IntroductionEvery author, I suppose, has in mind a set.docx

Introduction
Every author, I suppose, has in mind a setting in which readers
of his or her work could benefit
from having read it. Mine is the proverbial office watercooler,
where opinions are shared and
gossip is exchanged. I hope to enrich the vocabulary that people
use when they talk about the
judgments and choices of others, the company’s new policies, or
a colleague’s investment
decisions. Why be concerned with gossip? Because it is much
easier, as well as far more
enjoyable, to identify and label the mistakes of others than to
recognize our own. Questioning what
we believe and want is difficult at the best of times, and
especially difficult when we most need to
do it, but we can benefit from the informed opinions of others.
Many of us spontaneously anticipate
how friends and colleagues will evaluate our choices; the
quality and content of these anticipated
judgments therefore matters. The expectation of intelligent
gossip is a powerful motive for serious
self-criticism, more powerful than New Year resolutions to
improve one’s decision making at
work and at home.
To be a good diagnostician, a physician needs to acquire a large
set of labels for diseases, each
of which binds an idea of the illness and its symptoms, possible
antecedents and causes, possible

developments and consequences, and possible interventions to
cure or mitigate the illness.
Learning medicine consists in part of learning the language of
medicine. A deeper understanding of
judgments and choices also requires a richer vocabulary than is
available in everyday language.
The hope for informed gossip is that there are distinctive
patterns in the errors people make.
Systematic errors are known as biases, and they recur
predictably in particular circumstances.
When the handsome and confident speaker bounds onto the
stage, for example, you can anticipate
that the audience will judge his comments more favorably than
he deserves. The availability of a
diagnostic label for this bias—the halo effect—makes it easier
to anticipate, recognize, and
understand.
When you are asked what you are thinking about, you can
normally answer. You believe you
know what goes on in your mind, which often consists of one
conscious thought leading in an
orderly way to another. But that is not the only way the mind
works, nor indeed is that the typical
way. Most impressions and thoughts arise in your conscious
experience without your knowing how
they got there. You cannot tracryd>e how you came to the belief
that there is a lamp on the desk in
front of you, or how you detected a hint of irritation in your
spouse’s voice on the telephone, or
how you managed to avoid a threat on the road before you
became consciously aware of it. The
mental work that produces impressions, intuitions, and many
decisions goes on in silence in our
mind.

Much of the discussion in this book is about biases of intuition.
However, the focus on error
does not denigrate human intelligence, any more than the
attention to diseases in medical texts
denies good health. Most of us are healthy most of the time, and
most of our judgments and actions
are appropriate most of the time. As we navigate our lives, we
normally allow ourselves to be
guided by impressions and feelings, and the confidence we have
in our intuitive beliefs and
preferences is usually justified. But not always. We are often
confident even when we are wrong,
and an objective observer is more likely to detect our errors
than we are.
So this is my aim for watercooler conversations: improve the
ability to identify and understand
errors of judgment and choice, in others and eventually in
ourselves, by providing a richer
and more precise language to discuss them. In at least some
cases, an accurate diagnosis may
suggest an intervention to limit the damage that bad judgments
and choices often cause.
7
Two Systems
The Characters of the Story
To observe your mind in automatic mode, glance at the image
below.
Figure 1

Your experience as you look at the woman’s face seamlessly
combines what we normally call
seeing and intuitive thinking. As surely and quickly as you saw
that the young woman’s hair is
dark, you knew she is angry. Furthermore, what you saw
extended into the future. You sensed that
this woman is about to say some very unkind words, probably in
a loud and strident voice. A
premonition of what she was going to do next came to mind
automatically and effortlessly. You did
not intend to assess her mood or to anticipate what she might
do, and your reaction to the picture
did not have the feel of something you did. It just happened to
you. It was an instance of fast
thinking.
Now look at the following problem:
17 × 24
You knew immediately that this is a multiplication problem, and
probably knew that you could
solve it, with paper and pencil, if not without. You also had
some vague intuitive knowledge of the
range of possible results. You would be quick to recognize that
both 12,609 and 123 are
implausible. Without spending some time on the problem,
however, you would not be certain that
the answer is not 568. A precise solution did not come to mind,
and you felt that you could choose
whether or not to engage in the computation. If you have not
done so yet, you should attempt the
multiplication problem now, completing at least part of it.
You experienced slow thinking as you proceeded through a
sequence of steps. You first

retrieved from memory the cognitive program for multiplication
that you learned in school, then
you implemented it. Carrying out the computation was a strain.
You felt the burden of holding much
material in memory, as you needed to keep track of where you
were and of where you were going,
while holding on to the intermediate result. The process was
mental work: deliberate, effortful,
and orderly—a prototype of slow thinking. The computation
was not only an event in your mind;
your body was also involved. Your muscles tensed up, your
blood pressure rose, and your heart
17
rate increased. Someone looking closely at your eyes while you
tackled this problem would have
seen your pupils dilate. Your pupils contracted back to normal
size as soon as you ended your
work—when you found the answer (which is 408, by the way)
or when you gave up.
Two Systems
Psychologists have been intensely interested for several decades
in the two modagee fi Pn="cees
of thinking evoked by the picture of the angry woman and by
the multiplication problem, and have
offered many labels for them. I adopt terms originally proposed
by the psychologists Keith
Stanovich and Richard West, and will refer to two systems in
the mind, System 1 and System 2.
System 1 operates automatically and quickly, with little or no

effort and no sense of voluntary
control.
System 2 allocates attention to the effortful mental activities
that demand it, including
complex computations. The operations of System 2 are often
associated with the subjective
experience of agency, choice, and concentration.
The labels of System 1 and System 2 are widely used in
psychology, but I go further than most in
this book, which you can read as a psychodrama with two
characters.
When we think of ourselves, we identify with System 2, the
conscious, reasoning self that has
beliefs, makes choices, and decides what to think about and
what to do. Although System 2
believes itself to be where the action is, the automatic System 1
is the hero of the book. I describe
System 1 as effortlessly originating impressions and feelings
that are the main sources of the
explicit beliefs and deliberate choices of System 2. The
automatic operations of System 1 generate
surprisingly complex patterns of ideas, but only the slower
System 2 can construct thoughts in an
orderly series of steps. I also describe circumstances in which
System 2 takes over, overruling the
freewheeling impulses and associations of System 1. You will
be invited to think of the two
systems as agents with their individual abilities, limitations, and
functions.
In rough order of complexity, here are some examples of the
automatic activities that are
attributed to System 1:

Detect that one object is more distant than another.
Orient to the source of a sudden sound.
Complete the phrase “bread and…”
Make a “disgust face” when shown a horrible picture.
Detect hostility in a voice.
Answer to 2 + 2 = ?
Read words on large billboards.
Drive a car on an empty road.
Find a strong move in chess (if you are a chess master).
Understand simple sentences.
Recognize that a “meek and tidy soul with a passion for detail”
resembles an occupational
18
stereotype.
All these mental events belong with the angry woman—they
occur automatically and require little
or no effort. The capabilities of System 1 include innate skills
that we share with other animals.
We are born prepared to perceive the world around us,
recognize objects, orient attention, avoid
losses, and fear spiders. Other mental activities become fast and
automatic through prolonged
practice. System 1 has learned associations between ideas (the
capital of France?); it has also
learned skills such as reading and understanding nuances of
social situations. Some skills, such as
finding strong chess moves, are acquired only by specialized
experts. Others are widely shared.
Detecting the similarity of a personality sketch to an
occupatiohein occupatnal stereotype requires

broad knowledge of the language and the culture, which most of
us possess. The knowledge is
stored in memory and accessed without intention and without
effort.
Several of the mental actions in the list are completely
involuntary. You cannot refrain from
understanding simple sentences in your own language or from
orienting to a loud unexpected
sound, nor can you prevent yourself from knowing that 2 + 2 =
4 or from thinking of Paris when the
capital of France is mentioned. Other activities, such as
chewing, are susceptible to voluntary
control but normally run on automatic pilot. The control of
attention is shared by the two systems.
Orienting to a loud sound is normally an involuntary operation
of System 1, which immediately
mobilizes the voluntary attention of System 2. You may be able
to resist turning toward the source
of a loud and offensive comment at a crowded party, but even if
your head does not move, your
attention is initially directed to it, at least for a while. However,
attention can be moved away from
an unwanted focus, primarily by focusing intently on another
target.
The highly diverse operations of System 2 have one feature in
common: they require attention
and are disrupted when attention is drawn away. Here are some
examples:
Brace for the starter gun in a race.
Focus attention on the clowns in the circus.
Focus on the voice of a particular person in a crowded and

noisy room.
Look for a woman with white hair.
Search memory to identify a surprising sound.
Maintain a faster walking speed than is natural for you.
Monitor the appropriateness of your behavior in a social
situation.
Count the occurrences of the letter a in a page of text.
Tell someone your phone number.
Park in a narrow space (for most people except garage
attendants).
Compare two washing machines for overall value.
Fill out a tax form.
Check the validity of a complex logical argument.
In all these situations you must pay attention, and you will
perform less well, or not at all, if you
are not ready or if your attention is directed inappropriately.
System 2 has some ability to change
the way System 1 works, by programming the normally
automatic functions of attention and
memory. When waiting for a relative at a busy train station, for
example, you can set yourself at
19
will to look for a white-haired woman or a bearded man, and
thereby increase the likelihood of
detecting your relative from a distance. You can set your
memory to search for capital cities that
start with N or for French existentialist novels. And when you
rent a car at London’s Heathrow
Airport, the attendant will probably remind you that “we drive
on the left side of the road over

here.” In all these cases, you are asked to do something that
does not come naturally, and you will
find that the consistent maintenance of a set requires continuous
exertion of at least some effort.
The often-used phrase “pay attention” is apt: you dispose of a
limited budget of attention that
you can allocate to activities, and if you try to i>Cyou try tgo
beyond your budget, you will fail. It
is the mark of effortful activities that they interfere with each
other, which is why it is difficult or
impossible to conduct several at once. You could not compute
the product of 17 × 24 while making
a left turn into dense traffic, and you certainly should not try.
You can do several things at once, but
only if they are easy and undemanding. You are probably safe
carrying on a conversation with a
passenger while driving on an empty highway, and many parents
have discovered, perhaps with
some guilt, that they can read a story to a child while thinking
of something else.
Everyone has some awareness of the limited capacity of
attention, and our social behavior
makes allowances for these limitations. When the driver of a car
is overtaking a truck on a narrow
road, for example, adult passengers quite sensibly stop talking.
They know that distracting the
driver is not a good idea, and they also suspect that he is
temporarily deaf and will not hear what
they say.
Intense focusing on a task can make people effectively blind,
even to stimuli that normally attract
attention. The most dramatic demonstration was offered by
Christopher Chabris and Daniel

Simons in their book The Invisible Gorilla. They constructed a
short film of two teams passing
basketballs, one team wearing white shirts, the other wearing
black. The viewers of the film are
instructed to count the number of passes made by the white
team, ignoring the black players. This
task is difficult and completely absorbing. Halfway through the
video, a woman wearing a gorilla
suit appears, crosses the court, thumps her chest, and moves on.
The gorilla is in view for 9
seconds. Many thousands of people have seen the video, and
about half of them do not notice
anything unusual. It is the counting task—and especially the
instruction to ignore one of the teams
—that causes the blindness. No one who watches the video
without that task would miss the
gorilla. Seeing and orienting are automatic functions of System
1, but they depend on the allocation
of some attention to the relevant stimulus. The authors note that
the most remarkable observation of
their study is that people find its results very surprising. Indeed,
the viewers who fail to see the
gorilla are initially sure that it was not there—they cannot
imagine missing such a striking event.
The gorilla study illustrates two important facts about our
minds: we can be blind to the obvious,
and we are also blind to our blindness.
Plot Synopsis
The interaction of the two systems is a recurrent theme of the
book, and a brief synopsis of the plot
is in order. In the story I will tell, Systems 1 and 2 are both
active whenever we are awake. System
1 runs automatically and System 2 is normally in a comfortable
low-effort mode, in which only a

fraction of its capacity is engaged. System 1 continuously
generates suggestions for System 2:
impressions, intuitions, intentions, and feelings. If endorsed by
System 2, impressions and
intuitions turn into beliefs, and impulses turn into voluntary
actions. When all goes smoothly, which
is most of the time, System 2 adopts the suggestions of System
1 with little or no modification. You
generally believe your impressions and act on your desires, and
that is fine—usually.
When System 1 runs into difficulty, it calls on System 2 to
support more detailed and specific
20
processing that may solve the problem of the moment. System 2
is mobilized when a question
arises for which System 1 does not offer an answer, as probably
happened to you when you
encountered the multiplication problem 17 × 24. You can also
feel a surge of conscious attention
whenever you are surprised. System 2 is activ">< 2 is actated
when an event is detected that
violates the model of the world that System 1 maintains. In that
world, lamps do not jump, cats do
not bark, and gorillas do not cross basketball courts. The gorilla
experiment demonstrates that
some attention is needed for the surprising stimulus to be
detected. Surprise then activates and
orients your attention: you will stare, and you will search your
memory for a story that makes sense
of the surprising event. System 2 is also credited with the
continuous monitoring of your own

behavior—the control that keeps you polite when you are angry,
and alert when you are driving at
night. System 2 is mobilized to increased effort when it detects
an error about to be made.
Remember a time when you almost blurted out an offensive
remark and note how hard you worked
to restore control. In summary, most of what you (your System
2) think and do originates in your
System 1, but System 2 takes over when things get difficult, and
it normally has the last word.
The division of labor between System 1 and System 2 is highly
efficient: it minimizes effort and
optimizes performance. The arrangement works well most of the
time because System 1 is
generally very good at what it does: its models of familiar
situations are accurate, its short-term
predictions are usually accurate as well, and its initial reactions
to challenges are swift and
generally appropriate. System 1 has biases, however, systematic
errors that it is prone to make in
specified circumstances. As we shall see, it sometimes answers
easier questions than the one it
was asked, and it has little understanding of logic and statistics.
One further limitation of System 1
is that it cannot be turned off. If you are shown a word on the
screen in a language you know, you
will read it—unless your attention is totally focused elsewhere.
Conflict
Figure 2 is a variant of a classic experiment that produces a
conflict between the two systems. You
should try the exercise before reading on.

Figure 2
21
You were almost certainly successful in saying the correct
words in both tasks, and you surely
discovered that some parts of each task were much easier than
others. When you identified upper-
and lowercase, the left-hand column was easy and the right-
hand column caused you to slow down
and perhaps to stammer or stumble. When you named the
position of words, the left-hand column
was difficult and the right-hand column was much easier.
These tasks engage System 2, because saying “upper/lower” or
“right/left” is not what you
routinely do when looking down a column of words. One of the
things you did to set yourself for
the task was to program your memory so that the relevant words
(upper and lower for the first
task) were “on the tip of your tongue.” The prioritizing of the
chosen words is effective and the
mild temptation to read other words was fairly easy to resist
when you went through the first
column. But the second column was different, because it
contained words for which you were set,
and you could not ignore them. You were mostly able to
respond correctly, but overcoming the
competing response was a strain, and it slowed you down. You
experienced a conflict between a
task that you intended to carry out and an automatic response
that interfered with it.

Conflict between an automatic reaction and an intention to
conWhetion to ctrol it is common in
our lives. We are all familiar with the experience of trying not
to stare at the oddly dressed couple
at the neighboring table in a restaurant. We also know what it is
like to force our attention on a
boring book, when we constantly find ourselves returning to the
point at which the reading lost its
meaning. Where winters are hard, many drivers have memories
of their car skidding out of control
on the ice and of the struggle to follow well-rehearsed
instructions that negate what they would
naturally do: “Steer into the skid, and whatever you do, do not
touch the brakes!” And every human
being has had the experience of not telling someone to go to
hell. One of the tasks of System 2 is to
overcome the impulses of System 1. In other words, System 2 is
in charge of self-control.
Illusions
To appreciate the autonomy of System 1, as well as the
distinction between impressions and
beliefs, take a good look at figure 3.
This picture is unremarkable: two horizontal lines of different
lengths, with fins appended,
pointing in different directions. The bottom line is obviously
longer than the one above it. That is
what we all see, and we naturally believe what we see. If you
have already encountered this
image, however, you recognize it as the famous Müller-Lyer
illusion. As you can easily confirm by
measuring them with a ruler, the horizontal lines are in fact
identical in length.

Figure 3
22
Now that you have measured the lines, you—your System 2, the
conscious being you call “I”—
have a new belief: you know that the lines are equally long. If
asked about their length, you will
say what you know. But you still see the bottom line as longer.
You have chosen to believe the
measurement, but you cannot prevent System 1 from doing its
thing; you cannot decide to see the
lines as equal, although you know they are. To resist the
illusion, there is only one thing you can
do: you must learn to mistrust your impressions of the length of
lines when fins are attached to
them. To implement that rule, you must be able to recognize the
illusory pattern and recall what you
know about it. If you can do this, you will never again be fooled
by the Müller-Lyer illusion. But
you will still see one line as longer than the other.
Not all illusions are visual. There are illusions of thought,
which we call cognitive illusions.
As a graduate student, I attended some courses on the art and
science of psychotherapy. During one
of these lectures, our teacher imparted a morsel of clinical
wisdom. This is what he told us: “You
will from time to time meet a patient who shares a disturbing
tale of multiple mistakes in his
previous treatment. He has been seen by several clinicians, and
all failed him. The patient can
lucidly describe how his therapists misunderstood him, but he
has quickly perceived that you are

different. You share the same feeling, are convinced that you
understand him, and will be able to
help.” At this point my teacher raised his voice as he said, “Do
not even think of taking on this
patient! Throw him out of the office! He is most likely a
psychopath and you will not be able to
help him.”
Many years later I learned that the teacher had warned us
against psychopathic charm, and the
leading authority in the strn y in the udy of psychopathy
confirmed that the teacher’s advice was
sound. The analogy to the Müller-Lyer illusion is close. What
we were being taught was not how
to feel about that patient. Our teacher took it for granted that
the sympathy we would feel for the
patient would not be under our control; it would arise from
System 1. Furthermore, we were not
being taught to be generally suspicious of our feelings about
patients. We were told that a strong
attraction to a patient with a repeated history of failed treatment
is a danger sign—like the fins on
the parallel lines. It is an illusion—a cognitive illusion—and I
(System 2) was taught how to
recognize it and advised not to believe it or act on it.
The question that is most often asked about cognitive illusions
is whether they can be overcome.
The message of these examples is not encouraging. Because
System 1 operates automatically and
cannot be turned off at will, errors of intuitive thought are often
difficult to prevent. Biases cannot
always be avoided, because System 2 may have no clue to the
error. Even when cues to likely
errors are available, errors can be prevented only by the
enhanced monitoring and effortful activity

of System 2. As a way to live your life, however, continuous
vigilance is not necessarily good, and
it is certainly impractical. Constantly questioning our own
thinking would be impossibly tedious,
and System 2 is much too slow and inefficient to serve as a
substitute for System 1 in making
routine decisions. The best we can do is a compromise: learn to
recognize situations in which
mistakes are likely and try harder to avoid significant mistakes
when the stakes are high. The
premise of this book is that it is easier to recognize other
people’s mistakes than our own.
Useful Fictions
You have been invited to think of the two systems as agents
within the mind, with their individual
personalities, abilities, and limitations. I will often use
sentences in which the systems are the
subjects, such as, “System 2 calculates products.”
The use of such language is considered a sin in the professional
circles in which I travel,
because it seems to explain the thoughts and actions of a person
by the thoughts and actions of little
23
people inside the person’s head. Grammatically the sentence
about System 2 is similar to “The
butler steals the petty cash.” My colleagues would point out that
the butler’s action actually
explains the disappearance of the cash, and they rightly
question whether the sentence about

System 2 explains how products are calculated. My answer is
that the brief active sentence that
attributes calculation to System 2 is intended as a description,
not an explanation. It is meaningful
only because of what you already know about System 2. It is
shorthand for the following: “Mental
arithmetic is a voluntary activity that requires effort, should not
be performed while making a left
turn, and is associated with dilated pupils and an accelerated
heart rate.”
Similarly, the statement that “highway driving under routine
conditions is left to System 1”
means that steering the car around a bend is automatic and
almost effortless. It also implies that an
experienced driver can drive on an empty highway while
conducting a conversation. Finally,
“System 2 prevented James from reacting foolishly to the
insult” means that James would have
been more aggressive in his response if his capacity for
effortful control had been disrupted (for
example, if he had been drunk).
System 1 and System 2 are so central to the story I tell in this
book that I must make it absolutely
clear that they are217at they a fictitious characters. Systems 1
and 2 are not systems in the standard
sense of entities with interacting aspects or parts. And there is
no one part of the brain that either
of the systems would call home. You may well ask: What is the
point of introducing fictitious
characters with ugly names into a serious book? The answer is
that the characters are useful
because of some quirks of our minds, yours and mine. A
sentence is understood more easily if it
describes what an agent (System 2) does than if it describes

what something is, what properties it
has. In other words, “System 2” is a better subject for a
sentence than “mental arithmetic.” The
mind—especially System 1—appears to have a special aptitude
for the construction and
interpretation of stories about active agents, who have
personalities, habits, and abilities. You
quickly formed a bad opinion of the thieving butler, you expect
more bad behavior from him, and
you will remember him for a while. This is also my hope for the
language of systems.
Why call them System 1 and System 2 rather than the more
descriptive “automatic system” and
“effortful system”? The reason is simple: “Automatic system”
takes longer to say than “System 1”
and therefore takes more space in your working memory. This
matters, because anything that
occupies your working memory reduces your ability to think.
You should treat “System 1” and
“System 2” as nicknames, like Bob and Joe, identifying
characters that you will get to know over
the course of this book. The fictitious systems make it easier for
me to think about judgment and
choice, and will make it easier for you to understand what I say.
Speaking of System 1 and System 2
“He had an impression, but some of his impressions are
illusions.”
“This was a pure System 1 response. She reacted to the threat
before she recognized it.”
“This is your System 1 talking. Slow down and let your System
2 take control.”

24
Stripped down to its essentials, business is about one thing:
making decisions. We’re always deciding something - from the
small and the daily ( which emails to answer, what meetings to
have ) to the macro and the strategic ( what product to launch
and when ) to the intensely personal ( what job to take, whom
to hire, whom to marry ). But what does it take to make a
“good” decision? Is it about going by facts and percentages - or
about following your gut instinct? Does time produce better
decisions, or does pressure make you decide not only faster but
also more wisely? And finally, is better decision making some-
thing that you can learn? We asked 11 decisive leaders, inside
and outside of business, to answer these and other, related
questions. Does their advice help? You decide.
Ed Koch
Partner
Robinson Silverman Pearce Aronsohn & Berman LLP
New York, New York
To make good decisions, you need confidence in your judg-
ment. We all make bad decisions, but the important thing is
not to worry too much about them. Otherwise, you’ll never do
a thing. I was mayor of New York City for 12 years. I had a $28
billion budget. Each decision I made affected seven and a half
million people. The stakes were high. I had to show confidence
- in particular, confidence in my decision-making ability -
because a lot of people had put their trust in me. The worst
decision I ever made was to run for governor of New York State
in 1982. I did it on a lark, and it was stupid. Thank god the peo-

ple of New York had enough sense to understand that I didn’t
have my heart in that race - and to vote against me. They did
the right thing, and I was happier because of it.
As a judge, I have to decide on the credibility of two people
standing before me. I don’t know who is telling the truth, but I
know that one of them is lying. That’s when making decisions
gets sticky. Sure, the law helps me make such decisions. But
there have been many times when I’ve had a hell of a time
deciding. Even so, I never base my courtroom decisions on gut
instinct. I go by the evidence - or the lack of evidence - and by
the applicable law.
Ed Koch was mayor of New York City from 1978 to 1989.
Today he writes a weekly column for the New York Daily
News,
has his own radio talk show, and is the judge on the television
program “The People’s Court.”
Pamela Lopker
Chairman and President
QAD Inc.
Carpinteria, California
I make bad decisions all the time. But I’ve been successful
because I’ve developed a process for identifying and changing
those decisions quickly. I approach every decision with an eye
to the long-term outcome. That’s a hard method to adopt in a
fast-paced business environment. But it’s the only way to create
sustainable value on either a professional or a personal level.
The quick-fix method that I see so many companies rely on is
just that - a quick fix. There’s a big difference between invest-
ing heavily in marketing the product that you have today - with
no sense of what it takes to survive tomorrow - and investing
heavily in R&D today so that you can have tomorrow’s product.

Even in my personal life, I looked at decisions from the per-
spective of what’s going to be better for me over the long term.
When I was in college, I needed to decide on a career path.
While most of my peers were concerned with following their
passion, with doing what they “loved” to do, I was looking for a
career that would support me financially over the long run.
Sometimes making important decisions is just a matter of ask-
ing some basic questions: What are my skills? Where is a cer-
tain industry going? What should I be doing now to get to
where I want to be later? Because I was always strong in math
and in analytical thinking, I figured that I would do statistical
or actuarial work. Then I realized that statistics wasn’t a boom-
ing industry. Computer science seemed like a better long-term
bet, so I changed my major.
As a leader, I try not to make decisions for others. Sure, being a
dictator is often the fastest way to get things done. But it’s not a
process that allows an organization to sustain growth. I want the
people in my organization to learn the lessons that come with
making decisions: that everything is a compromise, that noth-
ing is ever completely logical, but that you can deal with things
through a logical decision-making process.
Pamela Lopker has been called America’s “richest self-made
1© All rights reserved. Fast Company, LLC • Visit:
http://www.fastcompany.com/learning
FC :L E A R N I N G
Decisions, Decisions
Unit of One
BY ANNA MUOIO
First appeared: FC18, p.93

woman.” QAD, a $172 million enterprise resource-planning
software company, is one of the 30 largest public companies to
be led by a female CEO. Its clients include Avon Products,
PepsiCo, Ford, and Johnson & Johnson.
W. Brian Arthur
Citibank Professor
Santa Fe Institute
Santa Fe, New Mexico
I received my PhD in operations research, which is a highly sci-
entific, mathematical way of strategizing and of making deci-
sions. I once thought that I could make any decision, whether
professional or personal, by using decision trees, game theory,
and optimization. Over time, I’ve changed my mind. For the
day-to-day work of running a business - scheduling a fleet of oil
tankers, choosing where to open a new factory - scientific deci-
sion theory works pretty well. But for just about every other
kind of decision, it doesn’t work at all.
For the big decisions in life, you need to reach a deeper region
of consciousness. Making decisions then becomes not so much
about “deciding” as about letting an inner wisdom emerge.
We’ve been bamboozled into believing that cognition is ration-
al - that our mind is a gigantic computer, or a blackboard on
which we can reach a decision by calculating pluses and
minuses. Recent research on cognition shows that our minds
rarely make strictly logical deductions. Instead, we rely on pat-
terns - and on feelings associated with those patterns.
So for those big decisions - Should I marry this person? Should
I follow that career? Should I sell my company? When should
we go public? - let patterns develop in your mind. Let clues and

evidence emerge from your environment. This approach to
decision making requires time, patience, and another key
ingredient: courage. It takes courage to listen to your inner wis-
dom. But once you hear that wisdom, making a decision
becomes fairly easy.
W. Brian Arthur’s work on the economics of increasing returns
and their role in technology-based industries has won him
international recognition in the scientific and business com-
munities. He is a pioneer of the new science of complexity and
the author of The Economy as an Evolving Complex System II
( Addison-Wesley, 1997 ).
Chung-Jen Tan
Senior Manager, Application Systems
IBM’s Thomas J. Watson Research Center
Yorktown Heights, New York
I’ve learned a lot about decision making by watching how a
machine plays chess. In 1996, Deep Blue played Garry
Kasparov, the world chess champion. Deep Blue won the first
game but lost the match. That experience taught us what we
needed to do to be ready for the rematch in 1997.
A human uses a combination of knowledge, strategy, and intu-
ition to make chess decisions. A machine relies on brute com-
putational power and on an ability to examine a tremendous
amount of data. On average, the human mind can manage
three or four positions per second. Deep Blue can evaluate 200
million alternatives per second. So the machine has a huge
advantage. But Deep Blue also had weaknesses, and they cen-
tered on its inability to be flexible. Our challenge was to equip
Deep Blue to make decisions like a human grandmaster.
We built in several programming tools that allowed us to adjust

some of the decision parameters dynamically and to change
strategies in between games. Joel Benjamin, the U.S. chess
champion, played chess with Deep Blue for nine months - test-
ing and tunneling the system - and we programmed some of his
knowledge into the computer.
An interesting thing happened when Deep Blue met Kasparov
for the rematch. While we had refined Deep Blue so that it
could make decisions and play more like a human, Kasparov
had refined his strategy so that he could play better against
standard computer-chess programs. In game six, Deep Blue
surprised Kasparov by sacrificing a knight to gain strategic
advantage. Kasparov, who hadn’t planned for such a decision,
realized how inflexible his own strategy had become. We
showed that a machine can reach a level of play comparable
with that of a grandmaster .
Chung-Jen Tan manages IBM’s Deep Blue computer-chess
project. Since 1984, Tan has worked on the architecture devel-
opment and machine design of highly parallel, scalable sys-
tems for solving large, complex problems.
Deborah Triant
CEO and President
Check Point Software Technologies Inc.
Redwood City, California
Making and implementing decisions boils down to a key ingre-
dient: listening.
I often wonder why schools emphasize debating. Why not have
listening classes as well? Debating is easy; listening with an
open mind is not. The worst thing that you as a leader can do
in the decision-making process is to voice your opinion before
anyone else can. No matter how open and honest your people
are, stating your opinion first will short-change the discussion

process and taint what you hear later. I’ve learned this the hard
way.
FC :L E A R N I N G
2© All rights reserved. Fast Company, LLC
There are two classes of decisions. The first is the easy kind.
For
instance, how do you choose which features to include in the
next release of your product? It’s a pretty straightforward
process: Survey your customers, identify the information you
need, and formulate a decision by using rational, objective
measurements. The second class is the tough kind. Fo r
instance: Should you hire this person? Should you go after this
key market? Should you switch jobs? Should you have a kid?
These are bet-your-life decisions for which there’s no obvious
right or wrong answer - and no way of gathering objective
infor-
mation.
To tackle decisions of either class, I first kick into a talkative
mode. I ask everybody I know to give me an opinion. I get dif-
ferent perspectives - and I listen to them. I also listen to that
thing called intuition. Some people warn against that
approach. But there’s a kind of processing that happens in a far
deeper place than logical processing does. Intuition offers a
way to integrate and synthesize, to weigh and balance informa-
tion. If I have to make a big decision, I listen to what others
think. But ultimately, I listen to my intuition. I postpone a deci-
sion until I wake up one morning and know where my gut is
going.
Deborah Triant was president and CEO of Sitka Corp., a sub-

sidiary of Sun Microsystems, before she joined Adobe Systems
as president of marketing in 1993. In 1995, she left Adobe to
head Check Point, a network-security and traffic-management
software company.
Roger Rainbow
VP, Global Business Environment
Shell International Ltd.
London, England
Nothing can paralyze a decision-making process more than
uncertainty can. The big decisions that have failed at Shell did-
n’t fail because of our operations or because of project man-
agement; they failed because we misunderstood the external
world. That’s why, when we’re on the verge of a big decision,
we do scenario planning. A scenario is valuable because it’s a
plausible, coherent story that we can use to articulate why we
want to do something and which issues to factor into the deci-
sion-making process.
Everyone has two things in mind when approaching a big deci-
sion. The first thing is a scenario - a view of how the world will
turn out. The second thing is an objective or a strategy. A good
decision-making process marries those two things.
Decisions fall into three categories. With the first category, you
know a lot. Take a plant that’s been operating for 20 years. You
know what makes it succeed or fail, and the decisions you take
regarding it tend to be fairly straightforward. They may be hard
to implement, but they’re simple to make.
With the second category, you know something but not every-
thing. This is where scenario planning helps. For instance, if
we’re trying to decide whether to invest in an oil field in
Russia,

we talk about which factors are uncertain and why. What has
to happen in order for this investment to succeed? What could
go wrong? What would the consequences be? Are any of those
consequences absolutely catastrophic? If so, how can we guard
against them?
With the third category, you know virtually nothing, and you’re
starting from scratch. This is where intuition comes into play -
and where you make truly creative decisions: You’re deciding
on things that haven’t been done before.
Each category of decisions requires different skills and process-
es. Understand which kind of decision you’re facing, and use
scenarios to narrow the range of uncertainty.
Roger Rainbow ( [email protected] ) joined Shell
in 1970. His team provides analyses of the business environ-
ment by preparing long-term scenarios that consider econom-
ic, social, technological, and environmental issues, as well as
the long-term supply and demand of energy sources.
Chris Newell
Executive Director, the Lotus Institute
Lotus Development Corp.
Cambridge, Massachusetts
The crux of making good decisions isn’t doing things right - it’s
making sure that you focus on the right things. As citizens of
the Information Age, we’re overwhelmed with data, reports,
facts - much of it noise that we need to filter out before we can
figure out what’s relevant to a decision. So I’ve learned to hone
my discrimination skills. But if you’re exploring something that
has no precedent - an idea, a product, a service - you can’t rely
solely on data to guide you. You have to rely on people too.
I’ve
developed a personal advisory council that I consult before

tackling a big decision, a group of people who are anchored by
similar values - though not necessarily by similar perspectives.
Sometimes making the “wrong” decision is the right thing to
do. Last year, I decided to overrun my budget - to continue
investing in LearningSpace, a product that Lotus was unsure
about investing in. I knew it was the right thing to do, even
though I couldn’t get the company to agree. When news of my
decision surfaced on the radar of some key people, I got ham-
mered. At times, I even doubted my own decision. A year later,
LearningSpace has become one of Lotus’s most important
FC :L E A R N I N G
strategic products.
I made one mistake: I didn’t communicate all of the implica-
tions of going over budget. Otherwise, I wouldn’t change a
thing about what I did.
Chris Newell founded the Lotus Institute in 1994. Its mission
is to explore ways in which groupware technology intersects
with cultural issues. It has developed two applications:
TeamRoom, which supports virtual teaming; and
L e a r ningSpace, which supports collaborative, di s t r i b u t i
v e
learning.
Buz Mertes
VP, Loss Management and Policy Servicing
GE Capital Mortgage Insurance Corp.
Raleigh, North Carolina

By transforming the art of decision making into a science, you
can save time, money, and frustration. My team handles tough
decisions every day. It has to decide whether we can “cure” a
loan for someone who has stopped making payments on it or
whether we have to recommend foreclosure because of real
financial trouble.
For a long time, we couldn’t figure out what allowed some of
our reps to make better decisions than others did. We pulled six
of our best reps off their jobs and analyzed their decision-mak-
ing processes for 10 months. We found that these reps had rad-
ically different styles. Our challenge was to figure out the criti-
cal processes that drove their decisions and then to make sure
that those decisions were driven by factual, up-to-date informa-
tion. We had a goal: to become more consistent in our decision
making and to improve our customers’ perception of us. We
ended up creating a software program, called Loss Mitigation
Optimizer, to aid us in that process.
Turning decision making into a science saved us time and
money. Before we implemented this technology, we were cur-
ing fewer than 30% of our cases. Now we cure more than 50%
of them. The decision-making process itself takes 30% to 50%
less time per deal. Our savings jumped dramatically - by about
$8,000 per case. In the project’s first 18 months, these addi-
tional savings came to $15 million in net income. Some peo-
ple think that decisions of this type can’t be driven by data. Our
results show otherwise.
Buz Mertes joined GE in 1984. Since 1996, Mertes has spon-
sored a series of projects that have increased the company’s net
income by more than $20 million.
Jerry Seeman
Senior Director of Officiating

National Football League
New York, New York
As a referee, I found that the pressure was the same whether I
was officiating a preseason game or a Super Bowl. Being on the
field is like being in a fishbowl: Everyone - players, coaches,
fans, the media - is waiting for your decision. A successful call
depends on three things: You must be in position, you must
have a deep knowledge of the game, and you must have intense
concentration. Remember, no matter what the reaction to your
decision may be, you answer to only one thing: your con-
science. Above all, when making a decision, you have to keep
your cool.
One of the biggest errors that I see officials fall into is making
calls too quickly. Each decision has two phases: You read and
analyze the play, and then you make the call. But when things
happen in a split second, it can be tempting to throw a penalty
flag before you know what happened. That’s why I tell all of my
officials to work in “cruise control.” The fans may go crazy, the
players and coaches may get excited, but there should be seven
people on the field who work every game the same way from
beginning to end - and who exude a quiet confidence.
Once you make a decision, you’d better be able to communi-
cate it. I remember having to make a call on a bizarre play in
a playoff game between Houston and Cleveland. After an
attempted onside kick, the kicking team illegally touched the
ball, which then went out of bounds. The rules dictate that the
kicking team should kick again. That team again tried an
onside kick, and again it illegally touched the ball - but this
time, it recovered the ball. I called that the receiving team
would gain control of the ball on the spot where it was illegal-
ly touched. This was a complicated play: The NFL probably
hasn’t seen another of its kind in the past 15 years. At first, the

fans didn’t understand my decision. But I explained to them
what the proper ruling was, and they accepted it. I was confi-
dent about my knowledge of the game. And I didn’t lose my
cool.
Jerry Seeman, one of the most celebrated referees in football
history, became an NFL line judge in 1975. He was appointed
referee in 1979. His responsibilities now cover the league’s
supervisory staff, as well as regional game observers, collegiate
scouts, and all game officials.
Max Bazerman
J. Jay Gerber Distinguished Professor of Dispute Resolution
and Organizations
Kellogg Graduate School of Management
Evanston, Illinois
When making a decision, don’t listen to your intuition.
Intuition will lead you astray; it’s drastically overrated. The
desire to follow intuition reflects the mythology of people who
FC :L E A R N I N G
don’t want to think rationally and systematically. They tell sto-
ries about how their intuition guided them through a decision,
but they don’t understand how or why. Often, when you hear
about intuition, what you’re really hearing is a justification of
luck. Intuition might be fine for the small decisions in life - like
what kind of ice cream to buy. But when you get to the biggies,
you need a more systematic thought process.
One of the biggest challenges I face is teaching people how to

change their decision-making behavior. Everyone makes mis-
takes and bad decisions. I try to show people that their mistakes
are predictable.
Here’s an interesting thought experiment: You’ve got to decide
between two things - two executives to hire for a key position,
two acquisition targets, two houses that you’re thinking about
buying.
You go through a systematic process of identifying all of the
fac-
tors and weighing them for each alternative. You do a little
arithmetic, and your analysis says to pick A over B. But your
intuition says to pick B over A. So what do you do?
Most people will go on their intuition - which raises the ques-
tion, Why did you do all that work in the first place? One of
these two options is wrong. So postpone your decision until you
can determine why your intuition is out of sync with the sys-
tematic analysis. That’s the purpose of systematic analysis: to
inform your intuition, to make you consider all of the options,
and to help you make a wise decision.
Max Bazerman ( [email protected] ) studies decision mak-
ing, negotiation, and environmental issues. He is the author of
Judgment in Managerial Decision Making ( John Wiley &
Sons, 1986 ) and Why Smart People Make Dumb Money
Moves ( forthcoming from Wiley, April 1999 ). Bazerman is a
visiting professor of business admi nistration at Harvard
Business School.
Howard Raiffa
Professor Emeritus
Harvard Business School
Boston, Massachusetts

One of the biggest pitfalls in decision making is not creating
enough alternatives. You can make a decision in order to solve
a problem - or you can make a decision in order to exploit an
opportunity. To make this point, I use the case study of a busi-
nessman named Bill. His dilemma: to sell or not to sell his
business. Bill and his partner had struggled for years to build a
soundproofing business in Brooklyn, and finally the company
was doing well. But Bill was bored; at age 57, he wanted a
change. The solution, he thought, was to sell out to his partner,
move to California, and start a new business. He framed his
problem around how much he should sell his part of the busi-
ness for - $400,000 ( a price that his partner could afford ) or
something higher.
At my suggestion, Bill went through a rigorous process of
reframing his decision. He realized that what he wanted was to
spend more time outdoors, to be challenged intellectually, and
to minimize stress. In the end, Bill decided to move to
California and to establish a branch of the soundproofing
business there. That way, he could change his life and also be
challenged - but without taking on an enormous amount of
risk. The business did well: Eight years later, he sold out to his
partner for $1.7 million.
Howard Raiffa is a pioneer in the development of decision
analysis, negotiation analysis, and game theory. He is coauthor,
with John S. Hammond and Ralph L. Keeney, of Smart
Choices: A Practical Guide to Making Better Decisions (
Harvard Business School Press, 1998 ).
FC :L E A R N I N G

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