Complexity
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Complexity Science for beginners / Why you should care / Whats to learn from it nonlinearity self-organization evolution feedback-loops fractals management
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Leverage Points
Places to Intervene in a
System
by Donella Meadows
The Sustainability Institute • 3 Linden Road • Hartland VT 05048
Phone 802-436-1277 • FAX 802-436-1281 • Email: [email protected]
For additional copies of this report, send US$10 to The Sustainability Institute.
Published by
© The Sustainability Institute, 1999.
A shorter version of this paper appeared in Whole Earth, winter 1997.
1
Folks who do systems analysis have a great
belief in “leverage points.” These are places
within a complex system (a corporation, an
economy, a living body, a city, an ecosys-
tem) where a small shift in one thing can
produce big changes in everything.
This idea is not unique to systems analy-
sis—it’s embedded in legend. The silver bul-
let, the trimtab, the miracle cure, the secret
passage, the magic password, the single hero
or villain who turns the tide of history. The
nearly effortless way to cut through or leap
over huge obstacles. We not only want to
believe that there are leverage points, we
want to know where they are and how to
get our hands on them. Leverage points are
points of power.
The systems analysis community has a
lot of lore about leverage points. Those of us
who were trained by the great Jay Forrester
at MIT have all absorbed one of his favorite
stories. “People know intuitively where
leverage points are,” he says. “Time after time
I’ve done an analysis of a company, and I’ve
figured out a leverage point—in inventory
policy, maybe, or in the relationship between
sales force and productive force, or in per-
sonnel policy. Then I’ve gone to the com-
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of attention to that point. Everyone is trying
very hard to push it in the wrong direction!”
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Asked by the Club of Rome to show how
major global problems—poverty and hun-
ger, environmental destruction, resource
depletion, urban deterioration, unemploy-
ment—are related and how they might be
solved, Forrester made a computer model
and came out with a clear leverage point:
Growth.1 Not only population growth, but
economic growth. Growth has costs as well
as benefits, but we typically don’t count the
costs—among which are poverty and hun-
ger, environmental destruction, and so on—
the whole list of problems we are trying to
solve with growth! What is needed is much
slower growth, and in some cases no growth
or negative growth.
The world’s leaders are correctly fixated
on economic growth as the answer to virtu-
ally all problems, but they’re pushing with
all their might in the wrong direction.
Another of Forrester’s classics was his
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which demonstrated that subsidized low-
income housing is a leverage point.2 The
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even the low-income folks in ...
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then checked himself. “Nature is prodigal with details but parsimonious with principles. I’ll sketch out the categories in this order: bifurcations; positive-feedback loops; negative-feedback controls; and emergency adaptations. “To anticipate myself, let me warn you that seldom does each individual mode of correction stand alone. Weblike, each affects the other modes. Dynamic systems can and do use all four modes simultaneously. Let me also forewarn you that none of the methods of correction is perfect. Each conceals traps and can have treacherous side effects, which may be why dynamic systems don’t last forever. But in spite of shortcomings, the modes of correction serve incomparably better than lack of corrections. In any case, they’re what we have to work with and depend on, gratefully and warily.” “How do you know these four are the only means that dynamic systems have of correcting themselves?” asked Kate. “I don’t know that they are. They’re the only ones I know of, either in economies or the rest of nature. It’s possible, of course, that my interest in economies has influenced what I see in the rest of nature. All I can tell you is that these four are my best shot, and if you dig up others, more power to you. “We’re already familiar with the fact of bifurcations, because bifurcations are developments. But not all developments are bifurcations.” “Would you define bifurcations , then?” asked Horten ...
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Draw a line around the system boundary
Indicate the most important challenges the system must face
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You have defined the domain of success/failure that you want to understand.
You have identified the entities inside the boundary that are needed to achieve success (through their interactions). Thus, you have defined your system.
You have identified the entities outside the boundary that will pose the challenges/opportunities that must be managed by the system for the achievement of success.
You understand that it is the information that comes in from the outside entities and is processed by the inside entities – according to an established set of rules – that defines the functioning of the system.
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Core Ideas
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A system’s structure describes the entities contained by the system and the particular way they are organized.
A system’s function describes how the entities interact with each other and how these interactions form the emergent properties of the system.
Emergent properties: The whole is greater than the sum of its parts.
Remarkably, a great variety of different systems have similar structural and functional characteristics.
Understanding these commonalities will make our work much easier.
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Feedback
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Leverage Points
Places to Intervene in a
System
by Donella Meadows
The Sustainability Institute • 3 Linden Road • Hartland VT 05048
Phone 802-436-1277 • FAX 802-436-1281 • Email: [email protected]
For additional copies of this report, send US$10 to The Sustainability Institute.
Published by
© The Sustainability Institute, 1999.
A shorter version of this paper appeared in Whole Earth, winter 1997.
1
Folks who do systems analysis have a great
belief in “leverage points.” These are places
within a complex system (a corporation, an
economy, a living body, a city, an ecosys-
tem) where a small shift in one thing can
produce big changes in everything.
This idea is not unique to systems analy-
sis—it’s embedded in legend. The silver bul-
let, the trimtab, the miracle cure, the secret
passage, the magic password, the single hero
or villain who turns the tide of history. The
nearly effortless way to cut through or leap
over huge obstacles. We not only want to
believe that there are leverage points, we
want to know where they are and how to
get our hands on them. Leverage points are
points of power.
The systems analysis community has a
lot of lore about leverage points. Those of us
who were trained by the great Jay Forrester
at MIT have all absorbed one of his favorite
stories. “People know intuitively where
leverage points are,” he says. “Time after time
I’ve done an analysis of a company, and I’ve
figured out a leverage point—in inventory
policy, maybe, or in the relationship between
sales force and productive force, or in per-
sonnel policy. Then I’ve gone to the com-
pany and discovered that there’s already a lot
of attention to that point. Everyone is trying
very hard to push it in the wrong direction!”
Leverage Points:
Places to Intervene in a System
by Donella H. Meadows
The classic example of that backward
intuition was my own introduction to sys-
tems analysis, Forrester’s world model.
Asked by the Club of Rome to show how
major global problems—poverty and hun-
ger, environmental destruction, resource
depletion, urban deterioration, unemploy-
ment—are related and how they might be
solved, Forrester made a computer model
and came out with a clear leverage point:
Growth.1 Not only population growth, but
economic growth. Growth has costs as well
as benefits, but we typically don’t count the
costs—among which are poverty and hun-
ger, environmental destruction, and so on—
the whole list of problems we are trying to
solve with growth! What is needed is much
slower growth, and in some cases no growth
or negative growth.
The world’s leaders are correctly fixated
on economic growth as the answer to virtu-
ally all problems, but they’re pushing with
all their might in the wrong direction.
Another of Forrester’s classics was his
urban dynamics study, published in 1969,
which demonstrated that subsidized low-
income housing is a leverage point.2 The
less of it there is, the better off the city is—
even the low-income folks in ...
Fresh Directions in Economics
Presentation on growing interest in heuristics, networks and complexity in economic thinking. Designed for VI Form economists
Optimization
The document discusses the limitations of optimization and optimality in engineering design. It argues that optimal systems are fragile and prone to failure since they are designed for a single condition, while robust systems can absorb variations without compromising function. The document provides a theorem showing that for response surfaces, systems are less likely to remain in a state of optimality due to entropy naturally increasing over time. It concludes that nature favors robust, fit systems over optimal ones, and engineering could benefit from embracing robustness over fragile optimality in design.
Chaos1
Chaos theory proposes that seemingly random events may actually arise from deterministic systems and can be predicted. It views organizations as complex systems with nonlinear relationships between variables. Applying chaos theory to organizational crises suggests that: 1) small changes can have large effects; 2) long-term predictions are impossible but short-term are feasible; 3) crises may arise from bifurcation points where outcomes oscillate. Chaos theory provides an alternative lens for analyzing unpredictable crisis events in organizations.
Chaos And Systems Theory
The document discusses complex adaptive systems and chaos theory. It notes that complex adaptive systems consist of interacting agents that self-organize and their dynamic interactions can result in emergent behaviors. Their behaviors may seem unpredictable as patterns can appear and disappear suddenly, but there is still an underlying order that is difficult to describe simply. Chaos theory also describes systems that are deterministic but unpredictable in practice, following rules but appearing random in their evolution over time. Punctuated equilibrium and bifurcations are discussed as features of systems at the "edge of chaos".
Discovering the World of Complexity
This document discusses complexity science and complex adaptive systems. It defines complexity and distinguishes between simple, complicated, and complex systems. Complex systems have many interrelated and autonomous parts that interact in non-linear ways, making their behavior hard to predict. The document introduces the Cynefin framework for categorizing systems and describes properties of complex adaptive systems, including emergence and self-organization. It emphasizes that the whole of a complex system is greater than the sum of its parts and advocates developing a complexity mindset to understand and leverage complexity.
1. What have we learned about the sustainable use of resources and.docx
1. What have we learned about the sustainable use of resources and the ability to maintain the ability to produce into the future? Reconsider the discussion of the political discussion in the Dogs paper. When society decides that regulations are necessary, what should be the role of the government? How should the regulations be implemented in order to be efficient? How do markets fit into the social decision process? Use examples for your explanation
2. According to Jacobs, how can methods on innovation in an ecosystem be applied to an economy? Use examples.
3. What are the factors that cause some cities to develop into vibrant economies and cause others to remain small?
4. Differentiate between positive and negative feedback loops. Give examples of each with regard to natural resource utilization. What is the importance of data collection and evaluation in understanding feedback loops?
5. Imagine you are making a presentation to a group of high school students. How would you explain the importance of a regulated market economy? (Three words) Select an example and describe how the system works. Keep in mind the goal of the system.
6. Imagine you are talking to a class of university freshman. They are concerned about what they should study. What challenges do you see in the future and how can those challenges be addressed by studying markets? Pick an example and explain how economics allows us to not only discover the challenge but also to find solutions
Here’s information that I got so far… but you should do research this is not enough
then checked himself. “Nature is prodigal with details but parsimonious with principles. I’ll sketch out the categories in this order: bifurcations; positive-feedback loops; negative-feedback controls; and emergency adaptations. “To anticipate myself, let me warn you that seldom does each individual mode of correction stand alone. Weblike, each affects the other modes. Dynamic systems can and do use all four modes simultaneously. Let me also forewarn you that none of the methods of correction is perfect. Each conceals traps and can have treacherous side effects, which may be why dynamic systems don’t last forever. But in spite of shortcomings, the modes of correction serve incomparably better than lack of corrections. In any case, they’re what we have to work with and depend on, gratefully and warily.” “How do you know these four are the only means that dynamic systems have of correcting themselves?” asked Kate. “I don’t know that they are. They’re the only ones I know of, either in economies or the rest of nature. It’s possible, of course, that my interest in economies has influenced what I see in the rest of nature. All I can tell you is that these four are my best shot, and if you dig up others, more power to you. “We’re already familiar with the fact of bifurcations, because bifurcations are developments. But not all developments are bifurcations.” “Would you define bifurcations , then?” asked Horten ...
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Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityUniversity of Rennes, INSA Rennes, Inria/IRISA, CNRS
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
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Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
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一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
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四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
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1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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Complexity
- 1. Complex Systems Complexity Science Why should we care? Maximilian-Julius Feger
- 2. What’s a Complex System? What can we learn?Why should you care?
- 3. What’s a Complex System? TBH no one knows - 1996 there were over 90 different definitions - Some examples: • “More than the sum of its parts” • “Agents who interact non-linearly” • “At the edge of chaos” And Names: •Complex System •Adaptive System •Dissipative Structure Gedankenexperiment: 100 scientists examine one goose top to bottom. Is there anything that they would not find out about it? They scientists would have been completely baffled over the V- shape of migrating geese
- 4. Complex Systems… 1. Consist of many decentralized parts (agents) 2. Self-organize (Ford car paint factory line) 3. Emerge in hierarchical order (e.g. regional, national, global economies) 4. Interact nonlinearly (division of labor) 5. Experience Feedback-loops (herd behavior) 6. Are sensitive to initial conditions (financial crisis) 7. Adapt to changes in their environment (evolution)
- 5. Why should you care? It is a slightly arresting notion that if you were to pick yourself apart with tweezers, one atom at a time, you would produce a mound of fine atomic dust, none of which had ever been alive but all of which had once been you. Bill Bryson, History of nearly Everything Economic progress, in capitalist society, means turmoil. Joseph Schumpeter …balance between order… and disorder… that is often called ‘the edge of chaos.' At this point of dynamic tension, truly novel emergent behavior can occur. Arie Lewin
- 6. Where can we find complex systems? What are they again?: 1. They thrive off uncertainty “God knows what the market will do tomorrow” “The Weather forecast is hardly on point” 2. They consist of repetitive structures yet they’re unique Fractals aka feedback-loops You’re a like a snowflake 3. Elements (agents) of the CS need to interact Ants Can you find the agents in these CSs? 1. Markets 2. Ecosystems 3. Solarsystems
- 7. 8 Ways to benefit from understanding complex systems 1. Chaos is necessary for progress and not be fought 2. Therefore, generate dis-equilibrium! 3. Embrace uncertainty 4. Surface conflict 5. Allow experiments 6. Support collective action 7. Self-organization through artefacts 8. Stabilize feedback
- 8. Effectuation (effectual logic) Causation (causal logic)
- 10. Further Information: • Santa Fe Institute of Complexity; Collected Works from many fields of complexity science https://www.complexityexplorer.org/ • System Innovation Course; condensed Material & Videos on how to benefit from complexity perspective https://systemsinnovation.io/ • A new IIASA study shows how even minor changes to available infrastructure can trigger tipping points in the collective adoption of sustainable behaviors. https://psyarxiv.com/w6dpa/download?format=pdf