there are potential statistical problems with this list. Those who read my blog every day using the main URL don't get counted; both last year's and this year's tallies were made from those who landed on specific URLs as reported by Google Analytics (but excluding visits I may have made). That may be okay; those who linked to specific pages may have cared more about them. Recent entries have a more difficult hurdle, as they haven't been around as long to be viewed. The dates don't quite line up with the calendar year, although I suspect that makes little difference in the results. If you know of a better way, let me know.

10. For some time now, I've been using an open source simulator for my system dynamics work because it seems to help me think more effectively. That doesn't mean I've given up on commercial tools; I still use iThink for creating interactive environments, and I will be teaching IMT 586 at the University of Washington using Vensim PLE (and I may be using it in professional applications, as well). Last April, I combined my interest in the arts with my interest in this new approach to system dynamics in a public article about marketing program for symphony orchestras. You selected TAFTO 2007, the pointer to that article, as number ten on the list.
    



9. I've written several articles about data and numbers. Making more sense with numbers part 3 offered an easy process to plot data you receive in email or reports.
   



8. The words we use can be vitally important in helping us think productively about key business, organizational, and social challenges. In A systems language for business, number eight on the list, I described one team's evolution towards a better language for discussing business issues, thanks to a course they took from me in system dynamics modeling and simulation.
   



7. Good data helps us ground our thinking in reality. Still more on data, a pointer to several online sources of data, captured the number seven spot.
   



6. Growth can create problems (witness any of the bubbles that have occurred over history), but where are good examples of successful companies that intentionally don't grow? Number four on the list is Small Giants: the American Mittelstand?, pointing to a book that answers that question.
   



5. Sometimes old technology still has utility; sometimes it still attracts interest. At number five, Technology comes full circle, a description of my continuing use of a slide rule in my work, certainly fits that description. For those who are interested, it points to a source for new slide rules.
   



4. When I first started work as an engineer, PERT charts were done using mainframe computers or hand-drawn charts. Today, project management has become a profession with a certification process, and automated tools with graphical user interfaces have long since replaced tables of numbers and dates. Your sixth-most-popular entry was Critical chains: a decade later, my revisiting of Eliyahu Goldratt's critical chain theory that linked to Tom von Alten's revisiting of his views on the approach.
   



3. Productivity is obviously important to you. Your third most popular posting of the year was a surprise to me: If you can say it, it's done, an entry about the array programming language J.
   



2. Barry Richmond has a deserved place as an educator and thinker on system dynamics and systems thinking. I posted a link to an article he wrote about systems thinking and followed up with "Scientific thinking" the modern way, a differing view on the application of modern scientific thinking in system dynamics. That was your second favorite posting from 2007.
   



1. The 2007 posting you viewed the most was the series Making musical sense by email, showcasing a conversation between music critic, composer, author, professor, and consultant Greg Sandow and me that used a system dynamics model to explore the aging of audiences for symphony orchestra concerts in the USA. Now I'm curious: was its popularity because of the topic (music), the approach (a somewhat novel approach to using system dynamics), or the fact it was a real conversation between two people? Let me know.
   

All of those postings were made in 2007. It wouldn't be fair to finish this list without noting that some postings from prior years did rank higher than some of these. Here's the all-time top ten list of postings from Making Sense With Facilitated Systems as measured by your viewings in the last twelve months:

15. TAFTO 2007 (2007)



14. Making more sense with numbers part 3 (2007)
    



13. A systems language for business (2007)
    



12. Still more on data (2007)
    



11. Small Giants: the American Mittelstand? (2007)
    



10. Technology comes full circle (2007)
    



9. System Dynamics for Cheapskates (November 2006)
   



8. Critical chains: a decade later (2007)
   



7. If you can say it, it's done (2007)
   



6. "Scientific thinking" the modern way (2007)
   



5. Making musical sense by email (2007)
   



4. System dynamics with MCSim (November 2006)
   



3. In praise of the lazy employee (April 2005)
   



2. System dynamics and program evaluation (June 2005)
   



1. Making sense with numbers (November 2006)
   

That list includes the top ten postings written in 2007 plus the five entries written in prior years that were at least as popular as the top ten 2007 postings.

As 2007 draws to a close, I want to thank you who read Making Sense With Facilitated Systems and to invite you to continue with me in 2008. If you have suggestions or feedback for this blog, contact me.

I would be honored to be of service to you or your organization in 2008. If you're trying to make sense of tough business or organizational challenges, curious how I might be able to help, or just want to talk about some of the issues you face or that I write about, get in touch.

System dynamics course

Have you heard of system dynamics here or in your reading elsewhere? Would you like to learn more, including how to create computer simulation models to make sense of some of the challenges and puzzles you face, be they at work or in the news?

The University of Washington Information School is offering IMT 586, a first course in system dynamics, in the winter quarter. Yes, I'll be teaching it. You can learn more about it, including tips on how to register, in my earlier posting called Information Dynamics: IMT 586. My instructor class description lists the three goals I have for this course. For anyone concerned about the level of mathematics required in this course, that page also points to a brief description by the author of our text describing the level of mathematics needed to do this work.

I look forward to meeting some of you in that class!

The voice of a child ...

I write here about the environment from time to time, for I think there is a significant likelihood that we will face important transitions in our lifetimes or the lifetimes of our offspring that will impact us in multiple ways: personally, in the way we live, and professionally, in the way we produce what we need to live and earn what we need to acquire those things we need to live. (If TIME is right, we may not have to wait that long for those transitions.)

Presentation Zen posted You can learn a lot from "a child", a speech by Severn Cullis-Suzuki at the 1992 Earth Summit in Rio De Janeiro. It touched on the big issues I perceive we face: figuring out how to make life sustainable on this planet, and figuring out how to live together. Watch it.

I also write about presentation skills from time to time. As Presentation Zen reports, Al Gore called this "the best speech at Rio."

Testing the speed limits

In the Fall 1990 Sloan Management Review, Christoph-Friedrich von Braun published "The Acceleration Trap," calling into question our focus on shorter time to market. He later published the related The Innovation War (Prentice-Hall International Series in Industrial and Systems Engineering) (a book still on my reading list).

Tom Peters blogged about it (briefly). Brice Dattée and Dr. David FitzPatrick published The Acceleration Engine: Pattern of Technological Development, a mathematical exploration of the topic from a slightly different perspective. Barry L. Bayus of the University of North Carolina at Chapel Hill wrote an interesting review of his book. Eugene Garfield wrote another review. Alexander Kandybin and Martin Kihn quoted von Braun's work in The Innovator's Prescription: Raising Your Return on Innovation Investment in strategy+business.

His words haven't been accepted universally, as anyone in a wide range of industries may attest to once they leave work at 9 or 10 in the evening. On the more literate side, Preston Smith wrote From Experience: Reaping Benefit from Speed to Market. It was the subject of a debate (Die Innovationsfalle) at the 2001 CeBIT.

If von Braun is right, there's another risk to growth besides running out of natural physical resources: there's running out of time. It's analogous to an addiction: we need to keep getting more and more of the substance in question (reducing time to market, in this case) to remain satisfied. If we can't maintain our "supply," we crash and go into withdrawal.

In this case, the risk von Braun pointed out was the limit to how short one can make product cycle times and the risks to any financial success that's built on steadily decreasing time to market. Perhaps we can eventually cycle through product generations faster than our customers will accept them (do you want to replace the computer you bought yesterday with a new generation today and then do it again tomorrow?). Perhaps we'll begin to hit physical limits to speed (zero time to market would seem to be a very hard limit to exceed). If we try to break through that limit, whatever it is, and fail, we lose the business benefits we've been sustaining based on constantly improving time to market in the past.

I'm sure many of us are tempted to say, "We don't know if there's a limit or not; we should push forward as hard as we can, and we'll let the real world tell us if there are limits." Unfortunately, if von Braun is correct, hitting those limits won't mean a leveling off; it will mean a crash, and that could have a ripple effect that none of us will enjoy.

Does this mean I'm against reducing time to market or cycle time in general? No. There are many places in our organizations where reducing delays can help, likely including the delay from a customer perceiving a real problem to being able to obtain a product or service to address that problem. Without thought and testing, though, it's hard to make generalizations.

I perceive that time to market reduction is like growth: neither serves as an eternal, prime goal, but each may have its place in at the right time and in the right situation. I do encourage you to do your own reading, think about it, and draw your own conclusions.

How do you know if it's the right time and situation for you? If you'd like to explore ways to discern whether now is such a time and this is such a situation for your organization and how you might create policies that further your goals, let's talk.

Information Dynamics: IMT 586

Have you ever wondered ...

• what causes some ideas, products, and companies to become fads that peak and die, while others have staying power?
  
  
• why there are business cycles?
  
  
• what causes some diseases to become epidemics and others to subside with little effect?
  
  
• why real change often takes so long?
  
  
• the role information plays in the answer to each of these questions?
  

Would you like to learn to answer these and other such questions
yourself? Are you a student at the University of Washington, or do you live within commuting distance?

Then sign up for the Information School's IMT 586, Information Dynamics I, in the Winter Quarter 2008. I look forward to seeing some of you there.

Focus on the patterns, not the events

If you've ever seen the video that accompanies The Beer Game, there's something eerily familiar in the news about real estate in the USA. (Disclaimer: The video I saw was a VHS tape with a PBS segment on a previous boom and bust cycle in real estate. I can't promise the current DVD contains the same material.) Despite 50 years of knowing that the principles of feedback control theory apply to human and organizational systems, we still create systems with poor information feedback that get us into the ecstasy of boom times followed by the despair of busts.

What does this mean to us, assuming we're not directly impacted by current real estate woes? Where do you see the potential for boom and bust in your world? How do you know? How do you test your hunches?

I can't tell you when you'll experience a bust, but I can help you discover how you can design a business or organizational system that is less likely to experience such boom and bust cycles.

Incidentally, if you'd like to play The Beer Game but don't think you have an opportunity, check out the online version.

Structure influences behavior

That's part of a message I try to convey: structures tend to create patterns, and events are usually part of patterns. If you have to fix (change, eliminate) an event, don't focus on the event. Rather, see if the event is part of a pattern, and focus on the structures that fix that pattern. Then you'll see the events become fixed.

That's the reason I apply system dynamics to organizational problems: it helps us find the pertinent structure.

In It's the invisible structures that get you, Andrew Taylor says it eloquently.

Rehearsing

I often help people with presentations, and I've noticed that those who rehearse seem to be those who do better. Now Garr Reynolds of Presentation Zen has done an excellent job of explaining the creative process of presenting ideas to others in his Steve Jobs and the art of the swordsman.

Note the two keys to presentation success:

• Intense rehearsal in a team setting
  
• Absolutely no attention to technique or form in the actual presentation
  

Reread Garr's comments, if you need to, and note comments such as, "...once we allow our mind to drift to thoughts of success and failure or of outcomes and technique while performing our art we have at that moment begun our sure decent." [sic]

How can we possibly get through a presentation while following the second key? By following the first key until we have internalized what we want to say, how we want to say it, how others will hear it and respond, and what we can do if something goes differently than we expect. Then we have to rehearse it some more.

As someone once noted, we often rehearse something until we get it right. That means we may have done it wrong 20 times and right once; which do you think will stick with us better?

I think the same thing applies in other areas of our professional lives, and I think Dietrich Dörner and Harald Schaub might agree. That's why I wrote A somewhat unified view of decision making: to suggest the importance of spending time wrestling with what we do at a time that's apart from the actual doing. Whether we use computer simulation, scenario planning, role playing, or something else, the opportunity to rehearse what we do professionally before we do it and to learn from what we actually do afterwards to improve for next time is exceedingly valuable. And it's the cyclic action learning that helps us improve and helps keep us from getting fixated on a bad idea.

If you're still thinking of presentations, check out Garr's presentation tips.

Is business getting worse?

Bloomberg says "CEOs See `No Clear Signs' of Crisis as Woes Intensify." Are things really getting worse, even as people put smiles on their faces, as that article seems to indicate?

We obviously won't know for a while. Even if things get worse for some companies, others will likely do okay, and some will thrive (or, if things go well, others will likely do okay, and some will suffer).

To a large degree, the key is being good at responding to what happens, not simply what happens. We get good by being lucky, by thinking clearly, or by having been in this situation before and having learned (or by some combination of those). While I have no help for you in the luck category, there are myriad approaches to thinking clearly, and I've tried to touch on a few in Making Sense With Facilitated Systems.

You might say that there's no way to experience the future before you get there (the third alternative). As Dietrich Dörner and Harald Schaub point out, that's not necessarily the case. Simulation (system dynamics, usually) is a way to explore challenges we might face in the future and to learn which strategies are likely to be more successful.

How are you preparing for the challenges you might face? If you'd like to talk about some of the possibilities, drop me a line.

Systems thinking and art

Not long ago, The Diagram published one of my system dynamics diagrams because they were attracted by its design ("But is it art?"). Recently I discovered a quotation I wanted to share with you, for I think it conveys something important about about organizational or societal simulation and modeling as well as about art.

Suggestion—the part standing for the whole—is a principal means by which art communicates; this is why art often tells us so much with such economy.

Jane Jacobs, The Death and Life of Great American Cities, p. 377.

That's what system dynamics in particular and systems thinking in general is all about: economy in expressing the essence of a problem to foster economy in solving the problem and economy in creating deeper insights to be able to solve the next, similar problem.

I like that quotation.

I like the book, too; I'll probably write more about it soon.

Counterintuitive Behavior of Social Systems

Jay Forrester's (new: link to several of his papers) Counterintuitive Behavior of Social Systems (new URL) is another classic worth reading and re-reading. The article offers food for thought, not final answers. If you start, I encourage you to keep going to the end (I'm saying that, because I know it's 28 pages of text and everyone's time is short). As a bit of encouragement, here are two quotations. First, from p. 24:

Figure 8 shows the world system if several policy changes are adopted together in the year 1970. Population is stabilized. Quality of life rises about 50 per cent. Pollution remains at about the 1970 level. Would such a world be accepted? It implies an end to population and economic growth.

Then, on page 27, he writes, "Our greatest challenge now is handling the transition from growth to equilibrium."

Start at the beginning to get the context for both quotations, and see what you think by the end. These are important issues; don't blindly accept his admittedly somewhat preliminary ideas (see section XI), but don't blindly reject them, either.

Thanks to the HPSIGWiki for the reminder.

Why are we headed there?

Yesterday I posted a rather dark story about what we could be facing. As with any system dynamics model, it's showing the likely effect of the modeled policies; it's not predicting the future. (There is a difference; call if you'd like to chat about it.)

If that message is so dark, why don't we see much action to change our course? (Admittedly, we're beginning to see more action now.) The Oil Drum published Living for the Moment while Devaluing the Future, an essay exploring just that question. For a more academic approach, see Larry Karp's Global Warming and Hyperbolic Discounting, an article referenced at the bottom of The Oil Drum article (now on my reading list—I've only had time to skim it so far).

I think these ideas are important to understand and explore as we try to craft a "soft landing" from our ecological overshoot.

I think they may also be important to us in business. We get used to constant discount rates, because that's what we use. Do our customers and our bosses (they do have similar roles in our lives) really think that way, or do they do hyperbolic discounting, too? Would it it make a difference which they use? Would that difference imply we should act differently than we do?

Where are our policies leading us?

A policy is a set of guidelines or rules by which we make decisions. We have certain policies by which we work and live, even if we don't always make those explicit. If we see a pattern of decisions, decisions that seem cut out of the same mold, that's likely evidence of a policy.

François Cellier of the Institute of Computational Science of ETH Zürich, Switzerland has published an article, Ecological Footprint, Energy Consumption, and the Looming Collapse, at The Oil Drum that examines the potential effects of our policies towards growth. It's a high-level view, to be sure, but sometimes those offer great insights. Be sure to read both the article and the accompanying slide set (the article isn't that long; it's the 333 comments that take up most of the length).

I think this is a very important discussion. That's why I think it's important for each of us to be skeptical about such claims. It's not because I think he's wrong; his analysis, at least so far, seems good. It's not a call to wait for "proof," for, as John Sterman points out, we're not really waiting; we are doing things to the environment every day. It's not a call to ignore the claims, for that's not being skeptical; it's a call to test them and then to act based on what we determine. It's not a call for depression; Cellier does show a way forward (especially in the slides).

By suggesting we be skeptical, I may give the impression I think we can ignore this for a bit. I want to re-emphasize that the IPCC and others have given some pretty clear signals that the time to act is now (actually, the time to act was some years in the past; the next available time to act is now).

What does this mean for our businesses and for business in general? I think it means figuring out what to do to ensure the sustainability of our businesses and our economic system in the face of the challenges the best science says await us. The key lesson from "Out of Gas: A Systems Perspective on Potential Petroleum-Fuel Depletion" was that we not wait too long to attend to signals we get, for our systems have inertia, and we can't, as much as we might wish, always change direction instantaneously. Pay attention to Cellier's description of easy and difficult problems starting on slide 38; the signals may not be as we'd normally expect. Sometimes we can't wait to feel the wind from an impending storm; we have to rely on forecasts from meteorologists to know when to board up windows in the face of an approaching hurricane.

We can also apply that message to more typical business decisions. Do we discover we will need to add (or remove) capacity well in advance, so we can react smoothly, or do we make such discoveries only when the market begins to complain loudly? How do we figure out whether our latest initiative is about to make real progress or it's about to fail and we should abandon it and change course?

Reacting too soon can lead to the Chicken Little trap: if we respond too quickly, we diffuse our energies by responding to simple noise; if we respond too slowly, we're trapped. One of the lessons I've learned is that feedback models (of the sort I've sometimes discussed here, also called system dynamics models) can help us find what things to monitor so that we have a clearer picture to guide our decisions.

What do you think?

But is it art?

Apparently The Diagram thought so. They found my TAFTO article (new URL), liked the graphics, and asked to publish one of its diagrams in their issue 7.2.

Perhaps that's another advantage of working slightly outside the mainstream approach—it gets noticed. Drawing a standard type of diagram with different tools made it stand out a bit and may help it communicate more effectively.

What do you think?

By the way, try their Graphviz interactive diagram.

IMT586: a course in system dynamics

While I have taught system dynamics and systems thinking courses and workshops for various organizations, some have asked if I was planning any public courses. I can now tell you that I'm the lecturer in spe for IMT586, a graduate course in information (system) dynamics for the Information School at the University of Washington. IMT586 will be offered starting in the winter quarter of 2008. It will be offered in the MSIM program to both day and executive students. It currently appears it will also be open to non-matriculated students, so, if you live within commuting distance of the University of Washington's main Seattle campus and are interested in learning system dynamics, check it out.

As we get closer and more information is available on the UW iSchool Web site, I'll post updates on Making Sense With Facilitated Systems.

Of course, if you want custom training tailored for your organization's needs, feel free to contact me.

An accidental experiment

I've published a number of At Any Rate™ columns through Pegasus Communications. They consist of text designed to capture people's interest up front and to remind them of what they experienced later as well as a simulation model people can download and explore. The model leads people through three stages: an initial stage-setting exercise, a more complete model to show added complexity in the problem at hand, and an exploration area where people can dig a bit deeper to try their hand at addressing the problem.

Pegasus Communications advertises each At Any Rate in their free Leverage Points newsletter that has a rather large circulation, and they set up a discussion area in their Pegasus Forums for each one.

In other words, that column seems to be planted in a fertile ground in which to talk about such things. The models are interactive. They tell a story. They are published on a high-visibility site and advertised in a high-distribution newsletter. There's a space established to enable discussion.

Yet I've gotten very few off-the-record comments (all favorable) about those columns. I've seen very few comments in the Pegasus Forum. I'm not sure anyone has contacted me about what they've seen there. I'm not complaining; I know that I don't write letters to the editor of the local newspaper, even if I strongly agree or disagree with what the newspaper has published. As a result, I don't necessarily expect (although I would welcome) lots of dialog about what I post online.

On Monday, April 9, I published a similar model (new URL) on Drew McManus's Adaptistration as part of his TAFTO 2007 (new URL) series. It was not interactive; rather, it contained diagrams, graphs, and a computer program (or a text-based model, which is the same thing). Admittedly, I tried hard to use literate programming ideas to intertwine the model and the story so that it would be more interesting and readable, and I let two others in the potential audience see an advance copy so I could find and fix any impenetrable sections.

Within a day, I had a thoughtful, lengthy comment added to that column. Two bloggers made quite favorable comments about the essay. I know of at least one person who had been telling me he'll get to the latest At Any Rate any day now who read and commented on my TAFTO column within a day.

What gives?

While I realize that the singular of data is anecdote, I think that this is showing me the barrier we erect when we ask people to download, run, and learn from an interactive model. While the barrier might be lower if I had used a simulator for At Any Rate that ran in a browser, I'm not sure; one would still need to take perhaps half an hour, perhaps more, to work through the model. It takes much less time to install the software, and i'ts a one-time action—a number of readers already have it.

The barrier may be more complex than simply the challenge of installing the isee Player required by the At Any Rate column. To explore and really learn from a simulation, someone needs to be willing to experiment. That means taking the time to understand the environment, to formulate hypotheses, to write those hypotheses down, to run various tests on the simulation model, to compare the results of the test with the hypotheses, and probably to try new experiments based on the learnings from initial experiments. That's far different than just opening the application, pressing a few buttons, and seeing what happens.

Needless to say, most of us who create such interactive simulations try hard to guide the user through the process. Most of us encourage people to form those hypotheses and to document them in writing or in graphs before starting a simulation. Yet I know (from personal experience—I'm not immune) that it's far too easy to treat a simulation as a video game: press the button, and see what happens. That's not often the path to deep learning.

With the non-interactive version, people can read just a paragraph or skim the entire article to see if it seems interesting. They can come back later to dig more deeply. They can print it out, if they wish, and read it on the bus on their commute. If a text version of the model is included, they can, if they want, copy it into the simulator and explore it themselves.

My lesson? Interactive simulation is no panacea, and it may be a disadvantage if I want to get my story told, especially if my audience consists of busy or high-level people. By telling a good story, I can help the reader learn something, most likely in less time.

Is there a role for exploration, experimentation, and interactive simulations? Certainly! But I need to be sure to consider the audience, their current interests, and what they know and want to learn.

I'd welcome others' insights and experiences. In an action research sense, I'll spend some time trying to disconfirm my conjecture; in the process, I might learn more.

Clark County Adaptive Management Program

Much of the time, we all keep certain details of our work private. Either we or our clients or customers don't want to tell others our secrets to success, lest others learn and take away our competitive advantage, or we don't want to expose our shortcomings, lest others find out which parts of our feet are made of clay.

I recently completed a project for the Clark County Adaptive Management Program. As a public program under the auspices of their Multi-Species Habitat Conservation Program (new URL) (MSHCP) (newer URL), it is subject to the Nevada Open Meetings Act, and thus their work and the work I did with them is public information.

If you're interested in what an early-stage dynamic modeling exercise might look like, take a look at their recently-published 2006 Biennial Adaptive Management Report (new URL) (newer URL). It talks about many things, including the work we did together to achieve three goals:

• Development of a system dynamics model(s) of conservation actions for implementation of the Multiple Species Habitat Conservation Plan.
  
• Use of the system dynamics model(s) to prioritize conservation actions to recommend for funding in the 2006 Biennial Adaptive Management Report.
  
• Use of the system dynamics model(s) to identify key uncertainties and information gaps to be recommended for funding in the 2006 Biennial Adaptive Management Report.
  

This effort was designed both to facilitate conversations among stakeholders who need to understand what the Adaptive Management Science Team is doing and how they make their recommendations to others involved in the MSHCP and to provide the Adaptive Management Science Team a new decision support tool.

Chapter 1 focuses on the model. You can download and explore a copy of the model we created together as Appendix B (new URL) (newer URL). If you don't own a copy of iThink™, you can download the free isee Player from isee Systems. I thank Sue Wainscott, Adaptive Management Coordinator, and the Adaptive Management Science Team for their support in this work. I also thank Ruth Siguenza, CPF, a long-term facilitator for the Clark County Desert Conservation Program (new URL) (newer URL), who first introduced Sue and me.

In many ways, this work resembles what Marjan van den Belt calls "mediated modeling," although I only discovered the term and her book Mediated Modeling: A System Dynamics Approach to Environmental Consensus Building part-way through this engagement.

By the way, if you happen to be in the desert near Clark County, Nevada and see a desert tortoise, please leave it alone; just touching it or picking it up can kill it. The Mojave Max Web site has more information on this amazing creature.

conservation
desert tortoise
endangered species
environment
system dynamics