The many model thinkers

By Angelika Schanda
Located in Nijmegen, Netherlands
European Master in System Dynamics, Class 2013-2015

Modelers frequently refer to the notion that the question is not whether to use models, but which models to use and how to improve or integrate them. This idea builds on the assumption that people are model thinkers by nature. Therefore, challenging your mental models and comparing them to others is vital for developing more useful models. Better still than using many mental models is to formalize models and – you guessed it – better than having one formal model is using many formal models. Therefore, learning about diverse models and modeling techniques at workshops, webinars or online courses can improve your overall work. One of those courses starts today, Monday October 6 (more can be found in the Young Modeler event calendar).

That humans are model thinkers is a notion supported by diverse sciences. System dynamics founder Jay Wright Forrester referred to our cognitive understanding of reality as ‘mental models’ (in other words: our thoughts about the world, see for example Forrester, 1975). Those models are a way to organize and make sense of the information we get, both directly from our senses and life experiences as well as from secondary information from other sources. These models are far from perfect or logically consistent, due to incomplete information and humans’ bounded rationality and biases. Therefore, Donella Meadows, a student of Forrester and co-author of the influential 1972 study The Limits to Growth, suggested to expose one’s mental models to “the free air” (Meadows, 2002). By sharing one’s view of the world with others, we can discover errors, integrate new information and develop our mental models further so that they may become more useful for decision making. This is one idea behind any kind of scientific discourse, which is why models are sometimes also referred to as hypotheses (Sterman, 2000).

Actively challenging one’s own mental models and related scientific paradigms is not a  widespread practice in science. It is not always clear in how far a model can be judged to be true or at least to be of sufficient quality to improve decision making. Therefore, Meadows calls for working with and comparing several models (or ideas) instead of choosing and defending just one of them. The paradigm switch from strong positivism to relativism in past decades and Karl Popper’s concept of falsifying instead of verifying research support this view. Nevertheless, it appears that researchers frequently deduct a hypothesis consistent with their own mental model and to more or less consciously set up studies in a way that supports their claims.

Formalizing and quantifying mental models is a systematic, structured way of testing the inner validity of an argument or claim. Complex concepts become operable and assumptions are made explicit. Implications of one or the other assumption about the world become visible in their impact on the whole. Finally, even better than having one formalized model is to use several formal models. This is not only an intuitive insight, but has been researched by Phil Tetlock, among others. In his publication “Expert Political Judgment” (2006) he researched in how far using single vs. multiple models and using mental vs. formal models leads to accuracy and precision of results. Hardly coming as a surprise, formal models ranked much higher than mental models, but also using several models gave better results than relying on a single model. Related to such insights, scholars such as Parker et al. (2002) promote the development of an integrative modeling approach with integration of as much as five dimensions. Beyond considering the use of several modeling techniques, different decision making tools, analysis on different scales, integration of stakeholders and joint analysis of issues (such as social and environmental problems) are applied.

These ideas of applying several models, of integrating tools and knowledge are fundamental for this blog. People who operate with a great diversity of both mental and formal models can come together so that they may learn from each other. They can discuss different concepts of what models are, how they can be built and how they can be used in practice.

Are you up for becoming a many model thinker yourself? Start out by trying one of the following (free) opportunities:

In his course Model Thinking, Scott E. Page from the University of Michigan demonstrates in 10 weeks and 20 themes why and how to use a diverse set of models. Content featured includes agent based modeling, cellular automata, spatial models, decision theories, Markov processes, game theory, Six Sigma and much more. You discover how to explain what seem to be paradoxes, how to distinguish tipping points from exponential growth, how diffusion takes place, what leads to path dependence and to understand other riddles in science. You can sign up for free at the Coursera e-learning platform anytime (also after the course start date).

For courses that deal with more specialized topics, consider Social and Economic Networks: Models and Analysis or Introduction to the Natural Capital Project Approach.

If you prefer more interactive opportunities to learn, sign up for a workshop about Anylogic on November 7 in Berlin, Germany. It is a software that allows building system dynamics, agent based as well as discrete event simulations.

Finally, don’t forget – no matter which methodology you prefer, be sure to ‘expose your mental models to the air’. Nothing is more helpful than sharing your ideas with others and testing them in practice!


  • Forrester, Jay Wright 1975 from “Counterintuitive Behaviour of Social Systems”, in Chapter 14 of Collected Papers of Jay W. Forrester. Waltham, MA: Pegasus Communications.
  • Meadows, D. (2002). Dancing with Systems. The Systems Thinker, 13(2).
  • Parker et al. (2002). Progress in integrated assessment and modeling. Environmental Modelling and Software 17(3), 209-217.
  • Sterman, J. D. (2000). Business dynamics : systems thinking and modeling for a complex world. Boston : Irwin/McGraw-Hill.
  • Tetlock, P.E. (2006). Expert Political Judgment: How Good Is It? How Can We Know? Princeton: Princeton University Press.

Passionate about systems thinking, traveling and social change initiatives. Learn more at

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