Model Thinking - Be the man who embraces multiple models

Recently, it was my turn to share during the weekly company presentation, and I pondered over what I should talk about. By chance, I remembered a book I had read before, “Model Thinking.” At the time, I felt that it was indeed a great book, but unfortunately, I hadn’t delved into it thoroughly. The content of the book is quite extensive, filled with various academic models, and its thickness alone could intimidate many readers. Hence, without that pressure, there wouldn’t be this sharing opportunity.

Author | Ngenie

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Questions list

1. Why should I read this book?

2. What is the core idea of this book?

3. How can one gradually acquire “model thinking”?

4. What guidance does “model thinking” provide for life and work?

5. After reading this book, what tools can I immediately use? What actions can be taken right away?

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Deconstruction of this book

2.1 Book introduction

The author of this book, Scott Page, is the “guru” of the Center for the Study of Complex Systems at the University of Michigan and an external research fellow at the Santa Fe Institute. He is an expert in complexity and diversity studies. In 2012, he taught a popular open course called “Model Thinking” at the University of Michigan. This book is a condensed compilation of the essence of that course. You can find the course on Coursera at this address: https://www.coursera.org/learn/model-thinking.

2.2 Book structure

The focus of this book lies in cultivating multi-model thinking. In the following mind map, I provide a hierarchical analysis of multi-model thinking and an understanding of the methodology. These insights are primarily derived from my comprehension of the book and compiled online resources.

Regarding the collection of models in this book, it encompasses 23 major categories. While a significant portion consists of mathematical models, there are also numerous case studies throughout the book. It is recommended to understand and learn based on these case studies.

2.3 Answering questions

1. The purpose of reading this book is to acquire a mindset called “model thinking,” or more straightforwardly, to learn the patterns of problem-solving approaches.
2. The core idea of this book is multi-model thinking. From the aforementioned mind map, it is evident how multi-model thinking is structured, its significance, and the methodology for employing it.
3. To develop one’s own multi-model thinking, there are four steps:
   • First, become proficient in several models.
   • Reflect on past problems and reapply suitable models, practicing them again.
   • Utilize the “hypothesis-analogy” methodology mentioned in this book. When faced with a problem, creatively adjust hypotheses and then employ analogies to select the most suitable combination of models.
   • Continuously experiment and accumulate knowledge in real-world problem-solving to allow your network of models to grow.
4. Model thinking provides a comprehensive set of problem-solving approaches for both life and work. Its effectiveness depends on an individual’s cultivation and application. At the very least, employing model thinking provides a more scientific basis when facing problems, avoiding blind actions and anxiety.
5. Personally, there are several models from the book that I can immediately utilize:
   • Power-law distribution model, applicable to the operation of my self-media.
   • Network model, useful in practical work. I plan to explore Bayesian networks for problem-solving related to key characters in a script.
   • Entropy model, as I have recently encountered significant uncertainties in daily life, using the entropy model to address life’s issues.
   • Markov model, for determining what can yield long-term positive utility and distinguishing it from short-term utility, fostering a long-term perspective in life.

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My takeaways

Revisiting the sharing of this book has provided me with a deeper understanding of “multi-model thinking”. Of course, this is also a method of model integration that I often utilize in my daily work. However, the mere act of selecting the appropriate models to solve problems is already quite challenging, not to mention the increasing number of models to learn, which leads to a rise in the time cost of trial and error and the possibility of minimal overall effectiveness. Therefore, “multi-model thinking” is not something that can be easily mastered after reading a few books or experiencing a few things. It requires continuous learning and improvement, much like Charlie Munger’s approach.

Another significant takeaway from this book’s sharing is that I once again tasted the sweetness of “output.” Our long-standing school education has accustomed us to the “learning trap,” which primarily emphasizes “input,” and we have not learned to actively “output.” Thus, I am considering establishing my own “continuous output” system to drive continuous progress through output. Moreover, through “output,” I can solidify my knowledge and experience a short-term sense of accomplishment. This definitely creates a positive feedback mechanism. As for the form of output, in this era of the Internet, it is no longer difficult; the key lies in establishing a well-structured system.

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Links to knowledge

1. “Beauty of Algorithms” is a book that primarily focuses on explaining the use of algorithms to solve problems, and it shares some similarities with this book.
2. “Seeking Wisdom: From Darwin to Munger” is a classic book by Charlie Munger, where he emphasizes the concept of “multiple mental models”.
3. There are many online resources that compile Charlie Munger’s mental models, such as this “list of 100 mental models recommended by Charlie Munger”.