Book Notes: Thinking in Systems

Thinking in Systems: A Primer by Donella H. Meadows, Diana Wright
My rating: 4 of 5 stars

Summary of Systems Principles

Systems

  • A system is more than the sum of its parts.
  • Many of the interconnections in systems operate through the flow of information.
  • The least obvious part of the system, its function or purpose, is often the most crucial determinant of the system’s behaviour.
  • System structure is the source of system behaviour. System behaviour reveals itself as a series of events over time.

Stocks, Flows, and Dynamic Equilibrium

  • A stock is the memory of the history of changing flows within the system.
  • If the sum of inflows exceeds the sum of outflows, the stock level will rise.
  • If the sum of outflows exceeds the sum of inflows, the stock level will fall.
  • If the sum of outflows equals the sum of inflows, the stock level will not change – it will be held in dynamic equilibrium.
  • A stock can be increased by decreasing its outflow rate as well as by increasing its inflow rate.
  • Stocks act as delays or buffers or shock absorbers in systems. Stocks allow inflows and outflows to be de-coupled and independent.

Feedback Loops

  • A feedback loop is a closed chain of causal connections from a stock, through a set of decisions or rules or physical laws or actions that are dependent on the level of the stock, and back again through a flow to change the stock.
  • Balancing feedback loops are equilibrating or goal-seeking structures in systems and are both sources of stability and sources of resistance to change.
  • Reinforcing feedback loops are self-enhancing, leading to exponential growth or to runaway collapses over time.
  • The information delivered by a feedback loop even nonphysical feedback-can affect only future behaviour; it can’t deliver a signal fast enough to correct behaviour that drove the current feedback.
  • A stock-maintaining balancing feedback loop must have its goal set appropriately to compensate for draining or inflowing processes that affect that stock. Otherwise, the feedback process will fall short of or exceed the target for the stock. Systems with similar feedback structures produce similar dynamic behaviours.

Shifting Dominance, Delays, and Oscillations

  • Complex behaviours of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behaviour.
  • A delay in a balancing feedback loop makes a system likely to oscillate.
  • Changing the length of a delay may make a large change in the behaviour of a system.

Scenarios and Testing Models

  • System dynamics models explore possible futures and ask “what if” questions.
  • Model utility depends not on whether its driving scenarios are realistic (since no one can know that for sure), but on whether it responds with a realistic pattern of behaviour.

Constraints on Systems

  • In physical, exponentially growing systems, there must be at least one reinforcing loop driving the growth and at least one balancing loop constraining the growth, because no system can grow forever in a finite environment.
  • Nonrenewable resources are stock-limited.
  • Renewable resources are flow-limited.

Resilience, Self-Organization, and Hierarchy

  • There are always limits to resilience.
  • Systems need to be managed not only for productivity or stability, they also need to be managed for resilience.
  • Systems often have the property of self-organization the ability to structure themselves, to create new structure, to learn, diversify, and complexify.
  • Hierarchical systems evolve from the bottom up. The purpose of the upper layers of the hierarchy is to serve the purposes of the lower layers.

Source of System Surprises

  • Many relationships in systems are nonlinear.
  • There are no separate systems. The world is a continuum. Where to draw a boundary around a system depends the purpose of the discussion.
  • At any given time, the input that is most important to a system is the one that is most limiting.
  • Any physical entity with multiple inputs and outputs is surrounded by layers of limits.
  • There always will be limits to growth.
  • A quantity growing exponentially toward a limit reaches that limit in a surprisingly short time.
  • When there are long delays in feedback loops, some sort of foresight is essential.
  • The bounded rationality of each actor in a system may not lead to decisions that further the welfare of the system as a whole.

Mindsets and Models

  • Everything we think we know about the world is a model.
  • Our models do have a strong congruence with the world.
  • Our models fall far short of representing the real world fully.

Springing the System Traps

Policy Resistance

Trap: When various actors try to pull a system state toward various goals, the result can be policy resistance. Any new policy, especially if it’s effective, just pulls the system state farther from the goals of other actors and produces additional resistance, with a result that no one likes, but that everyone expends considerable effort in maintaining.

The Way Out: Let go. Bring in all the actors and use the energy formerly expended on resistance to seek out mutually satisfactory ways for all goals to be realized or redefinitions of larger and more important goals that everyone can pull toward together.

The Tragedy of the Commons

Trap: When there is a commonly shared resource, every user benefits directly from its use, but shares the costs of its abuse with everyone else. Therefore, there is very weak feedback from the condition of the resource to the decisions of the resource users. The consequence is overuse of the resource, eroding it until it becomes unavailable to anyone.

The Way Out: Educate and exhort the users, so they understand the consequences of abusing the resource. And also restore or strengthen the missing feedback link, either by privatizing the resource so each user feels the direct consequences of its abuse or (since many resources cannot be privatized) by regulating the access of all users to the resource.

Drift to Low Performance

Trap: Allowing performance standards to be influenced by past performance, especially if there is a negative bias in perceiving past performance. sets up a reinforcing feedback loop of eroding goals that sets a system drifting toward low performance.

The Way Out: Keep performance standards absolute. Even better, let standards be enhanced by the best actual performances instead of being discouraged by the worst. Set up a drift toward high performance!

Escalation

Trap: When the state of one stock is determined by trying to surpass the state of another stock and vice versa-then there is a reinforcing feed back loop carrying the system into an arms race, a wealth race, a smear campaign, escalating loudness, escalating violence. The escalation is expo nential and can lead to extremes surprisingly quickly. If nothing is done, the spiral will be stopped by someone’s collapse because exponential growth cannot go on forever.

The Way Out: The best way out of this trap is to avoid getting in it. If caught in an escalating system, one can refuse to compete (unilaterally disarm), thereby interrupting the reinforcing loop. Or one can negotiate a new system with balancing loops to control the escalation.

Success to the Successful

Trap: If the winners of a competition are systematically rewarded with the means to win again, a reinforcing feedback loop is created by which, if it is allowed to proceed uninhibited, the winners eventually take all, while the losers are eliminated.

The Way Out: Diversification, which allows those who are losing the competition to get out of that game and start another one; strict limitation on the fraction of the pie any one winner may win (antitrust laws); policies that level the playing field, removing some of the advantage of the strongest players or increasing the advantage of the weakest; policies that devise rewards for success that do not bias the next round of competition.

Shifting the Burden to the Intervenor

Trap: Shifting the burden, dependence, and addiction arise when a solu tion to a systemic problem reduces (or disguises) the symptoms, but does nothing to solve the underlying problem. Whether it is a substance that dulls one’s perception or a policy that hides the underlying trouble, the drug of choice interferes with the actions that could solve the real prob Jem.

If the intervention designed to correct the problem causes the self-main taining capacity of the original system to atrophy or erode, then a destruc live reinforcing feedback loop is set in motion. The system deteriorates; more and more of the solution is then required. The system will become more and more dependent on the intervention and less and less able to maintain its own desired state.

The Way Out: Again, the best way out of this trap is to avoid getting in. Beware of symptom-relieving or signal-denying policies or practices that don’t really address the problem. Take the focus off short-term relief and put it on long-term restructuring.

If you are the intervenor, work in such a way as to restore or enhance the system’s own ability to solve its problems, then remove yourself.

If you are the one with an unsupportable dependency, build your system’s own capabilities back up before removing the intervention. Do it right away. The longer you wait, the harder the withdrawal process will be.

Rule Beating

Trap: Rules to govern a system can lead to rule-beating-perverse behaviour that gives the appearance of obeying the rules or achieving the goals, but that actually distorts the system.

The Way Out: Design, or redesign, rules to release creativity not in the direction of beating the rules, but in the direction of achieving the purpose of the rules.

Seeking the Wrong Goal

Trap: System behavior is particularly sensitive to the goals of feedback loops. If the goals-the indicators of satisfaction of the rules-are defined inaccurately or incompletely, the system may obediently work to produce a result that is not really intended or wanted.

The Way Out: Specify indicators and goals that reflect the real welfare of the system. Be especially careful not to confuse effort with result or you will end up with a system that is producing effort, not result.

  1. Numbers: Constants and parameters such as subsidies, taxes, and standards
  2. Buffers: The sizes of stabilizing stocks relative to their flows
  3. Stock-and-Flow Structures: Physical systems and their nodes intersection
  4. Delays: The lengths of time relative to the rates of system changes
  5. Balancing Feedback Loops: The strength of the feedbacks relative to the impacts they are trying to correct
  6. Reinforcing Feedback Loops: The strength of the gain of driving loops
  7. Information Flows: The structure of who does and does not have access to information
  8. Rules: Incentives, punishments, constraints
  9. Self-Organization: The power to add, change, or evolve system structure
  10. Goals: The purpose of the system
  11. Paradigms: The mind-set out of which the system-its goals, structure, rules, delays, parameters arises
  12. Transcending Paradigms

Guidelines for Living in a World of Systems

  1. Get the beat of the system.
  2. Expose your mental models to the light of day.
  3. Honour, respect, and distribute information.
  4. Use language with care and enrich it with systems concepts.
  5. Pay attention to what is important, not just what is quantifiable.
  6. Make feedback policies for feedback systems.
  7. Go for the good of the whole.
  8. Listen to the wisdom of the system.
  9. Locate responsibility within the system.
  10. Stay humble-stay a learner.
  11. Celebrate complexity.
  12. Expand time horizons.
  13. Defy the disciplines.
  14. Expand the boundary of caring.
  15. Don’t erode the goal of goodness.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.