Description
The purpose of this assignment is to examine the relationship between systems thinking, projects, and corporate strategy.Reflect upon the relationship between corporate strategy, projects, systems thinking. Using the “Levels of Perspective” framework discussed in the “Introduction to System Thinking” article by Kim located in the Topic Resources, compose a 500-750-word paper demonstrating the value of systems thinking in developing corporate strategy including the following.Describe the connection between systems thinking, projects, and corporate strategy.Describe an example of how an event, negative or positive, can grow into a vision or strategy by using feedback, loops, and labels.Minimum of five outside resources. Sources must be authoritative and not from a Wikipedia-type source. Prepare this assignment according to the guidelines found in the APA Style Guide
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Introduction to Systems Thinking
Daniel H. Kim
System. We hear and use the word all the time. “There’s no
sense in trying to buck the system,” we might say. Or, “Mary,
she’s a systems analyst.” Or, “This job’s getting out of control;
I’ve got to establish a system.” Whether you are aware of it or
not, you are a member of many systems—a family, a community, a church, a company. You yourself are a complex biological
system comprising many smaller systems. And every day, you
probably interact with dozens of systems, such as automobiles,
ATM machines, retail stores, the organization you work for, etc.
But what exactly is a system? How would we know one if we
saw one, and why is it important to understand systems? Most
important, how can we manage our organizations more effectively by understanding systems?
This volume explores these questions and introduces the principles and practice of a quietly growing field: systems thinking.
With roots in disciplines as varied as biology, cybernetics, and
ecology, systems thinking provides a way of looking at how the
world works that differs markedly from the traditional reductionistic, analytic view. But this is not an either-or distinction
we are making here. Because some problems are best solved
through analytic thinking and others through a systemic perspective, we need both to better understand and manage the
world around us.
Why is a systemic perspective an important complement to analytic thinking? One reason is that understanding how systems
work—and how we play a role in them—lets us function more
effectively and proactively within them. The more we understand systemic behavior, the more we can anticipate that behavior and work with systems (rather than being controlled by
them) to shape the quality of our lives.
It’s been said that systems thinking is one of the key management competencies for the 21st century. As our world becomes
ever more tightly interwoven globally and as the pace of change
continues to increase, we will all need to become increasingly
“system-wise.” This volume gives you the language and tools
you need to start applying systems thinking principles and practices in your own organization.
IMS0013E
Contents
What Is Systems Thinking? ……………………………………… 2
What Is a System?………………………………………………….. 2
Collections Versus Systems
Defining Characteristics of Systems
The Importance of Purpose
Putting Systems in Context: “The Iceberg” …………….. 4
What Do Systems Do? A Close Look at
Systemic Behavior…………………………………………………… 5
Fun with Feedback
The Building Blocks of Systemic Behavior: Reinforcing
and Balancing Processes
Looking for a Sign: Loops and Labels
The Good, the Bad, and the Ugly: A Closer Look at
Balancing Loops
Delays: The Hidden Troublemakers
Putting It All Together: Two Examples of How to
Manage Systems ………………………………………………….. 12
Managing Product Quality at FitCo
Fixes That Backfire at DevWare Corp.
Working on the System, Not in the System………………. 16
Appendix: “Acting” in Different Modes…………………… 17
A Glossary of Systems Thinking Terms…………………….. 19
Introduction to Systems Thinking
@1999 by Pegasus Communications, Inc.
All rights reserved. No part of this publication may be reproduced or transmitted
in any form or by any means, electronic or mechanical, including photocopying
and recording, or by any information storage or retrieval system, without written
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What Is Systems
Thinking?
What exactly is systems thinking? In
simplest terms, systems thinking is a way
of seeing and talking about reality that
helps us better understand and work
with systems to influence the quality of
our lives. In this sense, systems thinking
can be seen as a perspective. It also
involves a unique vocabulary for
describing systemic behavior, and so can
be thought of as a language as well. And,
because it offers a range of techniques
and devices for visually capturing and
communicating about systems, it is a set
of tools.
For anyone who is new to systems
thinking, the best way to “get your feet
wet” is to first learn about the defining
characteristics of systems; in short,
what is a system? But to be a true systems thinker, you also need to know
how systems fit into the larger context
of day-to-day life, how they behave,
and how to manage them. The final
three sections of this volume tackle
those issues.
What Is a System?
In the most basic sense, a system is any
group of interacting, interrelated, or
interdependent parts that form a complex and unified whole that has a
specific purpose. The key thing to
remember is that all the parts are interrelated and interdependent in some
way. Without such interdependencies,
we have just a collection of parts, not a
system.
Collections Versus Systems
Let’s illustrate this point with the following exercise. Take a look at the list of
items below and determine for yourself
which ones are systems and which ones
are just collections of parts. Ready, set, go!
• Bowl of fruit
• Football team
• Toaster
• Kitchen
• Database of customer names
• Tools in a toolbox
• A marriage
So, which ones are systems and
which are merely collections? This question isn’t as easy to answer as it might
seem at first. Your responses depend on
what assumptions you are making about
the item in question. Let’s walk through
each example (starting with the simpler
ones first) and make our assumptions as
explicit as we can.
Kitchen, database of customer
names, and tools in a toolbox. These
are all collections, because
none of them meets
our original criHoney, are we
teria of intera collection
relatedness and
or a system?
interdependence.
Even though the
kitchen itself is full of systems (refrigerator,
microwave, dishwasher),
it is still just a place that
has a collection of systems and other elements
in it. None of those things
interrelate or interact in an
interdependent way. (Note, though, that
once humans enter a kitchen, they,
together with the other elements, form
a system. It’s a curious fact, but whenever you add people to a collection, you
almost always transform a collection into
a system!)
Football team and toaster. Both are
systems. Notice that in addition to our
criteria of interrelatedness and interdependence, a team and a toaster are each
put together for a specific purpose.
Indeed, purpose acts as the predomi-
nant organizing force in any system. If
you want to understand why a system is
organized in a particular way, find out
the system’s purpose.
Bowl of fruit. Most people would
classify this as an obvious collection,
because the pieces of fruit are not interrelated in any way and do not interact
with each other. In truth, however, they
are interacting—at a microscopic level.
For instance, if you put certain fruits
together, they are apt to decay faster
because they interact at a molecular
level. Someone for whom these interactions are important (a fruitologist?)
might even consider this bowl of fruit
to be a very interesting system—one
whose purpose is to maximize the
biodegrading process.
Marriage. For any of you who saw
this one as a collection, please seek marriage counseling immediately! All kidding
aside, the question
I hope
we’re a
of whether one
system!
has a healthy
marriage has a lot
to do with whether
the relationship more
resembles a collection or a system.
Marriage is essentially a voluntarily
chosen state of interdependence with another
person (not codependence, which is
something altogether different). This
state actually characterizes any longterm relationship, including friendships.
Is there anybody among us who has not
been reminded by someone that our
actions have an impact on him or her?
Sometimes, that is how we first
encounter systems, and how we learn
(often painfully) that we are part of a
larger system than we may have realized.
Well, that was quite an excursion. I
hope this tour has revealed that systems
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are indeed all around us and that they
take many different forms. In spite of
these differences, though, all systems
share several defining characteristics. It
may be helpful at this point to summarize those characteristics.
Defining Characteristics of
Systems
Systems have purpose. As we saw in the
examples above, every system has some
purpose that defines it as a discrete
entity and that provides a kind of
integrity that holds it together. The purpose, however, is a property of the system as a whole and not of any of the
parts. For example, the purpose of an
automobile is to provide a means to
take people and things from one place
to another. This purpose is a property
of the automobile as a whole and cannot be detected in just the wheels, the
engine, or any other part.
All parts must be present for a system to carry out its purpose optimally.
If you can take pieces away from something without affecting its functioning,
then you have a collection of parts, not
a system. In the toolbox example, if you
remove a wrench, you have fewer tools,
but you have not changed the nature of
what is in the box. Likewise, if you can
add pieces to a collection without
affecting its functioning, it’s still just a
collection.
The order in which the parts are
arranged affects the performance of a
system. If the components of a collection can be combined in any random
order, then they do not make up a system. In our toolbox, it doesn’t matter
whether the screwdrivers are piled on
top or buried at the bottom of the box
(unless, of course, you really need a
screwdriver now!). In a system, however, the arrangement of all the parts
matters a great deal. (Imagine trying to
randomly rearrange the parts in your
automobile!)
Systems attempt to maintain stability through feedback. In simplest
terms, feedback is the transmission and
return of information. The most
important feature of feedback is that it
provides information to the system that
lets it know how it is doing relative to
some desired state. For example, the
normal human body temperature is
98.6 degrees Fahrenheit. If you go for a
run, the exertion warms your body
beyond that desired temperature. This
change activates your sweat glands until
the cooling effect of the perspiration
readjusts your temperature back to the
norm. Or, in our car example, imagine
that you are steering your car into a
curve. If you turn too sharply, you
receive feedback in the form of visual
cues and internal sensations that you
are turning too much for the speed at
which you’re traveling. You then make
adjustments to correct the degree of
your turn or alter your speed, or some
combination of both. If you are a passenger in a car driven by someone who
is not paying attention to such feedback, you might be better off getting a
ride with someone else!
The Importance of Purpose
We talked about systemic purpose a bit,
but let’s take a closer look at it. A key to
understanding any system is knowing
its purpose, either as a separate entity
or in relation to a larger system of
which it is a part. In human-made (or
1
3
mechanical) systems, the intended purpose is usually explicit and reasonably
clear, at least at the outset. The purpose
of a washing machine, for example, is to
wash clothes. The washing system is
designed so that all the components
work together to accomplish that purpose as effectively as possible.1 In
mechanical systems, the purpose is usually “hard-wired” into the design and
therefore does not evolve over time.
Your car, for example, was designed to
take you places and will continue to
operate with that purpose (provided
you do your part in taking regular care
of it). You’ll never encounter a situation
where you wake up one morning and
your car has changed its purpose to be
a lawnmower (though it may turn into
a big, heavy, unmoving paperweight!).
Living (or natural) systems, on the
other hand, are continually evolving
and have the capacity to change their
purpose, temporarily or permanently.
For example, one of the most basic
assumptions people make about animals is that they are driven only by survival instincts and the need to pass on
their genes. As we deepen our understanding of nature, however, scientists
are discovering that many animals seem
to have much more complex set of purposes—some of them quite social—that
govern their behavior. (Of course, we
humans take it for granted that we have
higher purposes beyond survival.)
Natural and social systems can be
far more difficult to understand than
nonliving systems, because we can
never know for sure what their purpose
Beware: Customers who buy these systems may use them for other purposes that fit their own needs.
In such situations, where a system is used for a purpose different from the one for which it was originally designed, the system is likely to degrade or fail. An unexpected use of washing machines actually occurred in Japan, where farmers employed the machines to wash their potatoes—and then
complained to the manufacturer about the frequent breakdowns! The company had the option of
trying to redesign the machine to accomplish both purposes effectively or to persuade the farmers
not to wash their potatoes in them. In this case, the company chose to change the design and tout
the machine’s ruggedness as an extra feature.
4
Introduction to Systems Thinking
or design is. As a result of this inability
to truly know their purpose and design,
we tend to take actions in these systems
without really understanding the
impact of our actions on the system.
Whenever we do this, we risk causing a
breakdown of the system. For example,
people smoked tobacco for years before
it was discovered that one of smoking’s
long-term consequences is lung cancer.
Even though we had a fairly good
understanding of the purpose of our
lungs, we did not have a sufficient
understanding of how the lungs worked
and what impact smoking would have
on them—and us—over a long period
of time. Since we aren’t the designers of
the human body, we have to learn about
how it works as a system largely by trial
and error. Similarly, farmers have had to
learn about ecological systems in much
the same way, and managers struggle
with organizational behavior for the
same reasons. Like the human body,
nature and human social systems don’t
come with an owner’s manual.
Despite our ignorance about natural and social systems, we still can’t
seem to resist attributing some purpose
to them. We even tend to impose a purpose on natural systems and then
behave toward them in a way that is
consistent with that purpose. For example, in some countries, people view
dogs as pets for families to enjoy. In
such regions, people might treat dogs
almost as members of the family. In
other parts of the world, dogs are seen
as a source of food, and people treat
them accordingly. In both situations,
the practices toward dogs are consistent
with each different, perceived purpose.
Neither viewpoint is intrinsically right
or wrong, although each may seem
wrong when viewed through the “lens”
of the other.
Clearly, there are lots of systems to
choose from if you want to study sys-
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temic behavior. But as we will see, social
systems make up the most complex class
of systems—which you probably already
know from direct experience in trying to
manage some of them!
Putting Systems
in Context:
“The Iceberg”
the patterns and events we observe. In
the example above about defective
products, perhaps shifts are scheduled
such that there is no overlap between
the outgoing and incoming work
crews—hence, there’s a greater likelihood of defects during these times.
Note that systemic structures can be
physical (such as the way a workspace is
organized, or the way a machine is
built) as well as intangible (such as ways
employees are rewarded, or the way
shift changes are timed).
A key thing to notice about the
three different levels of perspective is
that we live in an event-oriented world,
and our language is rooted at the level
of events. Indeed, we usually notice
events much more easily than we notice
patterns and systemic structures even
though it is systems that are actually
Before we dive more deeply into the
world of systems, it’s helpful to see how
systems fit into a broader context. We
can actually view reality from the following multiple levels of perspective:
events, patterns, and systemic structures
(see “The Iceberg”). As we’ll see below,
systems occupy a key position in this
framework. But what do these levels
mean? Some basic definitions and a few
examples might help:
Events are the occurrences we encounter on a
day-to-day basis. For
THE ICEBERG
example, we catch a cold,
a fire breaks out, or a
defective product comes
off the assembly line at
our company.
Patterns are the
Events
accumulated “memories”
of events. When strung
together as a series over
Patterns
time, they can reveal
recurring trends. For
example, we catch colds
more often when we’re
Systemic Structures
tired, fires break out
more frequently in certain neighborhoods, or
Because systemic structures generate patterns and
we notice a higher numevents—but are very difficult to see—we can
ber of product defects
imagine these three levels as a kind of iceberg, of
which events are only the tip. Because we only see
during shift changes.
the tip of the iceberg, the events, we often let those
Systemic structures
drive our decision-making. In reality, however, the
are the ways in which the
events are the results of deeper patterns and
parts of a system are
systemic structures.
Source: Innovation Associates
organized. These structures actually generate
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driving the events we do see. This tendency to only see events is consistent
with our evolutionary history, which
was geared toward responding to anything that posed an immediate danger
to our well-being. As we’ll see later in
this volume, it’s redesigning things at
the systemic level that offers us far more
leverage to shape our future than simply reacting to events does.
What Do Systems
Do? A Close Look
at Systemic Behavior
We’ve explored what defines systems and
how systems generate the patterns and
events we see around us. But how do we
actually start looking at reality from this
intriguing viewpoint? We need to do two
things: deepen our understanding of
how systems behave, and gain familiarity
with some terms and tools of systems
thinking in order to communicate our
understanding of that behavior. This section “walks” you through some basic system behaviors and uses two powerful
systems thinking tools—causal loop diagrams and behavior over time graphs—
to illustrate the concepts.
A
B
C
D
The feedback loop perspective, on
the other hand, sees the world as an
interconnected set of circular relationships, where something affects something else and is in turn affected by it: A
causes B causes C causes A, etc.
Fun with Feedback
To hone our systems thinking perspective, let’s look again at feedback. As we
saw earlier, feedback is the transmission
and return of information. The key
word here is return—it is this very characteristic that makes the feedback perspective different from the more
common perspective: the linear causeand-effect way of viewing the world.
The linear view sees the world as a
series of unidirectional cause-and-effect
relationships: A causes B causes C
causes D, etc.
MENTAL MODELS AND VISION:
MORE LEVELS OF PERSPECTIVE
We can gain even richer insights into systems by adding two more levels of perspective to the events/patterns/structure model. The two additional levels are
mental models and vision.
Mental models are the beliefs and assumptions we hold about how the world
works. We can view these assumptions as “systemic structure generators,”
because they provide the “blueprints” for those structures. In our example about
defective parts, maybe the production-line folks believe that they are responsible
only for what they produce, not what the shift after them produces. This mental
model may have led the company to create a structure whereby there is no overlap of staff during shift changes.
Vision is our picture of what we want for our future. It is the guiding force that
determines the mental models we hold as important as we pursue our goals. For
example, perhaps the people on each assembly-line shift hold a vision of competition—of striving to produce higher-quality products than any other shift. This
vision would drive the mental model that says that each line is responsible only
for what it produces.
See the “‘Acting’ in Different Modes” appendix on p. 17 for how to incorporate
mental models and vision into the events/patterns/structure framework and take
high-leverage actions to address a problem.
A
B
C
D
As trivial as this distinction between
these two views may seem, it has profound implications for the way we see
the world and for how we manage our
daily lives. When we take the linear
view, we tend to see the world as a
series of events that flow one after the
other. For example, if sales go down
(event A), I take action by launching a
promotions campaign (event B). I then
see orders increase (event C), sales rise
(event D), and backlogs increase (event
E). Then I notice sales decreasing again
(event F), to which I respond with
another promotional campaign (event
G) . . . and so on. Through the “lens” of
this linear perspective, I see the world as
a series of events that trigger other
events. Even though events B and G are
repeating events, I see them as separate
and unrelated.
From a feedback loop perspective
(see “Thinking in Loops” on p. 6), I
would be continually asking myself
“How do the consequences of my actions
feed back to affect the system?” So, when
I see sales go down (event A), I launch a
promotions campaign (event B). I see
orders increase (event C) and sales rise
(change in event A). But I also notice
that backlogs increase (event D)
(another eventual effect of event B),
which affects orders and sales (change in
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events C and A), which leads me to
repeat my original action (event B).
After looking at
both the linear and
feedback represenThose were
excellent slides
tations, you might
you used in your
be saying to yourpresentation.
self, “So what? I’m
too busy to draw
pretty pictures
about my actions.
My job is to produce results—so I
have to take actions
now. Describing
what has happened
in two different
ways still doesn’t
change what actually happens, so why
do the two perspectives matter?” But
here’s a key insight in systems thinking:
How we describe our actions in the
world affects the kinds of actions we take
in the world. So, let’s reexamine the linear and feedback perspectives. Notice
how the feedback view draws your
attention to the interrelationships
among all the events, whereas in the
linear view, you are probably drawn to
each cause-and-effect event pair. By
becoming aware of all the interrelationships involved in a
problem, you’re in a
Why, thank you!
much better position
But that wasn’t
to address the probwhat I meant
by feedback.
lem than if you only
saw separate causeand-effect pairs.
The point here isn’t to
“wax philosophical” about
the intrinsic merits of
two perspectives, but to
identify one that will
help us understand the
behavior of complex systems so that we can better
manage those systems. The main problem with the linear view is that although
it may be a technically accurate way of
describing what happened when, it provides very little insight into how things
happened and why. The primary purpose of the feedback view, on the other
hand, is to gain a better understanding
of all the forces that are producing the
behaviors we are experiencing.
THINKING IN LOOPS
Sales
Are
Down
Marketing
Promotions
Orders
Increase
Sales
Are
Up
Backlogs
Sales
Are
Down
Marketing
Promotions
Marketing
Promotions
(B)
Orders
Increase/Decrease
Sales Are
Down/Up
(C)
Backlogs
(D)
(A)
Thinking in loops helps us see the interrelationships among all the variables in
the system.
The Building Blocks of
Systemic Behavior: Reinforcing
and Balancing Processes
Feedback is just one piece of the picture
when we’re thinking about how systems
behave. To fill out the picture, let’s consider some examples of systemic behavior that we’ve all experienced. For
instance, maybe you’ve worked in a
company that was initially growing
exponentially in sales, only to collapse a
few years later. Or, maybe you’ve
engaged in one of America’s favorite
pastimes—dieting—where you kept
losing the same 15 pounds over and
over again. Or, you may recall that,
when you were first learning to ride a
bicycle, you wobbled down the street
trying to stabilize yourself and eventually fell down (wondering what was
wrong with three wheels anyhow).
All of these examples might seem
completely unrelated on the surface;
however, if we take a closer look at
them, we can identify some very basic
things that they have in common. In
fact, all systemic behavior can be
described through just two basic
processes—called reinforcing and balancing processes. Both of these “building blocks” of systemic behavior involve
distinctly different feedback. And, it’s
the combinations of these processes that
give rise to the vast variety of dynamic
behavior in the systems we see all
around us.
Reinforcing Processes: The Engines
of Growth and Collapse. Reinforcing
processes arise from what’s known as
positive feedback. No, this isn’t praise
for a job well done. In systems terminology, it means information that compounds change in one direction with
even more change in that direction. In
other words, successive changes add to
the previous changes and keep the
change going in the same direction.
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Let’s take a simple example of a savings account. If you have a positive balance, each time there is an interest
payment calculation, the amount will
be slightly bigger than the preceding
payment period. This is because the
balance has grown since the previous
calculation. The time period after that,
the interest amount will be bigger still,
because the balance has grown a little
more since the time before. Of course,
all this is assuming that you are not
making withdrawals during this time
(which may be a big assumption for
many of us!).
Savings
Balance
Interest
Payments
Savings
Time
Another example is the wonderful
growth engine that every marketer
knows about: the word-of-mouth effect.
As you increase the number of customers using your products, there are
more “mouths” to tell others about your
products. The resulting awareness leads
Number of
Customers
Sales
Word-of-Mouth
Effect
Customers
Time
7
BEHAVIOR OVER TIME GRAPHS
Throughout the rest of this volume, you’ll notice a few diagrams that look like
this:
These are called behavior over time graphs. They’re valuable because they show
how certain variables that may be of interest to us—such as our savings balance,
the number of customers we have, or our weight—are changing over time. They
also provide clues to the kind of systemic processes that may be at work. A rapidly rising or falling graph, for example, indicates a reinforcing process, whereas
an oscillating graph suggests what’s called a balancing process.
to more sales, which leads to even more
happy customers telling others. (Of
course, this scenario is based on the
assumption that your customers have
nice things to say about your product!)
In the bank-account and word-ofmouth scenarios, a reinforcing dynamic
drives change in one direction with
even more change in the same direction. You can detect this kind of loop at
work simply by sensing exponential
growth or collapse (such as the rapid
spread of an exciting new idea, or a
company that suddenly goes out of
business).
You can also think of reinforcing
processes as “virtuous circles” when
they produce desirable behavior. You
may have encountered virtuous circles
when you heard people talking about
coming down the learning curve (the
compounded increase in rate of learning as we learn more) or increasing
economies of scale (the higher the production volume gets, the lower our unit
costs become).
When reinforcing processes produce
behavior we do not want, they are called
“vicious cycles.” Oftentimes, a virtuous
loop can become a vicious loop when
something kicks it in the opposite
direction. In our word-of-mouth
(WOM) example, the loop can turn
“mean” if what people have to say about
our product is negative. The negative
WOM effect leads to lower sales, fewer
customers, less WOM effect, even lower
sales, etc.
These reinforcing processes are
already embedded in our everyday language, which speaks to their pervasive
presence. You’ve probably heard or used
expressions such as “we were caught in
a death spiral” or “things just kept
snowballing.” Mapping such processes
explicitly onto feedback loop diagrams
(or causal loop diagrams, as they are
called in the systems thinking field) lets
us see and talk about them collectively
so that we can respond more effectively
to them.
Balancing Processes: The Great
Stabilizers. We know there must be
more to systems than just reinforcing
loops, because our experience tells us
that nothing grows forever (well, okay,
except for taxes). We need something
else to describe other kinds of behavior
that do not look like continual exponential growth or decline. When we
look around us, we see a great deal of
stability, despite all the talk about the
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era of rapid change we are in. For
example, despite the rising or falling
fortunes of individual companies or
industries, the world of commerce continues to thrive around the globe. The
world does change, but it does so on a
platform of great stability. What
accounts for all this constancy? It is balancing loops, the other “building block”
of systemic behavior.
Balancing loops are continually trying to keep a system at some desired
level of performance, much as a thermostat regulates the temperature in
your house. Whereas the snowballing
effect of reinforcing loops destabilizes
systems (that is, puts them out of equilibrium), balancing loops are generally
stabilizing or goal seeking. They resist
change in one direction by producing
change in the opposite direction, which
negates the previous effects. (This is
why they are also called negative feedback loops.) For example, when the
thermostat in your home detects that
the room temperature is higher than
the thermostat setting, it shuts down
the heat.
There is always an inherent goal in a
balancing process, and what “drives” a
balancing loop is the gap between the
goal (the desired level) and the actual
level. As the discrepancy between the
two levels widens, the system takes corrective actions to adjust the actual level
until the discrepancy decreases. In the
thermostat example, gaps between the
actual room temperature and the temperature setting of the thermostat (the
goal) prompt the thermostat to adjust
the heating or cooling mechanisms in
the house to bring the actual temperaActual
Level
Desired
Level
Gap
Corrective
Actions
Temperature
8
Desired
Actual
Time
YOU TRY IT: REINFORCING PROCESSES
Now that you have a feeling for what reinforcing loops are like, try your hand at
drawing a few of them. They could be from your personal life (falling in love,
making an investment) or professional setting (launching a new product, learning a new skill). The main point is to depict a clear and compelling story of how
things mutually reinforce change in one direction in a complete circle.
ture closer to the desired temperature.
In this sense, balancing processes always
try to bring conditions into some state
of equilibrium.
It would not be a gross exaggeration
to say that balancing processes are everywhere. They are far more ubiquitous
than reinforcing loops. However, they’re
a lot less visible, because they quietly
function to keep things as they are. We
tend to notice things that have changed
much more than things that remain the
same. For example, think about the
times when you are aware of your body
temperature. Most likely, you notice it
only when it has “gr
