Over the last two blog posts and throughout the STW/STiA Systems Thinking Certification course the search has been for something concrete in systems thinking which to apply to new community paradigms. The concern arising from the reality that systems thinking can be overly abstract making its adoption problematic was raised in Systems Thinking 2nd Segment - Striving for a Better Understanding and other past articles in this series. The concern that the issues communities must deal with can be too abstract to be readily approachable was raised in relation to complexity in Complexity Addressed From On High and elsewhere. The irony is that systems thinking is supposed to be a means of addressing complexity. It is natural then to look for something concrete to build an effort upon, we want pragmatic solutions without wasting too much time on theory.
First, though we have to define what we mean when we ask for something to be concrete and we are not talking about driveways. Examined closely, concrete can be a troublesome, imprecise term if not talking about "heavy, rough building material made from a mixture of broken stone or gravel, sand, cement, and water, that can be spread or poured into molds and that forms a stone-like mass on hardening".
At worse, if we push the metaphor to its fullest extent, a hardened mass, it can then be thought of as a talisman against complexity, in that if we could make all our processes and outcomes concrete then we would never be afflicted by complexity. At best, concrete serves as a metaphor, not a particularly concrete concept, that can apply to understanding real life problems as in concrete reasoning but used, as we all do, in this manner the word concrete doesn't necessarily mean material.
For something then to be concrete, it does not have to be something determined by the senses but then it cannot be merely a possibility either. Concrete can still be defined as constituting an actual thing or instance as in the concrete proof of someone's sincerity, or a concrete occurrence of a systems archetype. It should be something existing in fact, as in concrete evidence. It could be the concrete application of a systems leverage point as developed by Donella Meadows. With systems thinking it should be defined in the context of concrete processes rather than focus on concrete outcomes as the Advisory Board does here. Our focus is usually on concrete outcomes with ends excusing means.
The difference, in my own view, is that systems thinking should be focused more on process or means and should be distinct though not separate from outcomes. Outcomes, need their own separate focus and systemic processes, more in line with dynamic systems methods than soft systems methods, but should still be extended from the systems thinking process that came prior in developing the approach. Moreover, systems thinking cannot see itself as being able to provide answers independent of the field with which it is working or be seen as a tactic to be used only occasionally. There has to be deep integration for this to work long term.
One problem with the term concrete is that it tends to create an image of ‘set in stone’ and while most would argue against setting strategies in stone, we are inadequate to deal with multi-loop nonlinear feedback systems which can only be imagined as being dynamic.
“In the long history of evolution, it has not been necessary until very recent historical times for people to understand complex feedback systems. Evolutionary processes have not given us the mental ability to interpret properly the dynamic behavior of those complex systems in which we are now embedded.”
According to Forrester, our own individual mental models are fuzzy, incomplete, and imprecisely formed, continually changing with time, even in conversations. Even with only a single subject each participant in a conversation employs a different mental model with different fundamental assumptions never brought into the open and different goals left unstated. Our thinking is not as concrete as we would like to think.
System dynamics computer simulation models, even though they deal with dynamic complex systems are a concrete process. They are explicit about assumptions and how they interrelate by clearly describing concepts that are fully understandable in words through a computer model which forces clarification of ideas so that unclear and hidden assumptions are exposed, examined and debated.
The essential element though is not having a computer but how the computer is used to create the model. The George Box rule, stated before, still applies, all computer models are wrong, but some are useful or as Forrester says in the article.
“With respect to models, the key is not to computerize a model, but, instead, to have a model structure and decision-making policies that properly represent the system under consideration.”
“A good computer model is distinguished from a poor one by the degree to which it captures the essence of a system that it represents.”
The essence of a community system is complex which means the data coming out of it is complex. It does not mean that we necessarily need more data, as Forrester asserts in the article.
“The problem is not shortage of data but rather inability to perceive the consequences of information we already possess. The system dynamics approach starts with concepts and information on which people are already acting.”
Further along in that same section, we arrive at the paradox of complex systems in our society, “Generally, behavior is different from what people have assumed.” Forrester goes on to demonstrate how System dynamics models help us understand how difficulties within actual social systems arise, and why so many past efforts to improve social systems have failed.
The country has slipped into short-term policies for managing cities that have become part of the system that is generating even greater troubles.
Rather than face the rising population problem squarely, governments try to relieve the immediate pressures by more policemen, financial aid, busing to suburban schools, and subsidized health facilities. As a consequence, increasing population reduces the quality of life for everyone.
With simple systems, causes are close to symptoms of a problem in both time and space. In complex systems or with wicked problems, causes are often far removed in both time and space from the symptoms, lying far back in time and arising from an entirely different part of the system from when and where the symptoms occur, easily misleading us into believing our actions to alleviate the symptoms to be concrete in nature.
Policy improvements in the short run often degrade a system in the long run while policies producing long-run improvements often initially degrade the system at the start. Because the short run is more visible and more compelling, calling for immediate attention its impact is not really more concrete but more entrenched as Forrester explains.
“However, sequences of actions all aimed at short-run improvement can eventually burden a system with long-run depressants so severe that even heroic short-run measures no longer suffice. Many problems being faced today are the cumulative result of short-run measures taken in prior decades.”
A second article, Leveraging Grantmaking: Understanding the Dynamics of Complex Social Systems, provided to me by Gene in response to a request for something more concrete related to system thinking, demonstrates how programs can be made more successful when these lessons were heeded. The article deals with the development of a 10-year plan to address homelessness in Calhoun County, Michigan (population 100,000).
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