In the classroom, we were systems students, but in our office, we are systems educators.
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As the authors explained, “stock–flow failure is a robust phenomenon that appears to be rooted in failure to appreciate the most basic principles of accumulation, leading to the use of inappropriate heuristics.” In other words, most of us are confusing stocks and flows, the basic building blocks of systems.Ĭlearly, we have a lot of work to do to master these systems principles if we as humans are going to be successful in tackling complex and systemic problems.Īt the same time as we were wading knee-deep through causal loops and feedback systems and STELLA software and the nuts and bolts of systems modeling, Marta and I were also submerged in these issues from the opposite end. Indeed, in the paper “ Why don’t well-educated adults understand accumulation? A challenge to researchers, educators, and citizens” (Cronin et al, 2009), systems researchers found that well under 50% of graduate level students from MIT and Harvard could correctly answer stock and flow questions about a similar example.
And it seems that our group was no anomaly. Only about one third of our class came up with the correct answer to this comparatively simple systems problem. If the leaving rate for experienced employees has been constant for a while, but it suddenly jumps up to a higher rate, what will happen to the number of experienced employees in the company over time? It takes 6 months to fully train a new employee. Every time an experienced employee leaves, a new employee is immediately hired to take his/her place. And it only took us about halfway through the first lecture to see for ourselves just how complex and unintuitive the subject could be.Īs an introductory example, Professor Peterson presented a very simplified stock and flow scenario: A company has experienced employees and employees-in-training. Taught by Steve Peterson, a former student of Dana Meadows’s, “System Dynamics in Policy Design and Analysis” was a gritty and engaging introduction to systems. It can be learned and practiced and refined, and so, this past winter, Marta and I returned to school as students in a systems dynamics course at Dartmouth’s Thayer School of Engineering. Like many things, systems thinking is a skill. (Image via Thayer School of Engineering at Dartmouth) On the final day of our systems dynamics class, each student presented his or her model at a project symposium. We found ourselves both surprised and encouraged. But over the past few months, we’ve had the opportunity to slow down and really focus on it as a tool and an approach.
Here at the Donella Meadows Institute, we have long used systems thinking as the lens through which we’ve addressed issues of environmental and economic unsustainability. Still, despite our natural shortcomings with systems, learning to understand and redesign them may be the best approach we have to tackle the increasingly large and complex issues facing our world today, from climate change to wealth inequality to energy security. We often see individual items where we should see elements of a system, we attribute a problem to a single effect, and we approach issues with narrow horizons of time and space. The problem with complex systems, though, is that it turns out we human beings are not much good at recognizing, understanding, or communicating them. This sketch by David Macaulay illustrates the two approaches, both of which we found useful. Systems can be examined by zooming in to look closely at their stocks and flows and other component parts, or by zooming out to see the entire system as one interrelated whole.
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