The art of systems thinking (The Art of Systems Thinking)

This book by Joseph O’Connor and Ian McDermot is one of the simplest and most understandable books on systems thinking I’ve read. Instead of abstruse theory and complex explanations, the authors offer a bunch of practical examples that they weave into the narrative so that you learn the concepts of systemic thinking in everyday situations, like quarrels with your soul mate, alcohol consumption or learning a new one. The book is literally readable, the benefit it is compact and consists of the following parts:

Part part 1 Thinking beyond the obvious 1. What is a system? The authors give a simple definition of “a system is an entity that, as a result of the interaction of its parts, can maintain its existence and function as a whole”, and then use it to compare systems and simply groups of objects to show the difference. Next, we are talking about systemic or emergent properties, when the whole is greater than the sum of the parts. Simple and complex systems are discussed, the system as a web of relationships, stability and the principle of leverage. 2. Contour thinking The authors talk about feedback loops that allow the system to acquire interesting properties, but at the same time complicate the prediction of what is happening in the system. These loops are reinforcing. (feedback) balancing (negative feedback). The authors show a bunch of examples and explain why reinforcing/weakening terminology is better:) Plus, they show what an interesting effect occurs when feedback is delayed and fluctuations occur in the system. Part part 2 Building mental models 3. Mental models When thinking, we rely on built-in mental models. (ideas, beliefs and beliefs)They determine our interpretation of events, choice of action and its implementation. We need to be aware of our mental models because we use them to make sense of other systems. Developing and maintaining these models 4 mechanism: striking out, construction, distortion and generalization. Well, there are other factors that lead to a distorted perception of experience: regression, time frame, selective interpretation of experience. 4. Cause and effect Causality in systems is more complex than linear - because of cycles, a cause can generate an effect and vice versa. There are three standard misconceptions from the linear world: the separability of cause and effect, the lack of time accounting. (investigation immediately)The proportionality of the effect of the cause. Further, the authors say that working with complex systems, it is necessary to define the boundaries of the system, as well as to look for attractors. (Stable states to which the system gravitates) 5. Beyond logic. Formal logic is not enough when dealing with systems. We need a systematic approach and metaposition, which allows us to go beyond the standard frame of reference. To change the state of systems, our mental models are often the best points of effort. Part part 3 - Thinking new. 6. Training - A story 2 Type of learning: simple and generative. In simple learning, we use feedback to adjust our actions to better achieve our goal. In generative learning we have 2 We not only adjust our actions, we also adjust our mental models.
7. Race, perspective. The importance of viewpoints and the expansion of our mental models. Systems thinking is used as an objective approach. (look out)and subjective approach (system-view). And the choice of approach depends on how we define the boundaries of the system. Part part 4 - Drawing conclusions A story about how you can visualize the structure of the system and relationships using feedback loops (caseload) Part part 5 - Close the circle. The authors show how to use all the previously mentioned tools of systems thinking, for example, if the results do not match the effort. Part part 6 - Sources. The history of how systems thinking emerged and developed in 20 century.

#Brain #SelfDevelopment