North Texas Society for Sustainability: Six factors to consider when making decisions

Message

Natural systems are complex systems - often with multiple feedback loops and intricately patterned relationships.  

We can often cause ourselves unintended difficulty by making life decisions based on the understandings we have gained from observation of simple systems and neglecting to consider factors found in complex systems.

In the discussion below, MIT Researcher Jay Forrester points out six ways we can miss the mark by innappropriately evaluating complex systems through the lens of experience gained from simple systems.

Permaculture design principles give us tools to plan and interact with complex systems taking into account the challenge and beauty of complexity...

*** Jay Forrester ***

"Complex systems behave in ways entirely different from our expectations derived from experience with simple systems. Because intuition is based on simple systems, people are misled when making decisions about complex systems.

Six examples show the dangers in judging real-life systems based on a lifetime of conditioning from simple systems:

Cause and Effect not Closely Related
From simple systems we learn that cause and effect are closely
related in time and space. When we touch a hot stove, we are burned
here and now. Experiences that are understandable almost always
drive home the lesson that the cause of a symptom is to be found
nearby and immediately before the observed consequence. But in
complex systems the cause of a symptom is usually far back in time
and arises from an entirely different part of the system. To make
matters even more misleading, complex systems usually present what
appear to be causes that are close in time and space to the immediate
problem, but those apparent causes are only coincident symptoms.
Learning ever since childhood teaches lessons that cause people to
misjudge and mismanage complex systems.

Long-Term vs. Short-Term tradeoffs
In a simple system, a goal can be accomplished and a task finished.
When the water glass is full we turn off the water, the objective has
been met, and there are probably no direct unpleasant consequences.
However, in complex systems there is nearly always a tradeoff. If
the short-term goal is maximized, the result is a longer-term
undesirable consequence. A child takes a toy from a playmate, the
goal of having another toy is achieved, but a fight is likely to ensue.
Borrowing on credit cards enhances the short-term standard of
living with the longer consequence that the standard of living must
be lowered to pay interest and refund the loan. Excessive welfare
programs in many countries relieved immediate social pressures but
led to mounting governmental debt and severe political consequences
as expenditures had to be curtailed. Gratification of immediate
desires may lead some to stealing with the later consequence of jail.

Ineffective Actions
In simple systems, it is clear what must be done to achieve a goal.
One turns the steering wheel in the right direction to keep a car on
the road. But in complex systems, the obvious decisions are often
ineffective. An exceedingly large fraction of policies in complex
systems have very little effect. Nevertheless those low-leverage
policies receive most of the attention in business and government.
Debate centers around decisions that will be defeated by
consequences emerging from other feedback loops in the system.
Taxes may be raised to balance the budget, but the extra
governmental income can become an excuse for more expenditure
and the budget remains in deficit. Experience from simple systems
misguides people to take actions that the system itself can defeat.

Wrong Directions for Effective Actions
In simple systems, the direction of action to achieve a goal is
obvious. Diligent work and longer hours will increase income. In
complex systems, even when a rare high-leverage policy has been
chosen, the desirable direction to change that policy is often unclear,
or worse, may usually be misjudged and the policy moved in the
wrong direction. In the Urban Dynamics model, low-cost housing

was found to be a high-leverage policy for affecting the vitality of a
city and well being of its residents. Governments had been

constructing low-cost housing, but that is the wrong direction. Old
and decaying housing, which is the principal stock of low-cost
housing, should be removed, not augmented. Low-income housing
uses land space that could instead be used for job-creating industrial
structures, while the housing draws in people who need jobs. The
additional housing reduces jobs while increasing the number of
people who need jobs. Additional housing is not a way to alleviate
poverty but instead is an active force for increasing poverty. The
validity of the model has been verified by urban trends. It is only
through comprehensive modeling of complex systems that we can
hope to overcome the policy errors that arise from a lifetime of
learning the wrong lessons from simple systems.

Blaming Others
In simple systems, the cause of a failure is clear. One trips over a
rock because the foot was not raised high enough; it is obvious that
the fault was our own. In complex systems, causes are more
obscure; it is not evident that we have caused our own crises, so,
there is a strong tendency to blame others. However, the practice of
blaming others diverts attention from the real cause of trouble,
which is usually our own actions. By looking to others as the
culprits, we take attention off the more embarrassing, but more
productive, need to change our own actions. A management will
blame the competition, or bankers, or its employees for low profits
or falling market share, even though other companies in the same
business, that deal with the same customers and bankers, are
successful. The difference must lie in the policies of the failing
company. The United States has a problem of illegal drugs, so drug
supplying countries are blamed, rather than asking why our country
is the largest market for drugs. There would be no suppliers if there
were no users. In simple systems, the source of a problem is evident
and lies in our own actions. In complex systems, causes are hidden
and blame can be attributed to scapegoats through which correction
is not possible.

Collapse of Goals
In simple systems, goals are reinforced and maintained. The goal of
staying in the proper highway lane is sustained by the threat of an
accident. In less obvious systems, goals can gradually erode. One's

goal of maintaining a sound financial condition can yield to pressure
to borrow for a vacation or to purchase a fancier automobile. The
goal can gradually decline from a safe financial condition, to wanting
to fall no farther into debt, to striving to meet debt payments, to
hoping to avoid foreclosure on one's house. In some countries there
was a time when unemployment rates of 4% were considered high,
gradually the goal eroded until 8% or more became the norm."

Author	Message
terryw Admin Group Joined: 31 May 2006 Location: United States Online Status: Offline Posts: 27	Topic: Six factors to consider when making decisions Posted: 01 Aug 2007 at 5:49pm
	Natural systems are complex systems - often with multiple feedback loops and intricately patterned relationships. We can often cause ourselves unintended difficulty by making life decisions based on the understandings we have gained from observation of simple systems and neglecting to consider factors found in complex systems. In the discussion below, MIT Researcher Jay Forrester points out six ways we can miss the mark by innappropriately evaluating complex systems through the lens of experience gained from simple systems. Permaculture design principles give us tools to plan and interact with complex systems taking into account the challenge and beauty of complexity... * Jay Forrester * "Complex systems behave in ways entirely different from our expectations derived from experience with simple systems. Because intuition is based on simple systems, people are misled when making decisions about complex systems. Six examples show the dangers in judging real-life systems based on a lifetime of conditioning from simple systems: Cause and Effect not Closely Related From simple systems we learn that cause and effect are closely related in time and space. When we touch a hot stove, we are burned here and now. Experiences that are understandable almost always drive home the lesson that the cause of a symptom is to be found nearby and immediately before the observed consequence. But in complex systems the cause of a symptom is usually far back in time and arises from an entirely different part of the system. To make matters even more misleading, complex systems usually present what appear to be causes that are close in time and space to the immediate problem, but those apparent causes are only coincident symptoms. Learning ever since childhood teaches lessons that cause people to misjudge and mismanage complex systems. Long-Term vs. Short-Term tradeoffs In a simple system, a goal can be accomplished and a task finished. When the water glass is full we turn off the water, the objective has been met, and there are probably no direct unpleasant consequences. However, in complex systems there is nearly always a tradeoff. If the short-term goal is maximized, the result is a longer-term undesirable consequence. A child takes a toy from a playmate, the goal of having another toy is achieved, but a fight is likely to ensue. Borrowing on credit cards enhances the short-term standard of living with the longer consequence that the standard of living must be lowered to pay interest and refund the loan. Excessive welfare programs in many countries relieved immediate social pressures but led to mounting governmental debt and severe political consequences as expenditures had to be curtailed. Gratification of immediate desires may lead some to stealing with the later consequence of jail. Ineffective Actions In simple systems, it is clear what must be done to achieve a goal. One turns the steering wheel in the right direction to keep a car on the road. But in complex systems, the obvious decisions are often ineffective. An exceedingly large fraction of policies in complex systems have very little effect. Nevertheless those low-leverage policies receive most of the attention in business and government. Debate centers around decisions that will be defeated by consequences emerging from other feedback loops in the system. Taxes may be raised to balance the budget, but the extra governmental income can become an excuse for more expenditure and the budget remains in deficit. Experience from simple systems misguides people to take actions that the system itself can defeat. Wrong Directions for Effective Actions In simple systems, the direction of action to achieve a goal is obvious. Diligent work and longer hours will increase income. In complex systems, even when a rare high-leverage policy has been chosen, the desirable direction to change that policy is often unclear, or worse, may usually be misjudged and the policy moved in the wrong direction. In the Urban Dynamics model, low-cost housing was found to be a high-leverage policy for affecting the vitality of a city and well being of its residents. Governments had been constructing low-cost housing, but that is the wrong direction. Old and decaying housing, which is the principal stock of low-cost housing, should be removed, not augmented. Low-income housing uses land space that could instead be used for job-creating industrial structures, while the housing draws in people who need jobs. The additional housing reduces jobs while increasing the number of people who need jobs. Additional housing is not a way to alleviate poverty but instead is an active force for increasing poverty. The validity of the model has been verified by urban trends. It is only through comprehensive modeling of complex systems that we can hope to overcome the policy errors that arise from a lifetime of learning the wrong lessons from simple systems. Blaming Others In simple systems, the cause of a failure is clear. One trips over a rock because the foot was not raised high enough; it is obvious that the fault was our own. In complex systems, causes are more obscure; it is not evident that we have caused our own crises, so, there is a strong tendency to blame others. However, the practice of blaming others diverts attention from the real cause of trouble, which is usually our own actions. By looking to others as the culprits, we take attention off the more embarrassing, but more productive, need to change our own actions. A management will blame the competition, or bankers, or its employees for low profits or falling market share, even though other companies in the same business, that deal with the same customers and bankers, are successful. The difference must lie in the policies of the failing company. The United States has a problem of illegal drugs, so drug supplying countries are blamed, rather than asking why our country is the largest market for drugs. There would be no suppliers if there were no users. In simple systems, the source of a problem is evident and lies in our own actions. In complex systems, causes are hidden and blame can be attributed to scapegoats through which correction is not possible. Collapse of Goals In simple systems, goals are reinforced and maintained. The goal of staying in the proper highway lane is sustained by the threat of an accident. In less obvious systems, goals can gradually erode. One's goal of maintaining a sound financial condition can yield to pressure to borrow for a vacation or to purchase a fancier automobile. The goal can gradually decline from a safe financial condition, to wanting to fall no farther into debt, to striving to meet debt payments, to hoping to avoid foreclosure on one's house. In some countries there was a time when unemployment rates of 4% were considered high, gradually the goal eroded until 8% or more became the norm."
	Mitakuye Oyasin All My Relations, Terry
	IP Logged

Systems Thinking Open Forum
North Texas Society for Sustainability :Systems Thinking :Systems Thinking Open Forum