By Donella Meadow
Review By: Christian Sprague
Thinking in Systems by Donella Meadows (2008) is a primer for understanding and dealing with complex systems. The book contains three parts. In part one, System Structure and Behavior, Meadows introduces System Dynamics (SD), a research field that models systems by breaking them down into simple components: inputs and outputs, stocks and flows, balancing and reinforcing feedback loops, statics and dynamics. A simple example from the book is that of a thermostat as a room temperature controller. Here, the thermostat acts as a stock-maintaining balancing feedback loop device. The heat from the outside and heat from the inside are two stocks that the device is balancing between.
Meadows draws from this example to propose that, “your mental model of the system needs to include all the important flows, or you will be surprised by the system’s behavior (pg. 40).”
In part two, Systems and Us, the tone of the book changes from concrete to conceptual and introduces (what we have now come to call) complex adaptive systems (CAS). Here, Meadows draws on ideas such as emergence, resiliency,
self-organization, simple-rules, hierarchy, and scale to define a CAS and suggests that human systems are CAS. However, from this connection, Meadows must reconcile the clear issues of applying SD framework to human systems, issues like fuzzy boundaries, non-predictive and
non-repetitive feedback loops, ubiquitous time delays, and human behavior. She reconciles this gap by leveraging the concept formalized by Herbert Simon: bounded rationality - the theory that people use their limited information (bound) to make rational decisions. The book heavily leans on bounded rationality to explain most human system failures, stating, “The bounded rationality of each actor in a system may not lead to decisions that further the welfare of the system as a whole (pg. 110). ”
Figure 1: Room Temperature Regulated by a Thermostat (pg. 36)
This core explanation of human system failure leads to the solutions proposed in part three: Creating Change in Systems and in our Philosophy. Here, Meadows repeatedly reasserts the need for a broader, meta-cognitive understanding of cultural paradigms and milieu (i.e., broadening our rationality). She emphasizes the necessity of these skills to overcome the paradigms that reinforce the feedback loops which prevent true change and problem solving (pg. 163-165). This sentiment echoes Albert Einstein’s similar observation that, “we cannot solve our problems with the same thinking we used to create them.” More concretely, Meadows suggests policymakers use a broadening base of information to craft policy that enforces simple rules that are (1) observable, (2) learnable, and (3) updatable – constituting a policy feedback loop.
Overall, the text is a blend of philosophy with mathematics, qualitative with quantitative, SD with CAS, and takes an iterative feedback loop approach to system design. However, the book fails to provide the reader with a clear sense of how to influence human systems beyond reducing them to an SD framework with an ad hoc information feedback loop - often untenable in real-world scenarios.
Meadows says little about power struggles, hierarchies, and perverse stakeholder incentives. In fact, Meadows skirts around topics related to complex (public policy) decision-making - often reducing them to stock and flow imbalances and problems of bounded rationality. Thus, while Meadows was intellectually born in the 1st wave and attempts to integrate some aspects of 2nd and 3rd wave critiques, she leaves the reader with no enactable take-a-ways beyond a nice primer to SD and CAS theory.
Meadows, D. H. (2008). Thinking in systems: A primer. chelsea green publishing.