Introduction to Systems Thinking
Daniel Aronson
Systems thinking
has its foundation in the field of system dynamics, founded in 1956 by MIT
professor Jay Forrester. Professor Forrester recognized the need for a better way of testing
new ideas about social systems, in the same way we can test ideas in engineering. Systems
thinking allows people to make their understanding of social systems explicit and improve them
in the same way that people can use engineering principles to make explicit and improve their
understanding of mechanical systems.
The Systems Thinking Approach
The approach of
systems thinking is fundamentally different from that of traditional forms of
analysis. Traditional analysis focuses on the separating the individual pieces of what is being
studied; in fact, the word "analysis" actually comes from the root meaning "to break
into
constituent parts." Systems thinking, in contrast, focuses on how the thing being studied
interacts with the other constituents of the system—a set of elements that interact to produce
behavior—of which it is a part. This means that instead of isolating smaller and smaller parts
of
the system being studied, systems thinking works by expanding its view to take into account
larger and larger numbers of interactions as an issue is being studied. This results in sometimes
strikingly different conclusions than those generated by traditional forms of analysis, especially
when what is being studied is dynamically complex or has a great deal of feedback from other
sources, internal or external.
The character of
systems thinking makes it extremely effective on the most difficult types of
problems to solve: those involving complex issues, those that depend a great deal dependence
on the past or on the actions of others, and those stemming from ineffective coordination among
those involved. Examples of areas in which systems thinking has proven its value include:
Use of Systems Thinking
An example that
illustrates the difference between the systems thinking perspective and the
perspective taken by traditional forms of analysis is the action taken to reduce crop damage by
insects. When an insect is eating a crop, the conventional response is to spray the crop with a
pesticide designed to kill that insect. Putting aside the limited effectiveness of some pesticides
and the water and soil pollution they can cause, imagine a perfect pesticide that kills all of the
insects against which it is used and which has no side effects on air, water, or soil. Is using this
pesticide likely to make the farmer or company whose crops are being eaten better off?

(Reading the
Diagram: The arrow indicates the direction of causation - that is, a change in the
amount of pesticide applied causes a change in the numbers of insects damaging crops. The
letter indicates how the two variables are related: an "s" means they change in the
same
direction - if one goes up then the other goes up, and an "o" means they change in
the opposite
direction - if one goes up then the other goes down (or vice versa). This diagram is read "a
change in the amount of pesticide applied causes the number of insects damaging crops to
change in the opposite direction." The belief being represented here is that "as the amount
of
pesticide applied increases, the number of insects damaging crops decreases.")
According to this
way of thinking, the more pesticide is applied, the fewer insects there will be
damaging crops, and the less total crop damage.
The temptation
is to say that eliminating the insects eating the crops will solve the problem;
however that often turns out to not be the case. The problem of crop damage due to insects
often does get better - in the short term. Unfortunately, the view diagrammed above represents
only part of the picture. What frequently happens is that in following years the problem of crop
damage gets worse and worse and the pesticide that formerly seemed so effective does not
seem to help anymore.
This is because
the insect that was eating the crops was controlling the population of another
insect, either by preying on it or by competing with it. When the pesticide kills the insects that
were eating the crops, it eliminates the control that those insects were applying on the
population of the other insects. Then the population of the insects that were being controlled
explodes and they cause more damage than the insects killed by the pesticide used to.
In other words,
the action intended to solve the problem actually makes it worse because the
way its unintended side effects change the system ends up exacerbating the problem.
In fact, some studies
suggest that a majority of the 25 insects that cause the most crop damage
each year became problems to begin with because of exactly this cycle. Graphically, the way
this happens can be represented as:
According to this
understanding, the greater the pesticide application, the smaller the numbers
of Insect A (the original pest) that will eat the crop. This leads to an immediate decrease in the
numbers of insects eating the crop (note that this is the effect those applying the pesticides are
intending). However, the smaller numbers of insect A eventually lead to greater numbers of
Insect B (the hash marks on the arrow indicate a delay), because insect A is no longer
controlling the numbers of insect B to the same extent. This leads to a population explosion of
insect B, to greater numbers of insect B damaging crops, and to greater numbers of insects
damaging the crop, exactly the opposite of what was intended. Thus, although the short-term
effects of applying the pesticide were exactly what was intended, the long-term effects were
quite different.
With this picture
of the system in mind, other actions with better long-term results have been
developed, such as Integrated Pest Management, which includes controlling the insect eating
the crops by introducing more of its predators into the area. These methods have been proven
effective in studies conducted by MIT, the National Academy of Sciences, and others, and
they also avoid running the risk of soil and water pollution.
The way that the
broader perspective of systems thinking creates the understanding necessary
for better long- term solutions was also evident in work I did with a company whose industry
was being deregulated. They seemed to be doing everything right in working on a customer-
relations problem they were experiencing: they had a team of capable people working on it,
they were using a process that had been successful many times in the past, and they even had
affected customers giving them feedback on proposals to rectify the situation.
However, they were
having difficulty seeing the big picture of how the way they historically did
things was contributing to the problem. Working together over two days, I was able to help
them see how the problem was being exacerbated and the most powerful actions they could
take to solve it. The session ended with the creation of a strategy for addressing the problem
that was unanimously supported by the team and the customers.
By seeing the whole
picture, the team was able to think of new possibilities that they had not
come up with previously, in spite of their best efforts. Systems thinking has the power to help
teams create insights like these, when applied well to a suitable problem.
(Other examples
of positive results obtained by systems thinking in service, human resources,
and high- technology industries can be found in Peter Senge's classic The Fifth Discipline and
in The Systems Thinker newsletter, published by Pegasus Communications.[1])
A Better Way to Deal with Our Most
Difficult Problems
So many important
problems that plague us today are complex, involve multiple actors, and are
at least partly the result of past actions that were taken to alleviate them. Dealing with such
problems is notoriously difficult and the results of conventional solutions are often poor enough
to create discouragement about the prospects of ever effectively addressing them. One of the
key benefits of systems thinking is its ability to deal effectively with just these types of problems
and to raise our thinking to the level at which we create the results we want as individuals and
organizations even in those difficult situations marked by complexity, great numbers of
interactions, and the absence or ineffectiveness of immediately apparent solutions.
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