The MENTAT HANDBOOK
The Mentat Handbook
Author: Grodon Orpar Playt III
Editor: James W. Meritt
Forward
When Gilbertus Albans originally founded the Order of Mentats and authored the Mentat
Handbook it only consisted of three ranks of Adepts. The new training program has been
extended three months and included three additional ranks. This expansion has dictated the
necessity of this new handbook, a thorough revision of Alban's Mentat Handbook to
accommodate these changes.
Author
Gordon Orpar Playt III is an author, statistician and military theoretician who retired as
Planetary Governor of Stormstile to accept a CHOAM directorship. Upon leaving the
Governorship he joined the Order of Mentats to become a driving force in the expansion of the
Order.
Editor
James W. Meritt assembled the guidance provided in numerous phamplets into a single
document.
Mentat Adept
A Mentat adept could be characterized as:
* A human in the generic, Bene Gesserit sense i.e. "an animal with reason and logic"
* An expert in all methods of logic and inference
* A conceptual generalist, in contrast to specialists in narrow areas
* One possessing a quasi-truth-sense based not on presence but on inference.
Mentats are "that class of Imperial Citizens trained for supreme accomplishments of logic."
They are trained to store vast amounts of data and to calculate probabilities on the basis of past
performance. Mentats operate by a kind of intuitive process, transforming a freak ability into a
teachable skill by applying psychological discoveries originally in physics and the other hard
sciences. A Mentat has been trained and conditioned to perform certain duties. The fact that it's
encased in a human body, however, must not be overlooked. Mentats do not provide guarantees.
The feats of logic and deduction available to a Mentat boggle the mind. Essentially, Mentats
were developed by Gilbert Albans with the primary purpose of replacing computers.
Data is the key to all Mentat abilities.
Mentat abilities can be broken down in general terms to three areas:
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1) General Data Sorting (Mentat system)
2) Economic Data Deduction (Mentat system)
3) Security Approximations (Mentat system, combat systems, economic systems)
A vast body of research in psychology and organizational studies has shown that people do not
optimize or act as if they optimize, that they don't have the mental capabilities to optimize their
decisions, that even if they had the computational power necessary, they lack the information
needed to optimize. Instead, people making a variety of personal and organizational goals, use
standard operating procedures to routinize decision-making, and ignore much of the available
information to reduce the complexity of the problems they face. It is not a question of
approximation; they do not even remotely describe the processes that human beings use for
making decisions in complex situations. A Mentat can - and must!
The Mentat adept is capable of achieving remarkable inferential linkages and gestalten spasms of
pure insight, but usually only when deep in a Mentat-trance. In spite of this and above all a
Mentat must be a generalist, not a specialist. It is wise to have decision of great moment
monitored by generalists. Experts and specialists lead you quickly into chaos. They are a source
of useless nitpicking, the ferocious quibble over a comma. The Mentat generalist, on the other
hand, should bring to decision-making a healthy common sense. He must not cut himself off
from the broad sweep of what is happening in his universe. He must remain capable of saying:
"There's no real mystery about this at the moment. This is what we want now. It may prove
wrong later, but we'll correct that when we come to it." The Mentat generalist must understand
that anything that can identify as our universe is merely part of larger phenomena. But the expert
looks backward; he looked into the narrow standards of his own specialty. The generalist looks
outward; he looks for living principles, knowing full well that such principles change. It is to the
characteristics of change itself that the Mentat-generalist must look. There can be no permanent
catalogue of such change, no handbook or manual. You must look at it with as few
preconceptions as possible, asking yourself: "Now what is this thing doing?
Religion
The Mentat School is not an anti-religious organization. There are many verses within the
Orange Catholic Bible that espouse our goal. Among these:
The LORD will afflict you with madness, blindness and confusion of mind.
You have closed their minds to understanding; therefore you will not let them triumph.
A man is praised according to his wisdom, but men with warped minds are despised.
So I turned my mind to understand, to investigate and to search out wisdom and the scheme of
things and to understand the stupidity of wickedness and the madness of folly.
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They know nothing, they understand nothing; their eyes are plastered over so they cannot see,
and their minds closed so they cannot understand.
So I will always remind you of these things, even though you know them and are firmly
established in the truth you now have.
He deprives the leaders of the earth of their reason; he sends them wandering through a
trackless waste.
"Therefore I say: Listen to me; I too will tell you what I know. I waited while you spoke, I
listened to your reasoning; while you were searching for words, and I gave you my full attention.
But not one of you has proved Job wrong; none of you has answered his arguments.
Not only was the Teacher wise, but also he imparted knowledge to the people. He pondered and
searched out and set in order many proverbs.
We know best what they listen to when they listen to you, and when they take counsel secretly,
when the unjust say: You follow only a man deprived of reason.
Mentat Costs
Mentats do not come cheaply, but there are those who find them rather useful. Mentats are NOT
a faction unto themselves but are bound by contracts and word bonds to their employers and
must act accordingly. The courts also enforce contracts for Mentats. These contracts represent a
lifetime right to their services so long as a certain amount is paid periodically to the school.
The initial contract will be purchased from the school, as will the periodic payments. The
contract owner may then sell the balance of the contract, and the purchaser will take over
periodic payments to the school. The payments will cease when the Mentat dies. Failure to
continue payments will result in default, and the school can reclaim the Mentat.
Any aspect of the contract is enforceable in the courts. It should be noted that the Mentat School
would have to reinvest most of their costs in retraining and security/maintenance. They will
NOT be permitted to accumulate wealth and become political players.
The minimum rank required before a Mentat can be sold is a Hypothesist. Commercially,
Hypothesists can be used to speculate on future market conditions, commodity prices, outcomes
of various economic tactics and likely changes in consumption of planets and populations.
Mentat Hierarchy
There comes a time when the training can no longer be done to a potential candidate, but must
now be done with him (or her). The candidate most likely would have been brought up within
the School, but potential Mentats may be identified "in the wild" and brought into the Order.
Prospective Mentats are required to have both the inner predisposition necessary to make the
training effective, and what Albans refers to as "a call to reason" to make the discipline tolerable.
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Given these qualities, following a solemn decision and much preliminary training, the initiate
will be welcomed into the program.
Assuming the success of the early conditioning and education, age fifteen was the year of
decision, of sponsorship as a Mentat candidate. The applicant's predisposition-his commitmenthad been amply demonstrated by fifteen, leaving only his "calling" to be heard to gain
acceptance. The applicant secluded himself and meditated, awaiting the call. For some it never
came. For others, the vocation grew from patient deliberation. For a few, a flash from the core of
being cried, "Yes" to the opportunities and dangers of life as a Mentat. Those who never received
the call were not disgraced; many still loved the Order and served it in a variety of ways - as
teachers of the young, as administrators, or in the auxiliary, the Friends of the Order of Mentats.
But if the call did come, the Order rejoiced; other applicants and their mentors pledged to help
and support the Called One throughout his life what- ever his final progress on his path through
the ranks of the Order.
"Twisted Mentats" are NOT a product of our school and have no place within the hierarchy.
Indeed, they have no place on our planet!
What follows in this Handbook is an enumeration of the Minor and Major Orders along with a
brief presentation on SOME of the material necessary to master each level. The descriptions are
in no way intended to be exhaustive since no single literary work could encompass the extensive
training with must be undertaken. It is intended solely as a familiarization for those who have
not undergone the extensive training and a reminder for those who have.
Minor Orders
Memorizer
The fully prepared Memorizer was capable of retaining both related and unrelated information.
Memorizers are able to repeat entire books from recall. They are able to replicate spatial
configurations after seeing the place (or plans for it) only once. Their chief accomplishment is
the ability to repeat conversations word for word from start to finish, mimicking the cadence and
vocal inflection of each participant.
Duty to serve as an Information Source
The Mentat primarily draws upon three areas of information:
* Economic
* Political
* Military
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Some of these areas (economic and military) are quantitative and reflect figures determined by
larger systems and choices. The political information, however, is largely determined by the
House Heads and their designees.
Mentat must use their abilities at data synthesis and analysis. The differing levels of ability are
reflected in how they exploit the system as well as the time it takes to gather data and the cost of
that effort.
The Mentat draws information from several sources, but primarily from Open Sources and
Espionage. These are subject to the advantages and disadvantages inherent to them.
Knowledge Ethics
* Ultimate responsibility for verity, truth, honesty, and timeliness of data used by and
conclusions of Mentats will rely with the House/Faction Leader.
* Mentats or their clients with access to Mentats shall NOT disseminate information learned
from the Mentat through any means nor shall they disseminate this information to members
outside their faction without serious justification. Violations of this will result in removal of the
Mentat serving in their employ.
* House Heads and their designees shall keep information up to date.
* House Heads and their designees shall maintain data relating to 'secret' information as clear and
precise as is possible. The difficulty for an enemy house to tap into the 'secret' information is
quite high and quite expensive. Regardless, for the system to function fairly, entries should not
be shallow, false, or misleading.
Non-Interaction is a PRIME concern!
A Mentat must observe and acquire information, not be part of the information (though that will
be inevitable). Even the Raw Mentat Heisenberg noted in Ancient times the law of physics
claimed that the mere act of observation-changed parameters. The Mentat MUST keep his
interactions (and hence contributions) with the information at an absolute minimum. A Mentat
must learn how to glide like a shadow, how to see without being seen. But any good Mentat
must know how to observe broader issues while remaining invisible, unknown to the subjects of
his scrutiny. Moving silently is the best way to acquire information.
Perception
Something cannot be recalled correctly unless it is first perceived correctly. An item cannot be
remembered if it is not noticed in the first place. The Mentat MUST be perpetually aware of all
things at all times.
Memory Skills Associated with Original Awareness
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 Increase your original awareness of events and things by increasing your abilities to
observe and establishing a reason for paying attention.
 Concentrate and focus on one thing at a time.
 Form images of what you want to remember by "seeing" things in vivid color and
concentrating on details.
 Establish goals of memorization so that you know from the outset what you are trying to
do and when you have achieved it.
 Use all of your senses when trying to memorize information.
 Keep an optimistic attitude by letting yourself know from the beginning of a task that it
is within the limits of your abilities.
 Find patterns in the information you are trying to remember through which you can
organize and associate necessary facts.
 Review the information you are trying to remember and periodically check your
progress.
 Break down large memory tasks into smaller tasks and group the small tasks to help add
depth to your subject.
Reading
A Mentat will be able to use his skills to imprint each page on his memory so that he can absorb
and comprehend it all in greater detail later.
Reading may be defined as an individual's total inter-relationship with symbolic information.
Reading is a communication process requiring a series of skills. As such reading is a thinking
process rather than an exercise in eye movements. Effective reading requires a logical sequence
of thinking or thought patterns, and these thought patterns require practice to set them into the
mind. They may be broken down into the following seven basic processes:
1. Recognition: the reader's knowledge of the alphabetic symbols.
2. Assimilation: the physical process of perception and scanning.
3. Intra-integration: basic understanding derived from the reading material itself, with minimum
dependence on past experience, other than a knowledge of grammar and vocabulary.
4. Extra-integration: analysis, criticism, appreciation, selection and rejection. These are all
activities, which require the reader to bring his past experience to bear on the task.
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5. Retention: this is the capacity to store the information in memory.
6. Recall: the ability to recover the information from memory storage.
7. Communication: this represents the application of the information and may be further broken
down into at least 4 categories, which are:
1. Written communication
2. Spoken communication
3. Communication through drawing and the manipulation of objects
4. Thinking, which is another word for communication with the self
By using appropriate techniques, the limitations of early education can be overcome and reading
ability improved by at least fivefold. A Mentat must not only learn how to overthrow this earlier
teaching, but also learn to reflexively use a new manner, developed for use and not just to learn.
Increasing Reading Rate
A well-planned reading program prepares for maximum increase in rate by establishing the
necessary conditions. Four basic conditions include:
1. Have your eyes checked. Before embarking on a reading program, make sure that any
correctable eye defects you may have are taken care of by checking with your eye doctor.
2. Eliminate the habit of pronouncing words as you read. If you sound out words in your throat
or whisper them, you can read slightly only as fast as you can read aloud. You should be able to
read most materials at least two or three times faster silently than orally. If you are aware of
sounding or "hearing" words as you read, try to concentrate on key words and meaningful ideas
as you force yourself to read faster.
3. Avoid regressing (rereading). The average human reading at 250 words per minute regresses
or rereads about 20 times per page. Rereading words and phrases is a habit that will slow your
reading speed down to a snail's pace. Because he reads slowly, his mind has time to wander and
his rereading reflects both his inability to concentrate and his lack of confidence in his
comprehension skills.
4. Develop a wider eye-span. This will help you read more than one word at a glance. Since
written material is less meaningful if read word by word, this will help you learn to read by
phrases or thought units.
Reading Rate Adjustment
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Poor results are inevitable if the reader attempts to use the same rate indiscriminately for all
types of material and for all reading purposes. He must learn to adjust his rate to his purpose in
reading and to the difficulty of the material he is reading. This ranges from a maximum rate on
easy, familiar, interesting material or in reading to gather information on a particular point, to
minimal rate on material which is unfamiliar in content and language structure or which must be
thoroughly digested.
Rate adjustment may be overall adjustment to the article as a whole, or internal adjustment
within the article. Overall adjustment establishes the basic rate at which the total article is read;
internal adjustment involves the necessary variations in rate for each varied part of the material.
There is no set rate, therefore, which the good reader follows inflexibly in reading a particular
selection, even though he has set himself an overall rate for the total job.
Overall rate adjustment should be based on your reading plan, your reading purpose, and the
nature and difficulty of the material. The reading plan itself should specify the general rate to be
used. This is based on the total "size up". It may be helpful to consider examples of how purpose
can act to help determine the rate to be used. To understand information, skim or scan at a rapid
rate. To determine value of material or to read for enjoyment, read rapidly or slowly according to
you feeling. To read analytically, read at a moderate pace to permit interrelating ideas. The
nature and difficulty of the material requires an adjustment in rate in conformity with your ability
to handle that type of material. Obviously, level of difficulty is highly relative to the particular
reader.
Internal rate adjustment involves selecting differing rates for parts of a given article. In general,
decrease speed when you find the following:
(1) Unfamiliar terminology not clear in context. Try to understand it in context at that point;
otherwise, read on and return to it later
(2) Difficult sentence and paragraph structure; slow down enough to enable you to untangle them
and get accurate context for the passage
(3) Unfamiliar or abstract concepts. Look for applications or examples of you own as well as
studying those of the writer. Take enough time to get them clearly in mind
(4) Detailed, technical material. This includes complicated directions, statements of difficult
principles, materials on which you have scant background
(5) Material on which you want detailed retention. In general, increase speed when you meet the
following:
(a) Simple material with few ideas which are new to you; move rapidly over the familiar ones;
spend most of your time on the unfamiliar ideas;
(b) Unnecessary examples and illustrations. Since these are included to clarify ideas, move over
them rapidly when they are not needed
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(c) Detailed explanation and idea elaboration which you do not need
(d) Broad, generalized ideas and ideas which are restatements of previous ones. These can be
readily grasped, even with scan techniques.
Improve Reading Skills
1. You don't have to be a great reader to get the point.
Some people read fast and remember everything. Others read slowly and take a couple of
times to get all the information. It doesn't matter, really, so long as when you read, you get
the information you're seeking.
2. Know WHY you're reading.
Are you reading for entertainment or to learn something? Decide why you're reading before
you start and you'll greatly improve your comprehension and your enjoyment.
3. You don't need to read everything.
Not every magazine, letter, and email you receive contains information you need. Don't
even look at it! Just doing this will double the amount of time you have available to read.
4. You don't need to read all of what you DO read.
Do you read every article of every magazine, every chapter of every book? If so, you're
probably spending a lot of time reading stuff you don't need.
Be choosy: select the chapters and articles that are important. Ignore the rest.
5. Scan before you read.
Look at the table of contents, index, topic headers, photo captions, etc. These will help you
determine if, a) you have a real interest in this reading, and b) what information you're likely
to get from it.
6. Prioritize your reading.
You can't read everything all at once. If it's important, read it now. If it's not, let it wait.
7. Optimize your reading environment.
You'll read faster and comprehend more if you read in an environment that's comfortable for
you.
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The MENTAT HANDBOOK
8. Once you start, don't stop!
Read each item straight through. If you finish and have questions, go back and re-read the
pertinent sections. If you don't have questions, you got what you needed and are ready to
move on.
9. Focus.
Remember, you're reading with a purpose, so focus on that purpose and the material. If you
lose interest or keep losing your place, take a break or read something else. You can keep
track of where you are by following along with your hand. This simple technique helps you
focus and increase your concentration.
10. Practice!
The more you read, the better reader you'll become.
A trade journal/magazine
Browse
Browse through the publication so that you get to know what's in it and where it's located. Notice
the layout and how the information is presented. Notice the table of contents and any special
sections.
Notice which articles pique your interest, but don't read them yet. Catch titles, subtitles, pictures,
and charts. When you find something interesting, think of how you can use it--reading for
information should be a goal seeking activity. Decide how much time you can afford, and then
go for it.
Locate the Most Important Articles
Get 80% of the information in 20% of the time by simply reading the title, subtitle, bold type,
last paragraph and first paragraph--spend only 30-45 seconds. Then reflect on the relevance of
the information for you. If it is important to read more, go to the next step. Otherwise, find
another article.
Take 1-2 minutes to skim through the article to find the core idea. Know what is being
expressed. Do you need more details? If not, find another article.
Read lightly and flexibly. Know what you need. Slow down to fulfill your purpose, answering
questions that are most important to you. Since very few words carry the meaning, speed up to
pass redundant or useless information.
File important articles, pass them on, or re-cycle the publication.
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Reports
In just 11-13 minutes you can get 80% of what you must know from even the most difficult
reports.
At the end of your workday, take 2 minutes to glance through the report's layout, table of
contents and ending. Decide on 3 things you must know from this report.
STOP! Do not read further. Flip the pages in front of your eyes like a fan 2 or 3 times. Make a
guess where you will find your answers. Leave it alone until tomorrow.
In the morning take no more than 7 minutes to search for and read the key points you felt you
had to know.
Double check to determine if there are any additional "life or death" needs associated with this
report. If yes, spend no more than 4 more minutes now and maybe 5-7 minutes the next day.
The Daily News
Disregard redundant information to save time now.
News is redundant: previewed yesterday...detailed today...summed up tomorrow.
When reading news, whether from a report, newspaper, magazine or newsletter, skip what you
already know. Make sure to you get the new information you need.
Look for the most pertinent information to match your purpose for reading. A strong purpose
immediately increases your reading speed and comprehension. Be clear about what you want,
then quickly search to find it. Don't just read for the sake of reading unless you have chosen to
pass leisure time.
Give yourself just 10-15 minute in the morning to review the news. This time constraint gently
forces you to get focused. Come back in the evening to get whatever you "have to" or "want to."
You may discover it to be ancient history by evening.
Read headlines and first paragraphs only.
Review headlines and select articles you want to read based on your interest or purpose for
reading. Read the first paragraph to preview the article.
80% of the key information is in the opening paragraph. The subsequent supporting text should
be read only as needed. Follow this strategy:
1. Ask yourself what other specific details you want. Let it go if there are none.
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2. Skim the article for the desired details. "Dip" into the article and read those paragraphs. Don't
read all the words unless you have the luxury of unlimited time.
3. When finished with an article, go on to the next. This whole process should not take more than
10-15 minutes.
Improving Reading Efficiency
Before reading a difficult piece of writing, take a few moments to close your eyes and relax
while taking two or three deep breaths. Say to yourself that you can read with full concentration,
recognize key information, and achieve high comprehension quickly to accomplish your needs.
Step 1: Prepare
Reading effectively begins with a clear sense of purpose. This means consciously stating a
desired outcome for reading. For example, we might want a brief overview of main points.
We might want to gain certain details such as the solutions to specific problems. Perhaps we
want to complete a task and seek only the ideas that will help us do so. Empowered with a
clear purpose, we then enter a state of relaxed alertness-the accelerative learning state. While
in this state, neither boredom nor anxieties exist. We are exerting effort, but we are not
worried about results.
Step 2: Preview
Previewing is based on an important principle: effective learning often takes place "from
whole to parts." That is, we start with the big picture and proceed to the smaller, more
detailed parts. First we survey the written material. Our aim is not to grasp the content in
detail, but to get a sense of its structure. Then we gather a list of key terms, or trigger words,
which embody the core concepts or events. Trigger words alert our minds to the details we
might want to explore more thoroughly later. When done effectively, previewing is short and
sweet-about five minutes for a book, three minutes for a report, and as little as 30 seconds for
an article. During that time, we clarify and refine our purpose, review the trigger words, and
decide whether to continue reading or call it quits. If we choose not to read something that
does not meet our needs or interests, it is all right. Previewing is like x-raying a book getting a broad sense of its underlying structure. Understanding structure gives us something
that learning theorists call a schema, a set of expectations about what is coming up next.
When we know the structure of written text, we become more accurate at predicting its
content. In summary, previewing gives us the skeleton of a book or article first.
Step 3: Mentat Reading System
The Mentat Reading technique begins with placing ourselves more fully into the relaxed,
alert state of mind and body called the accelerative learning state. In this state, distractions,
worries, and tensions seem to fall away. Then we adjust our vision for the Mentat Reading
focus state. Here the aim is to use our eyes in a new way: instead of bringing individual
words into sharp focus, we soften our eyes so that our peripheral vision expands and the
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whole printed page comes into view. Mentat Reading focus creates a physical and mental
window-allowing direct exposure of the incoming visual stimuli to the brain. In this state, we
mentally photograph the entire page, exposing it to the preconscious processor of the mind.
The exposure of each page stimulates a direct neurological response. The brain performs its
function of pattern recognition, unencumbered by the critical/logical thought process of the
conscious mind. At a rate of one page a second, we can Mentat Read a whole book in three to
five minutes. This is not traditional reading. After Mentat Reading, we may have little if any
of the material in conscious awareness, which means we may consciously know nothing. The
next steps create the conscious awareness we need.
Step 4: Activate
During activation we restimulate the brain-probing the mind with questions and exploring
parts of the text to which we feel most attracted. We then super read the most important parts
of the text by scanning quickly down the center of each page or column of type. When we
feel it is appropriate, we dip into the text for more focused reading to comprehend the details.
In dipping, we allow our intuition to say, "Hey, turn to the last paragraph on page 147! Yes,
that is the one. The ideas you want are right there." Other activation techniques developed
while reading this book include rhythmic perusal, skittering, and mind mapping. These also
help us gain access to the deeper impressions established by Mentat Reading. When we
activate, we involve our whole brain, connect the text with our conscious awareness, and
achieve our goals for reading.
Step 5: Rapid Reading
This final step of the Mentat Reading whole mind system is closest to conventional reading
and speed-reading. While rapid reading, we move our eyes quickly through the text, starting
at the beginning and going straight through to the end. We take as much time as we need,
feeling free to adjust our reading speed depending upon the complexity, prior knowledge,
and importance of the material.
Rapid reading is significant, because it dispels the prime fear of many beginning Mentat Readers
that they will forget what they have read, or that they never absorbed any of the text in the first
place. Rapid reading directly involves the conscious mind and satisfies our need for clear
comprehension of the content.
Remember, this step takes place after the other steps of the system. Those steps make us
increasingly familiar with the text. There will be times when we choose not to rapid read,
because we have already fulfilled our needs.
Eye Motions
A reader's eyes do not move over print in a smooth manner. If they did, they would not be able to
see anything, because the eye can only see things clearly when it can hold them still. If an object
is still, the eye must be still in order to see it, and if an object is moving, the eye must move with
the object in order to see it. When you read a line, the eyes move in a series of quick jumps and
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still intervals. The jumps themselves are so quick as to take almost no time, but the fixations can
take anywhere from a quarter to one and a half seconds. At the slowest speeds of fixation a
Mentat's reading speed would be less than one hundred w.p.m.
Thus the eye takes short gulps of information. In between it is not actually seeing anything; it is
moving from one point to another. We do not notice these jumps because the information is held
over in the brain and integrated from one fixation to the next so that we can perceive a smooth
flow. The eye is rarely still for more than half a second. Even when you feel the eye is
completely still (as when you look steadily at a fixed point such as the following comma), it will
in fact be making a number of small movements around the point. If the eye were not constantly
shifting in this way, and making new fixations, the image would rapidly fade and disappear. The
untrained eye takes about a quarter of a second at each point of fixation, so it is limited to about
four fixations per second. Each fixation of an average reader will take in two or three words, so
that to read a line on this page probably takes between three and six fixations. The duration of
the stops and the number of words taken in by each fixation will vary considerably, depending
on both the material being read and the individual's reading skill.
Although the sharpest perception occurs at the fovea, images that are off-center are still seen, but
less clearly. This peripheral vision performs a most valuable function during reading. Words that
lie ahead of the current point of fixation will be partially received by the eye and transmitted to
the brain. This is possible because words can be recognized when they are in peripheral vision
and the individual letters are too blurred to be recognized. On the basis of this slightly blurred
view of what is coming, the brain will tell the eye where to move to next. Thus the eye does not
move along in a regular series of jumps, but skips redundant words and concentrates on the most
significant words of the text.
Immediate memory span depends on the number of 'chunks' rather than the information content.
When we read, we can take in about five chunks at a time. A chunk may be a single letter, a
syllable, a word, or even a small phrase - the easier it is to understand; the larger will be the
chunks.
In the case of a skilled reader, the fixation points tend to be concentrated towards the middle of a
line of print. When the eye goes to a new line, it does not usually start at the beginning, instead it
starts a word or two from the edge. The brain has a good idea of what is to come from the sense
of the previous lines and only needs to check with peripheral vision that the first few words are
as anticipated. Similarly, the eye usually makes its last fixation a word or two short of the end of
a line, again making use of peripheral vision to check that the last few words are as expected.
There is a dwindling spiral of ability. The people re-reads more, then loses more trust in his
memory and finally concludes that he doesn't understand what he is reading. For over a hundred
years, experts in the field of medical and psychological research have concluded that most
humans only use from 4% to 10% of their mental abilities - of their potential to learn, to think
and to act. Speeding up a process such as reading is a very effective method of enabling a Mentat
to access a larger proportion of the 90-95% of the mental capacity that he is not using. When a
person is reading rapidly, he is concentrating more, and when he can raise his speed of reading
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The MENTAT HANDBOOK
above about 500 w.p.m. with maximum comprehension, he is also speeding up his thinking. New
depths of the brain become readily accessible.
In addition, accelerated reading can reduce fatigue. Faster reading improves comprehension,
because the reader's level of concentration is higher, and there is less cause for him to develop
physical tensions such as a pain in the neck or a headache. A further benefit is the improvement
of the completeness of thought.
There is an optimum reading speed for maximum comprehension, which is proportional to your
top speed. This rate will vary from one type of material to another, and finding the best rate for
the material you are reading is critical for good comprehension.
Visual Guides
A visual guide is a pointer, such as the end of a pencil or a fingertip, moved along underneath a
line of print. The reason children are discouraged from pointing to the words as they read them,
is that stopping to point at each individual word can indeed slow down reading. But if instead,
the finger is moved along smoothly underneath the line of text, it can help to speed up reading
considerably, for three reasons:
1. If the eye is trained to follow the visual guide, then most unnecessary back- skipping is
eliminated.
2. Deliberately speeding up the visual guide will help the eye to move along faster.
3. As the eye moves faster it is encouraged to take in more words with each fixation. This
increases the meaningful content of the material - each chunk makes some sense - so that
comprehension actually approves.
Visual Reading
One of the characteristics of visual storage is speed, so increasing the pace at which material is
covered, with the assistance of speed-reading exercises, usually increases the powers of
visualization. Those Mentats who can adapt to the visual mode of representation successfully are
multi-sensory.
The following technique addresses those Mentats who fall in between the two extremes of the
good visualizer and the Mentat who has not yet developed his visual capacity fully.
1. The first step is to check that you have the ability to picture in your mind's eye. Look at your
desk and pretend that this desk is really your bedroom, and that you are on the ceiling, looking
down at the four walls and everything contained inside. Mentally point to the wall where the bed
is, the walls with windows, the door, the shelves, and so on. Do this exercise again with the
layout of the whole house. This exercise will validate that you can make mental pictures of
concrete objects, a right-brain skill.
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2. Read a phrase or sentence out loud. The sentence is the easiest grammatical unit to use for this
particular method. A sentence should be chosen that uses nouns that are concrete and action
verbs, rather than abstract nouns and the verb 'to be', as these will prevent the use of right-brain
picturing abilities.
As soon as you have stopped reading the sentence, close your eyes and picture in your mind what
the sentence described. Notice the color, size, shape, foreground, and distance of the picture in
your mind. This will give you a further idea of your basic capacity to visualize. Used as a
repetitive exercise, this will improve your visualization.
3. Once you can form a reasonably good mental picture from a sentence you have just read, the
next goal is to find how many pictures you can hold on to. Read out between 3 and 9 visualisable
sentences. If you go beyond your capacity, you will lose the first and second picture. This will
tell you your capacity for a sequence of separate pictures. Practice will improve this ability.
People who find it easy to create pictures and take in large amounts of information have the
facility to take information spread out over several pictures and sequence this information into a
movie. When you can do this well, you will have a seemingly infinite memory capacity, taking
advantage of the right brain's incredible powers.
Those who have done little visualization in the past, tend to make pictures that are sparse in
detail and poor in quality. They may leave out submodalities, the major components of our
senses.
When reading a novel, many people fail to make adequate use of auditory imagery, even when
they are good visualisers. If you use your auditory imagery to give all the 'he said...' and 'she
said...' dialogue, then your memory of the story will be vastly improved. When you read a book
and use all the forms of imagery, you will experience the story as a three-dimensional movie in
stereophonic sound, with imagery of emotion and movement, touch, taste and even temperature.
You will be totally at one with the book and your subsequent recall will be nearly perfect. You
will hardly be aware of reading the words, unless there is a gross printing error.
It may be difficult to construct concrete images when reading abstract material such as
philosophy. A Mentat who has both high right-brain and left-brain capacity will tend to form
abstract patterns, rather like modern art, to hang the words and pictures upon. Modern physics
has little that can be visualized as concrete imagery, however, when a psychologist asked the raw
Mentat Einstein about his thinking processes, Einstein replied, 'I think in a combination of
abstract visual patterns and muscular sensations; it is only later, when I wish to speak or write to
another person, that I translate these thoughts into words.'
Memory
Memory never recaptures reality. Memory reconstructs. All reconstructions change the original,
becoming external frames of reference that inevitably fall short. In spite of this there are many
things you can do to improve your memory, among them the use of certain mental techniques, as
well as special care with nutrition and medicines.
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Stimulate Memory
Use your memory to the utmost. Challenge a novelty. Learn new skills. This will stimulate your
brain's neural circuits to grow.
Pay attention.
Don't try to memorize all the facts that happen, but focus your attention and concentrate in what
you consider more important, avoiding all other thoughts. Exercise: take any object, as a pen,
and concentrate on it. Think on its various characteristics: its material, its function, its color, its
anatomy, etc. Don't allow any other thought to occupy your mind while you are concentrating on
that pen.
Relax
It is impossible to pay attention if you are tense or nervous. Exercise: hold your breath for ten
seconds, and then release it slowly.
Associate facts to images.
Learn mnemonic techniques. They are a very efficient way to memorize large quantities of
information.
Visualize images
See figures with the "eyes of your mind". Exercise: Close your eyes and imagine a big and juicy
steak. Smell its aroma and feel the softness of its meat. Imagine yourself cutting it with a knife
and fork, and then tasting it. If your mouth filled with saliva while you visualized this scene, then
you have done a good work! Do these exercises with other objects, like a bowl of soup, an icecream cup, a chocolate pie, anywhere, as a dental office, an examination room, etc.
Sleep
To be able to have a good memory, it is essential that we allow the brain to have enough sleep
and rest. While sleeping, the brain disconnects from the senses, and proceeds to revising and
storing memory. Insomnia would produce a chronic fatigue and would impair the ability of
concentration and the storing of information.
The Link Method
The Link Method is one of the easiest mnemonic techniques available, but is still quite powerful.
It is not quite as reliable as a peg technique, as images are not tied to specific, inviolable
sequences.
It functions quite simply by making associations between things in a list, often as a story. The
flow of the story and the strength of the visualizations of the images provide the cues for
retrieval.
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How to use the Link method
Taking the first image, imagine associations between items in a list. Although it is possible to
remember lists of words where each word is just associated with the next, it is often best to fit the
associations into a story: otherwise by forgetting just one association, the whole of the rest of the
list can be lost.
As an example, you may want to remember a list of counties in the ancient South of England:
Avon, Dorset, Somerset, Cornwall, Wiltshire, Devon, Gloucestershire, Hampshire, Surrey
This could be done with two approaches, the pure link method, and the story method:
The pure Link Method
This would rely on a series of images coding information:
An AVON (Avon) lady knocking on a heavy oak DOoR (Dorset).
The DOoR opens to show a beautiful SuMmER landscape with a SETting sun (Somerset).
The setting sun shines down onto a field of CORN (Cornwall).
The CORN is so dry it is beginning to WILT (Wiltshire).
The WILTing stalks slowly fall onto the tail of the sleeping DEVil (Devon).
On the DEVil's horn a woman has impailed a GLOSsy (Gloucestershire) HAM (Hampshire)
when she hit him over the head with it.
Now the Devil feels SoRRY (Surrey) he bothered her.
Note that there need not be any reason or underlying plot to the sequence of images: all that is
important are the images and the links between images.
The Story Method
Alternatively this information may be coded by vividly imaging the following scene:
An AVON lady is walking up a path towards a strange house. She is hot and sweating slightly in
the heat of high SUMMER (Somerset). Beside the path someone has planted giant CORN in a
WALL (Cornwall), but it's beginning to WILT (Wiltshire) in the heat. She knocks on the DOoR
(Dorset), which is opened by the DEVil (Devon). In the background she can see a kitchen in
which a servant is smearing honey on a HAM (Hampshire), making in GLOSsy
(Gloucestershire) and gleam in bright sunlight streaming in through a window. Panicked by
seeing the Devil, the Avon lady panics, screams 'SoRRY' (Surrey), and dashes back down the
path.
Given the fluid structure of this mnemonic, it is important that the images stored in your mind
are as vivid as possible, and that significant, coding images are much stronger that ones that
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merely support the flow of the story. See the section on using mnemonics more effectively for
further information on making images as strong as possible.
This technique is expanded by adding images to the story. After a number of images, however,
the system may start to break down.
Peg System
A peg system can be used to help remember and associate numbers with other items. It is a very
powerful technique, but it is not as easy to use as the link technique because it requires some
learning in order to use. In a peg system, images are associated with numbers and then the
images are in turn linked together using some form of the link technique described above.
Creating a memorable association between each number and an image is the part that needs to be
learned. Once this is done though, remembering numbers can become remarkably easy.
Loci Method
"Place" objects associated with what you want to remember in different locations in the memory
of a familiar place. To recall it, go on a mental tour, following the places in natural order and
link the first statement to the first place, the second item to the second place, and so on. Follow
the same pattern in every room, always moving in the same direction. Do not try to speed up the
process of image association. Add an emotional expression to the image association. Play with
the irrational. Follow these simple guidelines:
* Be patient
* Avoid rushing to write your loci
* Skip doors unless they are very special
* Chose a permanent loci
* Avoid overcrowding your set of loci
The Number/Rhyme System
The Number/Rhyme technique is a very simple way of remembering lists of items in a specific
order. It is an example of a peg system - i.e. a system whereby facts are 'pegged' to known
sequences of cues (here the numbers 1 - 10). This ensures that no facts are forgotten (because
gaps in information are immediately obvious), and that the starting images of the mnemonic
visualizations are well know.
At a simple level it can be used to remember things such as a list of English Kings or of
American Presidents in their precise order. At a more advanced level it can be used to code lists
of experiments to be recalled in a science exam.
Number/Rhyme Technique
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This technique works by helping you to build up pictures in your mind, in which the numbers are
represented by things that rhyme with the number, and are linked to images that represent the
things to be remembered.
The usual rhyming scheme is shown below:
1 - Bun
2 - Shoe
3 - Tree
4 - Door
5 - Hive
6 - Bricks
7 - Heaven
8 - Skate
9 - Line
10 - Hen
If you find that these images do not attract you or stick in your mind, then change them for
something more meaningful to you.
These images should be linked to images representing the things to be remembered.
Try either visualizing these images as suggested, or if you do not like them, come up with
images of your own.
Once you have done this, try writing down the names of the philosophers on a piece of paper.
You should be able to do this by thinking of the number, then the part of the image associated
with the number, then the whole image, and finally then decode the image to give you the name
of the philosopher. If the mnemonic has worked, you should not only recall the names of all the
philosophers in the correct order, but should also be able to spot where you have left
philosophers out of the sequence. Try it - it's easier than it sounds.
Applying the
Number/Rhyme Technique
You can use a peg system like this as a basis for knowledge in an entire area: the example above
could be a basis for a knowledge of ancient philosophy, as images representing the projects,
systems and theories of each philosopher can now be associated with the images representing the
philosophers names.
The sillier the image, the more effectively you will remember it.
The Number/Shape System
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The Number/Shape system is very similar to the Number/Rhyme system. As with the
Number/Rhyme system it is a very simple and effective way of remembering lists of items in a
specific order. It is another example of a peg system.
How to use the
Number/Shape Technique
This technique works by helping you to build up pictures in your mind, in which the numbers are
represented by images shaped like the number, and are part of a compound image that also codes
the thing to be remembered.
One image scheme is shown below:
1 - Candle, spear, stick
2 - Swan (beak, curved neck, body)
3 - (rotate shape though 90 degrees!)
4 - Sail of a yacht
5 - A meat hook, a sea-horse facing right
6 - A golf club
7 - A cliff edge
8 - An egg timer
9 - A balloon with a string attached, flying freely
0 - A hole
If you find that these images do not attract you or stick in your mind, then change them for
something more meaningful to you.
As with the Number/Rhyme scheme, these images should be linked to images representing the
things to be remembered. Try either visualizing these images as suggested, or if you do not like
them, come up with images of your own.
In some cases these images may be more vivid than those in the number/rhyme scheme, and in
other cases you may find the number/rhyme scheme more memorable. There is no reason why
you could not mix the most vivid images of each scheme together into your own compound
scheme.
The Journey System
The journey method is a powerful, flexible and effective mnemonic based around the idea of
remembering landmarks on a well-known journey. In many ways it combines the narrative flow
of the Link Method and the structure and order of the Peg Systems into one highly effective
mnemonic.
Because the journey method uses routes that you know well, you can code information to be
remembered to a large number o easily visualized or remembered landmarks along the routes.
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Because you know what these landmarks look like, you need not work out visualizations for
them!
How to Use the Journey Technique
The journey method is based on using landmarks on a journey that you know well.
This journey could, for example, be your journey to work in the morning, the route you use to
get to the front door when you get up in the morning, the route to visit your parents, or a tour
around a holiday destination. It could even be a journey around the levels of a computer game.
Once you are familiar with the technique you may be able to create imaginary journeys that fix
in your mind, and apply these.
Preparing the Route
To use this technique most effectively, it is often best to prepare the journey beforehand so that
the landmarks are clear in your mind before you try to commit information to them. One-way of
doing this is to write down all the landmarks that you can recall in order on a piece of paper. This
allows you to fix these landmarks as the significant ones to be used in your mnemonic,
separating them from others that you may notice as you get to know the route even better.
You can consider these landmarks as stops on the route. To remember a list of items, whether
these are people, experiments, events or objects, all you need do is associate these things or
representations of these things with the stops on your journey.
Extending the Technique
This is an extremely effective method of remembering long lists of information: with a
sufficiently long journey you could, for example, remember elements on the periodic table, lists
of Kings and Presidents, geographical information, or the order of cards in a shuffled pack of
cards.
The system is extremely flexible also: all you need do to remember many items is to remember a
longer journey with more landmarks. To remember a short list, only use part of the route!
Long and Short Term Memory
You can use the journey technique to remember information both in the short term memory and
long term memory. Where you need to use information only for a short time, keep a specific
route (or routes) in your mind specifically for this purpose. When you use the route, overwrite
the previous images with the new images that you want to remember. To symbolize that the list
is complete, imagine that the route is blocked with cones, a 'road closed/road out' sign, or some
such.
To retain information in long-term memory, reserve a journey for that specific information only.
Occasionally travel down it in your mind, refreshing the images of the items on it.
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One advantage of this technique is that you can use it to work both backwards and forwards, and
start anywhere within the route to retrieve information.
Using the Journey System
with other Mnemonics
This technique can be used in conjunction with other mnemonics, either by building complex
coding images at the stops on a journey, linking to other mnemonics at the stops, moving onto
other journeys where they may cross over. Alternatively, you may use a peg system to organize
lists of journeys, etc.
The Major System
The Major Memory System is one of the two most powerful memory systems currently
available. It requires a significant investment of time to learn and master, however once it is
learned it is extremely powerful. It is the application of mainly this system that forms the basis of
some of the extraordinary, almost magical, memory feats performed by magicians and memory
technicians.
How to Use the Major Technique
The system works by converting number sequences into nouns, nouns into images, and linking
images into sequences. These sequences can be very complex and detailed.
The building blocks of the system are the association of the numbers below with the following
consonant sounds:
0s, z, soft-c - remember as 'z is first letter of zero'
1d, t, th remember as letters with 1 downstroke
2nremember as having 2 downstrokes
3mhas three downstrokes
4rimagine a 4 and an R glued together back-to-back
5Limagine the 5 propped up against a book end (L)
6j, sh, soft-ch, dg, soft-g - g is 6 rotated 180 degrees.
7k, hard-ch, hard-c, hard-g, ng - imagine K as two 7s rotated and glued together
8f, v imagine the bottom loop of the 8 as an eFfluent pipe discharging waste
(letter image of F in alphabet system)
9p, b b as 9 rotated 180 degrees.
These associations really must be learned before proceeding.
The system operates on a number of levels, depending on the amount of time a user is prepared
to devote to learning the system. The first level, the coding of single digit numbers into
consonants and small words, functions almost as a poor relation of the number/rhyme system. It
is at higher levels that the power of the system is unleashed, however this level must be
assimilated first.
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The trick with the conversion into words is to use only the consonants that code information
within the word, while using vowels to pad the consonants out with meaning. By choosing letters
for your word in the preferential order AEIOU you stand a better chance of being able to
reconstruct the image word if you forget it.
If consonants have to be used to make a word, use only those that are not already used - i.e. h, q,
w, x, and y
1. Single number words:
The first level codes single numbers into a short noun made up of the number consonant sound
and some vowels. On a sheet of paper, write the numbers 1 to 9, and apply these rules to create
your own memory words.
These words can be used in association much like the other peg technique memory words.
2. Double number words:
Similar rules apply to creating a standard word from two numbers. It is best not to try to use
single number word as a root, as this can confuse the image.
Add to your list of numbers 1 to 9 the numbers 10 to 99, and apply the rules to create memory
words for yourself.
3. Triple number words
Just using double number words may be enough to make this a sufficiently powerful mnemonic
for you. Alternatively you may decide to use triple number words, using the same construction
rules as double number words.
Even though words can be constructed from first principles it may be worth writing them down
at this level of complexity, and running through them many times to strengthen the link in your
mind between the numbers and the associated words. This will enable you to recall the number
word faster.
Applying these images
Once you have devised words and images to link to your numbers, you can start to apply the
technique to remember long numbers, etc. At as simple level you might decide just to remember
a long telephone number. To do this you might just associate a few images together using the
link or story technique. Alternatively, to remember a really long number, you might associate
words made up of the components of these numbers with stops on a journey.
Phonetic Numeric Code
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The MENTAT HANDBOOK
In this system each number has a consonant sound associated with it, and by taking a string of
numbers you can switch them into words and memorize them by merely adding vowel sounds
between their consonant sounds. Take a look at the numbers below, their sounds and the reasons
they have each sound associated with them.
1
2
3
4
5
6
7
8
9
0
t or d
n
m
r
l
sh, ch, j
k
f or v
b or p
s or z
here is a single up or down stroke in each letter
the n has 2 points on the ground
the m has 3 points on the ground
because of the r sound at the end of four
the 5 fingers on your left hand (palm down) make an l
because of the sound at the beginning of six or soft g
k is two 7's, one on top of the other
the 8 is like 2 v's together (then closed in)
the b is a 9 upside down
because of the sound in zero
Mnemonics
Mnemonics is a word that simply means 'A Memory Aid', and this System will enhance your
memory. It is a whole style of learning that is easy to use, because it is more natural to your brain
than the way that you have probably used consciously before
The three fundamental principles underlying the use of mnemonics are:
1. Association
2. Imagination
3. Location
Working together, these principles can be used to generate powerful mnemonic systems. Once
you have absorbed and applied these techniques you will understand how to design and apply
these principles to your field to design your own powerful, sophisticated recall systems.
Association
Association is the method by which you link a thing to be remembered to a method of
remembering it.
Things can be associated by:
* Being placed on top of the associated object
* Crashing or penetrating into each other
* Merging together
* Wrapping around each other
* Rotating around each other or dancing together
* Being the same color, smell, shape, or feeling
* Etc.
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The MENTAT HANDBOOK
Whatever can be used to link the thing being remembered with the image used to recall it is the
association image.
The key to remember is that the more unusual the situation, the more action and the more detail
and senses involved, the easier it will be for you to remember it: You will have more associations
attached to what you are memorizing. If you still have trouble making associations try some of
these ideas:
1. Try stacking the items on top of each other.
2. Change the size of an item to ridiculous proportions. (A Giant Shoe or an Elephant the size of
a Mouse.)
3. Change one item into the next item. (The Elephant turns into a small Statue.)
4. Use one item as the next item. (The Statue is used as a Baseball Bat.)
5. Give an item characteristics it shouldn't have. (A talking plant.)
6. Vary the number of items. (millions of plants.)
7. Try to involve as many senses as possible: this increases the number of associations that you
have tied to each item.
8. Go from the General to the Specific (bush to a rose bush in full bloom, ice cream to rocky
road ice cream.)
9. Use comedy, drama, tension or other emotions...
Imagination
Imagination is used to create the links and associations needed to create effective memory
techniques - put simple, imagination is the way in which you use your mind to create the links
that have the most meaning for you.
The more strongly you imagine and visualize a situation, the more effectively it will stick in your
mind for later recall. Mnemonic imagination can be as violent, vivid, or sensual as you like, as
long as it helps you to remember what needs to be remembered.
Location
Location provides you with two things: a coherent context into which information can be placed
so that it hangs together, and a way of separating one mnemonic from another: e.g. by setting one
mnemonic in one location, I can separate it from a similar mnemonic located in another place.
Location provides context and texture to your mnemonics, and prevents them from being
confused with similar mnemonics.
So using the three fundamentals of Association, Imagination and Location you can design
images that strongly link things with the links between themselves and other things, in a context
that allows you to recall those images in a way that does not conflict with other images and
associations.
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When you are creating a mnemonic, e.g. an image or story to remember a telephone number, the
following things can be used to make the mnemonic more memorable:
 Use positive, pleasant images. The brain often blocks out unpleasant ones.
 Exaggerate the size of important parts of the image
 Use humor (perhaps linked with point 2)! Funny or peculiar things are easier to
remember than normal ones.
 Similarly rude or sexual rhymes are very difficult to forget!
 Symbols (e.g. red traffic lights, pointing fingers, etc.) can be used in mnemonics.
 Vivid, colorful images are easier to remember than drab ones.
 Use all the senses to code information or dress up an image. Remember that your
mnemonic can contain sounds, smells, tastes, touch, movements and feelings as well as
pictures.
 Bringing three dimensions and movement to an image makes it more vivid. Movement
can be used either to maintain the flow of association, or can help to remember actions.
 Locate similar mnemonics in different places with backgrounds of those places. This will
help to keep similar images distinct and unconfused.
The important thing is that the mnemonic should clearly relate to the thing being remembered,
and that it should be vivid enough to be clearly remembered whenever you think about it. Some
useful mnemonics in a variety of areas follow.
Examples
The following examples were collected by Mr. Meritt and are included for illustrative purposes
only.
Alphabet
Awful Tie
Brave Noah
Cute Ma
Damp Rye
Efficient Law
Funny Shoe
Gurnsey Cow
Heavy Ivy
Anatomy
Idle Bee
Jagged Toes
Korean Tot
Loud Tin
Marble Tomb
New Tire
Old Towel
Plastic Dish
Quiet Tack
Red Dove
Solid Tub
Terrible Noise
Ugly Knot
Virtuous Nun
Wonderful Name
X-rayed Nero
Yellow Nail
Zigzag Notch
Randy Travis Drinks Cold Beers. Or Robert Taylor Drinks Cold Beer
Roots, Trunks, Divisions, Cords, Branches
You have I nose. You have II eyes.
I - Olfactory; II -- Optic
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Some Say Marry Money, But My Brother Says Big Bras Matter More--what cranial nerve is
Motor, Sensory, or Both
The duck is between two gooses.
duck = thoracic duct
2 gooses = azyGOUS and esophaGOUS
"A lady between two majors." - Pectoralis major attaches to lateral lip of bicipital groove, the
teres major attaches to medial lip of bicipital groove, and the latissimus dorsi attaches to the floor
of bicipital groove. The "lati" is between two "majors."
Point Shoot Score
Parasympathetic, sympathetic, somatomotor
Lateral is less, medial is more.
Lateral pectoral nerves goes through pectoralis major
while medial pn goes though both pec major and minor
ABC'S
*A*ortic arch gives off the *B*racheiocephalic trunk, the left *C*ommon Carotid, and the
left *S*ubclavian artery
NAVEL--order of things in thigh
nerve, artery, vein, empty space, lymphatics
Area and Circumference of a Circle
Tweedle-dee-dum and Tweedle-dee-dee,
Around the circle is pi times 3,
But if the area is declared,
Think of the formula pi "r" squared.
"Around the circle" means circumference.
Circumference = pi x 3
Area = pi x r squared
Aviation
"ANDS" - Compass changes: Acceleration causes the needle to swing northerly, deceleration
southerly.
"High to Low, look out below. Low to high, clear blue sky. " - Changing weather conditions: If
the temperature or barometric pressure drops you will be lower than the instruments indicate, if
you do not correct the change.
Biochemistry
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The MENTAT HANDBOOK
In the Phasted State Phosphorylate
Phosphorylation cascade active when blood glucose low.
Exons expressed, Introns in the trash.--DNA expression into mature mRNA
Pyrimidines are CUT from purines.
Pyrimidines are Cytosine, Uracil, Thiamine and are one ring structures.
Purines are double ring structures.
Biology
"Kittens Prefer Cream Or Fish, Generally Speaking "
"Kings Play Catch Over Farmer Gray's Shed"
"Keep People Coming On For Good-Sized Violins"
"Kids Prefer Cheese Over Fried Green Spinach".
" Kings play chess on Fridays, guzzling Schlitz"
Mnemonics for Kingdom, Phylum, Class, Order, Family, Genus, Species
"She was all gal (ALGAL) and he was a fun guy (FUNGI). They took a likin' (LICHEN) to
each other." - In order to remember that LICHEN are made up of ALGAE and FUNGI (it's better
spoken).
"Can Intelligent Karen Solve Some Foreign Mafia Operations?" - The Krebs Cycle: Citric
acid, Isocitric, Ketoglutaric, Succinyl, Succinic, Fumaric, Malic, Oxaloacetic.
Clinical
GET SMASH'D.--Causes of Acute pancreatitis
Gallstones, Ethanol, Trauma, Steroids, Mumps,
Autoimmune(PAN), Scorpion bites, Hyperlipidemia,
Drugs (azathioprine, diuretics)
Takayasu's diz = pulseless diz, therefore when you have Takayasu's, I can't Tak'a yu pulse.
P-Q-R-S-T--eliciting and HPI and exploring symptoms
P--palliative or provocative factors for the pain
Q--quality of pain (burning, stabbing, aching, etc.)
R--region of body affected
S--severity of pain (usually 1-10 scale)
T--timing of pain (e.g. -after meals, in the morning,
etc.)
Argyll-Robertson Pupil--syphilitic pupil
Accommodation reflex present, Pupillary reflex absent
29
The MENTAT HANDBOOK
The five W's--post-operative fever
Wind--pneumonia, atelectasis
Water--urinary tract infection
Wound--wound infections
Wonderdrugs--especially anesthesia
Walking--walking can help reduce deep vein thromboses and pulmonary embolus
Anna Cycled Immediately Downhill--Gell and Goombs classification of hypersensitivity
reactions
ACID
Type I Anaphylaxis
Type II Cytotoxic-mediated
Type III Immune-complex
Type IV Delayed hypersensitivity
"Lateral is less, medial is more"
(Re: The lateral pectoral nerves goes through the pectoralis major while the medial pn goes
through both the pec major and minor)
"C3,4,5 keep the diaphragm alive" Innervation of the phrenic nerve
"Some Say Marry Money, But My Brother Says Big Bras Matter More" For remembering which
cranial nerves are Sensory, Motor, or Both:
(Multiple endocrine neoplasia) Each of the MENs is a disease of three or two letters plus a
feature.
"MEN I" is a disease of the three Ps (pituitary, parathyroid and pancreas) plus adrenal cortex.
"MEN II " is a disease of the two Cs (carcinoma of the thyroid and catacholamines
[pheochromocytoma]) plus parathyroid for MEN IIa or mucocutaneous neuromas for MEN IIb
(aka MEN III).
"Robert Taylor Drinks Cold Beer" - Brachial Plexus: Roots, Trunks, Divisions, Chords,
Branches
"ACID" or "Anna Cycled Immediately Downhill"
Hypersensitivity reactions - Anaphylactic, Cytotoxic, Immune-complex, Delayedhypersensitivity
WBC Count
"Nobody Likes My Educational Background"
"60, 30, 6, 3, 1"
Neutrophils 60%
Lymphocytes 30%
Monocytes
6%
Eosinophils 3%
30
The MENTAT HANDBOOK
Basophils
1:
Colors of the Rainbow
Virgin In Bed Gives You Orgasmic Release
Rip Off Your Goolies Before I Vomit
Richard of York gave battle in vain
Read Out Your Good Book In Verse
For: violet, indigo, blue, green, yellow, orange, red.
(Or ROY G BIV, for the same colors in the opposite direction.)
Compass
Never Eat Shredded Wheat
Never Eat Slimy Worms
Never Eat Soggy Waffles
Never Eat Sour Watermelon
To remember the directions on a map, place the first letter of each word in a clockwise circle
starting at the 12 o'clock position:
N
W
E
S
"True Virgins Make Dull Company" - Computing true course: True heading minus Variation
plus or minus Magnetic variation plus or minus Deviation equals Course.
"East is Least, West is Best" - Compass variation - subtract easterly variation, add westerly
variation.
"Can Dead Men Vote Twice?" - Compass-Deviation-Magnetic-Variance-True
For converting between True, Magnetic, and Compass direction applying variation and
deviation:
True virgins make dull company
Or backwards:
Can dead men vote twice?
Electromagnetic Spectrum
Cary Grant eXpects Unanimous Votes In Movie Reviews Tonight
Cosmic Gamma X-rays Ultraviolet Visible Infrared Microwave Radio Television
Graphs
31
The MENTAT HANDBOOK
All Students Take Calculus for Positive Trigonometric Functions in Each Quadrant
Each word of the mnemonic starts with the letter of the word that tells which trigonometric
function(s) are positive in each quadrant of a graph (where the origin equals 0). Each letter
stands for a trigonometric function (e.g. Mentats = Sine) except for the first quadrant, where
conveniently "all" stands for "all."
1st quadrant -- All
2nd quadrant -- Sine
3rd quadrant -- Tangent
4th quadrant -- Cosine
Hardness scale for minerals
Terrible Giants Can Find Alligators Or Quaint Tigers Conveniently Digestible.
Talc, Gypsum, Calcite, Flourite, Apatite, Orthoclase feldspar, Quartz, Topaz, Corundum,
Diamond.
Terrific girls can flirt and other queer things can do.
For Moh's hardness scale
10 - diamond
9 - corundum
8 - topaz
7 - quartz (easily scratches glass)
6 - orthoclase feldspar (barely scratches glass)
5 - apatite (nail is about 5)
4 - fluorite
3 - calcite
2 - gypsum (fingernail is about 2.5)
1 - talc
Mechanics
"Right on! Left off." Or " "Righty tighty, lefty loosie"
Insertion of a bolt or nut is clockwise (right), turn counterclockwise (left) to get a bolt or nut
off of something. ("Right on" may be outdated slang; it means something is very good.)
Medicine
Two Zulu's Bruised My Cervix or To Zanzibar By Motorcar or Two Zulus Buggerd My Cat
These are used to remember the branches of the facial nerve...
T emporal nerve
Z ygomatic nerve
B uccal nerve
M arginal mandibular nerve
32
The MENTAT HANDBOOK
C ervical nerve
Some Lovers Try Positions That They Can't Handle
For the order of the bones in the wrist : Scaphoid, Lunate, Triquetral, Pisiform, Trapezium,
Trapezoid, Capitate, Hamate.
Some Say Marry Money But My Brother Says Big Breasts Matter Most
For the Cranial Nerves 1 through 12, in determining whether they are Sensory, Motor, or
Both (starting with Cranial Nerve 1)
Metric System prefix
After
Fellatio
Please
Note
You
Must
Cum
Kiss
My
Giant
Todger
atto
femto
pico
nano
micro
milli
centi
Kilo
mega
giga
tera
10*-18
10*-15
10*-12
10*-9
10*-6
10*-3
10*-2
10*3
10*6
10*9
10*12
Every
Person
That
Gave
Me
Kisses
Has
Diarea
Exta
Peta
Tera
Giga
Mega
Kilo
Hecto
Deca
10*18
10*15
10*12
10*9
10*6
10*3
10*2
10*1
diary
cows
make
milk
not
pink
fruit
asshole
deci
centi
milli
micro
nano
pico
femto
atto
10*-1
10*-2
10*-3
10*-6
10*-9
10*-12
10*-15
10*-18
Or
"King Hector Doesn't Usually Drink Cold Milk"
33
The MENTAT HANDBOOK
for Kilo
Hecto
Deca
Units
Deci
Centi
Milli
1000
100
10
1
0.1
0.01
0.001
Music
Fat Corpulent Germans Drink And Eat Badly
Fat Cats Go Down Alleys Eating Birds
Freddy Can Get Drunk At Every Bar
Father Charles Goes Down And Ends Battle
The circle of fifths-- "C" is a fifth of "F," etc.
Battle Ends And Down Goes Charles' Father
This Circle of Fifths mnemonic is cool because it works forwards and backwards (for the flats)
All Cows Eat Grass
The notes represented by the spaces on the bass clef, bottom to top.
Good Boys Do Fine Always
The lines on the bass clef
Father Charles goes down and ends battle.
The order of sharps; if a key has one sharp, it will be F, and if a key has two sharps, they will
be F and C.
For flat keys, the order is reversed:
Battle ends and down goes Charles' father.
FACE
The notes represented by the spaces on the treble clef, bottom to top
Every Good Boy Does Fine
Elephants Got Big Dirty Feet
Every Good Boy Deserves Fudge
Elvis' Guitar Broke Down Friday (the kids' favorite)
Empty Garbage Before Dad Flips
Every Girl Buys Dresses Friday (use sparingly)
Every Good Burger Deserves Fries
Eels Get Breakfast During February
The notes represented by the lines on the treble cleff, bottom to top
Order of Calculations in Algebra
34
The MENTAT HANDBOOK
Please Excuse My Dear Aunt Sally or Please Execute My Dog And Soon or Put Every Man
Down And Shout
Parentheses, Exponents, Multiplication, Division, Addition, Subtraction.
Periodic Table
"Hell! Here're Little Beatniks Brandishing Countless Numbers Of Flick kNives."
H
He
Li
Be
B
C
N
O F
er, Ne
"Naughty Maggie Always Sips Pure Sweet Claret"
N
Mg
Al
Si P S
Cl
"Hi Helen, Little Betty Boron Can Not Often Find
Neddy. Naughty Meg Always SiPS Chlorine in <thinko - no idea what this is>
Kenny's Car"
Harry HElped LIttle BEnny Balmer Carry Neat Oysters From Neptune's
NAtural MenaGerie ALways SInging Polite Sonnets CLearly ARf Key CAsually.
Hi! He Lies Because Boron CanNot Oxidize Fluorine.
Necromantic Nato Mg(abbv. for make Good) All Silicon Ports.
Superman Clean Argon's K-Capture.
the Lanthanide series
Little Cute People Need Plenty Sex Every Given Time Despite having Enough
Through Young Love. (La Ce Pr Nd Pm Sm Eu Gd Tb Dy Ho Er Th Yb Lu)
A mnemonic for the lanthanide elements (Ce - Lu):
Currently parties never provide sexy English girls that drink heavily,
even though you look.
The second half of the lanthanides
The Dancers Have Everything That You Love
Terbium Dysprosium Holmium Erbium Thulium Ytterbium Lutetium
Group
I Her Little Name Klub; Ruby, Cessie and Francie.
II Before Megan Can Start Barry Raids the alkaline earth metals
35
The MENTAT HANDBOOK
III Boring Al's Galloping Indian on a horse named Thallium
IV Carbon has Silicon German (word for breasts) and Tin Sin feinn drinks
in a Lead Pub (Sn for tin and Pb for lead)
V Now Paddy's Arse And Timony's Sub all go swimming in a Bismuth tub
Group VI and VII I already knew
0 His Noblemen Are Kwite Xtra Rude
first two periods of the periodic table
Happy Henry Likes Beer But Can Not Often Find N-E.
limping native king robbed caeser's frame
(li na k rb cs fr)
better maggi can straighten bad radium)
back allocate game in thallium
caravan singh gets standard plumbing
never produce asthmatic anti-biotics
(antimony - bismuth)
oxford sometimes sees terrible poverty
Scandinavian television corrupts many french coalmen's nieces and cousins
Sc
Ti V
Cr
Mn Fe Co
Ni
Cu Zn
the first 20 periodic table elements
Hi! He Lies Because Boron CanNot Oxide Fluoride
H He Li Be Bo C N O F
New Nation Might --- Sign Peace Security Clause
Ne Na Mg Al Si P S
Cl
A King Can
Ar K Ca
Physics
ROY G. BIV (pronounced like a person's name)
Red, Orange, Yellow, Green, Blue, Indigo, Violet: the colors of the rainbow, in order.
Sober Physicists Don't Find Giraffes In Kitchens.
The orbital names for electrons (SPDFGIK). After that it is alphabetical order.
36
The MENTAT HANDBOOK
Pharmacology
One heart two lungs--beta receptor activity
Beta-1 primarily on heart; airway is beta-2 receptors
Pi
Counting the letters of each word gives you the value of pi
Seven digits of Pi
May I have a large container of coffee?
Eight Digits of Pi
How I wish I could recollect pi easily today
Nine Digits of Pi
May I have a large container of orange juice?
Fourteen digits of pi
How I want a drink, alcoholic of course, after the heavy chapters on quantum mechanics.
Twenty digits of pi
Sir, I send a rhyme excelling
In sacred truth and rigid spelling
Numerical sprites elucidate
For me the lexicon's dull weight.
A Pi story
The poem encodes the first 740 decimals of pi. The encoding rule is this: a word of N letters
represents the digit N if N<9, the digit 0 if N=10, and two adjacent digits if N>10 (e.g., a 12letter word represents the digit '1' followed by '2').
Poe, E.
Near A Raven
Midnights so dreary, tired and weary.
Silently pondering volumes extolling all by-now obsolete lore.
During my rather long nap - the weirdest tap!
An ominous vibrating sound disturbing my chamber's antedoor.
"This", I whispered quietly, "I ignore".
Perfectly, the intellect remembers: the ghostly fires, a glittering ember.
Inflamed by lightning's outbursts, windows cast penumbras upon this floor.
37
The MENTAT HANDBOOK
Sorrowful, as one mistreated, unhappy thoughts I heeded:
That inimitable lesson in elegance - Lenore Is delighting, exciting...nevermore.
Ominously, curtains parted (my serenity outsmarted),
And fear overcame my being - the fear of "forevermore".
Fearful foreboding abided, selfish sentiment confided,
As I said, "Methinks mysterious traveler knocks afore.
A man is visiting, of age threescore."
Taking little time, briskly addressing something: "Sir," (robustly)
"Tell what source originates clamorous noise afore?
Disturbing sleep unkindly, is it you a-tapping, so slyly?
Why, devil incarnate!--" Here completely unveiled I my antedoor-Just darkness, I ascertained - nothing more.
While surrounded by darkness then, I persevered to clearly
comprehend.
I perceived the weirdest dream...of everlasting "nevermores".
Quite, quite, quick nocturnal doubts fled - such relief! - as my
intellect said,
(Desiring, imagining still) that perchance the apparition was
uttering a whispered "Lenore".
This only, as evermore.
Silently, I reinforced, remaining anxious, quite scared, afraid,
While intrusive tap did then come thrice - O, so stronger than sounded afore.
"Surely" (said silently) "it was the banging, clanging window lattice."
Glancing out, I quaked, upset by horrors hereinbefore,
Perceiving: a "nevermore".
Completely disturbed, I said, "Utter, please, what prevails ahead.
Repose, relief, cessation, or but more dreary 'nevermores'?"
The bird intruded thence - O, irritation ever since! Then sat on Pallas' pallid bust, watching me (I sat not, therefore),
And stated "nevermores".
Bemused by raven's dissonance, my soul exclaimed, "I seek intelligence;
Explain thy purpose, or soon cease intoning forlorn 'nevermores'!"
"Nevermores", winged corvus proclaimed - thusly was a raven named?
Actually maintain a surname, upon Pluvious seashore?
I heard an oppressive "nevermore".
My sentiments extremely pained, to perceive an utterance so plain,
Most interested, mystified, a meaning I hoped for.
"Surely," said the raven's watcher, "separate discourse is wiser.
38
The MENTAT HANDBOOK
Therefore, liberation I'll obtain, retreating heretofore Eliminating all the 'nevermores' ".
Still, the detestable raven just remained, unmoving, on sculptured bust.
Always saying "never" (by a red chamber's door).
A poor, tender heartache maven - a sorrowful bird - a raven!
O, I wished thoroughly, forthwith, that he'd fly heretofore.
Still sitting, he recited "nevermores".
The raven's dirge induced alarm - "nevermore" quite wearisome.
I meditated: "Might its utterances summarize of a calamity before?"
O, a sadness was manifest - a sorrowful cry of unrest;
"O," I thought sincerely, "it's a melancholy great - furthermore,
Removing doubt, this explains 'nevermores' ".
Seizing just that moment to sit - closely, carefully, advancing
beside it,
Sinking down, intrigued, where velvet cushion lay afore.
A creature, midnight-black, watched there - it studied my soul,
unawares.
Wherefore, explanations my insight entreated for.
Silently, I pondered the "nevermores".
"Disentangle, nefarious bird! Disengage - I am disturbed!"
Intently its eye burned, raising the cry within my core.
"That delectable Lenore - whose velvet pillow this was, heretofore,
Departed thence, unsettling my consciousness therefore.
She's returning - that maiden - aye, nevermore."
Since, to me, that thought was madness, I renounced continuing sadness.
Continuing on, I soundly, adamantly forswore:
"Wretch," (addressing blackbird only) "fly swiftly - emancipate me!"
"Respite, respite, detestable raven - and discharge me, I implore!"
A ghostly answer of: "nevermore".
" 'Tis a prophet? Wraith? Strange devil? Or the ultimate evil?"
"Answer, tempter-sent creature!", I inquired, like before.
"Forlorn, though firmly undaunted, with 'nevermores' quite
indoctrinated,
Is everything depressing, generating great sorrow evermore?
I am subdued!", I then swore.
In answer, the raven turned - relentless distress it spurned.
"Comfort, surcease, quiet, silence!" - pleaded I for.
"Will my (abusive raven!) sorrows persist unabated?
39
The MENTAT HANDBOOK
Nevermore Lenore respondeth?", adamantly I encored.
The appeal was ignored.
"O, satanic inferno's denizen -- go!", I said boldly, standing then.
"Take henceforth loathsome "nevermores" - O, to an ugly Plutonian shore!
Let nary one expression, O bird, remain still here, replacing mirth.
Promptly leave and retreat!", I resolutely swore.
Blackbird's riposte: "nevermore".
So he sitteth, observing always, perching ominously on these doorways.
Squatting on the stony bust so untroubled, O therefore.
Suffering stark raven's conversings, so I am condemned, subserving,
To a nightmare cursed, containing miseries galore.
Thus henceforth, I'll rise (from a darkness, a grave) -- nevermore!
-- Original: E. Poe
-- Redone by measuring circles.
Speed of Light
The speed of light is always 299,792,458 meters/second.
299 792 458 = "We guarantee certainty, clearly referring to this light mnemonic"
299 792 458 = "My ingenious astronomy student remembers an easy light mnemonic"
(number of characters of a word = digit)
Spelling and Grammar
"A friend is always there when the end comes." - For those who always look at "friend" and
think that it looks wrong
I before E except after C
And when saying "A" as in Neighbor or Weigh
And weird is weird.
Separate is A RAT of a word to spell
To remember to spell separate correctly, instead of "seperate".
When two vowels go walking the first does the talking
For words like "oat" or "eat"
The silent 'e' makes the vowel say its name
For words like cap/cape and hat/hate.
40
The MENTAT HANDBOOK
Once there was a young woman named Sep. He was violently afraid of rodents, especially rats.
One day, her little brother, who was a very cruel, unfeeling child, tapped her shoulder, and yelled
"Sep, a rat!" Her response, of course, was a loud "Eeeeeee!"
This is a very clever story to remind a person how to spell "separate."
A Rat In The House Might Eat The Ice Cream
The first letter of each word spells Arithmetic!
A rat in Tom's house may eat tom's ice cream
Same song, different verse.
"Would you rather have one S or two? Twice as much for dessert. " - deSSert - two s's; desert one s.
When you eat "dessert", you always want to come back for the second "s".
Another desert/dessert mnemonic
"sweet stuff " - Dessert has double esses
"Strawberry Shortcake" - Dessert has two s's in it ... like Strawberry Shortcake.
"A Dessert is Super Sloppy; A Desert is Sandy" - Yet more ways to remember "dessert" vs.
"desert"
The word "believe" has "lie" in it
"Your principal is your PAL " - The difference between Principle and PrinciPAL...
The sailor's favorite boat was named "PAN CAP IV"
Parts of Speech: Pronoun, Adverb, Noun, Conjunction, Adjective, Preposition, Interjection,
Verb
RAVEN
R emember
A ffect
V erb
E ffect
N oun
To remember when to use "affect" vs "effect" ...
Stellar spectral classes
Oh be a fine girl, kiss me right now - SMACK
Oh be a fine girl, kiss me right now sweetheart.
Oh Big And Ferocious Gorilla, Kill My Roommate Next Saturday!
On bad afternoons fermented grapes keep Mrs. Richard Nixon smiling.
41
The MENTAT HANDBOOK
For: 0, B, A, G, K, M, R, N, S.
Wow-Oh Be A Fine Girl. Kiss Me Right Now! *Smack*
(includes the W class)
Stalactites and Stalagmites
As mites go up, tites come down.
Stalactites: They hang on tite
: stalactites hang onto the ceiling. There's no c in stalagmite.
Stalagmites: They aren't stalactites.
StalacTITEs hold TIGHT to the roof, and stalagMITEs
MIGHT one day join up with them
Trignometric functions
"The Old Arab Carried A Heavy Sack Of Hay " or "Tessies old Aunt sits on her coffin and
hollers."
Tan = Opp/Adj; Cos= Adj/Hyp; Sin= Opp/Hyp - for remembering Trig identities
Weight of Water
"A pint's a pound the world around." - A pint of water weighs one pound.
Processor
Processors can combine, divide, sort and file pieces of discrete information with 99.99985
percent accuracy per 10,000 items. They are capable of introducing order and regularity to
seemingly unrelated sets of information.
Mathematics
An ability with basic arithmetic is core to the Mentat's abilities. To change this necessity from
slow tedium into a faster, more precise methodology a number of simple, straightforward
alternative to the "old" methods are given here.
Checking Calculations
Add the digits making up each multiplier and the answer using following rules:
1. When the sum goes over 9 reduce the two digits
2. Ignore any 9
3. Ignore any two digits touching each other that add up to 9
The digit sum of the multiplied numbers should equal the digit sum of the answer
42
The MENTAT HANDBOOK
Multiplication
1. Always place one zero in front of the first multiplier for each digit of the second multiplier.
2. Apply the rule according to the second multiplier, working through the digits of the first
multiplier from right to left
The rule will call for doubling or taking half. Taking half of even numbers presents no problem.
Uneven numbers ("odd" numbers) are divided as: half of 1 is 0, half of 3 is 1, half of 5 is 2, half
of 7 is 3, half of 9 is 4.
For odd numbers the rule will sometimes call for a special procedure.
A "neighbor" is the adjacent number for the following rules.
To Multiply
Rule
11
Add the neighbor
12
Double, add the neighbor
6
Add half the neighbor plus 5 if number is odd
7
Double, add half the neighbor, add 5 if number is odd
5
Take half of the neighbor, add 5 if the number is odd
9
1. Last digit: subtract from 10
2. Middle digits: subtract from 9 and add the neighbor
3. First digit: (the leading zero) subtract 1 from the neighbor.
8
1. Last digit: subtract from 10 and double
2. Middle digits: subtract from 9 and double, add the neighbor
3. First digit: (the leading zero) subtract 2 from the neighbor.
4
1. Last digit: subtract from 10, add 5 if odd
2. Middle digits: subtract from 9, add half neighbor, +5 if odd
3. First digit: (the leading zero): half the neighbor less 1.
3
1. Last digit: subtract from 10, double, +5 if odd
2. Middle digits: subtract from 9, double, add half neighbor, +5 if odd.
3. First digit: (the leading zero) half the neighbor and subtract 2.
Direct Multiplication
This method is ideal for multiplication with a number that consists of numbers between 1 and 3.
It can be used on any numbers, but with the second number higher than 3 speed multiplication
should be preferred.
2-digits multiply
1. Multiply down right side
2. Cross multiply
3. Repeat using a pair of digits one to the left.
43
The MENTAT HANDBOOK
Speed Multiplication
This method is ideal for multiplication of large numbers. In this method all numbers are
considered two-digit numbers with a left-hand ´tens´ and a right-hand ´units´ digit.
When multiplying the right hand digit we are only concerned with the units digit of the answer.
With the right hands digit we are only concerned with the tens digit of the answer.
Pair Product
To get the pair product of 47 x 4 proceed as following
U T
4 7
x 4
U T
4 7
x 4
16 28
^^
6 2
add 6 and 2 to get the pair product 8
The Pair Product needs to be well practiced to allow you to write down the finished answer with
no intermediate computation.
The big difference between the Speed Multiply and Direct Multiply method is that with Speed
Multiply the highest number to carry from one pair product to the other is a 1 or 2.
Single-digit multiplication
1. Add the ´units´ of the left hand number and the ´tens´ of the right hand number (Pair Product)
2. Each number is one digit to the answer of the problem
Double-digit multiplication
Here we need to work with two numbers at a time. For convenience mark the digits using your
fingers. Here these numbers will be market with dots (.. ).
1. The left-hand working number is where the next answer will be written.
2. The left-hand is also where you start multiplying with the lower right hand number.
3. Cross multiply the lower two numbers with the current pair (..).
a) Multiply the lower-right number first
b) All we care about is the sum of the left-hand ´units´ and the right-hand ´tens´.
To go smoothly, it is essential to practice Pair-Products.
44
The MENTAT HANDBOOK
Cross multiply each bottom number twice. Once with the crossed number, and once with the
neighbor (right neighbor).
3-digits multiply
1. Multiply down right side
2. Cross multiply the last two digits
3. Cross multiply the last three digits
4. Repeat using a triplet of digits one to the left.
N-digits multiply
1. Multiply down right side
2. Cross multiply the last two digits
3. Cross multiply the last three digits
4. Cross multiply the last four digits.
(...)
n-1. cross multiply the last n-1 digits.
n. cross multiply the last n digits.
n+1. repeat using a "n-plet" of digits one to the left.
Solving an Equation or Inequality
It takes two steps to solve an equation or inequality that has more than one operation:
1. Simplify using the inverse of addition or subtraction.
2. Simplify further by using the inverse of multiplication or division.
Quick Square of a two-digit number that ends in 5
Multiply the first digit by that number plus one.... stick a 25 after your product and there's your
answer
Computing the day of the week from the date
1.
2.
3.
4.
5.
6.
Take the last two digits of the year.
Divide by 4, discarding any fraction.
Add the day of the month.
Add the month's key value: JFM AMJ JAS OND 144 025 036 146
Subtract 1 for January or February of a leap year.
For a Gregorian date, add 0 for 1900's, 6 for 2000's, 4 for 1700's, and 2 for 1800's; for
other years, add or subtract multiples of 400.
7. For a Julian date, add 1 for 1700's, and 1 for every additional century you go back.
8. Add the last two digits of the year.
9. Divide by 7 and take the remainder.
45
The MENTAT HANDBOOK
Now 1 is Sunday, the first day of the week, 2 is Monday, and so on.
Multiplying two 2-digit numbers (same 1st digit)
1.Multiply their second digits (keep the carry).
2.Multiply the sum of the second digits by the first digit, add the carry (keep the carry).
3.Multiply the first digits (add the carry).
Multiplying two 2-digit numbers (difference of 1)
1.Square the larger number (multiply it by itself).
2.Subtract the larger number from the product.
OR
1.Square the smaller number (multiply it by itself).
2.Add the smaller number to the product. Pick the easier one to square.
Multiplying two 2-digit numbers (difference of 10)
1.Find the middle number of the two (the average).
2.Square this middle number (multiply it by itself).
3.Subtract 25 from this square.
Dividing mixed numbers by 2
1.If the whole number is even, divide by 2 - this is the whole number of the answer. The
numerator of the fraction stays the same; multiply the denominator by 2.
Or
1.If the whole number is odd, subtract 1 and divide by 2 - this is the whole number of the answer.
Add the numerator and the denominator of the fraction - this will be the new numerator of the
fraction; Multiply the denominator by 2.
Adding a Sequence of Consecutive Odd Numbers
1. Add one to the 2-digit number.
2. Divide this sum by 2 (take half of it).
3. Square this number. This is the sum of all odd numbers from 1 through the 2-digit
number chosen.
Adding consecutive numbers between two numbers
1.
2.
3.
4.
Add the numbers
Subtract the numbers and add 1
Multiply half the sum by this difference + 1, OR
Multiply the sum by half the difference + 1.
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The MENTAT HANDBOOK
Add a sequence from one to a selected 2-digit number
Multiply the 2-digit number by half the next number
Or
Multiply half the 2-digit number by the next number.
Adding a series of doubles
1. Have a friend choose a single digit number. (No restrictions for experts.)
2. Ask your friend to jot down a series of doubles (where the next term is always double the
preceding one), and tell you the last term.
3. Ask your friend to add up all these terms.
4. You will give the answer before he or she can finish: The sum of all the terms of this
series will be two times the last term minus the first term.
Adding a series of ten numbers
1. Have a friend choose and write down a single-digit number. (Two digits for experts.)
2. Ask your friend to name and note a third number by adding the first two.
3. Name a fourth by adding the second and third. Continue in this way, announcing each
number, through ten numbers.
4. Ask your friend to add up the ten numbers. You will give the answer before he or she can
finish: The sum of all the terms of this series will be the seventh number multiplied by
11.
Subtracting the squares of two numbers
1. Select a 2-digit number and then choose a number two larger or two smaller.
2. Multiply the middle number by 4.
Finding 5 percent of a number
1. Move the decimal point one place to the left.
2. Divide by 2 (take half of it).
Finding 15 percent of a number
1. Multiply the number by 3.
2. Divide by 2.
3. Move the decimal point one place to the left.
Finding 45 percent of a number
1. Multiply the number by 9.
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The MENTAT HANDBOOK
2. Divide by 2.
3. Move the decimal point one place to the left.
Finding 55 percent of a number
1. Multiply the number by 11. (Add digits from right to left).
2. Divide by 2.
3. Move the decimal point one place to the left.
Round Off Whole Numbers
1.
2.
3.
Find the place value you want (the "rounding digit") and look to the digit just to the
right of it.
If that digit is less than 5, do not change the "rounding digit" but change all digits to
the right of the "rounding digit" to zero
If that digit is greater than or equal to 5, add one to the rounding digit and change all
digits to the right of the rounding digit to zero.
Squaring a 2-digit number beginning with 1
1. Square the second digit (keep the carry)
2. Multiply the second digit by 2 and add the carry (keep the carry)
3. The first digit is one (plus the carry)
Squaring a 2-digit number beginning with 5
1. Square the first digit.
2. Add this number to the second number to find the first part of the answer.
3. Square the second digit: this is the last part of the answer.
Squaring a 2-digit number beginning with 9
1. Subtract it from 100.
2. Subtract the difference from the original number: this is the first part of the answer.
3. Square the difference: this is the last part of the answer.
Squaring a 2-digit number ending in 1
1. Subtract 1 from the number.
2. Square the difference.
3. Add the difference twice to its square.
4. Add 1.
Squaring a 2-digit number ending in 2
1. The last digit will be 4.
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The MENTAT HANDBOOK
2. Multiply the first digit by 4: the 2nd number will be the next to the last digit.
3. Square the first digit and add the number carried from the previous step.
Squaring a 2-digit number ending in 3
1. The last digit will be 9.
2. Multiply the first digit by 6: the 2nd number will be the next to the last digit.
3. Square the first digit and add the number carried from the previous step.
Squaring a 2-digit number ending in 4
1.
2.
3.
Square the 4; the last digit is 6. (Keep carry, 1.)
Multiply the first digit by 8 and add the carry (1); the 2nd number will be the next to
the last digit (keep carry).
Square the first digit and add the carry.
Squaring a 2-digit number ending in 5
1. Multiply the first digit by the next consecutive number.
2. The product is the first two digits.
3. The last part of the answer is always 25.
Squaring a 2-digit number ending in 6
1.Choose a 2-digit number ending in 6.
2.Square the second digit (keep the carry): the last digit of the answer is always 6.
3.Multiply the first digit by 2 and add the carry (keep the carry).
4.Multiply the first digit by the next consecutive number and. Add the carry:
The product is the first two digits
Squaring a 2-digit number ending in 7
1. The last digit of the answer is always 9.
2. Multiply the first digit by 4 and add 4 (keep the carry).
3. Multiply the first digit by the next consecutive number and add the carry:
The product is the first two digits.
Squaring a 2-digit number ending in 8
1. The last digit of the answer is always 4.
2. Multiply the first digit by 6 and add before the carry).
3. Multiply the first digit by the next consecutive number and add the carry: the product is
the first two digits.
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The MENTAT HANDBOOK
Squaring a 2-digit number ending in 9
1. The last digit of the answer is always 1.
2. Multiply the first digit by 8 and add 8 (keep the carry).
3. Multiply the first digit by using each consecutive number and add the carry: the product
is the first two digits.
Squaring numbers made up of ones (up to 9 digits)
The answer will be a series of consecutive digits beginning with 1, up to the number of ones in
the given number, and back to 1
Squaring numbers made up of threes
The square here, r up of:
a. one fewer 1 than there are repeating 3's
b. zero
c. one fewer 8 than there are repeating 3's same as the 1's in the square)
d. Nine.
Squaring numbers made up of sixes
The square is made up of:
a. One fewer 4 than there are repeating 6's
b. 3
c. Same number of 5's as 4's
d. 6
Squaring numbers made up of nines (up to 9 digits)
The answer will have one less 9 than the number, one 8, the same number of zeros as 9's, and a
final 1
Squaring numbers in the 20s
1.Square the last digit (keep the carry)
2.Multiply the last digit by 4, add the carry
3.The first digit will be 4 plus the carry
Squaring numbers in the 30s
1.Square the last digit (keep the carry)
2.Multiply the last digit by 6, add the carry
3.The first digits will be 9 plus the carry
Squaring numbers in the 40s
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The MENTAT HANDBOOK
1.Square the last digit (keep the carry)
2.Multiply the last digit by 8, add the carry
3.The first digits will be 16 plus the carry
Squaring numbers in the 50s
1.Square the last digit (keep the carry)
2.Multiply the last digit by 10, add the carry
3.The first digits will be 25 plus the carry
Squaring numbers in the 60s
1.Square the last digit (keep the carry)
2.Multiply the last digit by 12, add the carry
3.The first digits will be 36 plus the carry
Squaring numbers in the 70s
1.Square the last digit (keep the carry)
2.Multiply the last digit by 14, add the carry
3.The first digits will be 49 plus the carry
Squaring numbers in the 80s
1.Square the last digit (keep the carry)
2.Multiply the last digit by 16, add the carry
3.The first digits will be 64 plus the carry
Squaring numbers in the hundreds
The last two places will be the square of the last two digits (keep any carry) _ _ _ X X. be the
number plus the last two digits plus any carry: X X X _ _.
Squaring numbers in the 200s
1.The first digit of the square is 4
2.The next two digits will be 4 times the last 2 digits
3.The last two places will be the square of the last digit
Squaring numbers in the 300s
1.The first digit of the square is 9
2.The next two digits will be 6 times the last 2 digits
3.The last two places will be the square of the last digit
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The MENTAT HANDBOOK
Squaring numbers in the 400s
1.The first two digits of the square are 16
2.The next two digits will be 8 times the last 2 digits
3.The last two places will be the square of the last two digits
Squaring numbers in the 500s
1.The first two digits of the square are 25
2.The next two digits will be 10 times the last 2 digits
3.The last two places will be the square of the last two digits
Squaring numbers in the 600s
1.The first two digits of the square are 36
2.The next two digits will be 12 times the last 2 digits
3.The last two places will be the square of the last two digits
Squaring numbers in the 700s
1.Square the last two digits (keep the carry)
2.Multiply the last two digits by 14 and add the carry
3.The first two digits will be 49 plus the carry
Squaring numbers in the 900s
1.Subtract the number from 1000 to get the difference.
2.The first three places will be the number minus the difference.
3.The last three places will be the square of the difference (if 4 digits, add the first digit as carry).
Squaring numbers between 1000 and 1100
1.The first two digits are: 1,0 _ _, _ _ _
2.Find the difference between your number and 1000.
3.Multiply the difference by 2
4.Square the difference
Squaring numbers between 2000 and 2099
1.The first two digits are: 4 0 _ _ _ _ _
2.The next two digits are 4 times the last two digits.
3.For the last three digits, square the last two digits in the number chosen (insert zeros when
needed).
Squaring numbers between 3000 and 3099
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The MENTAT HANDBOOK
1.The first two digits are: 9 0 _ _ _ _ _
2.The next two digits are 6 times the last two digits
3.For the last three digits, square the last two digits in the number chosen (insert zeros when
needed)
Squaring numbers between 4000 and 4099
1. For numbers less than 4013: (For numbers greater than 4012, reverse the order)
2. The first three digits are: 1 6 0 _ _ _ _ _
3. The next two digits are 8 times the last two digits
4. For the last three digits, square the last two digits in the number chosen (insert zeros when
needed)
Statistics
Probability is a measure of the likelihood of an event occurring. There are several phrases that
describe the likelihood of this event: it's a sure thing; more than likely; chances are good;
chances are poor; unlikely; impossible.
Mathematicians assign a number between 0 and 1, inclusive. The probability of an event equals
the number of ways an event can occur divided by the total number of possibilities, provided that
each possibility has equal chance to occur. (see: Expected value)
To compute slightly less direct probabilities are as follows:
If A and B are two complementary mutually exclusive events (i.e., if A does not occur, then B
must occur and vice versa), then the probability of A and probability of B add up to 1, P (A) + P
(B) = 1
If event A and event B do not affect each other's chances of occurring (they are called
independent) and they have probabilities P (A) and P(B) respectively, then P(A and B) =
P(A)×P(B)
A statistic is a number calculated from numerical data. An example of a statistic is the mean.
Law of Large Numbers. If a trial (such a play of a game of chance) is repeated many times, then
the more times the trial is repeated, the more likely it is that the frequency of any particular event
will be close to the probability of that event. This may be taken as the definition of probability,
or it can be taken as a theorem, in which case it is called the Law of Large Numbers. This
accuracy occurs with a relative order of 1/sqrt(n), where n is the size of the population.
Law of Medium Numbers. For medium number systems, we can expect that large fluctuations,
irregularities, and discrepancies with any theory will occur more or less regularly i.e. anything
that can happen, will happen.
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The MENTAT HANDBOOK
Expected Value. Suppose have a game of chance (or an experiment) with a numerical outcome.
The expected value is the calculated by taking each outcome and multiplying its value by the
probability of that outcome, then adding all the products up. If all outcomes are equally likely,
then the expected value will equal the mean of all the outcomes. The more times the action
occurs, the more likely it is that the mean of all the accumulated outcomes will be close to the
expected value.
Generalized Thermodynamic law. More probable states are more likely to be observed than less
probable states, unless specific constraints exist to keep them from occurring.
The things we see more frequently are more frequent:
1. Because there is some physical reason to favor certain states.
2. Because there is some mental reason to favor observing certain states.
The mean of a list of numbers is calculated by adding all the numbers up, then dividing by how
many numbers there are. The mean is also called the "average."
The mean is represented by x with a line over it, read "x bar."
The variance measures how spread out a list of numbers is, how much the numbers differ from
their mean. To calculate the variance:
1. Take each data item.
2. Square each.
3. Add them all up
4. Divide by the number of data items
5. To get the variance.
Alternatively:
1. Take the first data item.
2. Subtract the mean from it.
3. Square the difference.
4. Do the same for the 2nd through the Nth data item.
5. Add them all up.
6. Divide the sum by the number of data items.
The basic concept of "analysis of variance" (ANOVA) is not a difficult one to grasp. Some basic
understanding of regression analysis, indicator or dummy variables combined with computer
statistical skills are important prerequisites to interpret the data for ANOVA, but the concept of
the analysis itself is quite simple.
In nonequivalent, quasi-experimental research designs the analysis of variance is an important
tool to understand the statistical differences between the averages or the "means" of two different
populations, however they are distinguished by research design. When the statistical significance
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The MENTAT HANDBOOK
of the differences of means can be assessed, then a more accurate comparison can be made
between groups. Statistical differences are assessed through an ANOVA analysis.
In an ANOVA analysis, the relationship between measurements of the mean and the variance or
"random error" of each group provides the information needed to determine if the difference
between the two is significant
The standard deviation is the square root of the variance. Like the variance, the standard
deviation measures spread. The variance involves squaring the data numbers. Taking the square
root of the variance gives you a number that is in the same units as the original data. This allows
for an intuitive interpretation of the standard deviation: Usually, depending on the shape of the
distribution about 2/3 of the data numbers are within one standard deviation of the mean.
Correlation Coefficient
I should point out that there are two ways of viewing independent variation. One is that the more
distinct and unrelated the covariation, the greater the independence. Then, a zero correlation
represents complete independence and -1.00 or 1.00 indicates complete dependence.
Independence viewed in this way is called statistical independence. Two variables are then
statistically independent if their correlation is zero.
There is another view of independence, however, called linear independence, which sees
independence or dependence as a matter of presence or absence, not more or less. In this
perspective, two things varying perfectly together are linear dependent. Thus, variables with
correlation of -1.00 or 1.00 are linear dependent. Variables with variation less than perfect are
linear independent.
One-way researchers often express the strength of the relationship between two variables is by
squaring their correlation coefficient. When we perceive two things that covary, what do we see?
When we see one thing vary, we perceive it changing in some regard, as the sun setting, the price
of goods increasing, or the alternation of green and red lights at an intersection. Therefore, when
two things covary there are two possibilities. One is that the change in a thing is concomitant
with the change in another, as the change in a child's age covaries with his height. The older, the
taller. When higher magnitudes on one thing occur along with higher magnitudes on another and
the lower magnitudes on both also co-occur, then the things vary together positively, and we
denote this situation as positive covariation or positive correlation.
The second possibility is that two things vary inversely or oppositely. That is, the higher
magnitudes of one thing go along with the lower magnitudes of the other and vice versa. Then,
we denote this situation as negative covariation or negative correlation. This seems clear enough,
but in order to be more systematic about correlation more definition is needed.
Perceived covariation must be covariation across some cases. A case is a component of variation
in a thing.
Four-fold table and correlation
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The MENTAT HANDBOOK
We can summarize this covariation in terms of a four-fold table. Let us define high as above the
means (averages), and low at or below these means. The numbers that appear in the cells of the
table are the number of circumstances that have the indicated joint magnitudes.
From the table, we can now clearly see the correlation between the two variables.
If the correlation were negative, then most cases would be counted in the lower left and upper
right cells. What if there were about an equal number of cases in all the cells of the fourfold
table? Then, there would be little correlation: the two variables would not covary. In other words,
sometimes high magnitudes on one variable would occur as often with low as with high
magnitudes on the other.
But all this is still imprecise. The four-fold table gives us a way of looking at correlation, but just
considering correlation as covarying high or low magnitudes is quite a loss of information, since
we are not measuring how high or low the figures are. Moreover, if we are at all going to be
precise about a correlation, we should determine some coefficient of correlation--some one
number that in itself expresses the correlation between variables. To be a useful coefficient,
however, this must be more than a number unique to a pair of variables. It must be a number
comparable between pairs of variables. We must be able to compare correlations, so that we can
determine, for example, which variables are more or less correlated, or whether variables change
correlation with change in cases. Finally, we want a correlation that indicates whether the
correlation is positive or negative. In the next chapter we can intuitively and precisely define
such a coefficient.
The Range
Given that the correlation coefficient measures the degree to which two things vary together or
oppositely, how do we interpret it? First, the maximum positive correlation is 1.00. Since the
correlation is the average product of the standard scores for the cases on two variables, and since
the standard deviation of standardized data is 1.00, then if the two standardized variables covary
positively and perfectly, the average of their products across the cases will equal 1.00.
On the other hand, if two things vary oppositely and perfectly, then the correlation will equal
1.00.
We therefore have a measure that tells us at a glance whether two things covary perfectly, or near
perfectly, and whether positively or negatively. If the coefficient is, say, .80 or .90, we know that
the corresponding variables closely vary together in the same direction; if -.80 or -.90, they vary
together in opposite directions.
The Zero
What then is the meaning of zero or near zero correlation? It means simply that two things vary
separately. That is, when the magnitudes of one thing are high; the other's magnitudes are
sometimes high, and sometimes low. It is through such uncorrelated variation--such
independence of things--that we can sharply discriminate between phenomena.
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The MENTAT HANDBOOK
Coefficient of Determination
The coefficient of determination is useful because it gives the proportion of the variance of one
variable that is predictable from the other variable.
Distributions
If the outcome numbers are discreet, meaning that there is a certain number of possible
outcomes, then the distribution is a list of all possible outcomes and each one's probability.
If the outcome numbers are continuous, meaning that the outcome could be any number in either
a finite range or an infinite range, then you can't list all possible outcomes and each one's
probability. What you can do instead is give a mathematical formula that would tell you, for any
given x, what the probability is that the outcome will be less than x. This is the distribution
function. Distributions are often visualized using the density function. On a graph of the density
function, if you pick any two possible outcome values on the x axis, and draw vertical lines at
those values up from the x axis to where they intersect the density function's curve, then you will
have an enclosed area with straight sides, a straight bottom, and a curved top. The size of that
area tells you the probability that the outcome will be between the two x values.
A commonly used distribution is the normal distribution. Its density function is "the bell curve."
This is the density function for a normal distribution with a mean of 0 and a standard deviation of
1. The density function is constructed so that the total area under the curve is 1. (The area under
the curve is unbounded, because the curve goes off forever in both directions without ever quite
touching the x-axis, but even so the area under the curve is finite and equal to 1.)
Algebraic Expressions with Summation Signs
For these expressions, the data items are represented as:
There are N data items.
For our coin with a 0 on one side and a 1 on the other, the data items are x1 = 0 and x2 = 1. N =
2.
Confidence Intervals
What is a confidence interval?
Simply speaking, confidence intervals are a useful way to consider margin of error, a statistic
often used in voter polls to indicate the range within which a value is likely to be correct (e.g.,
30% of the voters favor a particular candidate with a margin of error of + 3.5%). Similarly, in
this report, confidence intervals are used to provide a range that we can be quite confident
contains the success rate for a particular clinic during a particular time.
Why do we need to consider confidence intervals if we already know the exact values?
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The MENTAT HANDBOOK
No success rate or statistic is absolute. Suppose a clinic performed 100 cycles among women
younger than 35 in 1997 and had a success rate of 20% with a confidence interval of 12%-28%.
The 20% success rate tells us that the average chance of success for women younger than 35
treated at this clinic in 1997 was 20%. How likely is it that the clinic could repeat this
performance? For example, if the same clinic performed another 100 cycles under similar
clinical conditions on women with similar characteristics, would the success rate again be 20%?
The confidence interval tells us that the success rate would be likely to fall between 12% and
28%.
Why does the size of the confidence interval vary for different samples?
The size of the confidence interval gives us a realistic sense of how secure we feel about the
success rate. If the clinic had performed only 20 cycles among women younger than 35 instead
of 100 and still had a 20% success rate (4 successes out of 20 cycles), the confidence interval
would be much larger (between 3% and 37%) because the success or failure of each individual
cycle would count for more. For example, if just one more cycle had resulted in a live birth, the
success rate would have been substantially higher-25%, or 5 successes out of 20 cycles.
Likewise, if just one more cycle had not been successful, the success rate would have been
substantially lower-15%, or 3 out of 20 cycles. Compare this scenario to the original example of
the clinic that performed 100 cycles and had a 20% success rate. If just one more cycle had
resulted in a live birth, the success rate would only have changed slightly, from 20% to 21%, and
if one more cycle had not been successful, the success rate would only have fallen to 19%. Thus,
our confidence in a 20% success rate depends on how many cycles were performed.
Why should confidence intervals be considered when success rates from different samples are
being compared?
Confidence intervals should be considered because success rates can be misleading. For
example, if Clinic A performs 20 cycles in a year and 8cycles result in a live birth, its live birth
rate would be 40%. If Clinic B performs 600 cycles and 180 result in a live birth, its live birth
rate would be30%. We might be tempted to say that Clinic A has a better success rate than Clinic
B. However, because Clinic A performed few cycles, its success rate would have a wide 95%
confidence interval of 18.5%-61.5%. On the other hand, because Clinic B performed a large
number of cycles, its success rate would have a relatively narrow confidence interval of
26.2%-33.8%. Thus, Clinic A could have a rate as low as 18.5% and Clinic B could have a rate
as high as 33.8% if each clinic repeated its treatment with similar patients under similar clinical
conditions. Moreover, Clinic B'srate is much more likely to be reliable because the size of its
confidence interval is much smaller than Clinic A's.
Hypothesis Tests
A hypothesis test is a decision rule based on the sample data that leads to rejection or
"acceptance" of H0. Recall that we typically do not say that we accept H0, instead we say that
we do not reject H0.
Steps in a Test of Hypothesis
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The MENTAT HANDBOOK
A test of hypothesis is a procedure designed to determine whether the data provide enough
evidence to support a claim about the population. This claim is called the alternative or research
hypothesis.
Primary version
1. Begin with a research hypothesis.
2. Set up the null hypothesis.
3. Construct the sampling distribution of the particular test statistic to be used on the assumption
that the null hypothesis, Ho, is true.
4. Collect some data.
5. Compare the sample statistic to the sampling distribution.
6. Reject or fail to reject Ho, depending upon the probability, under Ho, of a sample statistic as
extreme as the one we have obtained.
Alternate Version
1. State the alternative hypothesis in words and symbols.
2. State the null hypothesis in words and symbols.
3. State any assumptions need to make the test valid.
4. Give the formula for the test statistic.
5. State alpha
6. Give the rejection region. The rejection region is the set of values of the test statistic that agree
with the alternative hypothesis. If the null hypothesis is true the probability that the test statistic's
value will be in this region is.
7. Calculate the value of the test statistic.
8. Make a decision about the null hypothesis.
9. State your conclusion about the alternative hypothesis.
Coefficient of Determination
A statistic that is widely used to determine how well a regression fits is the coefficient of
determination (or multiple correlation coefficient),. represents the fraction of variability in y that
can be explained by the variability in x. In other words, explains how much of the variability in
the y's can be explained by the fact that they are related to x, i.e., how close the points are to the
line.
The coefficient of determination is ...





The percent of the variation that can be explained by the regression equation.
The explained variation divided by the total variation
The square of r
The percent of variation that is unexplained by the regression equation
The unexplained variation divided by the total variation
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The MENTAT HANDBOOK
Standard Error of the Estimate
The coefficient of non-determination was used in the t-test to see if there was significant linear
correlation. It was the in the numerator of the standard error formula.
The standard error of the estimate is the square root of the coefficient of non-determination
divided by it's degrees of freedom.
Bayesian Inference
The only consistent way for a rational agent with limited information to make inferences about
the World is using Bayes' Rule.
Bayes' Theorem
* Posterior = Prior * Likelihood
* New Belief = Old Belief * Evidence
Bayesian Statistics
Statistics is primarily concerned with the analysis of data, either to assist in the appreciation of
some underlying mechanism, or to reach effective decisions. In both cases, some uncertainty
resides in the situation and the Mentat's tasks are both to reduce this uncertainty and to explain it
clearly. One way of looking at statistics stems from the appreciation that all uncertainty must be
described by probability: that probability is the only sensible language for a logic that deals with
all degrees of uncertainty, and not just with the extremes of truth and falsity. This is called
Bayesian Statistics. Decision-making is embraced by introducing a utility function, itself
probability-based, and then maximizing expected utility. Bayesian statistics is designed to handle
all situations where uncertainty is found. Since some uncertainty is present in most aspects of
life, it is held that Bayesian statistics should be appreciated and used by everyone. It is the logic
of contemporary society. It is 'common sense reduced to calculation.'
Statistics in Econometric modeling
Econometrics also contains inherent statistical limitations. The regression procedures used to
estimate parameters yield unbiased estimates only under certain conditions. These conditions are
known as maintained hypotheses because they are assumptions that must be made in order to use
the statistical technique. The maintained hypotheses can never be verified, even in principle, but
must be taken as a matter of faith. In the most common regression technique, ordinary least
squares, the maintained hypotheses include the unlikely assumptions that the variables are all
measured perfectly, that the model being estimated corresponds perfectly to the real world, and
the random errors in the variables from one time period to another are completely independent.
More sophisticated techniques do not impose such restrictive assumptions, but they always
involve other a priori hypotheses that cannot be validated.
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The MENTAT HANDBOOK
Another problem is that econometrics fails to distinguish between correlations and causal
relationships. Simulation models must portray the causal relationships in a system if they are to
mimic its behavior, especially its behavior in new situations. But the statistical techniques used
to estimate parameters in econometric models don't prove whether a relationship is causal. They
only reveal the degree of past correlation between the variables, and these correlations may
change or shift as the system evolves.
Pattern Matching and Recognition
There is a clear danger that the order introduced might or might not accord with reality, so the
Processor must attempt first to use the categories and labels that others provide.
If you put two things in the same class, they have to be "alike", similar, have resemblance, or
whatever expression you would like to use. It is clearly not possible to decide this without
knowing (or deciding) the purpose of the classification.
All classifications, even the most general are carried out for some more or less explicit "special
purpose" or set of purposes which should influence the choice of classification method and the
results obtained.
A pattern is any arrangement of objects or entities. The term "arrangement" is used here to
indicate that a pattern is by definition non-random and at least potentially describable. All
theories imply some pattern, but theories and patterns are not the same thing. In general, a theory
postulates structural relationships between key constructs. The theory can be used as the basis for
generating patterns of predictions.
Goodness of Fit to a Pattern
Pattern matching always involves an attempt to link two patterns where one is a theoretical
pattern and the other is an observed or operational one. The top part of the figure shows the
realm of theory. The theory might originate from a formal tradition of theorizing, might be the
ideas or "hunches" of the investigator, or might arise from some combination of these. The
conceptualization task involves the translation of these ideas into a specifiable theoretical pattern
indicated by the top shape in the figure. The bottom part of the figure indicates the realm of
observation. This is broadly meant to include direct observation in the form of impressions, field
notes, and the like, as well as more formal objective measures. The collection or organization of
relevant to the theoretical pattern operationalizations is termed the observational pattern and is
indicated by the lower shape in the figure. The inferential task involves the attempt to relate, link
or match these two patterns as indicated by the double arrow in the center of the figure. To the
extent that the patterns match, one can conclude that the theory and any other theories that might
predict the same observed pattern receive support.
With more complex theoretical patterns it is usually more difficult to construe sensible
alternative patterns that would also predict the same result. To the extent that theoretical and
observed patterns do not match, the theory may be incorrect or poorly formulated, the
observations may be inappropriate or inaccurate, or some combination of both states may exist.
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All research employs pattern-matching principles, although this is seldom done consciously. In
the traditional two-group experimental context, for instance, the typical theoretical outcome
pattern is the hypothesis that there will be a significant difference between treated and untreated
groups. The observed outcome pattern might consist of the averages for the two groups on one or
more measures. The pattern match is accomplished by a test of significance such as the t-test or
ANOVA. In survey research, pattern matching forms the basis of generalizations across different
concepts or population subgroups. In qualitative research pattern matching lies at the heart of any
attempt to conduct thematic analyses.
While current research methods can be described in pattern matching terms, the idea of pattern
matching implies more, and suggests how one might improve on these current methods.
Specifically, pattern matching implies that more complex patterns, if matched, yield greater
validity for the theory. Pattern matching does not differ fundamentally from traditional
hypothesis testing and model building approaches. A theoretical pattern is a hypothesis about
what is expected in the data. The observed pattern consists of the data that are used to examine
the theoretical model. The major differences between pattern matching and more traditional
hypothesis testing approaches are that pattern matching encourages the use of more complex or
detailed hypotheses and treats the observations from a multivariate rather than a univariate
perspective.
By extraction the sample pattern's algebraic feature, the human face image's eigenvalues, the
neural network classifier is trained for recognition.
There are several disadvantages of the pattern matching approach to construct validity. The most
obvious is that pattern matching requires that you specify your theory of the constructs rather
precisely.
Nearest Neighbor
In many problems data cannot be separated by lines, planes or hyperplanes and then some nonlinear methods must be used. The simplest such algorithm is the nearest neighbor classifier. You
simply take your unknown and compute the distance from it to all the other patterns you have the
answer for. The answer you guess for the unknown pattern is the class of the closest pattern.
In the nearest neighbor algorithm you have to keep a large inventory of patterns and their
classifications so searching through this inventory for the closest match may take quite a long
time.
Straight lines
Every straight line can be represented by an equation: y = mx + b. The coordinates of every point
on the line will solve the equation if you substitute them in the equation for x and y.
The slope m of this line - its steepness, or slant - can be calculated like this: m = change in yvalue/change in x-value
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The equation of any straight line, called a linear equation, can be written as: y = mx + b, where m
is the slope of the line and b is the y-intercept.
The y-intercept of this line is the value of y at the point where the line crosses the y-axis.
Regressions
Linear regression is described in every statistics book, and is performed by every statistics
program. The purpose of linear regression is to find the line that comes closest to your data.
More precisely, the linear regression program finds values for the slope and intercept that define
the line that minimizes the sum of the square of the vertical distances between the points and the
line. The equations used to do this can be derived with no more than high-school algebra (shown
in many statistics books). Put the data in, and the answers come out. There is no chance for
ambiguity. You could even do the calculations by hand, if you wanted to. Many relationships in
biology (and other fields of science) do not follow a straight line. To analyze such data, you two
choices:
1. Do mathematical transformations to force the data into a linear relationship. Then use linear
regression. Although these techniques are commonly used, you should avoid them. They are less
accurate than nonlinear regression, and are not any easier.
2. Use nonlinear regression Nonlinear regression is a general technique to fit a curve through
your data. It fits data to any equation that defines Y as a function of X and one or more
parameters. It finds the values of those parameters that generate the curve that comes closest to
the data (minimizes the sum of the squares of the vertical distances between data points and
curve). Except for a few special cases, it is not possible to directly derive an equation to compute
the best-fit values from the data. Instead nonlinear regression requires a computationally
intensive, iterative approach. You can't really follow the mathematics of nonlinear regression
unless you are familiar with matrix algebra. But you can use nonlinear regression without
understanding exactly how it works.
Some scientists and students are afraid to approach nonlinear regression, because it seems so
complicated. From a scientist's point of view, however, nonlinear regression is no more
complicated than linear regression. You put in data, choose a few options, and interpret the
results. The choice of using linear or nonlinear regression should be determined by the scientific
problem you are trying to solve.
The Regression Formula
First of all, an ANOVA analysis assumes that there is a cause- effect relationship. The statistical
analysis upon which the ANOVA is used, describes the relationship between cause and effect
through statistics:
Y = B0 + B1x1 + e
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Where:
Y = the effect
B0 = the intercept
B1 = the coefficient of the variable
x1 = the variable
e = random error
The formula above describes a "mean" or an average effect based on either a sample from a
population or an entire population. If the statistical regression is representative, it has what is
called a normal distribution. That is not every piece of data can be measured at the mean. Rather,
the data for the population is contained within three standard errors from the mean either to the
positive or negative side.
An ANOVA calculation is derived from a statistical calculation for significance based on a TStatistic calculated from the regression formula based on the least squares fit. A relatively higher
mean (Y) compared to the errors (e) indicates a more "precise" system or group from which the
data was derived. From the relative calculations of averages and errors for each group, a more
precise determination on the significance of the difference between the two groups can be
assessed.
Combinatorial Pattern Matching
Combinatorial Pattern Matching addresses issues of searching and matching strings and more
complicated patterns such as trees, regular expressions, graphs, point sets, and arrays. The goal is
to derive non-trivial combinatorial properties for such structures and then to exploit these
properties in order to achieve improved performance for the corresponding computational
problem.
Information Visualization and Visual Data Mining
Information visualization and visual data mining is how a Mentat browses large datasets and find
patterns, correlations, clusters, gaps, and outliers that reveal opportunities for action. Human
perceptual abilities are remarkable at spotting orderly and unusual patterns, but current untrained
Humans have not made good use of these abilities. A Mentat who has data can benefit from a
visual presentation. The patterns they see will often confirm their hard won understandings, but
more than likely they will discover anomalies in their data, surprising outliers, and interesting
clusters. Furthermore, visual patterns are more likely to be remembered and therefore facilitate
comparison across databases and recognition of changes over time.
Classification Trees
Classification tree analysis is one of the main techniques used in so-called Data Mining.
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The goal of classification trees is to predict or explain responses on a categorical dependent
variable, and as such, the available techniques have much in common with the techniques used in
the more traditional methods of Discriminant Analysis, Cluster Analysis, Nonparametric
Statistics, and Nonlinear Estimation. The flexibility of classification trees make them a very
attractive analysis option, but this is not to say that their use is recommended to the exclusion of
more traditional methods. Indeed, when the typically more stringent theoretical and distributional
assumptions of more traditional methods are met, the traditional methods may be preferable. But
as an exploratory technique, or as a technique of last resort when traditional methods fail,
classification trees are, in the opinion of many researchers, unsurpassed.
Classification trees readily lend themselves to being displayed graphically, helping to make them
easier to interpret than they would be if only a strict numerical interpretation were possible.
Classification trees can be and sometimes are quite complex. However, graphical procedures can
be developed to help simplify interpretation even for complex trees. If one's interest is mainly in
the conditions that produce a particular class of response, perhaps a High response, a 3D Contour
Plot can be produced to identify which terminal node of the classification tree classifies most of
the cases with High responses.
Amenability to graphical display and ease of interpretation are perhaps partly responsible for the
popularity of classification trees in applied fields, but two features that characterize classification
trees more generally are their hierarchical nature and their flexibility.
Hierarchical Nature of Classification Trees
The hierarchical nature of classification trees is illustrated by a comparison to the decisionmaking procedure employed in Discriminant Analysis. A traditional linear discriminant analysis
would produce a set of coefficients defining the single linear combination of the variables that
best differentiates. A score for each patient on the linear discriminant function would be
computed as a composite of each patient's measurements on the three-predictor variables,
weighted by the respective discriminant function coefficients. The predicted classification of
each item within the appropriate category would be made by simultaneously considering each
item's scores on the predictor variables.
In comparison, the decision tree would have the following hierarchical form, where p, a, and t
would be -91, -62.5, and 0, respectively, "If p + P is less than or equal to zero, the patient is low
risk, else if a + A is less than or equal to zero, the patient is low risk, else if t + T is less than or
equal to zero, the patient is low risk, else the patient is high risk." Superficially, the Discriminant
Analysis and classification tree decision processes might appear similar, because both involve
coefficients and decision equations. But the difference of the simultaneous decisions of
Discriminant Analysis from the hierarchical decisions of classification trees cannot be
emphasized enough.
The distinction between the two approaches can perhaps be made most clear by considering how
each analysis would be performed in Regression. Because risk is a dichotomous dependent
variable, the Discriminant Analysis predictions could be reproduced by a simultaneous multiple
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regression of risk on the three-predictor variables for all patients. The classification tree
predictions could only be reproduced by three separate simple regression analyses, where risk is
first regressed on P for all patients, then risk is regressed on A for patients not classified as low
risk in the first regression, and finally, risk is regressed on T for patients not classified as low risk
in the second regression. This clearly illustrates the simultaneous nature of Discriminant
Analysis decisions as compared to the recursive, hierarchical nature of classification trees
decisions, a characteristic of classification trees that has far-reaching implications.
Flexibility of Classification Trees
Another distinctive characteristic of classification trees is their flexibility. The ability of
classification trees to examine the effects of the predictor variables one at a time, rather than just
all at once, has already been described, but there are a number of other ways in which
classification trees are more flexible than traditional analyses. The ability of classification trees t
perform univariate splits, examining the effects of predictors one at a time, has implications for
the variety of types of predictors that can be analyzed. Even if one variable was measured as a
three-level categorical predictor (perhaps coded as 0 = not present; 1 = present; 3 = unknown or
unsure), without any underlying continuous dimension represented by the values assigned to its
levels, univariate splits on the predictor variables could still be easily performed. Additional
decisions would be added to the decision tree to exploit any additional information on risk
provided by the additional category. To summarize, classification trees can be computed for
categorical predictors, continuous predictors, or any mix of the two types of predictors when
univariate splits are used.
Traditional linear discriminant analysis requires that the predictor variables be measured on at
least an interval scale. For classification trees based on univariate splits for ordinal scale
predictor variables, it is interesting that any monotonic transformation of the predictor variables
(i.e., any transformation that preserves the order of values on the variable) will produce splits
yielding the same predicted classes for the cases or objects. Therefore, classification trees based
on univariate splits can be computed without concern for whether a unit change on a continuous
predictor represents a unit change on the dimension underlying the values on the predictor
variable; it need only be assumed that predictors are measured on at least an ordinal scale. In
short, assumptions regarding the level of measurement of predictor variables are less stringent.
Classification trees are not limited to univariate splits on the predictor variables. When
continuous predictors are indeed measured on at least an interval scale, linear combination splits,
similar to the splits for linear discriminant analysis, can be computed for classification trees.
However, the linear combination splits computed for Classification Trees do differ in important
ways from the linear combination splits computed for Discriminant Analysis. In linear
discriminant analysis the number of linear discriminant functions that can be extracted is the
lesser of the number of predictor variables or the number of classes on the dependent variable
minus one. The recursive approach implemented for Classification Trees module does not face
this limitation. For example, dozens of recursive, linear combination splits potentially could be
performed when there are dozens of predictor variables but only two classes on the dependent
variable. This compares with the single linear combination split that could be performed using
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traditional, non-recursive Linear discriminant analysis, which could leave a substantial amount
of the information in the predictor variables unused.
The approach implemented for Classification Trees for linear combination splits can also be used
as the analysis method for constructing classification trees using univariate splits. Actually, a
univariate split is just a special case of a linear combination split. Imagine a linear combination
split in which the coefficients for creating the weighted composite were zero for all predictor
variables except one. Since scores on the weighted composite would depend only on the scores
on the one-predictor variable with the nonzero coefficient, the resulting split would be a
univariate split.
The Power and Pitfalls of Classification Trees
The advantages of classification trees over traditional methods such as linear discriminant
analysis, at least in some applications, can be illustrated using a simple, fictitious data set. To
keep the presentation even-handed, other situations in which linear discriminant analysis would
outperform classification trees are illustrated using a second data set.
The Tree graph presents all this information in a simple, straightforward way, and probably
allows one to digest the information in much less time than it takes to read the two preceding
paragraphs.
When univariate splits are performed, the predictor variables can be ranked on a 0 - 100 scale in
terms of their potential importance in accounting for responses on the dependent variable.
A classification tree Class using the Discriminant-based univariate split selection method option
produces similar results.
A categorized scatterplot clearly shows why linear discriminant analysis fails so miserably at
predicting Class, and why the classification tree succeeds so well.
The plot clearly shows that there is no strong linear relationship of the two variables with Class,
or of any possible linear combination of them with Class. Class is not functionally related to
longitude or latitude, at least in the linear sense. The LDF (Linear Discriminant Function) Split
shown on the graph is almost a "shot in the dark" at trying to separate predicted Trop hurricanes
(above the split line) from predicted Baro hurricanes (below the split line). The CART univariate
splits, because they are not restricted to a single linear combination of longitude and latitude
scores, find the "cut points" on the Longitude dimension that allow the best possible (in this case,
perfect) classification of hurricane Class.
One could methodically describe the splits in this classification tree, exactly as was done in the
previous example, but because there are so many splits, the interpretation would necessarily be
more complex than the simple interpretation provided by the single discriminant function from
the linear discrimination analysis.
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However, recall that in describing the flexibility of Classification Trees, it was noted that an
option exists for Discriminant-based linear combination splits for ordered predictors using
algorithms.
The moral of this story of the power and pitfalls of classification trees is that classification trees
are only as good as the choice of analysis option used to produce them. For finding models that
predict well, there is no substitute for a thorough understanding of the nature of the relationships
between the predictor and dependent variables.
We have seen that classification trees analysis can be characterized as a hierarchical, highly
flexible set of techniques for predicting membership of cases or objects in the classes of a
categorical dependent variable from their measurements on one or more predictor variables.
Computational Methods
The process of computing classification trees can be characterized as involving four basic steps:
1. Specifying the criteria for predictive accuracy,
2. Selecting splits,
3. Determining when to stop splitting, and
4. Choosing the "right-sized" tree.
Specifying the Criteria for Predictive Accuracy
The goal of classification tree analysis, simply stated, is to obtain the most accurate prediction
possible. Unfortunately, an operational definition of accurate prediction is hard to come by. To
solve the problem of defining predictive accuracy, the problem is "stood on its head," and the
most accurate prediction is operationally defined as the prediction with the minimum costs. The
term costs need not seem mystifying. In many typical applications, costs simply correspond to
the proportion of misclassified cases. The notion of costs was developed as a way to generalize,
to a broader range of prediction situations, the idea that the best prediction has the lowest
misclassification rate.
The need for minimizing costs, rather than just the proportion of misclassified cases, arises when
some predictions that fail are more catastrophic than others, or when some predictions that fail
occur more frequently than others. The costs to a gambler of losing a single bet (or prediction) on
which the gambler's whole fortune is at stake are greater than the costs of losing many bets (or
predictions) on which a tiny part of the gambler's fortune is at stake. Conversely, the costs of
losing many small bets can be larger than the costs of losing just a few bigger bets. One should
spend proportionately more effort in minimizing losses on bets where losing (making errors in
prediction) costs you more.
Priors
Minimizing costs, however, does correspond to minimizing the proportion of misclassified cases
when Priors are taken to be proportional to the class sizes and when Misclassification costs are
taken to be equal for every class. We will address Priors first. Priors, or, a priori probabilities,
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specify how likely it is, without using any prior knowledge of the values for the predictor
variables in the model, that a case or object will fall into one of the classes. For example, in an
educational study of high school drop-outs, it may happen that, overall, there are fewer drop-outs
than students who stay in school (i.e., there are different base rates); thus, the a priori probability
that a student drops out is lower than that a student remains in school.
The a priori probabilities used in minimizing costs can greatly affect the classification of cases or
objects. If differential base rates are not of interest for the study, or if one knows that there are
about an equal number of cases in each class, then one would use equal priors. If the differential
base rates are reflected in the class sizes (as they would be, if the sample is a probability sample)
then one would use priors estimated by the class proportions of the sample. Finally, if you have
specific knowledge about the base rates then one would specify priors in accordance with that
knowledge. Minimizing costs corresponds to minimizing the overall proportion of misclassified
cases when Priors are taken to be proportional to the class sizes (and Misclassification costs are
taken to be equal for every class), because prediction should be better in larger classes to produce
an overall lower misclassification rate.
Misclassification costs
Sometimes more accurate classification is desired for some classes than others for reasons
unrelated to relative class sizes. Regardless of their relative frequency, carriers of a disease who
are contagious to others might need to be more accurately predicted than carriers of the disease
who are not contagious to others. But to reiterate, minimizing costs corresponds to minimizing
the proportion of misclassified cases when Priors are taken to be proportional to the class sizes
and when Misclassification costs are taken to be equal for every class.
Case weights
A little less conceptually, the use of case weights on a weighting variable as case multipliers for
aggregated data sets is also related to the issue of minimizing costs. Interestingly, as an
alternative to using case weights for aggregated data sets, one could specify appropriate priors
and/or misclassification costs and produce the same results while avoiding the additional
processing required to analyze multiple cases with the same values for all variables.
The relationships between priors, misclassification costs, and case weights become quite
complex in all but the simplest situations. In analyses where minimizing costs corresponds to
minimizing the misclassification rate, however, these issues need not cause any concern. Priors,
misclassification costs, and case weights are brought up here, however, to illustrate the wide
variety of prediction situations that can be handled using the concept of minimizing costs, as
compared to the rather limited (but probably typical) prediction situations that can be handled
using the narrower (but simpler) idea of minimizing misclassification rates. Furthermore,
minimizing costs is an underlying goal of classification tree analysis, and is explicitly addressed
in the fourth and final basic step in classification tree analysis, where in trying to select the
"right-sized" tree, one chooses the tree with the minimum estimated costs. Depending on the type
of prediction problem you are trying to solve, understanding the idea of reduction of estimated
costs may be important for understanding the results of the analysis.
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Selecting Splits
The second basic step in classification tree analysis is to select the splits on the predictor
variables that are used to predict membership in the classes of the dependent variables for the
cases or objects in the analysis. Not surprisingly, given the hierarchical nature of classification
trees, these splits are selected one at time, starting with the split at the root node, and continuing
with splits of resulting child nodes until splitting stops, and the child nodes that have not been
split become terminal nodes. Three Split selection methods are discussed here.
Discriminant-based univariate splits
The first step in split selection when the Discriminant-based univariate splits option is chosen is
to determine the best terminal node to split in the current tree, and which predictor variable to
use to perform the split. For each terminal node, p-levels are computed for tests of the
significance of the relationship of class membership with the levels of each predictor variable.
The next step is to determine the split.
Discriminant-based linear combination splits. The second split selection method is the
Discriminant-based linear combination split option for ordered predictor variables (however, the
predictors are assumed to be measured on at least interval scales). Surprisingly, this method
works by treating the continuous predictors from which linear combinations are formed in a
manner that is similar to the way categorical predictors are treated in the previous method.
Singular value decomposition methods are used to transform the continuous predictors into a
new set of non-redundant predictors. The procedures for creating "superclasses" and finding the
split closest to a "superclass" mean are then applied, and the results are "mapped back" onto the
original continuous predictors and represented as a univariate split on a linear combination of
predictor variables.
The third split-selection method is an exhaustive search for univariate splits method for
categorical or ordered predictor variables. With this method, all possible splits for each predictor
variable at each node are examined to find the split producing the largest improvement in
goodness of fit (or equivalently, the largest reduction in lack of fit). What determines the domain
of possible splits at a node? For categorical predictor variables with k levels present at a node,
there are 2(k-1) - 1 possible contrasts between two sets of levels of the predictor. For ordered
predictors with k distinct levels present at a node, there are k -1 midpoints between distinct
levels. Thus it can be seen that the number of possible splits that must be examined can become
very large when there are large numbers of predictors with many levels that must be examined at
many nodes.
How is improvement in goodness of fit determined? Three choices of Goodness of fit measures
are discussed here. One measure of noded dependency is a measure which reaches a value of
zero when only one class is present at a node (with priors estimated from class sizes and equal
misclassification costs, this measure is computed as the sum of products of all pairs of class
proportions for classes present at the node; it reaches its maximum value when close
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(The os at the node are equal). The two other indices are the Chi-square measure and the Gsquare measure, which is similar to the maximum-likelihood Chi-square used in structural
equation modeling. An exhaustive search for univariate splits method works by searching for the
split that maximizes the reduction in the error to as the selected goodness of fit measure. When
the fit is perfect, classification is perfect.
Determining When to Stop Splitting
The third step in classification tree analysis is to determine when to stop splitting. One
characteristic of classification trees is that if no limit is placed on the number of sp must bet are
performed, eventually "pure" classification will be achieved, with each terminal node containing
only one class of cases or objects. However, "pure" classification is usually unrealistic.
Likewise, if the observed classifications on the dependent variable or the levels on the predicted
variable in a classification tree analysis are measured with error or contain "noise," it is
unrealistic to continue to sort until every terminal node is "pure." Two options for controlling
when splitting stops will be discussed here. These two options are linked to the choice of the
Stopping rule specified for the analysis.
Minimum n. One option for controlling when splitting stops is to allow splitting to continue until
all terminal nodes are pure or contain no more than a specified minimum number of cases or
objects. The desired minimum number of cases can be specified as the Minimum n, and splitting
will stop when all terminal nodes containing more than one class have no more than the specified
number of cases or objects.
Fraction of objects. Another option for controlling when splitting stops is to allow splitting to
continue until all terminal nodes are pure or contain no more cases than a specified minimum
fraction of the sizes of one or more classes. The desired minimum fraction can be specified as the
Fraction of objects and, if the priors used in the analysis are equal and class sizes are equal,
splitting will stop when all terminal nodes containing more than one class have no more cases
than the specified fraction of the class sizes for one or more classes. If the priors used in the
analysis are not equal, splitting will stop when all terminal nodes containing more than one class
have no more cases than the specified fraction for one or more classes.
Selecting the "Right-Sized" Tree
Some generalizations can be offered about what constitutes the "right-sized" classification tree. It
should be sufficiently complex to account for the known facts, but at the same time it should be
as simple as possible. It should exploit information that increases predictive accuracy and ignore
information that does not. It should, if possible, lead to greater understanding of the phenomena
that it describes. Of course, these same characteristics apply to any scientific theory, so we must
try to be more specific about what constitutes the "right-sized" classification tree. One strategy is
to grow the tree to just the right size, where the right size is determined by the user from
knowledge from previous research, diagnostic information from previous analyses, or even
intuition. The other strategy is to use a set of well-documented, structured procedures for
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selecting the "right-sized" tree. These procedures are not foolproof but at least they take
subjective judgment out of the process of selecting the "right-sized" tree.
Direct stopping. We will begin by describing the first strategy, in which the researcher specifies
the size to grow the classification tree. This strategy is followed by using direct stopping as the
Stopping rule for the analysis, and by specifying the Fraction of objects which allows the tree to
grow to the desired size. There are several options for obtaining diagnostic information to
determine the reasonableness of the choice of size for the tree. Three options for performing
cross-validation of the selected classification tree are discussed below.
Test sample cross-validation. The first, and most preferred type of cross-validation is test sample
cross-validation. In this type of cross-validation, the classification tree is computed from the
learning sample, and its predictive accuracy is tested by applying it to predict class membership
in the test sample. If the costs for the test sample exceed the costs for the learning sample
(remember, costs equal the proportion of misclassified cases when priors are estimated and
misclassification costs are equal), this indicates poor cross-validation and that a different sized
tree might cross-validate better. The test and learning samples can be formed by collecting two
independent data sets, or if a large learning sample is available, by reserving a randomly selected
proportion of the cases, say a third or a half, for use as the test sample.
V-fold cross-validation. This type of cross-validation is useful when no test sample is available
and the learning sample is too small to have the test sample taken from it. A specified V value
for V-fold cross-validation determines the number of random subsamples, as equal in size as
possible, that are formed from the learning sample. The classification tree of the specified size is
computed V times, each time leaving out one of the subsamples froe could mputations, and using
that subsample as a test sample for cross-validation, so that each subsample is used V - 1 times in
the learning sample and just once as the test sample. The CV costs computed for each of the V
test samples are then averaged to give the V-fold estimate of the CV costs.
Global cross-validation. In global cross-validation, the entire analysis is replicated a specified
number of times holding out a fraction of the learning sample equal to 1 over the specified
number of times, and using each hold-out sample in turn as a test sample to cross-validate the
selected classification tree. This type of cross-validation is probably no more useful than V-fold
cross-validation when direct stopping is used, but can be quite useful as a method validation
procedure when automatic tree selection techniques are used. This brings us to the second of the
two strategies that can used to select the "right-sized" tree called minimal cost-complexity crossvalidation pruning.
Minimal cost-complexity cross-validation pruning. Two methods of pruning can be used
depending on the Stopping Rule you choose to use. Minimal cost-complexity cross-validation
pruning is performed when you decide to Prune on misclassification error as a Stopping rule, and
minimal deviance-complexity cross-validation pruning is performed when you choose to Prune
on deviance as a Stopping rule. The only difference in the two options is the measure of
prediction error that is used. Prune on misclassification error uses the costs that equal the
misclassification rate when priors are estimated and misclassification costs are equal. Prune on
deviance uses a measure, based on maximum-likelihood principles. We will focus on cost-
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complexity cross-validation pruning since deviance-complexity pruning merely involves a
different measure of prediction error.
The costs needed to perform cost-complexity pruning are computed as the tree is being grown,
starting with the split at the root node up to its maximum size, as determined by the specified
Minimum n. The learning sample costs are computed as each split is added to the tree, so that a
sequence of generally decreasing costs reflecting better classification are obtained corresponding
to the number of splits in the tree. The learning sample costs are called resubstitution costs to
distinguish them from CV costs, because V-fold cross-validation is also performed as each split
is added to the tree. Use the estimated CV costs from V-fold cross-validation as the costs for the
root node. Note that tree size can be taken to be the number of terminal nodes, because for binary
trees the tree size starts at one (the root node) and increases by one with each added split. Now,
define a parameter called the complexity parameter whose initial value is zero, and for every tree
(including the first, containing only the root node), compute the value for a function defined as
the costs for the tree plus the complexity parameter times the tree size. Increase the complexity
parameter continuously until the value of the function for the largest tree exceeds the value of the
function for a smaller-sized tree. Take the smaller-sized tree to be the new largest tree, continue
increasing the complexity parameter continuously until the value of the function for the largest
tree exceeds the value of the function for a smaller-sized tree, and continue the process until the
root node is the largest tree.
The sequence of largest trees obtained by this algorithm have a number of interesting properties.
They are nested, because successively pruned trees contain all the nodes of the next smaller tree
in the sequence. Initially, many nodes are often pruned going from one tree to the next smaller
tree in the sequence, but fewer nodes tend to be pruned as the root node is approached. The
sequence of largest trees is also optimally pruned, because for every size of tree in the sequence,
there is no other tree of the same size with lower costs. Proofs and/or explanations of these
properties can be found.
Tree selection after pruning. We now select the "right-sized" tree from the sequence of optimally
pruned trees. A natural criterion is the CV costs. While there is nothing wrong with choosing the
tree with the minimum CV costs as the "right-sized" tree, oftentimes there will be several trees
with CV costs close to the minimum. One should choose as the "right-sized" tree the smallestsized (least complex) tree whose CV costs do not differ appreciably from the minimum CV
costs. They proposed a "1 SE rule" for making this selection, i.e., choose as the "right-sized" tree
the smallest-sized tree whose CV costs do not exceed the minimum CV costs plus 1 times the
Standard error of the CV costs for the minimum CV costs tree.
One distinct advantage of the "automatic" tree selection procedure is that it helps to avoid
"overfitting" and "underfitting" of the data. The graph below shows a typical plot of the
Resubstitution costs and CV costs for the sequence of successively pruned trees.
The Resubstitution costs (e.g., the misclassification rate in the learning sample) rather
consistently decrease as tree size increases. The CV costs, on the other hand, approach the
minimum quickly as tree size initially increases, but actually start to rise as tree size becomes
very large. Note that the selected "right-sized" tree is close to the inflection point in the curve,
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that is, close to the point where the initial sharp drop in CV costs with increased tree size starts to
level out. The "automatic" tree selection procedure is designed to select the simplest (smallest)
tree with close to minimum CV costs, and thereby avoid the loss in predictive accuracy produced
by "underfitting" or "overfitting" the data.
As has been seen, minimal cost-complexity cross-validation pruning and subsequent "rightsized" tree selection is a truly "automatic" process. The algorithms make all the decisions leading
to selection of the "right-sized" tree, except for, perhaps, specification of a value for the SE rule.
One issue that arises with the use of such "automatic" procedures is how well the results
replicate, where replication might involve the selection of trees of quite different sizes across
replications, given the "automatic" selection process that is used. This is where global crossvalidation can be very useful. As explained previously, in global cross-validation, the entire
analysis is replicated a specified number of times holding out a fraction of the cases to use as a
test sample to cross-validate the selected classification tree. If the average of the costs for the test
samples, called the global CV costs, exceeds the CV costs for the selected tree, or if the standard
error of the global CV costs exceeds the standard error of the CV costs for the selected tree, this
indicates that the "automatic" tree selection procedure is allowing too much variability in tree
selection rather than consistently selecting a tree with minimum estimated costs.
Classification trees and traditional methods. As can be seen in the methods used in computing
classification trees, in a number of respects classification trees are decidedly different from
traditional statistical methods for predicting class membership on a categorical dependent
variable. They employ a hierarchy of predictions, with many predictions sometimes being
applied to particular cases, to sort the cases into predicted classes. Traditional methods use
simultaneous techniques to make one and only one class membership prediction for each and
every case. In other respects, such as having as its goal accurate prediction, classification tree
analysis is indistinguishable from traditional methods. Time will tell if classification tree analysis
has enough to commend itself to become as accepted as the traditional methods.
Clustering
'We define the organization as the grouping together of items which are then handled as a unit
and lose, to that extent, their individual identities. In other words, classification into a
classification slot, to all intents and purposes identifies it with that slot. Thereafter, it and other
items in the slot are treated as identical until they are examined individually. It would appear,
therefore, that things are grouped because they are in some sense related to each other; but more
basically, they are grouped because they are likely to be wanted together, and logical relationship
is the means of measuring this likelihood.' In the main, people have achieved the 'logical
organization' in two different ways. Firstly, through direct classification of components, and
secondly via the intermediate calculation of a measure of closeness between items. This
approach has proved theoretically to be intractable so that any experimental test results cannot be
considered to be reliable.
Measures of Association
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Some classification methods are based on a binary relationship between objects. On the basis of
this relationship a classification method can construct a system of clusters. The relationship is
described variously as 'similarity', 'association' and 'dissimilarity'. Ignoring dissimilarity for the
moment as it will be defined mathematically later, the other two terms mean much the same
except that 'association' will be reserved for the similarity between objects characterized by
discrete-state attributes. The measure of similarity is designed to quantify the likeness between
objects so that if one assumes it is possible to group objects in such a way that an object in a
group is more like the other members of the group than it is like any object outside the group,
then a cluster method enables such a group structure to be discovered.
Informally speaking, a measure of association increases as the number or proportion of shared
attribute states increases. Numerous coefficients of association have been described in the
literature. Several authors have pointed out that the difference in retrieval performance achieved
by different measures of association is insignificant, providing that these are appropriately
normalized. Intuitively, one would expect this since most measures incorporate the same
information. Many are monotone with respect to each other. It follows that a cluster method
depending only on the rank ordering of the association values would given identical clusterings
for all these measures.
There are five commonly used measures of association in information retrieval. Since in
information retrieval documents and requests are most commonly represented by term or
keyword lists, I shall simplify matters by assuming that an object is represented by a set of
keywords and that the counting measure gives the size of the set. We can easily generalize to the
case where the keywords have been weighted, by simply choosing an appropriate measure.
The distinction between overlapping and exclusive is important both from a theoretical and
practical point of view. Many classification methods can be viewed as data-simplification
methods. In the process of classification information is discarded so that the members of one
class are indistinguishable. It is in an attempt to minimize the amount of information thrown
away, or to put it differently, to have a classification that is in some sense 'closest' to the original
data, that overlapping classes are allowed. Unfortunately this plays havoc with the efficiency of
implementation for a particular application. A compromise can be adopted in which the
classification methods generates overlapping classes in the first instance and is finally 'tidied up'
to give exclusive classes.
Clump method
A further class of cluster methods based on measurement of similarity is the class of so-called
'clump' methods. They proceed by seeking sets which satisfy certain cohesion and isolation
conditions defined in terms of the similarity measure. The computational difficulties of this
approach have largely caused it to be abandoned.
Method to Cluster Objects
Most of these algorithms aim at reducing the number of passes that have to be made of the file of
object descriptions. There are a small number of clustering algorithms that only require one pass
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of the file of object descriptions. Hence the name 'Single-Pass Algorithm' for some of them.
Basically they operate as follows:
(1) The object descriptions are processed serially;
(2) The first object becomes the cluster representative of the first cluster;
(3) Each subsequent object is matched against all cluster representatives
existing at its processing time
(4) A given object is assigned to one cluster (or more if overlap is allowed)
according to some condition on the matching function;
(5) When an object is assigned to a cluster the representative for that cluster
is recomputed;
(6) If an object fails a certain test it becomes the cluster representative of a
new cluster.
Once again the final classification is dependent on input parameters that can only be determined
empirically (and which are likely to be different for different sets of objects) and must be
specified in advance.
Hypothesist
Hypothesists are trained to extrapolate from information to alternative explanations of the causes
or the effects of that information.
Mentats of Hypothesist rank and higher are barred from official Cheops competition.
Root Causes
Root Cause Analysis
All of the disciplines within all organizations routinely seek to solve their problems, to resolve
the day-to-day obstacles to their goals, as well as the bigger, general problems that develop to
threaten the success of their operations. All of those who are a part of an organization are
problem solvers . . . and root cause analysts, although many of us may prefer to think of our
problem solving process as something less fancy than "root cause analysis". But, as we come to
our problems in an effort to control and prevent interruptions, obstacles, errors, and counterquality occurrences, we none-the-less are all looking for the same things: root causes of
problems that when removed prevent the problem. So, whether our work is Quality, Engineering,
Safety, Production, Maintenance, or just about any other function in the organization, we should
become comfortable with the concept of root cause analysis, or whatever we want to call the task
of finding the root causes and best prevention solutions to our operations problems.
First let's clarify what it is we are talking about when we say "prevention solutions", or rather
what we are not talking about. Fixing things, cleaning up, removing, reworking, redesigning,
modifying, and fortifying, are not prevention and control steps. They instead are correction steps.
These actions may or may not be a result of prevention actions, but they in themselves are not
prevention steps. Prevention has to do with WHY the design was inadequate, WHY the machine
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needs repair, WHY cleanup is necessary. This is not to say that these correction-step responses
are not important to the operation. Certainly we want to discover immediately when things need
early repair. Root cause analysis should uncover such opportunities to remedy, but clearly, as our
primary goal for analysis, we want to design out of our operation the need for avoidable repair,
rework, clean up, and expensive redesign. We are trying to find something that someone can do
to keep the problem from ever happening again. Obviously the act of cleaning up the mess every
time the problem occurs is not prevention. We must instead design prevention and control into
how we do things. That is what meaningful root cause analysis is all about.
Before we can prevent anything within our organization, we must have four things:
1. We must have a way to identify, record, and compare the causes producing the problem that
we seek to correct and prevent.
Most of us, if we have experience at our jobs, will be able to spot something immediately that we
can do that we think might solve the problem. However, in most operations we will find that if
the problem solving is done only through the eyes of experience, the resulting solutions tend to
be one-dimensional. That is, a maintenance man sees something he can fix to get the machine up
and running again. The Engineer sees as a solution to the same problem a way to change the
machine design to avoid the problem. The Production supervisor sees a way to change the
procedure to avoid the problem. The Operations Manager may see an opportunity to farm the job
out to a vendor as the best solution to that same problem. While all of these responses may be
valid, the goal of meaningful root cause analysis is to accurately identify all of the causes, and to
record them in a way that provides decision support for the organization. For this reason the root
cause analysis methodology must not allow the analyst's personal preference, agendas, and bias
to control the investigation. We want our decision-makers to have visibility of all of the available
options, as well as a means to validate, compare and evaluate them before allocating resources of
the organization. This is an important difference from other root cause analysis systems that
makes the REASON concept so successful in producing tangible improvements in operations.
REASON does not allow personal bias or agendas to color, distort, or misguide.
2. We must have a clear understanding of the nature of the systems formed by those identified
causes.
We will want to know if the problem is a final result of many actions and inactions, decisions
and omissions that are a part of how we are doing things; or is the problem the first result of
someone coming in contact with an existing condition that waits quietly to cause problems. Our
root cause analysis method should show us the type of system with which we are dealing.
Clearly, if our analysis method drives the analysis process to identify only one root cause, or
requires the analyst to select personally from a prepared list of causes only one part of the causal
system as being the most significant, we at that point loose visibility of the whole system. At that
same time, the analysis becomes highly prone to error. It is for this reason that meaningful root
cause analysis must first focus upon the whole causal system. Appropriate prevention response
cannot be designed reliably without that visibility. The REASON method provides a clear
understanding of the nature of the internal system that produced the problem.
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3. We must know and understand the principles to which those causal systems adhere.
Once we know and understand the principles behind organizational phenomena, the mystery
surrounding causes is replaced with fundamental, practical systems knowledge. That is,
principles can be applied in order to design and assure continuing control of operations. The first
premise of engineering is that when principles are properly applied the result is predictable
success; and when principles are not properly applied, the result is predictable system failure.
With the essential visibility of the whole causal system, and the understanding of functioning
principles, root cause analysis provides practical capabilities to design quality into our
operations. This allows us to isolate and remove the sources of counter-quality. The REASON
method teaches and keys to these principles of control.
4. And . . . within our organization, we must have internal control of some part of the system.
Part of the root cause analysis process is identifying the points in the causal process where
internal control exists. Again, the analysis methodology must identify the complete causal
system and all points of control, if the organization is to have true administrative control. If our
root cause method allows the analyst to use personal bias to identify only what he considers to be
the one, most significant root cause, he in effect is being allowed to make the administrator's
decision . . . based upon assumptions.
Root cause analysis should therefore provide a means to depict and logically validate the cause
and effect relationships in the entire causal system, so that the person with the responsibility for
making the decision has a means of validating the data upon which his decision is to be based.
The administrator's broad knowledge of the organization's budget, planning, goals and
limitations, coupled with the capability to personally validate causal data for himself, better
assures sound decision making and improved operations control results. Because we control
what happens in our organizations with policies, procedures, and practices, a successful root
cause analysis must pinpoint prevention opportunities for policy/procedure/practices
improvement, as well as identify those necessary fixes and clean-ups that are more obvious and
immediate. The REASON method orders and depicts the data in a format that provides a means
to check for accuracy and completeness at each step.
In summary, root cause analysis should be the systematic process of gathering and ordering all
relevant data about counter-quality within an organization; then identifying the internal causes
that have generated or allowed the problem; then analyzing for decision-makers the comparative
benefits and cost-effectiveness of all available prevention options. To accomplish this, the
analysis methodology must provide visibility of all causes, an understanding of the nature of the
causal systems they form, a way to measure and compare the causal systems, an understanding
of the principles that govern those causal systems, and a visibility of all internal opportunities for
the organization to control the systems.
Conducting a Root Cause Analysis
After you identify that an adverse event has occurred you must have defined and disseminated
information throughout your organization as to what constitutes both a sentinel event and an
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adverse event about which you wish to be notified, and you must designate who is to be notified
and how. Make the notification simple. Use common sense. You want people to report to you.
THANK them for reporting the incident, make it easy to do, and make damned certain that they
are included for feedback when the final results are announced.
By having a reporting process established, you also have defined to whom those reports go. That
office, typically the office of the risk manager, then must determine expeditiously whether or not
a root cause analysis is needed. This may involve a decision by a Risk Management Advisory
Board or equivalent. That body can't just meet monthly....
If a root cause analysis is deemed appropriate:
Appoint an facilitator and an Mentat leader
* Facilitator: the process expert on conducting a root cause analysis
* Mentat Leader: the content matter expert pertaining to the event
Who's in charge? The Facilitator
The Mentat leader and facilitator sit down and identify
* What data has to be acquired and/or safeguarded, who should do it and how: medical records,
statements from personnel, maintenance records, instruction manuals, policy manuals, literature,
etc.
* Who should be on the Mentat? It is far better to be over-inclusive than under-inclusive. In point
of fact, in our consultations we invite every person in the involved department(s) to every root
cause analysis irrelevant of their involvement with the incident under analysis. There are two
reasons:
* Everyone learns the process, and,
* Some of the best ideas come from those not involved in the event.
Notify each invited person to bring with them a written (preferably on disk) sequence of
everything that they observed, every idea that has occurred to them.
Establish the first meeting date and time. It should be mentioned at this juncture that the
feedback received on the root cause analyses conducted using this approach have been very well
received. The fact that facilities with which we consulted presented root cause analyses that were
conducted on non-sentinel events amazed the reviewers. That they were done well impressed
them even more.
Three and occasionally four meetings of no longer than two hours each are sufficient for a
worthwhile root cause analysis, excluding additional time spent between those meetings.
Schedule two hours each, the third may well be less and the fourth may not be needed, but
typically allow a week between meetings.
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Start the first meeting; we prefer an active interplay between the facilitator and the Mentat
leader. Allow for brief introductions if there is anyone unknown. Always have a recorder to take
notes (preferably not an active participant in the analysis). Always have one or more "white
boards" and if possible have a computer with projector.
Tell everyone why the group is meeting. "We are here to find out all we can about such and such
an event; how it happened, how it might be prevented in the future." Emphasize that the purpose
is not to find fault, but to prevent future mishaps. There will be some initial disbelief here -- tell
the group that you expect that, and you just hope that they will come to trust the Mentat and the
process. We frequently give examples of RCA's in which it initially appeared that specific
persons were at fault but that the analytic outcome demonstrated a series of system failures that
were corrected without action against any person. We will commonly repeat the National Patient
Safety Foundation's philosophy that "...most errors result from faulty systems rather than human
error ... that people are in essence 'set up' to make errors for which they are not truly
responsible."
Now we're looking at the distinction between a proximal cause and a root cause (or as we prefer,
root contributor or contributory factor).
Block off a part of the board as a 'parking lot' in which to write items that don't apply now, but
which should not be forgotten.
Start by generating the sequence of events. Type this so that it can be easily seen and modified.
During this time, people will start suggesting causes, solutions, etc. Write them down in the
parking lot, avoiding discussion of anything but the event sequence for now. Make the sequence
detailed and complete, and continue until everyone is satisfied. This will typically take about one
hour. Save it to disk.
Identify the immediate corrective actions that were taken at or near the time of the event. Save it
to disk.
Now take a break -- though some Mentats will prefer to drive on, which should be allowed if that
feeling is unanimous.
Have the Mentat look at the sequence of events and mark every item that might in some way
have contributed to the adverse event. If just one person thinks it should be marked, mark it.
Now go to traditional brainstorming with the marked items from the event sequence serving as a
starting point, letting the group come up with any and all ideas about events, conditions or
whatever which might in some way have contributed to (not caused) the adverse event under
analysis. Use the parking lot when appropriate, to record ideas that are solutions, or incidental
but interesting thoughts. We advise verbal brainstorming, since we have found that people tend
to stimulate others' thoughts. Use previously identified items from other efforts as prompts to
stimulate the Mentat's brainstorming efforts.
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Use Barrier Identification (a simplified variant of barrier analysis) to identify those barriers
which either failed to function or did not exist. Add these to the list of potentially contributory
factors developed by brainstorming.
Now affinitize. Let the Mentat eliminate duplications, combine items, and then form logical
clusters from the brainstorm items. When everyone is reasonably satisfied with the affinitization
or clustering process, the first meeting ends, with the second meeting typically scheduled for one
week later.
During the intervening week, the Mentat leader and facilitator meet together and attempt to
develop a "Contributory Factor Diagram" from the material generated by the Mentat. This term
does not appear in the literature -- but there are lots of terms that do. We use this label to
emphasize that we wish to identify not just causes, but contributors to an adverse event. The
diagram is nothing but a flowchart with all the lines eventually leading upwards to the adverse
event. That's the top of the diagram. The second level is the names assigned to each cluster from
the affinitization process your Mentat went through. Under each cluster name, in parallel so that
equal weighting is implied, lies every member of that cluster. Move clusters around, see if one
subsumes another, etc. Play with the diagram. Develop flow harts. Even try to re-affinitize the
items, so long as you also retain an original version as your Mentat left it. Take a look at each of
those third tier items and ask the question "WHY?" or "HOW?" You may identify areas of
insufficient data, or you may be able to place new items at the fourth, fifth or even sixth level.
Your goal is to go as far as possible with the facilitator and Mentat leader asking the question
"Why?" until it can no longer be meaningfully asked. Do this for every third tier item. Code each
of the bottom items of every branch as "Insufficient Data", "Non-Contributory", or "Contributory
Factor" and color/shape code those three categories.
Assign persons to get the missing data before the next Mentat meeting.
Start your next meeting, and ask for the Mentat's input on your "Contributory Factor Diagram or
Tree." Let them check for omissions, better organization and more logical flow. Let them
generate alternatives. Have the Mentat verify or dispute your categorization; see if they can ask
the question "Why?" more or in different ways. Reach a consensus on the diagram. This will
typically take approximately one hour. By the end of this time, there should be few or no
Insufficient Data labels. Make certain that every factor labeled "Non-Correctable" is in fact so.
Every "Contributory Factor" which has no lower-level derivatives is a root cause -- we just avoid
that terminology for psychological and legal purposes.
Examine the items you have identified as "Non-Contributory." In the most formal quality
improvement sense, such items should not appear in your root cause analysis, since they are, as
indicated, "Non-Contributory." In point of fact, certain of these items will be of such high
visibility that you must mention them just so that reviewers, either internal or external know that
they were considered.
Prepare a list of such items. We frequently go so far as to retain them
on the Contributory Factor Diagram labeled as "High-Visibility, Non-Contributory Factors."
What constitutes a "thorough and credible" root cause analysis?
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Unfortunately, most organizations are still establishing the criteria by which to evaluate the
quality of a root cause analysis. This lack of published standards, however, does not mean that
there is safety from consequences. Facilities have already been placed on accreditation watch
because of less than adequate root cause analysis.
In evaluating the adequacy of a given root cause analysis, it is advisable to consider not only the
final work product, but also the process by which it was developed. Some points to consider:
1. The agency examining a root cause analysis will want to be assured of interdisciplinary
involvement.
2. That interdisciplinary involvement must include leadership representation.
3. There should be a clear effort to include individuals from all involved levels within the
organizational hierarchy.
4. There must be a demonstrated emphasis on root causes rather than proximate causes.
5. Performance improvement tools should be utilized in the root cause analysis process
methodology.
6. Use process flowcharts to clarify the way pertinent process are supposed to work,
compared with what actually occurred.
7. The process must demonstrate an effort to identify systems issues rather than simply
personnel failures or errors.
8. The root cause analysis should include a review of pertinent literature.
9. The root cause analysis must include recommendations for corrective action
(improvements) for the root causes identified, an action plan.
10. Each corrective action should have associated with it a person or persons responsible for
the implementation, and a reporting date.
11. Each action plan item should have a means by which its impact or effectiveness is
measured, who is responsible, and when.
12. The root cause analysis report should be distributed in accordance with your facility's
sentinel event policy.
13. Minutes of appropriate committees, including your executive committee, your medical
staff committee, etc., should reflect some cognizance of the root cause analysis and its
recommendations.
14. There must be clear evidence of responsible follow-through with the action plan.
Given the relative novelty of the root cause analysis methodology in its application to the
healthcare arena, compliance with any asserted criteria will not guarantee success should a given
root cause analysis come to be reviewed. This is an evolving area, and we can anticipate more
specific means by which to judge our efforts as the field matures in its use of this set of
performance improvement tools.
Root Cause Analysis
A technique used to identify the conditions that initiate the occurrence of an undesired activity or
state. Once the root causes are identified, steps to eliminate them can be determined. The result
of this technique can be summarized using fishbone diagrams. The key to applying the technique
in projects is to take problems expressed by the customers (not perceived problems) and
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determine if the statement sounds like an effect, a problem, or a cause. Remedies should be
aimed at the root causes and not the problems nor the effects.
Root Cause Analysis will provide the identification of all true causes, not symptoms and an
illustration of the interplay between causes/chain of related causes.
Applications
o To display characteristics of a given situation or problem.
o To brainstorm or identify potential causes, areas for further investigation, and/or
solutions.
o To depict what needs to be in place to enable a given outcome or result (see
Ishikawa Diagramming, positive Ishikawa). To help cross-functional
organizational units understand interaction relationships.
Procedures
1.
2.
3.
4.
5.
6.
7.
8.
Review all candidate problems.
Remove duplications.
Reprint problems.
Review each item in the consolidated problem list and ask: "...is this a cause or does this
sound like an effect?...", then continue to explore the chain of causes by asking:
"why...why...why?..." to separate out problems from symptoms.
Exhaust the list of possibilities to discover additional causes and effects.
Circle or highlight the most probable causes being careful not to include symptoms.
Discuss and prioritize for analysis/solution generation.
Validate against Mentat mates, raw notes, gut hunches, and other information collected
and available to the Mentat.
Instructions
To start the Root Cause Analysis review all candidate problems from the consolidated lists
obtained during the interview process. Remove duplication and combine like problem statements
to synthesize the list into a manageable size. (Assign original problem numbers for tracking.)
Reprint the problem statements, cut them into individual strips and tape to a flip chart or board
for review. Construct an overall problem, main effect or customer satisfier statement.
Review each item in the consolidated problem list using brainstorming and facilitation and ask:
"...is this a cause or does this sound like an effect? Focusing on causes, trace the chain of causes
by asking the questions "why, why, why..." until a root set of causes are determined. Insure that
causes are separated from their effects and that problems are separated from symptoms. A
helpful way of determining if something is a cause or effect is to say the phrase, "CAUSE 1,
therefore, PROBLEM STATEMENT, therefore, EFFECT". If that phrase makes sense then you
are on the right track. Or, ask "How Come?" which will lead to a root cause, and "So What?"
which will lead to the effect of the problem.
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Occam's Razor
"One should not increase, beyond what is necessary, the number of entities required to explain
anything"
Occam's razor is a logical principle that states that one should not make more assumptions than
the minimum needed. This principle is often called the principle of parsimony. It underlies all
scientific modeling and theory building. It admonishes us to choose from a set of otherwise
equivalent models of a given phenomenon the simplest one. In any given model, Occam's razor
helps us to "shave off" those concepts, variables or constructs that are not really needed to
explain the phenomenon. By doing that, developing the model will become much easier, and
there is less chance of introducing inconsistencies, ambiguities and redundancies.
Though the principle may seem rather trivial, it is essential for model building because of what is
known as the "underdetermination of theories by data". For a given set of observations or data,
there is always an infinite number of possible models explaining those same data. This is because
a model normally represents an infinite number of possible cases, of which the observed cases
are only a finite subset. The non-observed cases are inferred by postulating general rules
covering both actual and potential observations.
For example, through two data points in a diagram you can always draw a straight line, and
induce that all further observations will lie on that line. However, you could also draw an infinite
variety of the most complicated curves passing through those same two points, and these curves
would fit the empirical data just as well. Only Occam's razor would in this case guide you in
choosing the linear relation as best candidate model. A similar reasoning can be made for n data
points lying in any kind of distribution.
Also, if you have a few thousand points on the line and someone suggests that there is a point
that is off the line, it's a pretty fair bet that they are wrong.
Occam's razor is especially important for universal models such as the ones developed in General
Systems Theory, mathematics or philosophy, because there the subject domain is of an unlimited
complexity. If one starts with too complicated foundations for a theory that potentially
encompasses the universe, the chances of getting any manageable model are very slim indeed.
Moreover, the principle is sometimes the only remaining guideline when entering domains of
such high level of abstraction that no concrete tests or observations can decide between rival
models. In mathematical modeling of systems, the principle can be made more concrete in the
form of the principle of uncertainty maximization: from your data, induce that model which
minimizes the number of additional assumptions.
The reason behind the razor is that for any given set of facts there are an infinite number of
theories that could explain them. For instance, if you have a graph with four points in a line then
the simplest theory that explains them is a linear relationship, but you can draw an infinite
number of different curves that all pass through the four points. There is no evidence that the
straight line is the right one, but it is the simplest possible solution. So you might as well use it
until someone comes along with a point off the straight line.
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A related rule, which can be used to slice open conspiracy theories, is Hanlon's Razor: "Never
attribute to malice that which can be adequately explained by stupidity".
It can be used to dispense with relations, which are held to be nothing distinct from their
foundation in things; with efficient causality, which can be tended to view merely as regular
succession; with motion, which is merely the reappearance of a thing in a different place; with
psychological powers distinct for each mode of sense; and with the presence of ideas in the mind
of the Creator, which are merely the creatures themselves.
Occam's razor is often cited in stronger forms than Occam intended, as in the following
statements...
* "If you have two theories which both explain the observed facts then you should use the
simplest until more evidence comes along"
* "The simplest explanation for some phenomenon is more likely to be accurate than more
complicated explanations."
* "If you have two equally likely solutions to a problem, pick the simplest."
* "The explanation requiring the fewest assumptions is most likely to be correct."
* "Keep things simple!"
Notice how the principle has strengthened in these forms that should be more correctly called the
law of parsimony, or the rule of simplicity. To begin with we used Occam's razor to separate
theories, which would predict the same result for all experiments. Now we are trying to choose
between theories that make different predictions. We are just looking for guidance in developing
a theory.
This principle fades back into ancient history as it appears as "Nature operates in the shortest
way possible." The Ancient raw Mentat Aristotle went too far in believing that experiment and
observation were unnecessary. The principle of simplicity works as a heuristic rule-of-thumb but
some people quote it as if it is an axiom of physics. It is not. It can work well in philosophy or
particle physics, but less often so in cosmology or psychology, where things usually turn out to
be more complicated than you ever expected.
Simplicity is subjective and the universe does not always have the same ideas about simplicity as
we do. Successful theorists often speak of symmetry and beauty as well as simplicity.
The law of parsimony is no substitute for insight, logic and the scientific method. It should never
be relied upon to make or defend a conclusion. As arbiters of correctness only logical
consistency and empirical evidence are absolute. One should fully appreciate the need for
experimental verification.
The final word falls to that famous raw Mentat Einstein, himself a master of the quotable one
liner. He warned, "Everything should be made as simple as possible, but not simpler."
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Occam's razor is also called the principle of parsimony. These days it is usually interpreted to
mean something like "the simpler the explanation, the better" or "don't multiply hypotheses
unnecessarily." In any case, Occam's razor is a principle that is frequently used outside of
ontology, e.g., by philosophers of science in an effort to establish criteria for choosing from
among theories with equal explanatory power. When giving explanatory reasons for something,
don't posit more than is necessary. Or, as most would put it today, don't make any more
assumptions than you have to. We can posit the ether to explain action at a distance, but we don't
need ether to explain it, so why assume an ethereal ether?
But Occam's razor does not say that the more simpleminded a hypothesis, the better. If it did,
Occam's would be dull razor for a dim populace indeed.
The original principle seems to have been invoked within the context of a belief in the notion
that perfection is simplicity itself. For most of our disputes are not about this principle but about
what counts as necessary. Occam's razor means that when confronted with two explanations, an
implausible one and a probable one, a rational person should select the probable one, then the
principle seems unnecessary because so obvious. But if the principle is truly a minimalist
principle, then it seems to imply the more reductionism the better.
The Principle of Economy, states that "Scientists must use the simplest means of arriving at their
results and exclude everything not perceived by the senses." Taken to its logical conclusion this
philosophy becomes positivism; the belief that there is no difference between something that
exists but is not observable and something that doesn't exist at all.
Extrapolations
Forecasting
Forecasting is:
o
o
o
o
A statement about the future
A probabilistic statement about the future
A probabilistic, reasonably definite statement about the future
A probabilistic, reasonably definite statement about the future based upon an
evaluation of alternative possibilities
Forecasters may err when they analyze and measure only surface factors while ignoring
important underlying forces. Long-range predictions often do not pay enough attention to
substitution effects. There is a wide range of expenditure-substitution possibilities, and the more
"advanced a society economically, technologically and in educational attainment," the greater the
number of substitution possibilities because "these developments increase the number of
branches in each person's lifetime decision tree". The importance of assumptions in forecasting.
He points out the problematic tendency for several independent forecasters to rely on the same
assumptions, or to employ outmoded assumptions, even when current data are available.
Time factors help contribute to errors in forecasting. For example, forecasters sometimes do not
account for time lags such as when a fully developed technology may be delayed due to political,
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economic or social forces. Moreover, the process of phasing out existing facilities is sometimes
more time-consuming than anticipated. Another important time variable concerns the forecast's
time horizon: the longer the time period between the date the forecast is made and the target date,
the greater the possibility of change in major trend-determining factors. Therefore, "the length of
the forecast and their degree of error are almost always directly related". Because forecasts "are
summations of predicted values for several constituents of the phenomenon" that is the subject of
the forecast, forecasting accuracy depends both upon the proper selection of appropriate
components and upon "accurate prediction of the components' future values". A bias might
contribute to errors in forecasting.
Three factors contribute to errors in forecasting:
1. Inaccurate data coupled with unstable models
2. Lack of a global, qualitative approach
3. Explanation of the future in terms of the past"
The inaccurate data contribution will perpetually cause the Mentat to be unable to make a
projection and make computations and prime projections. This reason alone requires a Mentat to
maintain a comprehensive knowledge of his universe and keep it current at all times!
A pattern of expectations can be developed by generating predicted values for one of the
variables and giving fixed values of the others. Not all theories are stated in mathematical form,
especially in applied social research, but all theories provide information that enables the
generation of patterns of predictions.
Axiom of Experience
The future will be like the past, because, in the past, the future was like the past.
Technological Forecasting
Technological forecasting includes "all efforts to project technological capabilities and to predict
the invention and spread of technological innovations". Technological forecast includes three
elements:
1. The time of the forecast or the future date when the forecast is to be realized
2. The technology being forecast
3. The technology or the functional capabilities of the technology, and a statement about
probability
Forecasting a technology is a difficult task "beset with hazards". Some of these hazards include:
"the uncertainty and unreliability of data, the complexity of 'real world' feedback interactions, the
temptation of wishful or emotional thinking, the fatal attraction of ideology, and the dangers of
forcing soft and somewhat pliable 'facts' into a preconceived pattern". To offset the inherent
ambiguity and uncertainty of forecasting, technological forecasters have developed a set of
methodologies to assist them in their endeavor. In successful technological forecasts and
assessments, "market and technical analyses must be brought to bear simultaneously. Alone
either of them fails; together they can produce some very prescient forecasts"
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Historical Analogy
The use of analogy in forecasting involves a "systematic comparison of the technology to be
forecast with some earlier technology that is believed to have been similar in all or most
important respects". Forecasting by analogy is one of the simpler and more common ways to
forecast the growth of a new technology, though as a method its accuracy has been questioned on
several accounts.
Trend Extrapolation
A forecast can be generated by "observing a change through time in the character of something
and projecting or extrapolating that change into the future". In making such a forecast, the focus
is on the long-term trend, so short-term fluctuations are disregarded. Trend extrapolations require
that the forecaster have an understanding of the factors which contributed to change in the past,
and possess confidence in the notion that these factors will continue to influence developments in
a similar fashion in the future
One commonly employed approach to trend extrapolation involves the use of growth curves.
Growth curves are loosely based upon the notion that the growth of a technology can be charted
in the same way organic growth can be charted.
Time-series Forecasting
Time-series forecasting is a forecasting method that uses a set of historical values to predict an
outcome. These historic values, often referred to as a "time series", are spaced equally over time
and can represent anything from monthly sales data to daily electricity consumption to hourly
call volumes.
Time-series forecasting assumes that a time series is a combination of a pattern and some
random error. The goal is to separate the pattern from the error by understanding the pattern's
trend, its long-term increase or decrease, and its seasonality, the change caused by seasonal
factors such as fluctuations in use and demand.
Demand Forecasting
Projections of demand for a company's product or service. These forecasts drive a company's
production, capacity, and scheduling systems and serve as inputs to financial, marketing and
personal planning.
Fact 1
Demand Forecasting relies heavily on past information.
Fact2
Demand Forecasting is can be applied to three different time horizons. It is important to realize
that, depending upon the industry, the qualification of time spans can vary.
a. Short Term (less than 1 yr)
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b. Medium Term (less than 3 yrs)
c. Long Term (3 yrs or more)
Fact 3
There are three different types of forecasting methods:
i. Economic: Address business predicting, inflation rates, money supplies, and housing starts.
Macro Forecasting
ii. Technological: Rates of technology which create new products
iii. Demand forecasting: Projection of demand for a company's product or service. These
forecasts drive a company's production, capacity, and scheduling systems and serving as inputs
to financial, marketing and personal planning. Micro Forecasting
Pattern Based Forecasting
Forecasting method based on the assumption that the future is a function of the past.
Pattern Based Model
This model looks for underlying patterns in historical data. It implies that future events are
predicted only from past values and those other variables, no matter how potentially valuable are
ignored.
There are four components of pattern-based models:
Trend
Gradual upward and downward movement of data over time.
Seasonality
Data that repeats itself after a period of time (days, weeks, months, quarters).
Cycles
Patterns in data that occur every several years.
Random Variations
Random variations are the "blips" in the data caused by chance and unusual situations. They
follow no discernible pattern.
Moving Averages Method
Moving average forecasts use recent actual data values to generate a forecast. Use this method
for random data. This method also works best if you can assume that the market demands will
stay fairly the same over time. Mathematically, the moving average us the summation of
weighted demand data over time such that the sum equals one.
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Time Series Regression Method
This consists of Regression of past demand data against respective time periods. This usually
involves a linear regression, but can regress on several non-linear functions.
Seasonal Averages
Seasonal Averages can be applied to the Moving Averages Method and to the Time Series
Method.
Seasonal Index = Average of the ratio of actual demand to the forecast demand for all time
periods.
To forecast future periods multiply the unadjusted forecast (moving avg. or time series) by the
given seasonal index for the period.
Correlation Forecasting
Forecasting method that incorporates the variables that might influence the quantity being
produced.
Correlation forecasting assumes a demand for a product or service is dependent upon and
existing relationship between the demand variable and some other variables.
Important Facts:
* The demand variable is the Dependent Variable
* All other variables are Independent Variables
All Correlation forecasting models are usually expressed as multiple linear regression models.
Evaluating the Forecasts Accuracy
The forecast's accuracy is the difference between the forecast and the actual demand for a given
time period.
This difference can be found using any of the following:
* Mean Absolute Deviation
* Mean Squared Error
* Tracking Signal
Intelligence
From a data analysis perspective, intelligence is the process of gathering high-quality and
meaningful information about the subject matter being researched that will help the Mentat
analyzing the information draw conclusions or make assumptions.
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In order to attract and retain your best customers, you need a precise portrait of who they aretheir wants, their needs, their buying patterns. Intelligence paints that picture by analyzing and
interpreting vast quantities of data-customer demographics, product purchase histories, crosssales, service calls, Internet experiences and online transactions-turning information into insight
and developing conclusive, fact-based strategies to gain that competitive edge.
All of this information would provide you with an overall understanding of the industry, which
you would not have had unless the analysis had been conducted. In addition, you should have
sufficient information to assess the viability of investing in precious metals as well as the
associated risks.
From an information systems perspective, intelligence is the system that provides users with data
analysis to answer business questions and identify significant trends or patterns in the
information that is being examined. These are information systems that facilitate the data
gathering so those users can focus on the business questions they are trying to answer
Intelligence is the process of gathering meaningful information about the subject matter being
researched. Software applications have been developed that provide users with the capability to
conduct intelligence to answer questions and identify significant trends or patterns in the
information that is being examined.
The Mentat collects essential customer interaction data across multiple channels and distributes
actionable intelligence directly to decision-makers.
The better a vendor and IT understand the users, the more effectively they can design and focus
their efforts to meet the users' needs. This is especially true when bringing a new or unfamiliar
product to the users. Questions to answer include:
i. Who are the existing users?
ii. Who are the potential users, i.e., who in the organization could benefit from using this new
technology?
iii. How can the technology solve their business problems?
iv. What is going to motivate them to change the way they currently do things?
v. How do these benefits need to be communicated to them so they understand?
vi. What trends or strategic business issues influence the users' motivations to use it?
vii. To what information will they favorably respond?
How to Get the Information Needed to be Successful
Who to Get it From
Methods for collecting answers to the questions above differ depending on the goals and
objectives. If your objective is to increase market share within established segments, then
analyze the current users. A better understanding and profile of current customers can
accomplish two goals. First, it can increase cross-sales opportunities. In addition, by developing
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an accurate profile of current customers, you'll increase your opportunities to successfully reach
prospects within the same segment.
The task of reaching new segments is more challenging. Without the benefit of current
customers, it is necessary to go to other sources to develop an understanding of a particular
market segment. There are many ways to research new segments. Primary information and
secondary data can be collected from:
* Trade associations
* Influencers
* Complementary products that reach the same audience
* Internet searches
* Articles and journalists who write the articles
* Analysts
One of the most important goals of this research is to determine who the influencers are within a
segment. Reaching influencers is an important part of developing a segmentation strategy. The
value is twofold:
1) The influencers can provide a deeper understanding of the users
2) They can provide assistance with educating the users so the users will be more likely to adopt
the new technology
How to Get it
Qualitative research taps into that subjective vein of attitudes and behaviors that shape the
buying habits of users and help define the market. The results of qualitative research go beyond
the numbers to provide vendors and IT with the characteristics or attributes of the user. While the
quantitative approach has its role, the qualitative approach provides a depth to market research
that is not available through typical quantitative analysis.
Qualitative research is conducted primarily through exploratory in-depth interviews by engaging
interviewees in an interactive dialogue to delve into their opinions and truly understand the
dynamics of the users. Through this direct dialogue, users reveal their issues, needs and wants.
As a result, Mentats are able to pinpoint strategic issues, identify trends before they happen and
establish factors critical to successful technology adoption.
What is an Intelligence Program?
"A formalized, yet continuously evolving process by which the Mentat assesses the evolution of
its industry and the capabilities and behavior of its current and potential competitors to assist in
maintaining or developing a competitive advantage" intelligence program tries to ensure that the
organization has accurate, current information about its competitors and a plan for using that
information to its advantage.
How is Intelligence Different Than Espionage?
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The Mentat uses public sources to find and develop information on competition, competitors,
and the market environment. Unlike espionage, which develops information by illegal means
like "hacking," Intelligence uses public information - all information that can be legally and
ethically identified and accessed.
How to Determine Intelligence Information Needs?
Effective implementation of its intelligence program requires not only information about the
competitors, but also information on other environmental trends such as industry trends, legal
and regulatory trends, international trends, technology developments, political developments and
economic conditions. The relative strength of the competitor can be judged accurately only by
assessing it with respect to the factors listed above. In the increasingly complex and uncertain
business environment, the external factors are assuming greater importance in effecting
organizational change. Therefore, the determination of intelligence information needs is based
upon the firm's relative competitive advantage over the competitor assessed within the 'network'
of 'environmental' factors.
What are the General Uses of Intelligence Information?
The intelligence information obtained using intelligence can be used in programs that
supplement planning, mergers and acquisitions, restructuring, marketing, pricing, advertising,
and R and D activities.
What is the Role of the Internal Intelligence Unit?
Despite the increasing sophistication of intelligence tools and techniques, the most important role
in an intelligence program remains that of the organization or its internal Intelligence Unit. Once
the intelligence needs have been defined, the intelligence-unit is responsible for collection,
evaluation and analysis of raw data, and preparation, presentation, and dissemination of
intelligence. The intelligence-unit may handle all the activities itself, or it may assign some tasks
to an outside contractor. Often, decisions have to be made on assignments of data collection, and
data analysis and evaluation.
The Intelligence Unit has to decide upon the choice of sources of raw data. Should it use
government sources or online databases, interviews or surveys, drive-bys or on-site
observations? It has also to decide if and when to deploy 'shadowing' and defensive-intelligence.
Other decisions may involve choice of specialized interest groups (such as academics, trade
associations, consumer groups), private sector sources (such as competitors, suppliers,
distributors, customers) or media (such as journals, wire services, newspapers, financial reports)
as the sources of information. Very frequently, such issues involve balancing various constraints,
such as those of time, finances, staffing, etc. and therefore are based upon individual judgment.
Are there any Methods/Methodology for an Intelligence Program?
The purpose of an intelligence program is to gather accurate and reliable information. The
groundwork for the Intelligence Program is done through an internal Intelligence Audit that is
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primarily a review of the organization's operations to determine what is actually known about the
competitors and their operations. As a starting point for obtaining intelligence data, the
organization generally has some knowledge of its competitors, and its own intelligence needs. In
absence of a definition of its information needs, the organization may not be able to deploy its
resources effectively. To avoid such a scenario an organization may conduct an intelligence audit
that is effectively a review of its current operations to determine what is actually known about
the competitors and their operations. The intelligence audit helps in pinpointing the
organization's intelligence needs.
When the organization has some knowledge about its own intelligence needs, it precedes to the
stage of gathering intelligence data. Based upon the intelligence needs, relevant data can be
gathered from the organization's own sales force, customers, industry periodicals, competitor's
promotional materials, own marketing research staff, analysis of competitor's products,
competitor's annual reports, trade shows and distributors. Specific intelligence program
techniques include querying government resources and online databases, selective surveys of
consumers and distributors about competitor's products, on-site observations of competitor's
plant or headquarters, "shadowing" the markets, conducting defensive intelligence, competitive
benchmarking, and reverse engineering of competitor's products and services.
Raw data is evaluated and analyzed for accuracy and reliability. Every attempt is made to
eliminate false confirmations and disinformation, and to check for omissions and anomalies.
Omission, which is the seeming lack of cause for a business decision, raises a question to be
answered by a plausible response. Anomalies ask for a reassessment of the working assumptions.
While the conclusions one draws from the data must be based on that data, one should never be
reluctant to test, modify, and even reject one's basic working hypotheses. The failure to test and
reject what others regard as an established truth can be a major source of error.
Evaluation and analysis of raw data are critical steps of the Intelligence Program. Data that lacks
accuracy and reliability may be marginally correct data, concoction of very good data, bad data,
or even disinformation. All data is produced or released for some certain purpose. In the
Intelligence Program, reliability of data implies the reliability of the ultimate source of the data,
based upon its past performance. In the Intelligence Program, accuracy of data implies the
[relative] degree of 'correctness' of data based upon factors such as whether it is confirmed by
data from a reliable source as well as the reliability of the original source of data. Evaluation of
intelligence data is done as the facts are collected and unreliable or irrelevant data is eliminated.
Analysis of remaining facts includes 'sifting' out disinformation, studying patterns of
competitor's strategies, and checking for competitor's moves that mask its 'real' intentions. The
resulting intelligence information is integrated into the company's internal planning and
operations for developing alternative competitive scenarios, structuring attack plans and
evaluating potential competitive moves.
What are the Tools and Techniques?
Different types of intelligence tools and techniques are available for different requirements of
the Intelligence Program.
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Contacting Government Agencies can yield valuable data for the Intelligence Program, but may
often require excessive lead-time.
Searching Online Databases is a faster method of finding competitive information, although it is
more expensive. With increasing sophistication and affordability of information technology, this
technique is expected to become less expensive. Database search does not provide information
that has not been released to the public or that has not yet been collected.
From Companies and Investment Community Resources Some types of data that are not widely
available from databases can be procured by contacting the corporation itself or from investment
community sources.
Surveys and Interviews Surveys can yield plenty of data about competitors and products, while
Interviews can provide more in-depth perspectives from a limited sample.
Drive-by and On-site Observations of the competitor's [full or empty] parking spaces, new
construction-in-progress, customer service at retail outlets, volume and pattern of [suppliers' or
customers'] trucks, etc. can yield useful intelligence information about the state of the
competitor's business.
Competitive Benchmarking is used for comparing the organization's operations against those of
the competitor's.
Defensive Intelligence involves monitoring and analyzing one's own business activities as the
competitors and outsiders see them.
Reverse Engineering of competitor's products and services may yield important intelligence
information about their quality and costs.
Any 'Standard' Tools and Techniques for all Intelligence Activities?
Not all intelligence program tools and techniques are suitable for all intelligence objectives; the
Intelligence Unit has to use judgment in determining the relevant intelligence needs and the most
appropriate tools and techniques. Specific tools and techniques are chosen depending upon
various factors such as intelligence needs, time constraints, financial constraints, staffing
limitations, likelihood of obtaining the data, relative priorities of data, sequencing of raw data,
etc. While government sources have the advantage of low cost, online databases are preferable
for faster turnaround time. Whereas surveys may provide enormous data about products and
competitors, interviews would be preferred for getting a more in-depth perspective from a
limited sample. Therefore, human judgment is an essential element of the decision regarding
which intelligence techniques to deploy in a specific situation.
How can it be foiled?
* Thwart or jeopardize Very likely the target competitor would be aware of the organization's
intelligence moves and could make all possible efforts to thwart or jeopardize the organization's
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intelligence program. The competitor may have its own intelligence activities targeted at the
organization. Or it might intentionally generate disinformation to mislead the organization's
efforts. In fact, the organization's intelligence activities may find data that the competitor has
'planted' to keep the organization "preoccupied" and "off-balance".
* False confirmation The competitor could also create the problem of false confirmation by
releasing similar, but misleading (or incomplete), facts to different media sources. The
competitor may also use common ploys to pump information from the organization's employees.
Such ploys include "the phantom interview", "the false flag job seeker", "the seduction," and "the
nonsale sale."
* Phantom Interview The competitor, posing as a potential employer, inquires from the
organization's employees about their duties and responsibilities.
* False Flag Job Seeker A competitor's trusted employee , in the guise of a potential job seeker,
tries to learn about the organization in the course of the employment process.
* Seduction Involves flattery of organization's employees to encourage disclosure of important
facts. In the nonsale sale technique, the competitor pursues the organization's nonemployee
associates such as distributors and suppliers to elicit information about the organization's pricing
structure, customer service, etc.
What are the Information Hazards?
* Incomplete or inaccurate information The objective of the Intelligence Program is to gather
relevant information that is valid and accurate. Incomplete or inaccurate information may
jeopardize the organization's intelligence efforts.
* False Confirmation There might be instances of false confirmation in which one source of data
appears to confirm the data obtained from another source. In reality, there is no confirmation
because one source may have obtained its data from the second source, or both sources may have
received their data from a third common source.
* Disinformation The data generated may be flawed because of disinformation, which is
incomplete or inaccurate information designed to mislead the organization's intelligence efforts.
* Blowback Blowback may occur when the company's disinformation or misinformation that is
directed at the competitor contaminates its own intelligence channels or information. In all such
cases, the information gathered may be inaccurate or incomplete.
Many organizations are just opening their eyes to the value of intelligence. For others, they have
seen the potential, went at it, but fell short to realize it. This is a list of 10 practical tips, in my
experience the most important ones, to meet the challenge of establishing an intelligence cell. It
is the result of over ten years of professional experience in the implementation of intelligence
cells.
1. Intelligence needs leadership from the top
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The intelligence function in an organization, to have a real impact, needs full support from
the CEO. The CEO must, by emphasizing its importance and by the allocation of resources,
send a clear signal that intelligence is important to the survival and growth of the
organization. Visibility and independence of the intelligence function is crucial. While all
organizations do perform the intelligence function, for most this process is ad hoc, inefficient
and haphazard. At this time, the CEO or his right arm must talk to other CEO's or specialists
who have gone through the process of establishing an intelligence function, to learn from
their successes and mistakes. For those who have seen these successes and mistakes first
hand, you may recognize some of the elements listed in this article.
2. Choose a champion and form a strong Mentat.
You must choose a talented, credible and enthusiastic individual to champion the intelligence
function. Depending on your type of business, this champion may be a generalist or a
specialist. It is often better to hire in-house, but if no suitable candidate can be found within
your walls, carefully hire a dependable and energetic individual. A good mix of people in his
Mentat would often require some expertise in the business you're running to create useful
analysis, an information professional to exploit sources and data-warehousing, and an
information technology specialist to manage your network applications. Try to attract very
curious, independent, mature, sociable and persuasive individuals. These may be part-time on
the project, depending on your resources. Make sure they are well trained. A specialist may
help you in this important task.
3. Identify your intelligence needs
You must, before doing anything else, define what you expect from the intelligence function.
This will drive the whole process. Identify users, type and scope of intelligence needed. The
WHO, WHAT, WHEN, WHERE, WHY and HOW must be tackled. The most important
users are the organization's decision makers. In identifying your intelligence needs, always
bear that in mind. Intelligence drives decision-making, period.
4. Perform an intelligence audit
This is done to chart your intelligence and information sources, inside and outside of your
organization. Know-how, know-whom and expertise must be captured to plan your
intelligence collection effort and to help you focus for the next step. Also, a majority of
intelligence professionals believe that in most cases, more than fifty percent of your
information and intelligence needs can be found within your organization.
5. Involve and motivate the troops
While the creation of an intelligence cell is primordial, no really useful intelligence function
can be sustained in the long run if you do not mobilize your entire organization to contribute.
This is where your champion and his Mentat must animate, drive and support the thirst and
exchange of knowledge and intelligence. You must promote information seeking and sharing
to fully reap the benefits of intelligence. It can be helped, for example, by making it part of
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the job description, giving it support, creating incentives and rewards. You may need to give
some awareness or specialized intelligence training. Emphasize its importance. Remember
tip #1.
6. Remember: information is raw, intelligence is sweet
As the saying goes, too much information is like too little. What you desperately need is
intelligence. Intelligence is processed information. Too many organizations gather too much
information without collating, evaluating, analyzing, integrating and interpreting the
information to turn it into intelligence. The mission is not to build a library, but to find
pertinent information and create usable intelligence. For that, involve your experts and, if
needed, branch out to academics, consultants or other types of content or process experts.
7. Intelligence is a shared commodity
Good Intelligence needs to be disseminated to the right person, in the right format, at the
right time. Need I say more? Well, yes. Everybody knows: information is power. Intelligence
must then be some kind of "superinformation". This means that for information and
intelligence, sharing must give more power to the individual who volunteers it, than to the
one who keeps it to oneself, for your organization to create a useful intelligence function that
can help you prevent disasters, lost opportunities and find new ones. This is, in some
organizations, the most daunting task to achieve. You may need a professional to accomplish
this. The act of information seeking, analyzing and sharing should not be a yearly, quarterly
or monthly task but a continuous process done routinely every day. Finally, you need to
provide the means to disseminate and share effectively. An intranet would, in most
circumstances, supply the means for this.
8. Don't get bogged down in pricing the intelligence function
While it is important to evaluate the performance of your intelligence Mentat and its
network, for making it better and more responsive, it is an impossible task to pinpoint your
ROI in the intelligence function. Can you evaluate the cost of not having it? Can you cost an
unknown missed opportunity? Too often, CEO's and directors take this dollars and cents
approach that is missing the point.
9. Be open, you may not like what you hear
A good intelligence officer will sometimes challenge deep currently held beliefs. Provide
immunity for him. His job is to tell you the truth, not to please you. Beware if all your hear
and see does not go against your business or personal beliefs. However, your intelligence
officer's assertions must be based on thorough analysis, not guesses or hunches.
10. Last but not least - Security and ethics
The competition is often not stupid. Some may also be crooks. Your employees may, by not
knowing better, negligence or mischief, give away your "secrets". Good security will help to
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prevent this. Also, when implementing the intelligence system in your organization, make
sure you establish and disseminate a code of ethics to guide them in their intelligence
activities. Not doing this, like proper security, may bring you down.
CONCLUSION - This list does not contain everything you wanted to know, but were afraid to
ask, about how to establish a successful business and intelligence cell. I urge you to find out
more about this often unknown or forgotten, but crucial, business function. In hope that this list
will prevent a lot of headaches, good luck!
Intelligence Analyst Tendencies
Along with the tendency for new analysts to reflect the "academic" part of table 1 when they
hand in their work, there are other mistakes that a typical newcomer would do:
o Starts researching before asking the right questions that need answering and fails
to identify what is required
o Spends too much time on research and too little on analysis
o Recites facts instead of interpreting facts
o Forgets to state what is known and what is rumor
o Does not clearly present the "bottom line" or what is the essence of the analysis
o Produces a data dump instead of a concise analysis - needs to begin with the
conclusions and explore the implications
o Concentrates on the past and does not try to anticipate the future
o Fails to understand the importance of a deadline
Where to go from here
If you are managing a few analysts that need some coaching out of these tendencies, there are a
few things you can do to help their evolution into seasoned analysts:
o Do an initiation briefing stipulating that failures, like those mentioned, will likely
happen and are normal
o Communicate your organization's sense of mission and vision
o Explain clearly the difference between academic and intelligence writing
o Present the intelligence analysis process clearly and thoroughly
o Provide positive reinforcement to help cope with early failures
Competitive and intelligence is a growth industry right now. This growth means that many more
managers are trying to cope with a higher proportion of new analysts entering their
organizations. While attempting to cope, after some time, many managers are ready to conclude
that analysts are born, not made. This idea may have some truth to it, albeit somewhat extreme.
We all know that there is no substitute for experience and the maturation of an analyst has no
magic formula - mostly trial and error, with efficient coaching.
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This short guide, hopefully, has helped you starting thinking that maybe, some new analyst may
be rescued... And for those newbies who are entering our line or work, don't despair, as you can
see, new intelligence analysts can be drilled if there is fertile ground.
Basic Interviewing Techniques
Interviews can be conducted over the phone, in person or, using other communication systems.
In most cases, intelligence professionals will conduct phone interviews. However, the best way
to perform interviews remains in the direct human encounter. This article will lay out the basics,
step by step, for interviewing human sources in your intelligence work.
In the Beginning: The Question
Your search for the right human source begins with the question, or set of questions, you must
find an answer to. At this point, you must research your subject matter to map what you need to
know. Develop a set of questions and find what you can't answer with other means. You may
not have found the information needed in your initial search, may require validation or
confirmation. Once you have pretty much narrowed your focus, look for the right human
sources. Obviously, relevance to your question or subject matter is of prime importance in
selecting your human sources.
Selecting Human Sources
The potentially adequate human source for you:
o Has the either the know-how, know-whom or expertise in the subject you are
inquiring about;
o Is accessible from your location and can be reached;
o Has the potential to credibly and reliably answer your questions;
o Will not jeopardize your intelligence efforts, in the case that security is an
important issue for the project at hand
o Will not require you to break your ethical and moral standards of professional
practice.
Human sources will give you, in most cases, more relevant and precise information than other
sources. You can find a relevant source by soliciting your internal and external network of
contacts, going to trade shows, perusing trade publications and ordering conference proceedings,
looking up company organizational charts, business directories, ask for an expert reference from
trade and professional associations, etc.
There are seven major human sources to target for intelligence, in the outside "open source"
arena. Please remember that this is my unique form of radical characterization and should not be
taken too literally. Each target group has a different input in your collection effort. Percentages
represent a general index and may differ depending on the task at hand and the scope of the
project. The seven groups are:
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1. Entry-Level: not usually well connected because working at the lower end of the
hierarchy and less knowledgeable, but can give you basic information and occasionally a
pearl of information you never thought them capable of. Spend 10% of your time on this
group.
2. Run-of-the-Mill: often well connected people in the business but at lower and mid-level
ranks, know the intricacies of the operational or technical side of the subject and will
often provide you with detailed insights. Spend 20% on this group.
3. Top Dogs: CEO's and VP's who are well connected, knowledgeable and often talk too
much for their own good... If you have access, spend 20% on this group. Bandwagon
Journalists: members of this group are influential, have rarely anything substantial to
contribute, except for some behind the scenes information they can't usually dish out on
paper. Might be interesting though! Spend no more than 10% on this group.
4. Ivory Tower Academics: members of this group are usually not very influential as they
are mainly are involved in theoretical research, but can open your eyes to a different
perspective. Spend no more than 10% of your time on this group.
5. Mainstream Thinkers: these are well connected to one another and influential, but tend to
reflect conventional wisdom rather than revolutionary or innovative thinking. Spend 10%
on this group.
6. Rising Stars: usually are part of a small group, often not connected nor influential, but
soon to be leaders in their field and thus may provide cutting-edge thinking and
information. Spend 20% on this group.
Like any other source of information, multiplicity of human sources helps you verify the
reliability of collected information. But first, you must be able to get the information. That is our
next step.
Planning First Contact
Once your initial list of sources is completed, you need to plan your first contact. If time permits,
do some research on the source you wish to contact: academic and professional background,
articles published, family setting, contacts, hobbies, etc. This research should pretty much
establish the credibility of your source. You need to be able to anticipate how the person will
respond to your first contact by asking yourself this question: why would this person answer me?
Try to establish your psychological advantage. This means finding the edge you want to use to
get this person to talk to you. Often, getting the person's attention with what interests them most
is enough to get the conversation going. Before calling the person, try to find out different
settings where the interview could potentially take place, so you will be able to suggest the best
place.
First Contact
It is usually best to call mornings on Tuesdays, Wednesdays and Thursdays. Only because your
source will be less distracted by other things and will be in a better mood to talk. Let's do a step
by step:
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o When calling, smile. It will show in your tone of voice and will likely sound more
appealing.
o Identify yourself clearly
o State the purpose of your call
o State the reference that lead you to the person, if any
o Reassure your source for confidentiality
o Give an estimate of length of the interview
o If available and needed, offer some compensation for travel and time given
If the source seems open, try to establish a time and place of the meeting, or a timing for a
subsequent call. Emphasize the exchange of information and propose, if possible, a summary of
your research results when your project will be completed. Re-motivate the source by showing
your interest in meeting her in person.
If you encounter problems, don't overkill. You do not want to burn the source forever for you or
your organization. Leave your contact number in case the source changes their mind.
The Interview
The most important factor for getting information in the interview is to get the right climate
between you and your source. You need to create a climate of confidence. This is not easy with a
stranger. Here is a few concrete actions you can take to get there:
o You need, if required, to reassure source for confidentiality
o Ask for permission to take notes during the interview
o Exhibit a genuine human interest in her, not only for what she can get you - you
can do that by... LISTENING! Usually, the best motivator for a source is your
complete attention
o Start with smaller stuff and go to more sensitive issues
o Be direct and honest
o Be modest, even look naive if need be - nobody wants to talk to a "know-it-all"
o Keep mostly to the subject matter, unless you can tap on a shared experience or an
apparent passion from your source in a specific subject [remember the biography
you assembled on this person]
o Offer future help or part of project report - make clear the exchange of
information is a two-way street
Once you feel you have established the right climate, you need to get the information you need.
Here's a few tips to accomplish this:
o Keep it simple - your questions should be short and contain only one part, not two
or three questions into one
o Bracket data - for example, "Does ABC Corp sell between 15-30 million or
between 30 and 60 million dollars worth of Widgets?"
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o Keep an open mind - while it is important that you prepare a set of questions, do
NOT READ off your questionnaire nor only stick to it, because of...
o Golden nuggets - If you follow the flow of the conversation and listen to your
source, you may exploit golden nuggets of information and branch into space that
may be more pertinent than the questions you prepared
o Pick their brains - these sources may be experts in their field, so when they give
you information, do not feel shy to pick their brains by asking them for an
analysis, asking the "so what?" and the "what if?" that you will eventually have to
do when compiling your final report
When Going Nowhere
What to do when you feel you are going nowhere? This may be for one of three reasons:
1. The source does not hold a belief can have access to, the information you need. You made a
mistake in selecting her. Once this is established, thank the person for her time and leave a good
impression of your visit by leaving a contact number in case that person finds something for you.
2. The source does not feel like giving you the information and this may be for security
purposes, their own ethics or because she may now see this as a waste of time. You have to
decide if you want and should pursue the matter further, but do not break your ethical guidelines:
* Restate confidentiality
* Give a reference to a third person for helping her to check vote a codround
* Emphasize the expertise of the person - this may boost their ego and may make them talk more
3. You have problem directing the interview. You may get on the right track by:
* Redirecting the conversation toward your subject matter
* Being more precise in your questions and project your point about this
* Giving examples of answers needed, type of analysis required, etc.
Closing the Meeting
Now that you have acquired all that is needed, you have to make an adequate exit. Remember to
re-motivate the person, because you never know when you could need her help again or when
she may volunteer further information:
You may give a future objective, in the form of a future question or point of interest for you.
Offer future help or part of project report, if possible Point of contact if more information is*
Reciteming
Where to go from Here
Finally, your interview is over. Sometimes, it may be good to call back the source, thanking her
and giving her feedback on your project. Now you need to complete your report. Next step is
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finalizing your intelligence collection and starting processing the information into intethod of ,
including the evaluation of the reliability of the information gathered, before disseminating your
final results.
General Systems Thinking
General Systems Theory constitutes a somewhat fuzzily defined academic domain, that touches
virtually all traditional disciplines, from mathematics to technology.
F to philosophy and the social sciences. It is more specifically related to the "sciences of
complexity".
Systems theory or systems science argues that however complex or diverse the world that we
experience, we will always find different types of organization in it, and such organization can
be described by can pros and principles which are independent from the specific domain at
which we are looking. Hence, if we would uncover those general laws, we would be able to
analyze and solve problems in any domain, pertaining to any type of system. The systems
approach distinguishes itself from the more traditional analytic approach by emphasizing the
interactions and connectedness of the different components of a system.
The complexity of the world mechanics is the strand of complex systems that make it up. And
for this the approximations of mechanics work successfully.
Unless some simplifications can be made, the amount of complexity increases at least as fast as
the square of the number of equations i.e. the problem gets big fast.
The General Systems movement attempts to stipulanking about medium number systems by
finding general laws.
Understanding General Systems Theory
If multiple disciplines focused their research and theory development efforts, they would be able
to identify laws and principles which would apply to many systems. This would allow scholars
and scientists to make certain of system characteristics such as wholeness, differentiation, order,
equifinality, progression and others. With a common framework, scientists could better
communicate their findings with each other and build upon each other's work. He believed that
over time, what was discovered would come to be applicable to at analygeneral.
We speak of a health care system, a family system, body systems, information systems, banking
systems, political systems, etc. One of the reasons we do this is because the amount of
knowledge and information available has increased tremendously during this time period. We
cannot know all there is to know. We seek some way of ordering what we encounter to avoid
being overloaded with information. We focus in on small areas of knowledge rather than
attempting to comprehend the whole.
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Whether we like it or not, we are enmeshed in many systems. It is to our benefit to gain some
basic understanding of how systems work. We can more effectively care for patients, families
and communities when we do understand. We can more effectively bring about desired changes
in our workplace if we are able to step back and consider how best to accomplish this within our
workplace system.
Levels of Complexity
Level of Complexity Example
Characteristics
Level 1
Level 2
The organizational chart
Dynamic, moving, predictable, must
be controlled externally
Dynamic, predictable, capable of
self-regulation within certain limits.
Open, dynamic, programmed for
Structural Framework
Clockwork
Level 3
Cybernetic device such as
Thermostat
Level 4
The cell
self-maintenance under changing
external conditions
Level 5
The plant system
Open, dynamic, genetically
determined, capable of selfregulation through wide range of
changing external and internal
conditions.
Level 6
The animal system
Open, dynamic, genetically
determined system that adjusts to its
environment by making internal
adjustments and by forming simple
social groups.
Level 7
Humans
Open, dynamic, self-regulating,
adaptive through wide circumstances
because of ability to think abstractly
and communicate symbolically
Level 8
The social system
More complex than an individual,
more open to environmental
influence, more adaptive to
circumstance because of collective
experience and wider reservoir of
skills.
Level 9
The transcendental
Most freely adaptable to
circumstance because it rises above
and extends beyond the boundaries
of both individuals and social
systems.
Common Elements
* input
* output
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* throughput or process
* feedback
* control
* environment
* goal
Key Terms
Term
Definition
Input
The energy and raw material transformed by the system
Throughput The processes used by the system to convert raw materials or energy from
the environment into products that are usable by either the system itself or
the environment.
Output
The product or service which results from the system's throughput or
processing of technical, social, financial and human input.
Feedback
Information about some aspect of data or energy processing that can be
used to evaluate and monitor the system and to guide it to more effective
performance.
Subsystem A system which is a part of a larger system. They can work parallel to
each other or in a series with each other.
Static system neither system elements nor the system itself changes much over time in
relation to the environment
Dynamic system
the system constantly changes the environment and is changed by the
environment
Closed systems
fixed, automatic relationships among system components and no
give or take with the environment
Open systems interacts with the environment trading energy and raw materials for goods
and services produced by the system. They are self-regulating, and capable
of growth, development and adaptation.
Boundary
the line or point where a system or subsystem can be differentiated from
its environment or from other subsystems. Can be rigid or permeable or
some point in between. Systems or subsystems will engage in boundary
tending.
Goal
the overall purpose for existence or the desired outcomes. The reason for
being. Currently, many organizations put their goals into a mission
statement.
Entropy
The tendency for a system to develop order and energy over time. Rules
are made, policies and protocols are written,
Negentropy The tendency of a system to lose energy and dissolve into chaos
Control
the activities and processes used to evaluate input,
throughput and output in order to make corrections
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Equifinality
objectives can be achieved with varying inputs and in different ways.
Basic Principles of a Systems Approach
1. A system is greater than the sum of its parts. Requires investigation of the whole situation
rather than one or two aspects of a problem. Mistakes can't be blamed on one person,
rather a systems analyst would investigate how the mistake occurred within a subsystem
and look for opportunities to make corrections in the processes used.
2. The portion of the system studied must exhibit some predictability.
3. Though each sub-system is a self-contained unit, it is part of a wider and higher order.
4. The central objective of a system can be identified by the fact that other objectives will be
sacrificed in order to attain the central objective.
5. Every system, living or mechanical, is an information system. Must analyze how suitable
the symbols used are for information transmission.
6. An open system and its environment are highly interrelated.
7. A highly complex system may have to be broken into subsystems so each can be
analyzed and understood before being reassembled into a whole.
8. A system consists of a set of objectives and their relationships.
9. A system is a dynamic network of interconnecting elements. A change in only one of the
elements must produce change in all the others.
10. When subsystems are arranged in a series, the output of one is the input for another;
therefore, process alterations in one requires alterations in other subsystems.
11. All systems tend toward equilibrium, which is a balance of various forces within and
outside of a system.
12. The boundary of a system can be redrawn at will by a system analyst.
13. To be viable, a system must be strongly goal-directed, governed by feedback, and have
the ability to adapt to changing circumstances.
A Bit More
"Modern science is characterized by its ever-increasing specialization, necessitated by the
enormous amount of data, the complexity of techniques and of theoretical structures within every
field. Thus science is split into innumerable disciplines continually generating new
subdisciplines. In consequence, the physicist, the biologist, the psychologist and the social
scientist are, so to speak, encapsulated in their private universes, and it is difficult to get word
from one cocoon to the other..."
"Entities of an essentially new sort are entering the sphere of scientific thought. Classical science
in its diverse disciplines, be it chemistry, biology, psychology or the social sciences, tried to
isolate the elements of the observed universe - chemical compounds and enzymes, cells,
elementary sensations, freely competing individuals, what not -- expecting that, by putting them
together again, conceptually or experimentally, the whole or system - cell, mind, society - would
result and be intelligible. Now we have learned that for an understanding not only the elements
but their interrelations as well are required..."
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"It is necessary to study not only parts and processes in isolation, but also to solve the decisive
problems found in organization and order unifying them, resulting from dynamic interaction of
parts, and making the behavior of the parts different when studied in isolation or within the
whole..."
General system theory, therefore, is a general science of "wholeness...The meaning of the
somewhat mystical expression, "The whole is more that the sum of its parts" is simply that
constitutive characteristics are not explainable from the characteristics of the isolated parts. The
characteristics of the complex, therefore, appear as "new" or "emergent"...
We can also say: While we can conceive of a sum being composed gradually, as system as total
of parts with its interrelations has to be conceived of as being composed instantly..."
"In our considerations we started with a general definition of "systems" defined as a "set of
elements standing in interrelations... No special hypothesis or statement were made about the
nature of the system, of its elements or the relations between them. Nevertheless from this purely
formal definition of "system" many properties follow which in part are expressed in laws wellknown in various fields of science, and in part concern concepts previously regarded as
anthropomorphic, vitalistic. or metaphysical. The parallelism of general conceptions or even
special laws in different fields therefore is a consequence of the fact that those are concerned
with "systems" and that certain general principles apply to systems irrespective of their nature...
There appear to exist general system laws which apply to any system of a particular type,
irrespective of the particular properties of the systems and the elements involved. Compared to
the analytical procedure of classical science with resolution into component elements and oneway or linear causality as basic category, the investigation of organized wholes of many
variables requires new categories of interaction, transaction, organization, teleology..."
"These considerations lead to the postulate of a new scientific discipline which we call general
system theory. Its subject matter is formulation of principles that are valid for "systems" in
general, whatever the nature of the component elements and the relations or "forces" between
them..."
"It seems, therefore, that a general theory of systems would be a useful tool and providing on the
one hand, models that can be used in, and transferred to, different fields, and safeguarding, on
the other hand, from vague analogies which often have marred the progress in these fields."
"New" World Order
The order of the empirical world itself has an order which might be called an order of the second
degree.
Basic Concepts of the Systems Approach
The systems approach integrates the analytic and the synthetic method, encompassing both
holism and reductionism. Systems studied by physicists are closed: they do not interact with the
outside world. When a physicist makes a model of the solar system, of an atom, or of a
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pendulum, he or she assumes that all masses, particles, forces that affect the system are included
in the model. It is as if the rest of the universe does not exist. This makes it possible to calculate
future states with perfect accuracy, since all necessary information is known.
Such an assumption is simply impossible for most practical phenomena. Organisms are open
systems: they cannot survive without continuously exchanging matter and energy with their
environment. The peculiarity of open systems is that they interact with other systems outside of
themselves. This interaction has two components: input, that what enters the system from the
outside, and output, that what leaves the system for the environment. In order to speak about the
inside and the outside of a system, we need to be able to distinguish between the system itself
and its environment. System and environment are in general separated by a boundary. For
example, for living systems the skin plays the role of the boundary. The output of a system is in
general a direct or indirect result from the input. What goes out, needs to have gotten in first.
However, the output is in general quite different from the input: the system is not just a passive
tube, but an active processor. The transformation of input into output by the system is usually
called throughput. This has given us all the basic components of a system as it is understood in
systems theory.
When we look more closely at the environment of a system, we see that it too consists of systems
interacting with their environments. If we now consider a collection of such systems which
interact with each other, that collection could again be seen as a system. The mutual interactions
of the component systems in a way "glue" these components together into a whole. If these parts
did not interact, the whole would not be more than the sum of its components. But because they
interact, something more is added. With respect to the whole the parts are seen as subsystems.
With respect to the parts, the whole is seen as a supersystem.
If we look at the supersystem as a whole, we don't need to be aware of all its parts. We can again
just look at its total input and total output without worrying which part of the input goes to which
subsystem. This point of view considers the system as a "black box", something that takes in
input, and produces output, without us being able to see what happens in between. (in contrast, if
we can see the system's internal processes, we might call it a "white box"). Although the black
box view may not be completely satisfying, in many cases this is the best we can get. In most
cases they have little idea about the particular mechanisms, which lead from the cause to the
effect. The only thing that can be clearly established is the final result.
The black box view is not restricted to situations where we don't know what happens inside the
system. In many cases, we can easily see what happens in the system, yet we prefer to ignore
these internal details. The "black box" view of a system will be much simpler and easier to use
for the calculation of overall levels than the more detailed "white box" view, where we trace the
movement of every component through every particular state.
These two complementary views, "black" and "white", of the same system illustrate a general
principle: systems are structured hierarchically. They consist of different levels. At the higher
level, you get a more abstract, encompassing view of the whole, without attention to the details
of the components or parts. At the lower level, you see a multitude of interacting parts but
without understanding how they are organized to form a whole. According to the analytic
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approach, that low level view is all you need. These interactions are not simple, linear cause and
effect relations, but complex networks of interdependencies, which can only be understood by
their common purpose. This "common purpose" functions at the level of the whole. It is
meaningless at the level of an individual component.
One-way to understand this is the idea of "downward causation". According to reductionism, the
laws governing the parts determine or cause the behavior of the whole. This is "upward
causation": from the lowest level to the higher ones. In emergent systems, however, the laws
governing the whole also constrain or "cause" the behavior of the parts.
This reasoning can be applied to most of the things that surround us. Each level in the hierarchy
of systems and subsystems has its own laws, which cannot be derived from the laws of the lower
level. Each law specifies a particular type of organization at its level, which "downwardly"
determines the arrangement of the subsystems or components at the level below. When we say
that the whole is more than the sum of its parts, the "more" refers to the higher level laws, which
make the parts function in a way that does not follow from the lower level laws.
Although each level in a hierarchy has its own laws, these laws are often similar. The same type
of organization can be found in systems belonging to different levels. For example, all open
systems necessarily have a boundary, an input, an output and a throughput function. The material
is different, but the function is the same. Closed systems at different levels have many features in
common as well. The binding forces which hold together the planets in the solar system, the
atoms in a molecule, or the electrons in an atom, although physically different, have a very
similar function. The embeddedness of systems in supersystem holds for all types of systems.
Thus we find similar structures and functions for different systems, independent of the particular
domain in which the system exists. General Systems Theory is based on the assumption that
there are universal principles of organization, which hold for all systems, be they physical,
chemical, biological, mental or social. The mechanistic worldview seeks universality by reducing
everything to its material constituents. The systemic worldview, on the contrary, seeks
universality by ignoring the concrete material out of which systems are made, so that their
abstract organization comes into focus.
What is a System?
A system is defined as an "entity which can maintain some organization in the face of change
from within or without." Or "a set of objects or elements in interaction to achieve a specific
goal."
What is the Function of a System?
The function of any system is to convert or process energy, information, or materials into a
product or outcome for use within the system, or outside of the system (the environment) or both.
Indeed, if a system is to survive, it must save some of the outcome or product to maintain the
system.
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Complementarity Law
Differing perspectives on the same system are neither 100% independent nor 100% compatible;
yet together they reveal more truths about the system than either could alone.
System Holism Principle
A system as a whole works differently than the parts of the system. The parts alone cannot do
what the system can.
Principle: Therefore, it is necessary for a system to have functional parts that communicate
efficiently.
Ubiquity and unification principle
Certain mechanisms and laws hold for many different kinds of systems studied in biology,
psychology, or engineering.
Seven Steps towards Logic Based General Systems Theory
1. Revising definition of System in terms of Model Theory
2. Introducing time and intentional modal operators for description of actions and
information states
3. Introducing model transformations as a framework for representation of systems
dynamics. Revising definition of Machine
4. Building Complex systems out of simple ones
5. Creating new abstract models of complex system. Abstract computational ecosystem as
an example
6. Getting new models to work: LEM - a computer implementation of Abstract
Computational Ecosystem
7. Experiments with emergent organization
Major Orders
Generalist
Generalists overcome the literalism of the junior orders by "bringing to decision making a
healthy common sense" and achieving awareness of the "broad sweep of what is happening is his
universe."
Generalists are expected to possess broad and accurate knowledge of at least 94.75 percent of
everything occurring in his universe. But you will NEVER get everything! As the Zensuni
philosophers say: "Uproot your questions from their ground and the dangling roots will be seen.
More questions!"
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The principles of expertise can change, no one can catalogue all knowledge and the Generalist
himself is part of the set of phenomena to be learned.
The Importance of Purpose
A model must have a clear purpose, and that purpose should be to solve a particular problem. A
clear purpose is the single most important ingredient for a successful modeling study. Of course,
a model with a clear purpose can still be incorrect, overly large, or difficult to understand. But a
clear purpose allows model users to ask questions that reveal whether a model is useful for
solving the problem under consideration. This purpose will, in almost all cases, come assigned
from the Mentat's Master, though in rare cases it may be self-determined.
Beware the analyst who proposes to model an entire social or economic system rather than a
problem. Every model is a representation of a system-a group of functionally interrelated
elements forming a complex whole. But for the model to be useful, it must address a specific
problem and must simplify rather than attempting to mirror in detail an entire system.
A model designed to understand how the business cycle can be stabilized is a model of a
problem. It deals with a part of the overall economic system. A model designed to understand
how the economy can make a smooth transition from one form of energy to alternative energy
sources is also a model of a problem; it too addresses only a limited system within heir natural
economy. A model that claims to be a representation of the entire economy is a model of a whole
system. The usefulness of models lies in the fact that they simplify reality, putting it into a form
that we can comprehend. But a truly comprehensive model of a complete system would be just
as complex as that situation and just as inscrutable. The map is not the territory-and a map as
detailed as the territory would be of no use.
The art of model building is knowing what to cut out, and the purpose of the model acts as the
logical knife. It provides the criterion about what will be cut, so that only the essential features
necesulate offulfill the purpose are left. The model builders-not to mention the Mentat's clientwould probably not understand its behavior, and its validity would be largely a matter of faith.
A model designed to examine just the business cycle or the energy transition would be much
smaller, since it would be limited to the factors believed to be relevant to the question at hand.
Wisdom for Deciding Goals
Wisdom is the ability to determine which problems should be solved. To be able to determine
which projects are worth working on, are worthless or not worth the effort is wisdom. It is an
important subset of intelligence. Wisdom and ability to plan ahead are of course closely linked,
but wisdom in its classic form is usually intuitive rather than deductive. It cannot exist in a
vacuum, it has to be linked to the ability to solve passing and act to be real wisdom, and
otherwise the person will be just sprouting good intentions or advice without doing anything.
Solving Problems
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When we speak of problem resolution we mean solving a problem at its root cause(s) so it never
occurs again. This goes far beyond the general problem solving practice the reused by many
today. People work very hard at satisfying the affected customer. The organization's work force
moves from one firefight to another. This is an ineffective use of the organization's resources, not
to mention the frustration for people of having to "solve" the same problem over and over. After
the d energy's immediate concerns have been successfully resolved, each of us must be
committed to analyzing and changing the offending work process, or the fire fights will continue.
In order for a person to be an effective problem eliminator, he/she must first have a method of
problem solving. For organizations to be he outsiul at problem elimination, every person in the
organization must have the same problem solving method. This allows us to be more efficient, as
well as effective, in problem elimination.
Eight key steps to effective problem elimination
Step One: Choose the Right Problem Solver(s) to Assist
The appropriate person or Mentat to help solve the problem you've chosen would be those
who are directly affected by the problem and those used, but work process knowledge. When
you control the root cause(s) of the problem, you should apply the eight steps of problem
elimination to resolving the problem forever. In this case, you would establish requirements
with the people in the rest of the workflow. This would help to ensure you did not implement
a change which would cause problems in their work process. Then, before implementing a
change, you would share what you are planning with them prior to implementation.
Whenever you are the primary person responsible for resolving the root cause(s) of the
problem, you will use these same eight steps, but in a more informal way than the problem
you are measuring is beyond the scope of the work group, a Mentat will be necessary to
successfully resolve the problem. They will ensure the problem is resolved forever at root
cause. It is critical that all members of the problem solving Mentat have a common
methodology of solving problems (like at itsht steps covered here).
Step Two: Develop a Clear Problem Definition
"If you don't know where you're headed, any road will get you there," said the Cheshire Cat
in Alice in Wonderland. This is particularly true for problem solving efforts. Too often, the
individual or the Mentat jumps into action assuming they all understand the problem, only to
be derailed later because a clear problem definition was neglected. A problem definition
should:
1) Contain a specific description of the problem or nonconformance
2) Include measurement data
3) Not suggest cause
4) Be agreed to by all participating problem solvers.
Step Three: Install a Temporary Fix
There are times when a temporary fix is critical to keeping the process functioning until the
complete problem solving effort can be accomplished. A temporary fix is usually an
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additional expense of money and time, like an inspector, checker or rework person, but
cannot be avoided without greater consequences. The temporary fix allows business
processes to continue, however, it should never be confused with problem elimination.
Without correcting the root cause of the problem within the work process, the same type of
problem can impact other customers.
Step Four: Identify Root Causes
At this stage, it is critical to call upon the expertise and experience of all the people who
work in the work process to generate as many possible root causes as possible. You may be
able to call all the people together at one time to brainstorm a list of possible root causes or
you may not. Where you can't get everyone together, you can still capture their thoughts on a
Cause and Effect Diagram.
Step Five: Validate Root Cause(s)
Once you or the Mentat has generated as many root causes as possible based upon
experience, it's time to validate the root causes using measurement. It is critical to confirm
our suspicions with data by measuring the root causes before proceeding. This validation
will require the analysis of each nonconformance. Each incident should be analyzed for cause
and posted on a checksheet. A checksheet is a simple form with the possible root causes list
down the left side of the page and the days of the week listed across the top of the page.
Step Six: Design and Communicate Corrective Actions
It's time to address the root cause chosen for action with the design and communication of
the appropriate corrective action. The corrective action must fundamentally change the work
process ( otherwise it's only a "fix"). Remember, the goal is to eliminate this root cause
forever. As was done in the development of possible root causes, the individual or Mentat
members should brainstorm as many corrective actions as possible. After creating a list of
possibilities, search deeper for the "second right answer". The most obvious answer has
probably been tried before, try another, which may be less obvious. Now, it's time to choose
the corrective action, or combination of corrective actions, which is easiest to install and least
expensive to install, while still completely resolving the root cause. After the corrective
action is chosen, evaluate the work process and communicate to everyone impacted by the
change what the corrective actions will be before proceeding. The Mentat also needs to ask:
1) What approval is needed before proceeding
2) Who else needs to be informed of what is planned
3) Who will take responsibility for communicating to those people
4) How will we know the chosen root cause is eliminated?
Step Seven: Implement the Corrective Action Plan
Since the plan for the corrective action has been fully developed and communicated, the
corrective action needs to be implemented according to the plan. At this point the plan should
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be worked as designed, with course corrections as dictated by unanticipated changes made by
the Mentat and only the Mentat.
Step Eight: Validate Success
The only way to validate the success of the corrective action implementation is with
measurement data. If the root cause has been eliminated, no problem due to that cause should
recur. Once again the checksheet should be used to continue to analyze the problem for root
causes. The root cause(s) covered in the corrective action plan should have zero
nonconformance. This will prove the corrective action was effective.
Common Sense Problem Solving
Nothing is so uncommon as common sense. Common-sense reasoning is required for solving
problems in the common-sense world.
To solve the typical textbook problem, the Mentat will scan the problem, make a mental marker
that places the problem in the appropriate field of knowledge. Continue for a second, the expert
makes another mental marker for the next more precise area.
As the scan goes on, there may be a number of such markers further refining the concepts needed
to solve the problem. These markers are held in the Mentat's mind, usually without that person
being consciously aware of what's happening. The trained mind is very powerful.
When the specific parameters of the problem are reached, the expert begins making notations
and works back up through the hierarchy which has been marked out during the scanning. This
results in presenting the solution in reverse order from the actual solution that was done
The Mentat should have available to him a fairly wide class of immediate logical consequences
of anything he is told. This property is expected to have much in common with what makes us
describe certain humans as having common sense. We shall therefore say that anyone has
common sense if he automatically deduces for himself a sufficiently wide class of immediate
consequences of anything he is told and what it already knows.
Common-sense knowledge includes the basic facts about events (including actions) and their
effects, facts about knowledge and how it is obtained, facts about beliefs and desires. It also
includes the basic facts about material objects and their properties.
One path to human-level AI banned during the Butlerian jihad used mathematical logic to
formalize common-sense knowledge in such a way that common-sense problems can be solved
by logical reasoning. This methodology required understanding the common-sense world well
enough to formalize facts about it and ways of achieving goals in it. Basing AI on understanding
the common-sense world is different from basing it on understanding human psychology or
neurophysiology. That approach, based on logic and computer science, was complementary to
approaches that start from the fact that humans exhibit intelligence, and that explore human
psychology or human neurophysiology.
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Philosophers all included common-sense knowledge when they discussed formal logic.
However, formalizing much of common-sense knowledge and reasoning proved elusive, and the
twentieth century emphasis has been on formalizing mathematics. Some important philosophers
have claimed that common-sense knowledge is unformalizable or mathematical logic is
inappropriate for doing it. Though it is possible to give a kind of plausibility to views of this sort,
it is much less easy to make a case for them that is well supported and carefully worked out. If a
common-sense reasoning problem is well presented, one is well on the way to formalizing it.
Formal Decision Making/Problem Solving
Generation of Alternatives
Unless there are alternatives to select between, there really isn't a decision to make. Generating
alternatives, examining their properties, and choosing among the alternatives are all activities
that may add considerable cost to the decision-making process
Alternatives are different means of meeting the general purpose and need of a proposed action,
project, or program. The no-action alternative is the option of not engaging in the proposed
project or the other action alternatives and provides the baseline against which the impacts of the
action alternatives are compared.
The identification, description, evaluation, and comparison of alternative ways to meet the basic
purpose and need of a proposed action are crucial to the objectivity of the EA process. In most
cases, the Mentat can identify several alternatives that are reasonable, feasible, and would
achieve the stated needs of the action. In the absence of an objective and thorough alternatives
analysis, the process tends merely to affirm a chosen action and loses power as a decisionmaking tool.
The thorough description of alternatives in a process facilitates their side-by-side comparison in
terms of their technical, environmental, and economic risks and benefits. The alternatives
analysis of a Mentat should discuss alternatives to a specific action, such as not proceeding with
the action, carrying out the action in a different location or facility, or implementing a nonstructural solution. It is generally not sufficient to discuss only alternatives within an action, such
as using different designs or materials, or changing the orientation of the facility slightly within
the project boundaries.
The alternatives considered should include the "no-action" alternative the option of not carrying
out any of the action alternatives. The no-action alternative represents an objective baseline
against which the other alternatives can be measured and may, in the final analysis, be the
alternative that is preferred.
Some basic alternative:
* Things are worse
* Things are the same
* Things are better
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Whatever strategy we decide to use in approaching decision problems, it is wise to make a habit
of determining if any of the alternatives is dominated by any other alternative and could
therefore be eliminated.
Lateral Thinking and Generation of Alternatives
Most of the time, we have a vague awareness of a situation and nothing more. And it is difficult
to convert this vague awareness into a definite statement or a definite pattern. Unless we can
recognize the dominant idea, we are going to be dominated by it. Liberation from rigid patterns
and the generation of alternative patterns are the aims of lateral thinking. Both processes can be
made easier if one can pick out the dominant idea. If one cannot be picked out the dominant idea
then any alternatives one generates are likely to be imprisoned within that vague general idea.
In the natural search for alternatives, one stops when he finds a possible solution. However, in
lateral thinking, the aim is to produce as many alternatives as possible. We are not concern with
the best solution, but rather, we try to have as many different approaches to solve a problem. We
can consider both reasonable and unreasonable alternatives as well. The purpose is to loosen up
rigid patterns and to provoke new patterns. It let the mind breaks free from normal convention,
this is them which natural search does not have.
Similar to problem solving in general. We should always look at a problem from different
angles. Squeeze out all possible information from the question and then focus on individual piece
of information to give us multiple views of the issue. This way of approaching a problem.
Gould enable us to come out with interesting solutions to a question -- the main essence of lateral
thinking. However, we face the possible trouble of picking the wrong focus and heading towards
the wrong direction, just like in the beginning stages of problem solving.
Scenarios
A scenario is described in simncy of as: "a series of events that we imagine happening in the
future." In other words, scenario writing is "making up stories about the future". The term
"scenario" has numerous meanings. It can be used as a description for "a hypothetical, likely or
unlikely, development or situation; a development which is described as that caused to some
extent by the actions and reactions of various actors: a desirable or nondesireable development or
situation". It has been asserted that it is a method that can be employed to focus attention on
causal processes and crucial decision points.
Scenarios serve three basic purposes:
1) To display the interactions among several trends and events in order to provide a holistic
picture of the future
2) To help check the internal consistency of the set of forecasts on which they are based
3) To depict a future situation in a way readily understandable by the non-specialist in the
subject area
Making Decisions
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The Nature of Decisions
Decision:- "...a choice between options..."
Utility Theory proposes that we make decisions to maximize utility or usefulness Statistical,
Catastrophe and Chaos Theories indicate future may be predictable/unpredictable as weather
long-term stable but short-term unstable, according to climate How can we choose between
options in dynamic situations if the future is unknowable? Can we/should we avoid making
decisions if the future is unknowable?
Distinct advantages that decision analysis has over the less formal decision-making techniques:
1. Decision analysis forces the decision-maker to consider all possible alternatives and their
corresponding outcomes.
2. Decision analysis provides an excellent way to evaluate the sensitivity of various factors
to overall profitability.
3. Decision analysis provides a means to compare the relative desirability varying degrees
of risk and uncertainty.
4. Decision analysis is a convenient and unambiguous way to communicate judgments
about risk and uncertainty.
5. Exceedingly complex options can be analyzed using decision analysis.
How do we go about making decisions anyway?
Decision-Makers' Biases
It seems that untrained humans, complex as ever, are prey to a wide variety of behavioral
influences and pressures when they make decisions. Some of the biases that affect their decisions
are:
o
o
o
o
o
o
o
o
o
Adjustment and Anchoring. Decision Maker selects a Datum and fits other data to
it improperly. Uses only freely available data. An event is believed to occur
frequently if it is easy to recall similar events
Conservatism. Failure to revise estimates as frequently as necessary
Data Saturation. Reaching premature decisions on too small a sample and then
ignoring further data
Self-fulfilling Prophecy. Values certain outcomes and acquires and analyses only
data that supports that outcome
Attribution Error. Associates success with inherent personal ability and failure
with bad luck.
Gambler's Fallacy. Assumes the occurrence of one set of events enhances the
probability of an event that has not yet occurred.
Habit. Familiarity with one rule results in its excessive use
Law of Small Numbers. Confidence in predictions based on small samples with
non-discomforting evidence, than in predictions based on large samples with
discomforting evidence
Order Effects. Order of information presentation affects retention and weighting
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o Outcome Irrelevant Learning. Use of an inferior rule leads to belief in results
because of inability to evaluate choices not selected
o Panic. Under stress, facing many options which cannot be evaluated, either selects
at random or fails to act at all
Explanation Based Decision Making
This covers cases of complex diagnostic decisions. Decision-making begins with the
construction of a causal model to explain the available facts and then base their subsequent
decisions on the causal interpretation imposed on the evidence. Alternative narrative accounts
are compared and the most coherent narrative account is chosen
Coherence is a function of:
o Completeness: The degree to which the story accounts for all the facts
o Consistency: The degree to which the story is internally consistent or
noncontradictory
o Plausibility: The degree to which the story is externally consistent or in line with
what you know about the world.
o Choice set: This is the set of specified possible outcomes for the decision.
o Match process: The decision maker picks a response from the choice set based on
the match between the explanation structure and the characteristics of the choices.
Representativeness Heuristic
People judge probabilities "by the degree to which A is representative of B, that is, by the degree
to which A resembles B." People thus reduce probability estimation to a similarity task. Most of
the time this works pretty well, but it can also lead to systematic biases.
The Conjunction Fallacy
Linda is 31 years old, single, outspoken and very bright. As an aristocrat, she was deeply
concerned with issues of discrimination and social justice.
Which is a more likely alternative?
Linda is a bank teller
Linda is a bank teller who is active in the feminist movement.
The Law of Small Numbers
I buy two lottery tickets keeping one for myself and giving one to you as a present. The lottery
winner is chosen by randomly picking 5 Ping-pong balls from a rotating kettle containing 31
ping-pong balls, which are numbered 0-30.Which lottery ticket would you rather have?
a. 1 2 3 4 5
b. 8 0 20 12 24
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Suppose that an unbiased coin is flipped three times, and each time the coin lands on HEADS. If
you had $100 to bet on the next toss, what side would you choose?(GAMBLER'S FALLACY)
People assume that a sample will be more representative of the population from which it was
drawn than the laws of probability would predict.
Planners might try to reconcile the issue of politically, or environmentally, sensitive sites that are
also military targets.
Finally, we have a classic decision tree. The comparison starts with establishing a comparative
outcome measure in the right hand column of boxes.
So, have you made your choice?
Which of the three decision-making methods is best suited to untrained humans, and which to
Mentats? Come to that which, if any, is valuable, or would you rate them suspect?
And that is one of the main issues with decision-methods
* Individuals and groups make decisions differently
* Experts make decisions differently from naive beginners
* Experts make decisions in different ways according to the urgency
* Experts under pressure "satisfice"
* Homo sapiens evolved by satisficing; remember, who trades off options when the large
carnivore is five steps behind?
Game Theory
Game theory is concerned with the decision-making process in situations where outcomes
depend upon choices made by one or more players. The word "game" is not used in the
conventional sense but describes any situation involving positive or negative outcomes
determined by the players' choices and, in some cases, chance. In order for game theory to apply,
certain assumptions must be made. The first is that each player is rational, acting in his selfinterest. In addition, the players' choices determine the outcome of the game, but each player has
only partial control of the outcome.
Types of Games
Cooperative Games
Games for which a binding contract is negotiated such that a joint strategy (i.e., collusion), is
feasible.
Noncooperative Games
Games in which contract enforcement and negotiation are infeasible; firms act independently.
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Static Games
Single-period games, i.e. played a single time or one in which the payoff does not vary across
time..
Repeated Games
Games played more than once over time.
Constant Sum Games
Regardless of strategies chosen, the payoffs sum to a constant or fixed value.
Zero-sum game
A zero-sum game is one in which no wealth is created or destroyed. So, in a two-player zero-sum
game, whatever one player wins, the other loses. Therefore, the player share no common
interests. There are two general types of zero-sum games: those with perfect information and
those without.
In a game with perfect information, every player knows the results of all previous moves. Such
games include chess, tic-tac-toe, and Nim. In games of perfect information, there is at least one
"best" way to play for each player. This best strategy does not necessarily allow him to win but
will minimize his losses. For instance, in tic-tac-toe, there is a strategy that will allow you to
never lose, but there is no strategy that will allow you to always win. Even though there is an
optimal strategy, it is not always possible for players to find it. For instance, chess is a zero-sum
game with perfect information, but the number of possible strategies is so large that it is not
possible for our computers to determine the best strategy.
In games with imperfect information, the players do not know all of the previous moves. Often,
this occurs because the players play simultaneously.
Non-zero sum games
The theory of zero-sum games is vastly different from that of non-zero-sum games because an
optimal solution can always be found. However, this hardly represents the conflicts faced in the
everyday world. Problems in the real world do not usually have straightforward results. The
branch of Game Theory that better represents the dynamics of the world we live in is called the
theory of non-zero-sum games. Non-zero-sum games differ from zero-sum games in that there is
no universally accepted solution. That is, there is no single optimal strategy that is preferable to
all others, nor is there a predictable outcome. Non-zero-sum games are also non-strictly
competitive, as opposed to the completely competitive zero-sum games, because such games
generally have both competitive and cooperative elements. Players engaged in a non-zero sum
conflict have some complementary interests and some interests that are completely opposed.
These may be divided into:
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* Positive-sum: Gains exceed losses.
* Negative-sum: Losses exceed gains.
* Variable Sum Games: Sum of the payoffs varies with the strategies.
Good Things
A "Good" Decision?
There is a basic the dilemma in judging whether a decision can be deemed good or not. It really
all depends on your viewpoint. You can take either of two viewpoints: 1. A decision is "good" if the decision maker has taken account of all the relevant data, has
weighed up the pros and cons, and has developed a balanced judgment
2. A decision is "good" of the out-turn is that which the decision-maker intended
A "Good" Model?
The problem with the last three decision criteria is that while they do deal directly with questions
of value and choice, they do not deal explicitly with element of uncertainty. As they offer the
decision maker no mechanism by which to incorporate information about his uncertainty co
Using statistical significance as the test of model validity can lead modelers to mistake historical
correlations for causal relationships. It also can cause them to reject valid equations describing
important relationships. They may exclude an equation as statistically insignificant simply
because there are few data about the variables, or because the data don't contain enough
information to allow the application of statistical procedures.
Ironically, a lack of statistical significance does not necessarily lead some modelers to the
conclusion that the model or the equation is invalid. When an assumed relationship fails to be
statistically significant, the modeler may try another specification for the equation, hoping to get
a better statistical fit. Without recourse to descriptive, micro-level data, the resulting equations
may be ad hoc and bear only slight resemblance to either economic theory or actual behavior.
Alternatively, the modelers may attempt to explain the discrepancy between the model and the
behavior of the real system by blaming it on faulty data collection, exogenous influences, or
other factors concerning the states of nature (that is, probabilities) these criteria must be
considered naive.
"Good" Decision-Making and/or Problem-Solving
An effective process must have:
* A clearly defined problem
* Agreement on who has the responsibility for making the decision
* Agreement of participants on procedures and methods
* An open and trusting environment to generate alternatives
* Appropriate data and information
* An open and trusting environment to analyze alternatives
* An action plan that defines responsibilities and accountabilities
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* A commitment from Mentat members to support and implement the Mentat's decisions.
Perfecting "good" Models
The forecasts produced by models often don't square with the modeler's intuition. When they feel
the model output is wrong, many modelers simply adjust their forecasts. This fudging, or add
factoring as they call it, is routine and extensive. Of course, the adjustments made by add
factoring are strongly colored by the personalities and political philosophies of the modelers.
Add factoring has been criticized on the grounds that it is unscientific. They point out that,
although the mental models used to add factor are the mental models of seasoned experts, these
experts are subject to the same cognitive limitations other people face. And whether good or bad,
the assumptions behind add factoring are always unexaminable.
Types of Decisions
Decisions Under Certainty
Decisions under certainty are the kind we make when we go shopping or choose a place to go on
vacation. The task in such decisions is to examine the properties of the alternatives and to figure
out which of the alternatives we like best. When we make a choice, we assume that we will get
the alternative we want.
Decisions Under Uncertainty
Decisions under uncertainty are like decisions under risk in that they are also governed by a
chance event. They differ from decisions under risk because they occur in situations in which we
can't put our faith in probabilities. First, the relevant probabilities may be unknown. Second, if
we are making an important decision that involve catastrophic outcomes, probabilities may be of
secondary importance.
A choice of strategy must be made with no knowledge of the likelihood of each of the events.
There are many decision criterion that can be chosen. Four will be considered.
Consider decision making under extreme uncertainty. In this scenario the states of nature affect
the value of the decision's payoff, but cannot be controlled by the decision maker. Some decision
theorists suggest following the maximax rule. Under this rule the decision maker identifies the
most favorable outcome for each possible decision and chooses the decision with the maximum
payoff of all of the best outcomes. This is also known as the optimistic criterion as it seeks the
best of all possible worlds and assumes (or hopes) this is what will happen.
Decisions Under Risk
Gambling decisions are typical of decisions under risk. A chance event, the position at which a
metal ball comes to rest on the roulette wheel, determines the outcome of the gambler's choice.
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An essential feature of decisions under risk is that we can calculate a probability for the effect of
the chance event.
Decisions Under Conflict
Decisions under conflict are common in competitive games, like chess and tennis, and in
business and war. When you choose a move in chess, or a strategy in tennis, you know that your
opponent will do his best to counter your move or foil your strategy.
Each decision type requires a different approach. In decisions under certainty, the main difficulty
is deciding which alternative is best. In decisions under risk and uncertainty, the big problem is
dealing with the effects of chance; and in decisions under conflict, it is taking account of the
hostile action of our opponent.
Decision Making Strategies
Equal Likelihood Criterion
Assume each event is equally likely. Then choose the strategy with the best-expected return.
The Satisficing Strategy
The process shown above has a distinguishing characteristic. The decision-maker(s) try to
consider all the possible options, and to trade-off between them in order to find the preferred
option. While this might seem logical, it is not necessarily how human's evolved to make
decisions under pressure.
We evolved an innately human ability to make fast decisions under fight-or-flight pressures. If
we had not, we would not have evolved as a species. Under such conditions, we do not consider
and weigh up all the options - that would be naive. Instead, we use our experience of what has
worked before in similar situations. We might mentally generate options, but we will stop doing
so as soon as we identify and option that will serve the purpose. At that point we will go with the
selected option.
The initial satisficing decision might have been wide of the mark, even for an expert decisionmaker - he or she may have read the cues wrong. However, this is a cyclic process. As the action
unfolds, the decision-maker has expectations that can be verified by the merging cues. If the cues
are as expected, fine. If, on the other hand, the cues are out of line with expectations, then the
expert decision-maker will reevaluate the situation and satisfice again.
So, satisficing is a decision-making process employed instinctively by an expert under time
pressure, and it "homes in" on a final solution.
Decision-making situations that we meet in daily experience are often a good deal messier than
the idealized situations we have described above. Perhaps the most important complication we
encounter is that we may be forced to search for alternatives.
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The Minimax Strategy
This strategy is a very conservative, pessimistic strategy that assumes that whatever action we
choose, nature is against us and will cause the worst possible outcome.
The mini-max strategy calls for choosing the action that gives us the best (largest) of these
minima. That is, it chooses the action whose worst possible outcome is not as bad as the worst
possible outcomes of the other actions.
The mini-max strategy has the nice property that it guarantees an outcome that is no worse than
the minimum value for the action. The outcome may be better than that minimum, but it will
certainly be no worse. However, this strategy, which focuses on preventing disaster, has the
unfortunate property that it may eliminate the best outcomes from consideration.
The Maximin Strategy
Maximin strategy, also known as the Pessimistic Decision Criterion or the Widows' and Orphans'
Criterion. Choose the strategy that give the best possible result when the worst occurs.
Mean-Variance Analysis
Using this approach, the analyst follows these rules:
* Prefer the action with the highest expected value and the lowest variance.
* Given equal variances for different actions, choose the one with the highest expected value
* Given equal expected values, choose the action with the smallest value. This approach
combines information about choice, chance, and value, which makes it better than the other
rules. The main drawback is that there is a situation that is indeterminate, namely unequal
expected values and unequal variances. One action may have a greater expected value, but also a
greater variance than the others. Mean-variance analysis offers no decision in this case, which is
unacceptable to the decision maker.
Coefficient of Variation Analysis
The coefficient of variation of an action is the ratio of the standard deviation of the return to the
expected value. This rescales the problem and translates absolute risk into relative risk. The rule
is to choose the action with the smallest coefficient of variation as this is thought to be the least
risky course of action. The main problem with this criterion is that the decision maker is assumed
to be extremely risk averse, when he may not be. It forces him to give up the chance of large gain
because of the variability involved, and he may not want that.
The Maxi-max Strategy
A more adventurous approach to making decisions is to use the maxi-max strategy, also known
as the Optimistic Decision Criterion or the Gambler's Criterion. This is an optimistic strategy that
assumes that nature will cooperate with us to provide the best possible outcome for the action we
choose. The maxi-max strategy chooses the action that yields the best of the best possible
outcomes.
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Choose the strategy that gives the greatest possible payoff, no matter what the risk of a large
loss.
The Proportionate Strategy
This strategy allows a compromise--depending on how optimistic you feel--between the very
pessimistic mini-max strategy and the very optimistic maxi-max strategy. To use the Hurwicz
strategy, select a value between 0 and 1 for the coefficient of optimism, A. Low values of A,
such as 0.1 or 0.2, are pessimistic and reflect a belief that bad things are more likely to happen.
High values, such as 0.8 or 0.9, are optimistic.
Maximin Strategy
A slightly more sophisticated idea is the maximin criterion. Under this rule the decision maker
must identify the worst possible outcome for each decision and then choose the decision with the
best payoff from among these. This is a pessimistic criterion, as it seeks to avoid the worst case
among but holds no hope of anything better.
Maximum Expected Utility (or Bayes) Strategy
The advantage of this approach is that it uses all the information available to the decision maker,
includes no superfluous information, and produces decisions which are consistent with the
decision maker's own values. It also provides a formal mechanism by which he can incorporate
his own judgment and experience into the decision. It is not guaranteed to produce the "right"
decision in every situation, but to expect such is naive, owing to the very uncertainty built into
the problem. What this approach does guarantee is rationality, a property of the decision making
process, not of the product. This is the most anyone can hope for, and is the key to economic
decision making under uncertainty.
Minimizing Maximum Regret Strategy
Still more sophisticated is the minimax regret criterion. Choose the strategy for which the
maximum regret. For each state of nature there is one action leading to the best possible
outcome. The difference in value between this and the outcome associated with another decision
is the potential regret (or opportunity cost) of that decision. Under the minimax regret rule the
decision maker must first determine the maximum potential regret associated with each action.
Then he is to choose the decision with the minimum of these maximum potential regrets. The
idea here is that it protects managers from making decisions that turn out not to be best after the
state of nature is known. The drawback is that this approach will be overly conservative (that is,
risk averse) when the chance of an undesirable state of nature is small.
A decision procedure which works very well for those cases in which expected value fails is the
strategy of minimizing maximum regret. Here regret means pretty much what you would expect.
We can take the difference between the value of the outcome you actually obtained and the
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maximum value you could have obtained if you had chosen a different alternative as a measure
of regret.
(1) Compute the possible regret for each alternative under each state of nature.
(2) Identify the maximum possible regret for each alternative.
Choose the alternative with the smallest maximum regret.
Mixed or Pure Strategies?
There is a simple test to determine whether a pure or a mixed strategy is best. If the maximum of
the row minima (the maxi-min) equals the minimum of the column maxima (the mini-max), then
a pure strategy if best. In this situation, each player does best playing the mini-max strategy. If
we play our mini-max strategy, our opponents will always lose by deviating from their mini-max
strategy.
Combined Strategies
The first step in the right direction is to assume a probability distribution on the outcomes (states
of nature). This step is subjective. Ideally, the analyst should try to acquire as much information
as possible about the problem, marshall all his wisdom, intuition and judgment and encode his
uncertainty as a probability distribution. If the set of possible outcomes is countable then a
discrete probability distribution will suffice. If the set of outcomes in uncountable (measurable)
then he must use a continuous model, a probability density function (such as the normal
distribution). In either case positive probability can then be associated with ranges of values of
the random value in question. Furthermore, the center of this distribution can be indicated by its
expected value and the dispersion about this center by the variance.
Other Decision Methods
1. Majority Rule Voting
Decisions are make by voting with majority ruling.
2. Minority Rule Voting
A sub-group of the Mentat makes the decision for the entire Mentat
3. Autocracy
A decision is made by a single person who has enough authority to carry out the decision
4. Autocracy with Polling
A single person solicits opinions, then make the decision
5. Decision by Non-decision
No conclusion or agreement is reached and no single person has sufficient authority to make a
unilateral decision
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6. Consensus
Mentat agrees to decision and commits to it
7. Unanimity
Every person on Mentat agrees and commits to it.
Values, Objectives and Goals
The Client's Values and Goals
The first difficulty with optimization models is the problem of specifying the objective function,
the goal that the model user is trying to reach. The answer depends, of course, on the perspective
of the person you ask.
The objective function embodies values and preferences. Intangibles often can be quantified, at
least roughly, by breaking them into measurable components. There are also techniques available
for extracting information about preferences from interviews and other impressionistic data. Just
the attempt to make values explicit is a worthwhile exercise in any study and may have
enormous value for the clients of a modeling project.
It is important that potential users keep in mind the question of values when they examine
optimization models. The objective function and the constraints should always be scrutinized to
determine what values they embody, both explicitly and by omission. Imagine that a government
employee, given responsibility for the placement of sewage treatment plants along a river,
decides to use an optimization model in making the decision. The model has as its objective
function the cheapest arrangement of plants; a constraint specifies that the arrangement must
result in water quality standards being met. It would be important for the user to ask how the
model takes into account the impacts the plants will have on fishing, recreation, wild species, and
development potential in the areas where they are placed. Unless these considerations are
explicitly incorporated into the model, they are implicitly held to be of no value.
Optimization techniques can be extremely useful. But they must be used for the proper problems.
Optimization has substantially improved the quality of decisions in many areas. Whenever the
problem to be solved is one of choosing the best from among a well-defined set of alternatives,
optimization should be considered. If the meaning of best is also well defined, and if the system
to be optimized is relatively static and free of feedback, optimization may well be the best
technique to use. Unfortunately, these latter conditions are rarely true for the social, economic,
and ecological systems that are frequently of concern to decision makers.
Value to the Mentat
Criteria of Significance
The normal approach to judging the significance of a thing is to evaluate its qualities and
characteristics against a list of criteria. As one example, the significance in terms of two groups
of criteria:
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1. The importance of an item in displaying information and allowing analysis of the
evolution that item
2. The contribution a feature makes to defining the characteristics of an item.
Virtually every study to date has commenced by drawing up - in greater or lesser specific detail such a list of criteria in terms of which significance will be judged, and has then proceeded to
identify as significant a suite of things which best fit those criteria.
A development aimed at making this approach more systematic and defensible has been to
classify groups of phenomena which are of interest, to draw up a type profile of each class of
phenomena within those classified groups, and to then compare individual examples of the
phenomena in each class against the type profile for that class, so as to determine which
examples fall above or below a 'threshold of significance'. In this approach, to fall above the
threshold of significance essentially means that the example under consideration fits the
characteristic type profile for its class to an above - average degree of excellence - that is, it is a
particularly well-developed or well-expressed representative example of its class. In this
approach, the defining characteristics of a type profile are the criteria against which the
(representative) significance of things will be judged.
These criteria or type-profile based approaches to judging significance are the most obvious and
logical means available of judging significance, and will most likely remain so.
The Basis for Choosing Criteria of Significance
However these approaches, taken in isolation, beg the philosophical question of why the
particular chosen criteria (or type profile characteristics) determine significance, and not some
other criteria. This leaves open the question of whether the criteria used are purely arbitrary, or
have some justifiable rationale underpinning them. Although not without value, these may be
relatively crude criteria from many perspectives, and it is important to guard against placing
undue emphasis on them. From some perspectives such as the scientific and ecological, more
subtle attributes may in fact be of more importance.
To define a basis for choosing criteria in terms of which to judge value, it is first necessary to
acknowledge that there is no absolute basis on which to determine what the 'correct' criteria are.
The decision to adopt particular criteria to assess significance is in the end a value judgment that
can in the final analysis only be subjective. This does not mean, however, that the choice of
criteria need be arbitrary or illogical. The lack of an ultimate, objective basis for value judgments
does not imply that 'anything goes'. Instead, it is rational to choose criteria which best reflect a
consensus of opinion as to what it is about natural phenomena that is important and worth
protecting. That is to say, the underlying basis for choosing criteria to judge significance must be
a judgment, or decision, as to what it is about the natural world that we hold to be of value.
It is important to be aware of the implications of the idea that a choice of criteria for judging
significance will be based on a consensus of opinion about values. This approach is inherently
fraught with danger, since the consensus of opinion as to the best values to adopt may change
over time, and indeed the history of ethical thought is replete with examples of this. The
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problem, however, is that since we are making a value judgment, there is no ultimate or absolute
authority to which we can appeal to determine the 'correct' values and criteria to adopt, and so
consensus would appear to be the best, or perhaps only, means available. One might argue, in
fact, that the ultimately subjective nature of value judgments means that we have only two
choices anyway, namely to make a purely personal judgment, or to accept a consensus judgment.
Both approaches have their place in the development of values and ethics, with personal
rebellion against a consensus opinion often being a catalyst for what later comes to be regarded
as progress in values and ethics.
In general however choosing criteria for significance on the basis of a broad consensus of
opinion would appear to be the best method available to us, since it will at least reflect a large
body of thought and opinion on what it is which can be perceived to be of value.
It is useful to think of this as an ethical issue, since we are trying to determine how we should act
in relation to natural phenomena, and to do this we need to decide what we consider to be the
values of natural things so that we can act to protect those values. It goes without saying that the
preceding discussion has only skimmed the surface of a large and complex philosophical issue
revolving around ethics and values.
However there is an expectation amongst many members of the public that professional
assessments of the significance of a thing should be objective, empirical and repeatable - in other
words, scientific. This is in principle not possible, since a significance assessment is at bottom a
value judgment, not an empirical measurement of some objective quantity. It is important to fully
recognize this fact, and be aware that whilst we may (and should) use objective criteria to
measure how well a phenomenon contributes to a certain type of value, the relevance of that
underlying value to conservation is itself subjectively determined. The usefulness of a
significance assessment should not be judged against a yardstick of objectivity so much as one of
explicitness. That is, we need to spell out the values in terms of which we are judging
significance since this provides the only transparent means for peer review or public review to
properly assess the judgments we have made. Explicitness and the capacity for peer review that it
promotes provide the only practical way of responding to social expectations of objectivity in the
face of the manifestly judgmental characteristic of significance.
As with many aspects of ethical thought, the consensus of ethical opinion relating to nature has
changed and developed over time. The simplest view on conservation is the anthropocentric or
utilitarian one: that the important conservation values of nature are those that are directly useful
to humans.
Choosing Criteria of Significance
The implication of the above discussion is that we judge the significance of particular
phenomena by a two-stage process, which involves firstly a value judgment, and secondly an
objective assessment against specific criteria relating to those values judged to be important:
1. We implicitly or explicitly make a judgment as to what it is that is of value. There is no
absolute basis for making such a judgment, however neither need it be arbitrary. In
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choosing the values we consider most meaningful, we have regard to the broad consensus
of opinion, although the ultimately subjective nature of such value judgments means that
we may be justified in advocating newer or less popular conceptions of what is of value.
In either case, we need to be explicit or transparent about these, and to be able to argue
that they constitute a useful value set in terms of which to judge significance.
2. The Mentat now can objectively assess particular phenomena to determine how important
(i.e., how significant) they are in contributing to those values. This is done by drawing up
a list of criteria by which the contribution of things to a particular value can be measured,
and then objectively assessing how well any given example of a phenomenon measures
up against those criteria.
Choice of Values
The values in terms of which natural phenomena are widely considered to be significant have
been mentioned above. These broad value sets, which incorporate and synthesize most reasons
that have been advanced in the literature for considering items to have value, are:
o Intrinsic Values
o Ecological or Natural Process Values
o Anthropocentric or (Geo)heritage Values
It is advocated here that all three of these value sets are important, since they each relate directly
to one or both of the aims of. All three of these value sets should be used as a basis for drawing
up objective criteria in terms of which to judge the conservation significance of specific
phenomena.
Choice of Objective Criteria for Assessment of Values
The following paragraphs discuss the sorts of objective criteria that can be used to assess the
significance of particular phenomena against each of the three basic value sets identified above:
Intrinsic Values and Representativeness
If we agree that items in general have intrinsic value, then it makes little sense to single out some
particular thing as having intrinsic value, and say that other n things do not have such value. In
fact, the concept of intrinsic value undermines value systems that differentiate things on scales of
relative significance and ultimately put people at the top. However, for this reason it is difficult
to 'operationalise' - i.e., to quantify in an objective way and act upon in practical conservation
management - the concept of intrinsic value, since it does not provide any direct, practical means
of differentiating between things of higher and lower priority for conservation. 'Intrinsic value' is
a concept that cannot be directly measured or quantified.
Nonetheless, the idea of intrinsic value is fundamental to the approach because it makes explicit
the idea that human interests should not be considered the sole arbiter of how we manage the
environment. A recognition of intrinsic values makes us consider all the impacts of our actions
on the environment, not just those particular impacts which directly our interests.
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From this perspective, it is desirable to find some way of incorporating the idea of intrinsic value
into conservation strategies and management actions. The approach taken in this discussion is to
consider intrinsic value as an underlying value that can be 'operationalised' through surrogate
means revolving around the concept of 'representativeness'. The logic of this 'surrogate' approach
proceeds as follows:
If we consider that items as a whole have intrinsic value, but also allow that Mentats have a
legitimate right to exploit and consume some specific resource, then we must in practice
determine which things we can ethically exploit despite their intrinsic value, and which we
should conserve because of their intrinsic value. In this approach, we do give ethical
consideration to all things, but in certain cases we make the ethical judgment that our own
justifiable utilitarian interests over-ride the intrinsic value of certain natural things.
Now, if the justifiable requirements of society mean that we cannot respect the intrinsic value of
everything to the extent of maintaining each and every individual thing in its natural state, then it
would seem that the next best alternative is to endeavor to at least maintain the diversity of
things. That is, we need to endeavor to maintain at least representative samples of all the
elements within the variety of existence. In other words, to respect the intrinsic value of items
implies that we should try to ensure that our alteration, exploitation and consumption of the
resource does not result in entire classes of phenomena ceasing to exist, or becoming incapable
of operating and changing at natural rates and magnitudes.
A procedure by which we can objectively assess the representative significance of specific
elements of this variety, in order to identify a suite of representative phenomena whose
conservation will best respect the intrinsic value of them involves undertaking a systematic
inventory process in which we first classify the range of phenomena which constitute the system
and then identify the best or most representative examples, in good condition, of each class of
phenomenon in our classification.
In this approach, each class of phenomenon within our classification is defined in terms of its
type profile, and it is the characteristics of the type profile that constitute the objective criteria
against which we ultimately measure the intrinsic value of specific phenomena.
The approach of using 'representativeness' as a surrogate for intrinsic value cannot be perfect or
absolute, as is implied by its surrogate nature. The notion that diversity itself is a value worth
aiming to preserve is itself simply a value judgment. However, as noted above, all judgments of
significance must ultimately be based on value judgments which cannot be absolute and the
'representative' approach goes a long way towards satisfying widely held views on why
phenomena may be of conservation value.
Process Values
To assess the value of an item, we need to determine the role that that specific item plays in the
broader processes of which it is a part. Such a determination is a matter of scientific research and
monitoring. This allows us to determine whether the disturbance, degradation or destruction of
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the phenomenon in question will result in an unacceptable degree of change or degradation to the
broader processes of which it is a part.
The limits of acceptable change will vary depending upon the sensitivity of the particular
situation and also to some extent on the context.
In any case, the criteria in terms of which we can measure the value of a particular element
consist of objective scientific data on the role that that element plays in maintaining the natural
processes in its broader environment. Measured against such objective criteria, an element would
be considered to have high significance if its degradation or destruction would cause changes to
the broader environment that is beyond the limits of acceptable change that can be defined for
that environment.
This of course raises the question of how we objectively define the Limits of Acceptable
Change; however, for the purposes of the present discussion this question is a separate issue that
need not be addressed here.
The assessment of systems as having high significance in virtue of their ecological values has
been a strong theme in a number of detailed studies.
Anthropocentric Values
We can determine the degree to which particular features are of direct anthropocentric value to
human society by determining the degree to which particular elements are in fact valued by
humans. This approach bypasses the problem that people may value specific items for highly
subjective reasons and simply measures the degree to which people do in fact value certain
things.
Something may be valued for a variety of specific anthropocentric reasons (or values). The
following list notes some of these reasons, and indicates objective criteria by which we can
measure the degree to which people consider particular phenomena significant in terms of each
reason or value:
Geoheritage (anthropocentric) Value: Criteria (by which value to humans can be measured)
Aesthetic value: Formal landscape quality assessment methods; Frequency with which
phenomenon has been featured in paintings and photographs; Community opinion (assessed
by polling?).
Scientific/research/educational value: Degree of excellence with which a feature is considered to
display aspects of the nature and development of geological, landform or soil systems in its
region; Use as type sites; Frequency of citation in scientific papers; Use as a teaching site;
Whether feature is a site at which important measurements or discoveries have been made;
Usage value: Frequency of usage. Degree to which relevant groups value feature as a venue for
their activities (determined by poll or literature survey);
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Social/historical value: Degree to which a feature has played a role in the life or development of
past or present human communities (as determined by historical and archaeological research);
'Sense of Place' value: Degree to which a human community regards a feature as integral to the
'identity' of their place
Spiritual/religious value: Degree to which a feature figures as sacred or holy in a community's
spiritual life
In practice these criteria are often measured in a fairly rough way using essentially anecdotal
evidence. However, it is possible to measure each criterion in a relatively rigorous fashion. It
must of course be acknowledged that such procedures have limitations.
Descriptive Models of Decision Making
What the rationale choice models assume
* People always try to maximize their utility
* People can examine all options
* People know the distribution of outcomes
There are reasons to doubt both of these assumptions
* Experimental evidence shows that that people sometimes choose options with lower expected
utilities (risk aversion and certainty)
* Humans have limited sensory and cognitive capacities such that it may be impossible to
consider all possible alternatives and all relevant features of the problem.
Bounded Rationality
Decision makers don't optimize utility, rather they settle for alternatives that are good enough.
Individuals must generate alternatives themselves. Therefore individuals may not consider all
alternatives.
Alternatives are evaluated against a threshold as they are generated. When the threshold is
satisfied generation of alternatives stops Elimination by aspects
Decision makers have several criteria that they consider when making decisions. These criteria
are ordered in terms of importance. Each criteria has a threshold below which an alternative is
rejected
Criteria are looked at sequentially based on order of importance. The process ends when only
one choice is left or the choices are so limited that an exhaustive consideration of all criteria can
be accomplished
The Availability Heuristic
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The availability heuristic states that people judge the probability of a class by the ease with
which instances can come to mind
Consider the letter R
Is R more likely to appear in:
A. The first position of a randomly sampled word
B. The third position of a randomly sampled word
Results
6. 69% of subjects choose option A
7. Most subjects thought A was twice as likely as B
Risk and Uncertainty in Managerial Economics
Managerial economics is applied microeconomics. It has both a descriptive side and a
prescriptive side. The descriptive part seeks to explain and predict such microeconomic
phenomena as consumer demand for a product and the way the firm or industry responds to that
demand. The prescriptive (or normative) part seeks to guide the manager or concerned official
toward optimal economic decision-making.
Traditionally, microeconomic theory has assumed that deterministic models were adequate to
explain and predict economic phenomena, such as price and output levels. In a deterministic
model it as assumed that complete and perfect information is available to all economic agents,
that is, there is no uncertainty about parameter values in the model, nor any element of risk. Then
the forces of supply and demand can be modeled with equations and solved for the equilibrium
condition. Furthermore, the profit maximizing condition can be easily derived and implemented.
The advantage of this deterministic modeling approach is that simple models can be postulated
and solved analytically.
The drawback to this approach is that much realism is sacrificed for the sake of simplicity. As
uncertainty is in fact pervasive and ubiquitous in reality, the deterministic approach may be
abandoned in favor of a stochastic modeling approach, which explicitly takes this problem of
imperfect information into account. It is the effect of this lack of perfect information on
managerial economics in general and economic decision making in particular that we wish to
consider in this paper.
At this point we note that some distinguish between risk and uncertainty. Risk is taken to mean a
situation in which the outcome is not known in advance but the possible outcomes can be listed
and assigned probabilities. Uncertainty is often taken to exist when probabilities cannot even be
assigned to the possible outcomes, nor all the outcomes listed. In management economics this
distinction is nonexistent. Rather, these two categories are really points along a continuum of
imperfect or incomplete information, ranging from mild uncertainty where some information
missing to extreme uncertainty when much information needed for decision making missing. It is
always possible for the modeler to assume a probability model for the stochastic component of a
system or assign probabilities subjectively. By gathering all relevant information, data,
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judgment, and operational experience and encoding this information in the form of a probability
distribution, the analyst can manage uncertainty of any type, origin, or degree. As long as this
modeling effort is done in a manner that is consistent with the mathematical laws of probability,
including Bayes' Theorem, the decision maker will be coherent.
Decision Theory
States of Nature
* Certainty, the deterministic case
* Uncertainty, without probabilities
* Risk, with probabilities
Payoffs
* Payoff tables, for discrete states and decisions
* Payoff formulas
Utility
Utility is usually a nonlinear function of monetary payoff. For example, as wealth increases the
marginal utility of another dollar decreases. Also, a loss and a gain might have equal monetary
value but different utility.
Required Environment
* Knowledge of payoffs
* Knowledge of probabilities
* Favorable odds
* Ability to cumulate gains with losses
* Play many times
* Don't bet the whole company
Decision Trees
Sequences of Decisions
* States of nature
* Payoffs
* Probabilities
All of these can be dependent on prior decisions.
Procedure
1. Construct the geometry of the tree
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1.
2.
3.
2.
3.
4.
identify initial decision alternatives
for each alternative decision identify the possible states of nature
for each state of nature go back to the first step
Assign probabilities wherever there are alternative states of nature.
Assign payoffs to the final branch ends of the tree
Starting with the final branch ends compute expected values of the preceding branches.
This is called folding back.
5. Repeat the preceding step back to the root of the root.
6. Reverse direction, away from the root, always taking the branch with the highest
expected value.
The Lexicographic Method
The lexicographic method is so-named because of its resemblance to the procedure for ordering
words in the dictionary, To decide which of two words comes first, one looks at the first letter.
With the lexicographic method, we must specify the order of importance of the properties of the
alternatives. We should be aware that other decision-makers might choose to order the properties
differently and as a result arrive at different decisions.
To make a decision by this method, consider the most important property first. If one alternative
is better than the other alternatives on the most important property, then that alternative is the
one chosen.
Additive Weighting
The additive-weighting method takes all of the properties into account but does not give them
equal weight. The more important properties receive heavy weights and the less important ones
lighter weights.
To use the additive-weighting method, one must have numbers both for weights of the properties
and for the values of the properties.
To make a decision by the additive-weighting method, multiply numerical values of the
properties by the weights of the properties for each alternative. Then choose the alternative with
the largest sum as "best."
Simulationist
Mentats who free their reasoning from dependence on absolutes, and who can correct for
assumptions hidden in another's inferences achieve the title of Simulationists. The Simulationist
conceives and proposes in detail alternate futures, courses of action, and extrapolations of events.
The purpose of a simulation is to give the participant practice in the skill, instead of just talking
about the skill. A good simulation has realism, is applicable to the course material, is relevant to
the business world, involves Mentats, and has timely feedback.
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Assumptions
Many scientists have adopted or reinvented Occam's Razor as in Leibniz' "identity of
observables" and Isaac Newton stated the rule: "We are to admit no more causes of natural things
than such as are both true and sufficient to explain their appearances."
The most useful statement of the principle for scientists is: "when you have two competing
theories which make exactly the same predictions, the one that is simpler is the better."
Beware of optimization models that purport to forecast actual behavior. The output of an
optimization model is a statement of the best way to accomplish a goal. To interpret the results as
a prediction of actual behavior is to assume that people in the real system will in fact make the
optimal choices. It is one thing to say, "in order to maximize profits, people should make the
following decisions," and quite another to say "people will succeed in maximizing profits,
because they will make the following decisions." The former is a prescriptive statement of what
to do, the latter a descriptive statement of what will actually happen.
Assumptions of a Liner Regression
a. The error term is normally distributed
b. There is no serial correlation among error terms
c. Magnitude of the error term is independent of the size of any of the independent variables
d. Assumptions can be tested though analyses of the residuals
Assumptions of a Simulation
Any model is only as good as its assumptions. In the case of simulation models, the assumptions
consist of the descriptions of the physical system and the decision rules. Adequately representing
the physical system is usually not a problem; the physical environment can be portrayed with
whatever detail and accuracy is needed for the model purpose. Also, simulation models can
easily incorporate feedback effects, non-linearities, and dynamics; they are not rigidly
determined in their structure by mathematical limitations as optimization models often are.
Simulation models do have their weak points, however. Most problems occur in the description
of the decision rules, the quantification of soft variables, and the choice of the model boundary.
Accuracy of the Decision Rules
The description of the decision rules is one potential trouble spot in a simulation model. The
model must accurately represent how the actors in the system make their decisions, even if their
decision rules are less than optimal. The model should respond to change in the same way the
real actors would. But it will do this only if the model's assumptions faithfully describe the
decision rules that are used under different circumstances. The model therefore must reflect the
actual decision-making strategies used by the people in the system being modeled, including the
limitations and errors of those strategies.
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Unfortunately, discovering decision rules is often difficult. They cannot be determined from
aggregate statistical data, but must be investigated first hand. Primary data on the behavior of the
actors can be acquired through observation of actual decision-making in the field, that is, in the
boardroom, on the factory floor, along the sales route, in the household. The modeler must
discover what information is available to each actor, examine the timeliness and accuracy of that
information, and infer how it is processed to yield a decision. Modelers often require the skills of
the anthropologist and the ethnographer. The best simulation modeling draws on extensive
knowledge of decision making that has been developed in many disciplines, including
psychology, sociology, and behavioral science. The diverse background knowledge of a Mentat
will be essential for the correct formulation of a simulation model to avoid oversimplification
and other inaccuracies.
Soft Variables
The majority of data are soft variables. That is, most of what we know about the world is
descriptive, qualitative, difficult to quantify, and has never been recorded. Such information is
crucial for understanding and modeling complex systems. Yet in describing decision making,
some modelers limit themselves to hard variables, ones that can be measured directly and can be
expressed as numerical data. They may defend the rejection of soft variables as being more
scientific than "making up" the values of parameters and relationships for which no numerical
data are available. How, they ask, can the accuracy of estimates about soft variables be tested?
How can statistical tests be performed without numerical data?
Actually, there are no limitations on the inclusion of soft variables in models, and many
simulation models do include them. After all, the point of simulation models is to portray
decision-making as it really is, and soft variables-including intangibles such as desires, product
quality, reputation, expectations, and optimism - are often of critical importance in decision
making. Imagine, for example, trying to run a facility solely on the basis of the available
numerical data. Without qualitative knowledge about factors such as operating procedures,
organizational structure, political subtleties, and individual motivations, the result would be
chaos. Leaving such variables out of models just because of a lack of hard numerical data is
certainly less "scientific" than including them and making reasonable estimates of their values.
Ignoring a relationship implies that it has a value of zero-probably the only value known to be
wrong!
Of course, all relationships and parameters in models, whether based on soft or hard variables,
are imprecise and uncertain to some degree. Reasonable people may disagree as to the
importance of different factors. Modelers must therefore perform sensitivity analysis to consider
how their conclusions might change if other plausible assumptions were made. Sensitivity
analysis should not be restricted to uncertainty in parameter values, but should also consider the
sensitivity of conclusions to alternative structural assumptions and choices of model boundary.
Sensitivity analysis is no less a responsibility for those modelers who ignore soft variables.
Apparently hard data such as economic and demographic statistics are often subject to large
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measurement errors, biases, distortions, and revisions. Unfortunately, sensitivity analysis is not
performed or reported often enough. Many modelers have been embarrassed when third parties,
attempting to replicate the results of a model, have found that reasonable alternative assumptions
produce radically different conclusions. (See: Chaos Theory)
Model Boundary
The definition of a reasonable model boundary is another challenge for the Mentat. In theory,
one of the great strengths of simulation models is the capacity to reflect the important feedback
relationships that shape the behavior of the system and its response to policies. In practice,
however, many simulation models have very narrow boundaries. They ignore factors outside the
expertise of the model builder or the interests of the sponsor, and in doing so they exclude
important feedbacks.
The consequences of omitting feedback can be serious. A broad model boundary that includes
important feedback effects is more important than a great amount of detail in the specification of
individual components.
Overly narrow model boundaries are not just a problem in energy analysis. Most of the models
used by government agencies rely significantly on exogenous variables. Population models
assumed food production was exogenous. Agriculture models assumed that energy prices and
other input prices were exogenous. Energy models assumed that economic growth and
environmental conditions were exogenous. Economic models assumed that population and
energy prices were exogenous. And so on. Because they ignored important intersectional
feedbacks, the models produced inconsistent results.
Assumptions in Econometric Models
The chief weak spots in econometric models stem from the assumptions of the underlying
economic theory on which they rest: assumptions about the rationality of human behavior, about
the availability of information that real decision makers do not have, and about equilibrium.
Many economists acknowledge the idealization and abstraction of these assumptions, but at the
same time point to the powerful results that have been derived from them. However, a growing
number of prominent economists now argue that these assumptions are not just abstract- they are
false.
Assumptions in "Best Fit" Equation
By simple random search, the analyst looks for the set of variables and functional forms that give
the best equations. In this context the best equation is going to depend heavily upon the prior
beliefs of the analyst. If the analyst believes that interest rates do not affect the velocity of
money, he finds a 'best' equation that validates his particular prior belief. If the analyst believes
that interest rates do affect the velocity of money, he finds a 'best' equation that validates this
prior belief.
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Simulation Methods
Simulations combine an interaction potential with a numerical solution of the equation of motion
followed by statistical treatment of the results.
The main purpose of the simulation is insight, not data. Even if simulations may contribute to
both theory and experiments, the most important result of simulations is undoubtedly the
development of intuition and ideas through interactive simulations.
Limitations of simulation
The first limitation of simulations is that agreement between the simulation and the behavior of
the real system at the macroscopic level proves nothing about the simulation at the microscopic
level. Assessment of the realism of simulation requires an insight that transcends the simulation.
The second limitation of simulations is that simulations are not persuasive. We may believe the
microscopic model and we may trust the correctness of the method. Once the simulation starts,
the components move under their mutual interaction, and the situation becomes much to complex
to be followed mentally by the untrained mind. A skeptic can always choose to believe that the
microscopic model is incorrect, the model itself is buggy or the statistics are insufficient.
The third limitation of simulations is that the insight, which is the purpose of the simulation, is
far from being automatic. If we cannot find a simple macroscopic model, the data generated in
the simulation may forever remain just data.
The Interactions
The interactions used in the simulation may be generic or realistic. A generic interaction attempts
to capture the essential physics while the structure of the potential is simplified as much as
possible. Generic interactions are used to study phenomena and models. A realistic interaction
attempts to describe real materials under specific conditions. Realistic interactions may be either
accurate or approximate. From a simulation point of view, the approximate methods are
interpolation schemes used to calculate the interaction susceptibility from parameters derived
from experiments or from first principle calculations.
The principles and implementation of the simulation methods are almost independent of the
interaction method used.
The Principle in a Simulation.
At the initialization, a configuration is set up. The system is then equilibrated by propagation in
time. When the system has equilibrated, the production phase starts. Data are stored when the
production phase starts and then after each major timestep. The major timestep is an abstraction.
Frequently the major timestep is too long for the simulation method and the program internally
builds up the major timesteps through a series of minor timesteps.
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Stochastic and Deterministic Simulations
Simulations are either stochastic or deterministic, depending on the nature of the equation of
motion used in the simulation. For the stochastic methods the equation of motion is artificial and
tries to generate configurations with certain statistical properties. Average data are calculated as
ensemble averages
Monte Carlo is the most important of the stochastic techniques.
Deterministic methods aim at observation of the evolution in time of the system. This is usually
done by numerical solution of the equation of motion. Average data are calculated as a time
average over the trajectory.
Some elements of randomness are often introduced in the purely deterministic methods to
improve the approach.
Phases in a Simulation
A simulation consists of 3 phases: initialization, equilibration and production.
In the initialization the positions and movement of the components are generated or loaded from
a previous simulation. The simulation is run until equilibrium is reached and the memory of the
initial configuration has been erased. If the initial configuration is far from equilibrium, one may
reach a good estimate for the equilibrium properties if the initial, atypical configurations are
discarded.
During the production phase the simulation is continued while data are analyzed concurrently
with the simulation. The results are extracted from the simulation by visualization and animation.
Program Design
The setup, simulation, graphics, and analysis initialization of the simulation is made by loading
data from a previous simulation or by forming a new configuration.
As simulations may consume enormous computational resources it is important that the program
provides an analysis module for use while the simulation is in progress. The analysis module
should contain facilities for a preliminary analysis of the results as well as a facility for detailed
analysis of the performance of the simulation algorithm.
The output from a simulation program is primarily data for further analysis by other methods.
The data may also form the starting point for further simulations. Images and graphs stored
during the simulation may also be an efficient way of reviewing the simulations. It is convenient
to review the progress of extended simulations by examining it while the simulation is in
progress.
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Random Numbers
Random numbers are an important ingredient of stochastic simulation algorithms.
A sequence of pseudo-random numbers may be generated using a reproducible, deterministic
algorithm. The essential property of this algorithm is that the numbers have the same statistical
properties as independent, identically distributed numbers.
A linear congruental generator has the transition function. The advantages of the linear
congruental generators are that they have high speed and use a minimum of memory. They are
reproducible and portable.
The quality of the generated numbers is analyzed by numerical and number theoretic methods.
Neighbor Lists
Even for relatively small systems, it will pay off to maintain a list of the significant interactions:
the neighbor list. The calculation of the interactions can then be made much faster by neglecting
the insignificant ones.
If the Mentat only needs to loop over pairs of components, the use of a half-list is more efficient.
However, if the Mentat ever needs to loop over neighbors of a particular component, the use of a
full-list is more efficient.
Static Components
Static components can eliminate some the problems caused by the presence of free surfaces.
Static components take part in the interactions but do not change during the simulation.
Change
The components to be grown during the simulation are allocated as inactive atoms at the startup
of the simulation. Change is then simulated by activating these components sequentially during
the simulation.
Constraints
During the simulation it is useful to be able to constrain a single component or a group of actors
to change in a particular way with a constant rate, while all other degrees of freedom take part in
the simulation.
At the beginning of each major timestep the constrained actors are moved the appropriate
distance along the direction of the constraint. During the major timestep, the constrained atoms
only move orthogonal to the direction of the constraint.
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The implementation of the constraints amounts to removing the component of the force parallel
with the direction of the constraint. For Monte Carlo the random move is generated as usual, but
the unwanted component of the move is eliminated before proceeding with the evaluation of the
move.
Models
Different models may be used to represent the structure of the system. The models are important
because the choice of model has implications for both the data structure and the simulation
methods.
Particle models use a description in terms of components moving as point masses in space. The
identity of each component is fixed and the dynamics consists of the parts moving subject to the
interactive forces. For particle models, the intercomponent distance is a continuous variable and
cannot be tabulated. Consequently, the computational efficiency is lower than for a grid model.
The computation of interactions may be made through dynamically updated neighbor lists. In a
particle model vacancies are not explicitly represented, their number is not conserved, and their
positions are generally hard to determine.
Grid models use a description in terms of components and vacancies occupying the sites of a
regular grid. The dynamics consist of parts changing their identity or of pieces moving from one
site to another. As the elements can only occupy the sites of the grid, there are no forces, and
deterministic simulation is difficult. Computations for grid models are faster than for particle
models. The neighbor lists are static and may be determined during startup of the simulation. The
interactions are easily tabulated. In a grid model vacancies are included explicitly, and the
structure and dynamics of vacancies may be studied by exactly the same methods as for the
individual components.
Energy Minimization
(mod to NLP methodology)
Steepest descent is used to find the minimum energy configuration. The principle is to perform
the energy minimization through repeated minimizations along the direction of the force.
It is obvious that steepest descent may converge to a stationary point, which is not a minimum.
As the potential energy surface frequently has numerous local minima, it requires some insight
and a bit of luck to make steepest descent converge to the global minimum.
Monte Carlo algorithms
The significant contribution to the phase-space average comes from the parts of phase-space
where the energy, is close to its minimum, the exponential function suppresses the contributions
from regions of higher energy.
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In the Monte Carlo algorithm random moves are generated and accepted or rejected with
appropriate probability. There are several options for the random moves. Atoms may be moved
randomly relatively to their present configuration and an attempted move may involve one or
more atoms. One may loop through the atoms sequentially or in random order.
When an attempted move has been generated, the neighbor list must be checked and, if
necessary, updated before the energy may be calculated. If the attempted move is rejected, the
part under consideration must be moved back, the previous size and shape of the box must be
restored, and the lists checked again.
As we want the algorithm to establish the canonical contribution the transition probability should
satisfy the equation
Monte Carlo simulations use large quantities of random numbers and the quality of the random
number generator is important for the quality of the calculated results.
Guide to Models
The Inevitability of Using Models
Formal modeling of social and economic systems is ancient. Models have been used to analyze
everything from inventory management in corporations to the performance of planetary
economies, the interplay of global population, resources, food, and pollution.
Models have been commonplace in forecasting and public policy analysis, especially in
economics, energy and resources, demographics, and other crucial areas. More and more policy
debates-both in government and the private sector involve the results of models. The ability to
understand and evaluate complicated models has become a prerequisite for the policymaker,
legislator, lobbyist, and citizen alike.
Because models are so poorly understood by most people, it is easy for them to be misused,
accidentally or intentionally. Thus there have been many cases in which models have been used
to justify decisions already made and actions already taken, to provide a scapegoat when a
forecast turned out wrong, or to lend specious authority to an argument.
If these misuses are to stop and if modeling is to become a rational tool of the Mentat. The
models it describes are the kinds used in foresight and policy analysis. The characteristics and
capabilities of the models, their advantages and disadvantages, uses and misuses are all
addressed. The fundamental assumptions of the major modeling techniques are discussed, as is
the appropriateness of these techniques for foresight and policy analysis. Consideration is also
given to the crucial questions a Mentat should ask when evaluating the appropriateness and
validity of a model.
Mental Models
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Fortunately, Mentats are already familiar with models. Our decisions and actions are based not
on the real world, but on our mental images of that world, of the relationships among its parts,
and of the influence our actions have on it.
Mental models have some powerful advantages. A mental model is flexible; it can take into
account a wider range of information than just numerical data; it can be adapted to new situations
and be modified as new information becomes available. Mental models are the filters through
which we interpret our experiences, evaluate plans, and choose among possible courses of action.
The great systems of philosophy, politics, and literature are, in a sense, mental models.
But mental models have their drawbacks also. They are not easily understood by others;
interpretations of them differ. The assumptions on which they are based are usually difficult to
examine, so ambiguities and contradictions within them can go undetected, unchallenged, and
unresolved.
The mental models we use to make decisions are usually extremely simple. Often these models
are also flawed, since we frequently make errors in deducing the consequences of the
assumptions on which they are based.
The failure of Mankind to use rational mental models in human decision-making has been well
demonstrated by research on the behavior of people in organizations. This research shows that
decisions are not made by rational consideration of objectives, options, and consequences.
Instead, they often are made by rote, using standard operating procedures that evolve out of
tradition and adjust only slowly to changing conditions. These procedures are determined by the
role of the decision makers within the organization, the amount of time they have to make
decisions, and the information available to them.
But the individual perspectives of the decision makers may be parochial, the time they have to
weigh alternatives insufficient, and the information available to them dated, biased, or
incomplete. Furthermore, their decisions can be strongly influenced by authority relations,
organizational context, peer pressure, cultural perspective, and selfish motives. Psychologists and
organizational observers have identified dozens of different biases that creep into human
decision-making because of cognitive limitations and organizational pressures. As a result, many
decisions turn out to be incorrect; choosing the best course of action is just too complicated and
difficult a puzzle.
Normal, untrained people are simply not capable of making error-free decisions that are based on
rational models and are uninfluenced by societal and emotional pressures.
Enter the Mentat's model. In theory, Mentat models offer improvements over normal mental
models in several respects:
* They are explicit; their assumptions are stated in the written documentation and open to all for
review.
* They infallibly compute the logical consequences of the modeler's assumptions.
* They are comprehensive and able to interrelate many factors simultaneously.
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A Mentat's model that actually has these characteristics has powerful advantages over a mental
model. In practice, however, our models are often less than ideal:
* They are so poorly documented, if at all, and complex that no one can examine their
assumptions.
* They are so complicated that the client has no confidence in the consistency or correctness of
the assumptions.
* They are unable to deal with relationships and factors that are difficult to quantify, for which
numerical data do not exist, or that lie outside the expertise of the Mentat who built the model.
Because of these possible flaws, our models need to be examined carefully by potential users.
But on what basis should models be judged? How does one know whether a model is well or
badly designed, whether its results will be valid or not? How can a prospective user decide
whether a type of modeling or a specific model is suitable for the problem at hand? How can
misuses of models be recognized and prevented?
Three types of Models: Optimization, Simulation, and Econometrics
One of the most useful classifications divides models into those that optimize versus those that
simulate. The distinction between optimization and simulation models is particularly important
since these types of models are suited for fundamentally different purposes.
Optimization
Optimize means "to make the best of most of; to develop to the utmost." The output of an
optimization model is a statement of the best way to accomplish some goal. Optimization models
do not tell you what will happen in a certain situation. Instead they tell you what to do in order to
make the best of the situation; they are normative or prescriptive models.
An optimization model typically includes three parts.
1. The objective function specifies the goal or objective.
2. The decision variables are the choices to be made.
3. The constraints restrict the choices of the decision variables to those that are acceptable
and possible.
An optimization model takes as inputs these three pieces of information-the goals to be met, the
choices to be made, and the constraints to be satisfied. It yields as its output the best solution,
i.e., the optimal decisions given the assumptions of the model.
Limitations of Optimization
Many optimization models have a variety of limitations and problems that a potential user should
bear in mind. These problems are:
* Difficulties with the specification of the objective function
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* Unrealistic linearity
* Lack of feedback
* Lack of dynamics.
Linearity. Another problem, and one that can seriously undermine the verisimilitude of
optimization models, is their linearity. Because a typical optimization problem is very complex,
involving hundreds or thousands of variables and constraints, the mathematical problem of
finding the optimum is extremely difficult. To render such problems tractable, modelers
commonly introduce a number of simplifications. Among these is the assumption that the
relationships in the system are linear. In fact, the most popular optimization technique, linear
programming, requires that the objective function and all constraints be linear.
Linearity is mathematically convenient, but in reality it is almost always invalid. The linear
relationship within the model almost always leads to an absurdity.
Lack of Feedback. Complex systems in the real world are highly interconnected, having a high
degree of feedback among sectors. The results of decisions feed back through physical,
economic, and social channels to alter the conditions on which the decisions were originally
made. Some models do not reflect this reality, however.
Models that ignore feedback effects must rely on exogenous variables and are said to have a
narrow boundary. Exogenous variables are ones that influence other variables in the model but
are not calculated by the model. They are simply given by a set of numerical values over time,
and they do not change in response to feedback. The values of exogenous variables may come
from other models but are most likely the product of an unexaminable mental model. The
endogenous variables, on the other hand, are calculated by the model itself. They are the
variables explained by the structure of the model, the ones for which the modeler has an explicit
theory, the ones that respond to feedback.
Ignoring feedback can result in policies that generate unanticipated side effects or are diluted,
delayed, or defeated by the system. In theory, feedback can be incorporated into optimization
models, but the resulting complexity and non-linearity usually render the problem insoluble.
Many optimization models therefore ignore most feedback effects. Mentats should be aware of
this when they look at a model. They should ask to what degree important feedbacks have been
excluded and how those exclusions might alter the assumptions and invalidate the results of the
model.
Lack of Dynamics. Many optimization models are static. They determine the optimal solution for
a particular moment in time without regard for how the optimal state is reached or how the
system will evolve in the future.
Not all optimization models are static. Some models are dynamic in the sense that it produces a
"snapshot" of the optimal state of the system at five-year intervals.
The delays found in complex systems are especially important because they are a major source
of system instability. The lag time required to carry out a decision or to perceive its effects may
cause overreaction or may prevent timely intervention. Delays are a crucial component of the
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dynamic behavior of systems, but-like nonlinearity-they are difficult to incorporate into
optimization models. One simplification is to assume that all delays in the model are of the same
fixed length. The results of such models are of questionable value.
When To Use Optimization
Optimization models are valid for making prescriptive statements. They are valid for forecasting
only if people do in fact optimize, do make the best possible decisions. It may seem reasonable
to expect people to behave optimally - after all, wouldn't it be irrational to take second best when
you could have the best? But the evidence on this score is conclusive: real people do not behave
like Optimization models. Humans make decisions with simple and incomplete mental models,
models that are often based on faulty assumptions or that lead erroneously from sound
assumptions to flawed solutions.
The capacity of the human mind for formulating and solving complex problems is very small
compared with the size of the problem whose solution is required for objectively rational
behavior in the real world or even for a reasonable approximation to such objective rationality.
For this reason alone a Mentat would be necessary.
Optimization models augment the limited capacity of the Mentat to determine the objectively
rational course of action. It should be remembered, however, that even optimization models must
make simplifying assumptions in order to be tractable, so the most we can hope from them is an
approximation of how people ought to behave. To model how people actually behave requires a
very different set of modeling techniques, which will be discussed now.
Simulation
The purpose of a simulation model is to mimic the real system so that its behavior can be
studied. The model is a laboratory replica of the real system. By creating a representation of the
system in the laboratory, a modeler can perform experiments that are impossible, unethical, or
prohibitively expensive in the real world. Simulations of physical systems are commonplace and
range from wind tunnel tests of aircraft design to simulation of weather patterns and the
depletion of oil reserves. Economists and social scientists also have used simulation to
understand how energy prices affect the economy, how corporations mature, how cities evolve
and respond to urban renewal policies, and how population growth interacts with food supply,
resources, and the environment. There are many different simulation techniques, including
stochastic modeling, system dynamics, discrete simulation, and role-playing games. Despite the
differences among them, all simulation techniques share a common approach to modeling.
Optimization models are prescriptive, but simulation models are descriptive. A simulation model
does not calculate what should be done to reach a particular goal, but clarifies what would
happen in a given situation. The purpose of simulations may be foresight or policy design. In
other words, simulation models are "what if' tools. Often such "what if' information is more
important than knowledge of the optimal decision.
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Every simulation model has two main components. First it must include a representation of the
physical world relevant to the problem under study. How much detail a model requires about the
physical structure of the system will, of course, depend on the specific problem being addressed.
Second, a simulation model must portray the behavior of the actors in the system. In this context,
behavior means the way in which people respond to different situations, how they make
decisions. The behavioral component is put into the model in the form of decisionmaking rules,
which are determined by direct observation of the actual decision-making procedures in the
system.
Given the physical structure of the system and the decision-making rules, the simulation model
then plays the role of the decision makers, mimicking their decisions. In the model, as in the real
world, the nature and quality of the information available to decision makers will depend on the
state of the system. The output of the model will be a description of expected decisions. The
validity of the model's assumptions can be checked by comparing the output with the decisions
made in the real system.
Econometrics
Strictly speaking, econometrics is a simulation technique, but it deserves separate discussion for
several reasons. First, it evolved out of economics and statistics, while most other simulation
methods emerged from operations research or engineering. The difference in pedigree leads to
large differences in purpose and practice. Second, econometrics is one of the most widely used
formal modeling techniques. Econometrics is now taught in nearly all business and economics
programs in the Empire. Econometric forecasts are regularly reported in the media, and ready-to
use statistical routines for econometric modeling are now widely available. And third, the well
publicized failure of econometric models to predict the future has eroded the credibility of all
types of models, including those built for very different purposes and using completely different
modeling techniques.
Econometrics is literally the measurement of economic relations, and it originally involved
statistical analysis of economic data. As commonly practiced today, econometric modeling
includes three stages - specification, estimation, and forecasting. First the structure of the system
is specified by a set of equations. Then the values of the parameters (coefficients relating
changes in one variable to changes in another) are estimated on the basis of historical data.
Finally, the resulting output is used to make forecasts about the future performance of the
system.
Specification
The model specification is the description of the model's structure. This structure consists of the
relationships among variables, both those that describe the physical setting and those that
describe behavior. The relationships are expressed as equations, and a large econometric model
may have hundreds or even thousands of equations reflecting the man interrelationships among
the variables.
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For example, an econometric model of the macroeconomy typically will contain equations
specifying the relationship between some production and consumption, investment, government
activity, and trade. It also will include behavioral equations that describe how these individual
quantities are determined. The modeler may expect, for instance, that high unemployment
reduces inflation and high sersa. One of the equations in the model will therefore express that the
rate of inflation depends on the amount of unemployment. Another equation may relate
unemployment to the demand for goods, the wage level, and worker productivity. Still other
equations may explain wage level I terms of yet other factors.
The calcetrics draws on economic theory to guide the specification of its models. The validity of
the models thus depends on the validity of the underlying economic theories. Though there are
many flavors of economics, a small set of basic assumptions about human behavior are common
to most theories, including modern n more efcal theory and the "rational expectations" school.
These assumptions are: optimization, perfect information, and equilibrium.
In econometrics, traders are assumed to be concerned with just one thing-maximizing their
profits. Consumers are assumed to optimize the "utility" they derive from their resources. Dee
startuabout how much to produce, what goods to purchase, whether to save or borrow, are
assumed to be the result of optimization by individual decision makers. Non-economic
considerations (defined as any behavior that diverges from profit or utility maximization) are
ignored or treated as local aberrations and special cases.
Economic agents would need accurate information about the world to accurately optimize. The
required information would go beyond the current state of affairs; it also would include complete
knowledge to thosailable options and their consequences. In most econometric models, such
knowledge is assumed to be freely available and accurately known.
The third assumption is that the economy is in or near equilibrium nearly all of the time. If
disturbed, it is usually assumed to return to equilibrium rapidly and in a sions of d stable manner.
The prevalence of static thinking is the intellectual legacy of the pioneers of mathematics and
economics.
These questions proved difficult enough without tackling the more difficult problem of
dynamics, of the behavior of a system in flux. As a result, dynamic economic theory-including
the one tnt fluctuations of inflation, of the business cycle, of the growth and decline of industries
and nations - remained primarily descriptive and qualitative long after equilibrium theory was
expressed mathematically.
Many econometric models assume that markets are in equilibrium at all times. When adjustment
dle, modeare modeled, variables are usually assumed to adjust in a smooth and stable manner
toward the optimal, equilibrium value, and the lags are nearly always fixed in length. For
example, most macroeconometric models assume that capital stocks of firms in the economy
adjust to the optimal, profit-maximizing level, with a fixed lag of several years. The lag is the
same whether the industries that supply investment goods have the capacity to meet the demand
or nox systemet clearly, when the supplying industries have excess capacity, orders can be filled
rapidly; when capacity is strained, customers must wait in line for delivery. Whether the dynamic
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nature of the lag is expressed in a model does make a difference. Models that explicitly include
the determinants of the investment ignore will yield predictions significantly different from
models that assume a fixed investment lag regardless of the physical capability of the economy
to fill the demand. In general, models that explicitly portray delays and their determinants will
yield different results from models that simply assume smooth adjust values from one optional
state to another.
Estimation
The second stage in econometric modeling is statistical estimation of the parameters of the
model. The parameters determine the precise strengths of the relationships specified in the model
structure. Sometimes the modeler would use past data to estimate precisely, the strong the
relationship between inflation and unemployment has been. Statistical parameter estimates
characterize the degree of correlation among the variables. They use historical data to determine
parameter values that best match the data themselves.
All modeling methods must specify the structure of the system and estimate parameters. The use
of statistical procedures to derive the parameters of the model is the hallmark of econometrics
and distinguish that from other forms of simulation. It gives econometricians an insatiable
appetite for numerical data, for without numerical data they cannot carry out the statistical
procedures used to estimate the models.
Forecasting
The third step in econometric modeling is forecasting, making predictions about how the reched
or m will behave in the future. In this step, the modeler provides estimates of the future values of
the exogenous variables, that is, those variables that influence the other variables in the model
but aren't themselves influenced by the model. An econometric model may have dozens of
exogenous variables, and each system in forecast before the model can be used to predict.
Limitations of Econometric Modeling
The reliance of econometric estimation on numerical data is another of its weaknesses. The
narrow focus on hard data blinds modelers to less tangible but no less important factors. They
ignore both potentially observable s to asses that haven't been measured yet and ones for which
no numerical data exist. (Alternatively, they may express an unmeasured factor with a proxy
variable for which data already exists, even though the relationship between the two is tenuousas when educational expenditure per capita is used as a proxy for the literacy of a population.)
Among the factors excluded from econometric models because of the hard data focus are many
important determinants of dest? But asking, including desires, goals, and perceptions. Numerical
data may measure the results of human decision making, but numbers don't explain how or why
people made particular decisions. As a result, econometric models cannot be used t anticipate
how people would react to a change in decision-making circumstance for formality, econometric
models are unable to provide a guide to performance under conditions that have not been
experienced previously. Econometricians assume that the correlations indicated by the historical
data will remain valid in the future. In reality, those data usually span a limited range and
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provide no argument outside of historical experience. As a result, econometric models are often
less than robust: faced with new policies or conditions, the models break down and lead to
inconsistent results.
Validation is another problem area in econometric modeling. The dominant criterion used by
econometric modelers to determine people lidity of an equation or a model is the degree to which
it fits the data. The statistical significance of the estimated parameters in an equation is not an
indicator of the correctness of the relationship. Statistical significance indicates how well an
equation fits the observed data; it does not indicate whether a relationship is a correct or true
characterization of the way the world works. A statistically significant relationship between
variables in physical on shows that they are highly correlated and that the apparent correlation is
not likely to have been the result of mere chance. But it does not indicate that the relationship is
causal at all.
As noted earlier, in order to forecast, the modeler must provide estimates of the future values of
the exogenous vao urban and an econometric model may have dozens of these variables. The
source of the forecasts for these variables may be other models but usually is the intuition and
judgment of the modeler. Forecasting the exogenous variables consistently, much less correctly,
is difficult.
Of course, policy evaluation and for a commoepend on an accurate knowledge of the history and
current state of the world, and econometrics has been a valuable stimulus to the development of
much-needed data gathering and measurement by governments and private companies. But
econometric models do not seem well suited to the types of problems of concern iner words
analysis and foresight. Though these models purport to simulate human behavior, they in fact
rely on unrealistic assumptions about the motivations of real people and the information
available to them. Though the models must represent the physical world, they commonly ignore
dynamic processes, disequilibrium, and the physical basis for delays between actions and results.
Though they may incorporate hundreds of variables, they often ignore soft variables and try
these quantities. In real systems the feedback relationships between environmental, demographic,
and social factors are usually as important as economic influences, but econometric models often
omit these because numerical data are not available. Furthermore, econometrics usually deals
with the short term, while underlie takes a longer view. Over the time span that is of concern in
foresight, real systems are likely to deviate from their past recorded behavioral making unreliable
the historical correlations on which econometric models are based.
Checklist for the Mentat
The preceding discussion has focused on the limitations of various modeling approaches in order
to provide potential model consumers with a sense of what to look out for when choosing a
model. Despite the limitations of modeling, there is no doubt that computer models can be and
have been extremely useful foresight tools. Well-built models offer significant advantages over
often-faulty mental models currently in use.
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The following checklist provides further assistance to decision makers who are potential model
users. It outlines some of the key questions that should be asked to evaluate the validity of a
model and its appropriateness as a tool for solving a specific problem.
* What is the problem at hand? What is the problem addressed by the model?
* What is the boundary of the model? What factors are endogenous?
*system use? Excluded? Are soft variables included? Are feedback effects properly taken into
account? Does the model capture possible side effects, both harmful and beneficial?
* What is the time horizon relevant to the problem? Does the model include as endogenous
components those factors that may change significantly. The time horizon?
* Are people assumed to act rationally and to optimize their performance? Does the model take
non-economic behavior (organizational realities, non-economic motives, political factors,
cognitive limitations) into account?
* Does the model assume people have perfect information about the future reason the way the
system works, or does it take into account the limitations, delays, and errors in acquiring
information that plague decision makers in the real world?
* Are appropriate time delays, constraints, and possible bottlenecks taken into account?
* Is the model robust in the face of extreme variations s now ta assumptions?
* Are the policy recommendations derived from the model sensitive to plausible variations in its
assumptions?
* Are the results of the model reproducible? Or are they adjusted (add factored) by the model
builder?
* Is the model currently operated by the Mentat that built it? How long does it take for the model
Mentat to evaluate a new situation,
* Modify the model, and incorporate new data?
* Is the model documented? Is the documentation available? Can third parties use the model and
run their own analyses with it?
Goal of the Mentats
No one can make decisions on the basis of model results that are simply presented, "take 'em or
leave 'em." In fact, the primary function of model building should be educational rather than
predictive. Models should not be used as a substitute for critical thought, but as a tool for
improving judgment and intuition.
Towards that end, the role of Mentat models in policymaking needs to be redefined. It should be
remembered that we all use models of some sort to make decisions and to solve problems. Most
of the pressing issues with which public policy is concerned are currently being handled solely
with mental models, and those mental models are failing to resolve the problems. The alternative
to continued reliance on mental models is computer modeling. But why turn to Mentat-based
models if they too are far from perfect?
The value in our models derives from the differences between them and other mental models.
When the conflicting results of a mental and a Mentat-based model are analyzed, when the
underlying causes of the differences are identified, both of the models can be improved.
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Mentat-based modeling is thus an essential part of the educational process rather than a
technology for producing answers. The success of this dialectic depends on our ability to create
and learn from shared understandings of our models, both mental and computer. Properly used,
computer models can improve the mental models upon which decisions are actually based and
contribute to the solution of the pressing problems we face.
Advisor
Only one novice in twenty achieves the coveted sixth rank. They are skilled in wisdom and
diplomacy, possessing all the abilities of the lower ranks and adding sophistication and
understanding. Advisors plan for the long run, they negotiate delicate matters and judge matters
of life and death.
Wisdom
* The quality of being wise; knowledge, and the capacity to make due use of it; knowledge of the
best ends and the best means; discernment and judgment; discretion; sagacity; skill; dexterity. "
"It is hoped that our rulers will act with dignity and wisdom that they will yield everything to
reason, and refuse everything to force." "Common sense in an uncommon degree is what the
world calls wisdom."
* The results of wise judgments; scientific or practical truth; acquired knowledge; erudition.
Synonyms -- Prudence; knowledge. Wisdom, Prudence, Knowledge. Wisdom has been defined
to be "the use of the best means for attaining the best ends." "We conceive prudence as the virtue
by which we select right means for given ends, while wisdom implies the selection of right ends
as well as of right means." Hence, wisdom implies the union of high mental and moral
excellence. Prudence is of a more negative character; it rather consists in avoiding danger than in
taking decisive measures for the accomplishment of an object. There are cases in which an
individual may be a prudent statesman, but still be far from being a wise one. Prudepply invn
carried too far, degenerates into a "reptile virtue," which is the more dangerous for its plausible
appearance. Knowledge, a more comprehensive term, signifies the simple apprehension of facts
or relations. "In strictness of language there is a difference between knowledge and wisdom;
wisdom always supposing Models and action directed by it." "Knowledge and wisdom, far from
being one, have overtimes no connection. Knowledge dwells in heads replete with thoughts of
other men; Wisdom, in minds attentive to their own. Knowledge, a rude, unprofitable mass, The
mere materials with which wisdom builds, Till smoothed, and squaredeld difftted to its place,
Does but encumber whom it seems to enrich. Knowledge is proud that he has learned so much;
Wisdom is humble that he knows no more."
The Orange Catholic Bible is rather simple on who is gets wisdom and who does not: " He grants
wisdom to whom He pleases, and whoever is granted wisdom, he ires. Some are given a great
good and none but men of understanding mind."
Wisdom and Intelligence
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A distinction should be made between wisdom and intelligence. The difficulty to distinguish
these two notions may be due to the western-world intellectual tradition. At least the following
two factors appear to be unique to wisdom:
1. Exceptional understanding of ordinary experience. This is made up of items like:
* The ability to see essences
* Understand contexts
* Be in touch with the self
2. Judgment and communication skills. This is made up of things like:
* Perceptiveness
* The ability to weigh consequences and consider multiple points of view
* The ability to analyze and communicate about life
Wisdom and Ethics
One common belief is that wisdom has an ethical component, or that ethics forms the basis of
wisdom. It is the other way around: wisdom leads to the development of an ethical view, since
ethical actions usually have long- range positive consequences. Ethics can be based on rational
judgments of what is good or useful and do not need any supernatural backing.
Wisdom and Daily Life
* Allows individual to resolve dilemmas, make personal decisions, and take initiatives. To be
able to do so, one has to:
* Be in touch with one's feelings, needs, and expectations
* Differentiate the needs of the self from the expectations of others and social pressure
* Be able to manage interpersonal relationships (including the ability to resolve conflicts using
tolerant modes
* Be open to the other, to differences
* Be able to adjust to changes
* Advising others. Advisory role is an important one and has always been associated with
wisdom.
* "Management and guidance of society," which can be seen as a leadership role, ranging from
raising a family to conducting a business.
* The ability to view life introspectively and retrospectively. A person should be able to evaluate
his or her own life and be able to find a meaning and continuity to it.
* The ability to question the meaning of life and to place in the larger context of one's personal
history as well as
* History in general. It should be noted that all these functions are interrelated and should not
dissociated from each other.
The Wisdom of Old Age
It is probable that under a lifetime the brain abstracts more or less general rules and experiences
from the many special cases. People learn the most common consequences of certain actions, and
make so many analogies that powerful abstractions develop. This leads to that a wise person has
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a good chance to guess the results of an action even in the long run. Unfamiliar situations may
pose a problem, but if a person has lived a sufficiently varied life and abstracted enough general
rules he might be able to use inductive reasoning and apply his wisdom anyway.
Wisdom is commonly attributed to aged or old people. Indeed, with time people learn life's
lessons, they have processed a lot of the experiences that they have lived and thus become wiser.
It is the contrary that happens: wisdom decreases with age. Age does not bring wisdom, it merely
allows people to manifest more profoundly the expressions of wisdom because of the experience
of age.
The drawback is of course that if conditions change this old wisdom may loose its usability,
since the world no longer follows the map. It is worth noting that the views on old people vary
between static and dynamic cultures: in a static culture old people are valued as wise and
experienced, in dynamic cultures they are often seen as a conservative burden and unable to
adapt.
The question is how to develop methods to enhance our own wisdom and at the same time keep
our minds flexible. Thanks, in part, to mélange most Mentats hope to live for a very long time,
and thus expect to get plenty of chances to extend their wisdom, it would be even better if we
could become wiser faster. One method could be to optimize wisdom in areas which are general
enough not to be changed markedly with time (such as mathematics and systems theory) or
which are not expected to change much (like how physical objects behave) and hope some of the
results can be applied in other areas. The big problem is whether it is possible to develop general
and communicable rules of wisdom even in more dynamical areas, or if the only way towards the
wisdom of age is constant training/living for a long period.
Wisdom can be understood as a gradual and maturing process. Although growing and maturing
in wisdom is not a fully understandable process, it is not a miraculous one either; it has to be
integrated and nourished, we have to decide to be consciously wise.
Diplomacy
* The art and practice of conducting negotiations between nations
* Skill in handling affairs without arousing hostility: TACT
* Sensitive mental or aesthetic perception
* A keen sense of what to do or say in order to maintain good relations with others or avoid
offense
Synonyms TACT, ADDRESS, POISE, SAVOIR FAIRE mean skill and grace in dealing with
others. TACT implies delicate and considerate perception of what is appropriate. ADDRESS
stresses dexterity and grace in dealing with new and trying situations and may imply success in
attaining one's ends. POISE may imply both tact and address but stresses self-possession and
ease in meeting difficult situations. SAVOIR FAIRE is likely to stress worldly experience and a
sure awareness of what is proper or expedient.
Diplomacy is saying "nice doggy" until you find a rock.
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Obviously, the most important factor in achieving peace is diplomacy, and narrowly defined
security becomes an issue only once diplomatic efforts have been exhausted. The Mentat is
strongly aware of the need for preventive diplomacy to nip war and conflict in the bud
Multi-track Diplomacy in wars
Here are the basics of diplomacy in wars: Split the world into allies and enemies, join forces with
your allies and destroy your enemies. Quite an improvement over the one-against-all variant...
Basic Diplomacy
Diplomacy, when done right, is one of the (not to say the) most challenging and Interesting thing
about life!
The other reason is the power of it. Diplomacy can and WILL make the difference between
winning and losing an Empire.
First Contact
One of the most important things in the beginning of any encounter is to let people know what
your intentions are.
That first message is very important. At this early stage the entire encounter could be decided.
Your message needs to be modest. Let them know your people are friendly, and that you want to
be everybody's best friend.
Don't try to intimidate people in the too early, this makes people careful and will the situation
probably evolve into nobody trusting you.
You could ad some lines explaining that you are fond of your privacy and request the other
Houses to try to keep clear of your interests (they will probably respond by asking what they are,
just kindly reply them that for the safety of your client you are not allowed to say precisely what
they are, but that they will be warned if they get too close).
BORDER CONTROL
After a while, you will meet your neighbors. Probably this will inflict a discussion on the topic.
There are a few rules you should obey:
1) Don't get exited/angry
Always try to be reasonable, or at least appear like that. You will probably want to have these
people as allies, the first contact with them is crucial.
2) Defining Boundaries
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When it comes to defining boundaries, try to be reasonable. Explain them carefully why they
can't have that information (e.g. to close to your client's interests).
3) Your intentions
Always tell them that you have the best intentions and really hope for a closer alliance.
4) Giving some things up
If you have wide enough resources you can give up something you already exploited. It will
convince them that you are an ally and they will easier trust you.
5) Be firm
Although this might seem to contradict with what was said earlier, it really doesn't. You have to
be firm in whatever you do. This will give the impression that you are a steady ally, one they can
trust.
Sometimes, you will not need to define exact borders. This adds to your alliance, making a
bigger co-operation possible.
BECOMING ALLIES
You need allies. You need allies that you can trust. Having a good first contact is the best start
for an alliance and the most important.
There are 2 situations that will get you alliances.
The first situation is the one discussed above: associates. These alliances need time to grow. The
first thing that will happen is the discussion about boundaries, described previously.
To give your alliance a better start, you might want to give a gift. Don't ask anything in return
for it.
After that the first thing you will probably do is exchanging information. How this will happen is
entirely up to you.
The second situation that can form an alliance is the need for one. This need will most likely be a
mutual enemy or some other kind of danger. These alliances will form much quicker and are
therefore less strong.
I Need Assistance
First, you have to find somebody to help you. When choosing the right ally there are a few things
to keep in mind:
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* Don't let your enemy know you need help. This will make him careful or make him attack you
before you had time to get stronger or anybody responds.
* Choose your allies right. Make sure they aren't allies or friends of your enemy.
* See to it that your positions are useful. Don't take an ally at the other side of the Galaxy. Your
best choice is to take an ally that is also a neighbor of your enemy and experiences an equal
threat.
How to ask for help
When you chose the right ally, time has come to contact him. In the contacting message, try to
convince your (future) ally of the danger your enemy exposes both of you to. Also, try to
convince them that THEY need an alliance, not you. Your main goal in this stage will be
defense, not attack.
This is a good method of getting allies when you need them. However when you have some
more time you can give the alliance a better chance by sending him some messages warning him
about the raptors.
This will make it much more easier to form an alliance with them when the need arises.
KEEPING AN ALLIANCE ALIVE
When the alliance is formed, the hardest part is over. There really are only a few things to do to
keep an alliance alive:
1) Share information about others. Warn him when someone inquires about him
2) Exchange information regularly
3) Help him whenever you can. Give him support his defense and, if you have a close alliance,
his attacks.
4) Never give away information about him.
5) Don't get arrogant. Treat him as an equal.
MASS DIPLOMACY/PSYCHOLOGY
This is one of the best parts about diplomacy: trying to convince the masses. Use these
techniques for winning a battle without a single fight. Be a better diplomat than your opponent
and after a while he will surrender and come to a peace agreement.
When fighting these word battles, try follow the following 'rules':
1) Be reasonable and calm. Give good arguments for everything you say.
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2) Act like your enemy has hurt your feelings, try to justify your actions
3) Never swear
4) Try to make your enemy look bad by giving your view on what he recently did, but do this
like said in rule 1.
5) Warn people about your enemy. How evil he is.
6) Fight what he said, unravel his lies.
You can use these public messages also to justify your actions. E.g. he did that, that and that. We
are a patient House but even to our patience comes an end. Unless he stops these practices we
will have to take actions.
PEACE TREATY'S
Peace is a wonderful thing. You should do as much as possible to preserve it. Peace treaties are
necessary for this. Always try to turn war into peace when wars is a bad thing for you (which is
often the case).
For this you can choose out different peace treaties:
1) Close Borders treaty
With this treaty you decide to have a closed border between your empires. A close border means
that no ships of involved races may cross it and that all ships in enemy space must be pulled back
immediately. This ensures peace only for a short period of time as tensions will be high.
2) Give and take treaty
This treaty is for solving smaller disagreements. You decide that: (a) will give this ship and that
planet to (b) and that (b) will give this planet and that amount of minerals to (a). At the same
time (a) and (b) agree not to attack each other's ships. This could be done with or without Closed
Borders.
3) Half-surrender treaty
This is only possible if party (a) is much stronger then party (b) but party (b) is too big to get
defeated without (a) having many losses. Party (b) becomes a part of party (a)'s empire and has
to pay him a yearly amount of minerals to (a). However (b) is allowed to keep his independent
government.
There are of course other treaties, but these are the most important.
If both parties are equally strong then you need to negotiate peace talks.
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These peace talks are often started by a message coming from one of the parties.
After that it comes to discussing peace.
Important when discussing peace is to set your limits and don't go over them. Don't let your
enemy think you are afraid.
On the other hand, don't be too arrogant. If you are, your enemy might decide on not having a
treaty at all.
BACK-STABBING
Handling backstabbing allies
What to do when an ally backstabs you? Actually there are only a few diplomatic things you can
do:
You can kill a few of his agents, threaten him and those ways try to get him back at your side
(providing he isn't stronger then you are).
You can try to talk him back. Reasoning with him and make the ground under his feet shake (not
literally). When doing this, try to follow the same rules you used when defining borders.
Tell everybody he backstabbed you and therefore is not a safe ally. This won't bring him back
but will make others think twice before they form an alliance with him.
If you are stronger than him you can attack him, using mass diplomacy to explain your actions to
other players. This will make your other allies think twice before they backstab you.
Back-stabbing an ally
Think very careful before you backstab an ally. Make sure that you are much stronger than him
or that you can form an alliance with someone else (prob. his enemy). Make sure that he doesn't
find out about your intentions. Surprise is very important.
Getting someone to backstab your enemy.
Here you can show what a great diplomat you are! Trying to get someone to your site is one of
the (if not the) most difficult diplomatic actions. It requires much planning and much careful
talking.
The first thing you have got to do is convince him that your enemy isn't a safe ally. Don't try to
speed things up. Just make him feel not at ease with his current ally. Explain if you have to, just
drive him paranoid. This first step should ideally be done without sending a message directly. If
necessary make one of your allies send him some disturbing messages.
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Then, when he is feeling uneasy, send him a message to convince him to backstab your enemy.
In this message, try to be sincere, don’t use as many words. You will need to offer him things
(planets, minerals, a yearly income...) to make him betray his ally. Your gifts should reflect his
importance.
Of coarse, you can first convince him why an alliance with you is better than one with your
enemy but that depends on the personality of him, you try to convince.
Try to keep these negotiations a secret. Don't let your enemy find out about them. Even after you
convinced him it's likely that you want to keep the alliance a secret until you come in action.
Multi-Track Diplomacy
Multi-track diplomacy is more than convention diplomacy. It is a important that you adhere to all
twelve basic principles that when combined, form the basis for multi-track diplomacy. These
twelve principles are:
1. Relationship: building strong interpersonal and intergroup relations throughout the fabric of
society.
2. Long-term commitment: making an ongoing commitment to people and to processes that may
take years to come to fruition.
3. Cultural synergy: respecting the cultural wisdom of all the parties and welcoming the creative
interaction of different cultural ways.
4. Partnership: modeling collaborative processes by partnering with local parties and with other
institutions and coalitions.
5. Multiple technologies: utilizing a variety of technologies, as appropriate, and creating new
methods, as needed, to meet the unique needs of each situation.
6. Facilitation: assisting parties in taking responsibility for their own dreams and destiny.
7. Empowerment: helping people become empowered agents of change and transformation
within their societies.
8. Action research: learning from all that we do and sharing that learning with others.
9. Invitation: entering the system where there is an invitation and an open door.
10. Trust: building relationships of mutual trust and caring within the system.
11. Engagement: acknowledging that once we enter a system, we become a unique part of it, an
engaged, caring, and accountable partner.
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12. Transformation: catalyzing changes at the deepest level of beliefs, assumptions, and values,
as well as behaviors and structures.
Planning Activities
Critical Path analysis starts after you have figured out all the individual activities in your project.
For each activity you have:
* A projected normal time duration
* The names of any other activities that have to be completed before this one can start
* The identification of related (example: following, concurring) activities
* A cost to complete (optional)
* A shorter time to complete on a crash basis (optional)
* A higher cost to complete on a crash basis (optional)
Network Analysis of Projects and the Critical Path Method
Critical Path Methodology
Critical Path Method (CPM), is a procedure for using network analysis to identify those tasks
that are on the critical path: i.e. where any delay in the completion of these tasks will lengthen
the project timescale, unless action is taken. For all tasks off the critical path, a degree of
tolerance is possible (e.g. late start, late completion, early start, etc.). Network charts and CPM
analysis used to be carried out by hand.
The Critical Path Method (CPM) is one of several related techniques for doing project planning.
CPM is for projects that are made up of a number of individual "activities." If some of the
activities require other activities to finish before they can start, then the project becomes a
complex web of activities.
A critical path method (CPM) network is a shows the sequence of tasks, simultaneous activities,
and time requirements for a project. The critical path is the sequence of activities requiring the
longest amount of time. The only way to decrease project schedule time is to reduce the time
required for an activity on the critical path.
The level of detail of a CPM network depends on the purpose of the network. When a under
development a CPM network may be extremely extensive. For a client, however, however, CPM
networks should be restricted to ten or fewer activities per page, for readability. For large
projects, more detail is required to monitor and coordinate individual activities. In these cases an
alternate chart may be more appropriate.
With enough information, CPM can help you calculate:
* What is the optimal task sequence
* Identify simultaneous development activities
* How you can best allocate resources
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* Calculate what will be the total project effort and schedule
* How long your complex project will take to complete
* Which activities are "critical," meaning that they have to be done on time or else the whole
project will take longer
* Whether you should try to speed up the project, and, if so, what is the optimal plan for
speeding up the project.
Better execution of the above tasks in turn helps you to meet your goals by improving your
efforts.
The planning chart shows the relationship between each activity, no activity can begin before its
precedent activities are completed. The precedents are the activities that the arrows come from.
The time (in days) for each activity is noted in its box.
These relationships create pathways through the process. Summing the times along each pathway
gives the pathways length or duration. The longest pathway is the critical pathway; the critical
pathway is the longest pathway in the process. The process cannot end before the critical
pathway ends.
Any project to shorten the overall project time must start with the critical pathway. A case
manager can focus on completing these activities and attaining these outcomes to meet elapsed
time goals.
The Primary Planning Charts also make a great "what if..." tool during pathway design. The
process also helps people think parallel.
One last, technical, note. The difference between other planning charts and CPM is in the times
for each activity or outcome. CPM simply takes the expected (usually average) time, other
planning charts may the best case, expected case, and worst case estimates to calculate the
duration:
Average Time = (Best Case + (4 x Expected Case) + Worst Case) / 6
This extends the possible analyses to explore Best Case vs. Worst Case. Can (should) we create
separate pathways for the different groups? How can we improve Worst Case? Learn from the
Best Case? This gives an approximation for a statistical distribution that may be evaluated for
percentile times. See " Probabilistic Solutions to Project Scheduling" below.
How to create Planning Charts
Do the first three steps before beginning to develop either type of chart.
1. Initially use whiteboard, flipchart sheets or other large space. With experience this will be
performed entirely within the Mentat's mind
2. Make a list of all tasks or activities involved in all phases of your project.
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3. Put them into sequential order.
4. Now draw your Primary chart on the board. Your first pass will probably not be your last. The
chart doesn't have to be perfect the first time. Be prepared to adjust tasks once you see the
sequence laid out.
5. Next you will have to estimate the time it will take to complete each task and put the time next
to that task on your list. You'll be using that information for the auxiliary chart as well.
6. Label each task on your primary chart with the time you determined in step #5.
7. Readjust the sequence of tasks as necessary.
8. Now determine who is responsible for each task on the list along with what resources will be
required and put his/her name next to that task.
9. Label each task on your primary chart with the name of the person responsible.
10. Readjust sequence, if necessary, until all Mentat members agree to its accuracy.
11. Once your primary chart is complete, if it is on a board where it can't be saved, redraw it on a
permanent media so that it can be posted during Mentat meetings, or redraw it and make copies
for your Mentat members.
12. Now, using the times on your list and the sequence in your primary chart, you can draw your
secondary chart
13. Decide at what level you want to examine your timelines--weekly, monthly, whole project. It
is recommended you start with an overview of the whole project.
14. Label the secondary chart across the top by week. Use start or end dates for each week.
15. Label the secondary chart along the left side with all of the tasks (or consolidate tasks under
headings that make sense for an overview).
16. Now draw horizontal bars for each task beginning at the start date for that task and ending
with the completion date for that task.
17. When you have completed a timeline for each task and all Mentat members agree to its
accuracy, follow the same procedure in step #11.
18. Draw a secondary chart for the first week's activity by putting each day of the week across
the top and each task for the week along the left side. Then follow procedure in step #16.
19. Label bars with name(s) of Mentat member(s) responsible for that task.
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20. Save chart and make copies for all Mentat members.
Probabilistic Solutions to Project Scheduling
Some statistically-based planning methods are similar to CPM in that both are network oriented.
However, CPM is a deterministic methodology in that each activity is considered of exact fixed
length. Some considers each activity stochastic in that variability is allowed in each activity.
When one develops a statistical model, each activity is assigned three lengths:
a = an optimistic time (probability .9 of completion)
m = a typical time (modal)
b = a pessimistic time estimate (probability of .1 of completion)
The statistical model upon which this is based is known as the Beta distribution. The Beta
distribution looks and behaves much like the normal distribution when m is exactly centered
between a and b. When m is closer to a than to b, the Beta distribution becomes a positively
skew unimodal distribution and when m is closer to b than to a, the Beta distribution becomes a
negatively skew unimodal distribution. This difference allows a better fit of real-world data to
activities than would the normal distribution. When activities that are Beta distributed are added,
the resulting sum approaches the normal distribution that can be used to estimate completion
times.
Several approached to this are possible. In the more complex modeling, each activity would be
dealt with as a Beta-distributed variable, and the critical path(s) would be determined in that
way. Notice the plural in the prior sentence on the word path. Because of the stochastic nature of
each activity, the critical can change as the length of activities change. When modeling a project
network in this manner, the alternative CPM modeling strategy is used to determine the critical
path.
A second methodology considers only activities that have been previously determined to be on
the critical path using a CPM model previously selected. In most cases, it is sufficient to provide
reasonable probability estimates of project length. Advantages of this method include only
having to develop three estimates for activities on the critical path and the inherent simplicity of
the methodology.
Developing an Approximate Solution
a.
Determine the critical path using CPM methodology. This could be done using either of
the two CPM methodologies examined previously..
b.
Estimate three times for each activity on the critical path.
a = optimistic time (probability .9 of completion)
m = typical time (modal)
b = pessimistic time estimate (probability of .1 of completion)
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[these are the parameters for the requisite Beta distribution]
c.
Determine the expected completion time, te, for each activity.
d.
Determine the completion time variance, v, for each activity.
e.
Sum the expected completion times and the variances for all activities on the critical path.
Denote the sum of the expected completion times as S, and the sum of the variances as V.
f.
Compute the probability of completing on time by computing where D is the desired
completion time. Use the normal distribution to determine the probability of completion.
Critical Path Methodology Analysis Steps
CPM analysis starts when you have a table showing each activity in your project. For each
activity, you need to know which other activities must be done before it starts, and how long the
activity takes.
Envision a network diagram of the project that shows which activities follow which other ones.
The analysis method the Mentat be using requires an "activity-on-arc" (AOA) diagram. An AOA
diagram has numbered "nodes" that represent stages of project completion. You make up the
nodes' numbers as you construct the diagram. You connect the nodes with arrows or "arcs" that
represent the activities that are listed in the above table.
Critical Path Methodology Steps Summary
CPM helps you identify a complex project's critical paths. You can find how long a project will
take and which activities must be on time. If you also have information about costs and crash
costs and times, CPM helps you determine how long the project should take, and which activities
should be sped up ("crashed"). The steps are:
1. Have a list of the activities.
2. Draw the network diagram.
3. Specify activity names, node numbers, times, and costs
4. Determine the path information.
5. Calculate the paths' times.
6. Identify the critical paths, and the activities in each path.
7. Calculate the project's total cost.
8. Solve, and fix errors, if any.
9. For an economic analysis, change the maximum time constraint and solve again. Repeat until
costs, including penalties and bonuses, start to go up.
Critical Action Path and its Analysis
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Critical Path Analysis is an extremely effective method of analyzing a complex project. It helps
you to calculate the minimum length of time in which the project can be completed, and which
activities should be prioritized to complete by that date.
Where a job has to be completed on time, critical path analysis helps you to focus on the
essential activities to which attention and resources should be devoted. It gives an effective basis
for the scheduling and monitoring of progress.
The critical Action path is composed of two sources of schedule information: Critical Path and
Critical Events.
Critical Path
Critical Path information is obtained from the site's analysis of all activities scheduled to
complete the mission and achieve the desired end result. It is defined as the longest path (in
terms of duration) through the schedule of project activities that achieve site closure. The
duration of activities on the critical path drives the site closure date. Delay in a critical path
activity will delay the closure of the site; similarly, acceleration of the site closure date can occur
only if acceleration occurs with critical path activities. Many other non-critical path activities are
included in the site's cleanup plan, however, sufficient float (i.e., slack time) exists with these
activities to allow some flexibility in their accomplishment without affecting the site closure
date.
The specific project activities that comprise the critical path may change. An example of such
critical path changes would be changes to the planned end states associated with breakthrough
technologies. For sites to close earlier, enhanced performance of the critical path activities would
have to occur or funding/compliance conditions would need to be modified.
Critical Events
Critical Events are those selected milestones, events, decisions, and/or projects that are not on
the critical path but occur within the next three to five years and are of sufficient programmatic
risk to warrant upper level management and stakeholder attention.
Sequential and Parallel activities
The essential concept behind Critical Path Analysis is that some plan activities are dependent on
other activities being completed first.
These dependent activities need to be completed in a sequence, with each activity being more-orless completed before the next activity can begin. Dependent activities are also called 'sequential'
activities.
Other activities are not dependent on completion of any other tasks, or may be done at any time
before or after a particular stage is reached. These are non-dependent or 'parallel' tasks.
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Carrying out a Critical Path Analysis
The process of carrying out a critical path analysis is shown below:
1) List all activities in plan
Show the earliest start date, estimated duration and whether the tasks are parallel or sequential. If
the tasks are sequential, show what they depend on. Start week shows purely when resources
become available. Whether a task is parallel or sequential depends largely on context.
2) Construct the planning graph with the days or weeks through to task completion
3) Visualize the tasks
Start on the earliest start dates, and mark on the duration. Show the tasks as arrows, and the ends
of tasks with dots. Above the tasks arrows, mark the time taken to complete the task. Do not
worry about task scheduling yet - all we are doing is setting up the first draft of the analysis.
Once you have plotted the tasks, plot in lines to show dependencies.
Schedule Activities
Take the draft analysis, and use it to schedule the actions in the plan, in such a way that
sequential actions are carried out in the required sequence. Parallel actions should be scheduled
so that they do not interfere with sequential actions on the critical path, if possible.
While scheduling, bear in mind the resources you have available, and allow some slack time in
the schedule for hold-ups, over-runs, failures in delivery, etc.
Presenting the Analysis
The final stage in this process is to prepare a clean final copy of the analysis. This should
combine the draft analysis with your scheduling and analysis of resources to show when you
anticipate that jobs should start and finish.
There are two formats for this clean copy. The choice of the most effective form of presentation
comes down to the circumstances of the analysis and personal taste. Of course, the particular
format must bear in mind the preferences, interests and concerns of the client.
Carrying out the critical path analysis above shows us:
* That if all goes well the project can be completed in what time
* What will be necessary if we want to complete the task as rapidly as possible, we need:
* What the critical path is
What are low priority tasks as long as they is completed by a specified time
Critical Path Analysis is an effective and powerful method of assessing:
* Tasks which must be carried out
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* Where parallel activity can be carried out
* The shortest time in which a project can be completed
* Resources needed to achieve a project
* The sequence of activities, scheduling, and timings involved
* Task priorities
* Etc.
An effective critical path analysis can make the difference between success and failure on
complex projects, and can be an effective tool for assessing the importance of problems faced
during the implementation of the plan.
The Value of Strategic Planning
Increasing competition, rising customer expectations and the possibility of mergers, buyouts,
partnerships and other alliances are forcing many companies to rethink their strategies for the
future. If your company faces similar challenges, strategic planning can help you anticipate and
adapt to change. Proper planning will guide you through an interactive process to:
* Gather input from all appropriate sources.
* Evaluate your current situation.
* Develop a long-term strategic view.
* Establish priorities for the use of limited resources.
* Build consensus and commitment for the future of the organization.
* Communicate the long-term view to others in the organization.
Strategic Planning is not magic. It is hard work aimed at establishing a process for analyzing,
making decisions about, and directing your business. Strategy goes beyond predicting and
reacting to your environment. It helps you anticipate the areas where change is likely to occur
and exploit these new opportunities.
Strategic Planning isn't intended to replace intuition or to outperform entrepreneurial
executives; however, it does help understand and prepare for the future impact of current
decisions.
Strategic planning forces companies to examine and innovate by drawing attention periodically
to the major questions a business should ask itself:
* What are the fundamental characteristics of our industry and how are they changing?
* What are the competitive opportunities of which we should take advantage and competitive
threats against which we must defend?
* What are the strengths on which we might build?
* Which of our weaknesses must we eliminate?
* How do our current customers define us?
* How do we provide them value?
* What is our business in their terms?
* What will our business be in the future?
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* Against whom should we compete?
* How should we deploy our physical, people, knowledge, and financial assets?
Planning and effective time use
By now you should know the value of your time, and should understand how to find out what
you should be concentrating on.
The next stage in concentrating on results is to learn how to plan. Planning can be considered to
be an investment in efficiency and success. Planning is the process by which you work out what
you want to achieve, and then think through the who, what, when, where, why and how of
achieving that goal in the most effective way possible.
By planning well you can ensure that you concentrate only on those tasks that will move you
towards your goal in the most effective way possible, without being distracted by unimportant
but urgent tasks.
Planning breaks down into two main strands: personal planning, which is best done by setting
goals, and project planning, which is best achieved by a formalized application of the planning
process.
Strategic planning techniques
It might be wise not to overestimate the value of planning techniques. They can only be as good
as the quality of information that they manipulate and of the perceptiveness of those that use
them. Planning techniques should only be viewed as tools for supporting the planning process
and are not any substitute of that process.
Examine scenario planning, a set of techniques with which managers can think the unthinkable
without losing credibility. Scenarios allow an opportunity for considering alternative
environments and how decisions could be played out. Two scenarios would probably be
sufficient. Three main types of scenario analysis techniques are, intuitive logics, trend-impact
analysis and cross-impact analysis. It could be argued that scenario planning can be particularly
effective when used in long-term planning for large companies. Short-term planning, on the
other hand, requires the sort of emphasis on detail which scenario analysis does not provide.
Eight tools which are indispensable for the analysis of data used in strategic decision-making:
1.The experience curve
2.Matrices:
a. Directional policy matrix
b. Hofer matrix
c. Patel and Younger matrix
3.Profit improvement of market strategy (PIMS)
4.Porter's value chain
5.Lewin's Force-Field Analysis
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6.Delphi
7.Morphology
8.Wargames
All these analysis tools and models are the subject of every serious textbook on strategic
management. It could be argued that managers should not restrict themselves to using just one
analysis instrument, as each one has its advantages and disadvantages. On the contrary, it could
be claimed that the effectiveness of instruments is likely to increase if management were to view
them as a series of tools.
Strategic Planning Process
The annual strategic planning process, according to many managers I've talked with, seems to
intrude like an unwelcome punishment for having made it through another year. It really doesn't
have to be that way.
Following are eight ideas for simplifying your planning process while building in more
satisfaction and profit.
A plan should do at least three things for you:
1. Set goals in terms of financial measures and other definable accomplishments.
2. Chart the road for getting there with milestones along the way.
3. Allocate resources for the near term to integrate with a strategic plan. Organize to measure
against plan on a monthly basis to get full value from it.
Guidelines
1. Decide what you want the plan to accomplish. Prioritize primary goals for the plan, estimate
the effort required, and then decide on the scope for the plan. Not all elements of a plan require
the same level of excruciating detail. For example, evaluating new product and service costs in
detail may be vital but older, more stable products may only warrant fine-tuning.
2. Avoid over or under-planning. If you have to dust off the old plan before you open it up to
start over it's a clue that either the plan was so perfect it ran on autopilot or you didn't use it. If it
was perfect, please give me a call right now and you can write the next article on this subject. If
you didn't use it, maybe you just didn't need that level of planning. Consider adjusting it or using
it to a greater extent throughout the year.
3. Use facilitated cross-functional Mentats to kick off the process and keep it on track. It really
helps to have a process leader who will keep you focused and facilitate the meetings as well as
the over-all process. The task usually falls to one of the bosses and they might not be the right
person for the job. They have too much to do and have their own axe to grind just like the rest of
you. It pays to pick someone who can be neutral and is skilled in the process.
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4. Use a manual and a standard format. Standardization and manuals help keep the deadwood out
(If you don't build it in that is.) and simplify the entire process from planning through creation
and implementation. Start simply and adjust on a year-by-year basis.
5. Break the plan and the process into smaller more manageable pieces. You then have the
chance to apply your priorities and effort levels accordingly. Delegation also rears its beautiful
head as an option for sharing the load.
6. Avoid the "make it fit" syndrome. I have yet to meet a manager who didn't occasionally try to
use a shoehorn to jam 7 pounds of cost and effort into a 5-pound budget limit. Two things can
happen, however, and only one of them is good. On the good side, you might somehow discover
or luck into a way to make it fit. On the down side, that overage could explode in the middle of
the year leaving you with a mess to clean up next planning cycle. Personally, I got tired of being
hammered on by one myopic boss who insisted on the shoehorn, withheld the resources to make
it happen, and then looked for a scapegoat for the inevitable problems. If you're going to set
stretch goals, make sure you plan the effort to make the sales increase, cost reduction, or
whatever is required.
7. Plan for the planning process. A good strategic business plan should be a moneymaker and an
integral part of everyone's job and the process is built into the budget. The problem of not having
enough time seems to result from the fact that few companies plan for their planning process. All
too many departments see planning as an intrusion on the task of making money or getting their
real jobs done.
8. Check your plan against the corporate mission. Your mission is an overarching guide for the
future. Any potential conflicts are a sure sign that something is out of harmony. Take heed before
it catches you by surprise. One major organization suffered for years through the process of
rigorously setting goals and then put them in a file without checking them against their mission.
They wondered what kept going wrong until new management brought in new methods and
systems to set goals and create plans that were consistent with the organizational mission. The
process was difficult but the positive results paid off very well.
Negotiation:The Basics
Anything you'll ever want is presently owned or controlled by someone else. It makes sense that
you learn how to negotiate to get what you want and deserve.
By learning to be a good negotiator, much of the stress and frustration you presently experience
will go out of your life. In other words, you'll be able to take control of your life by negotiating
successfully. Your personal and professional relationships will be enhanced. It's possible to get
whatever you want by negotiating successfully with others. By learning to structure the
negotiation, and you must keep in mind you are negotiating all the time, much of the pressure
and stress will be removed from your life.
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We expect to negotiate when we think about business but it's not just spread sheets, profit and
loss statements and numbers, it's handling people. It's time to learn how to get them (employees,
competitors, clients and the opposition, so to speak) what they want while we are getting what
we want.
If you are willing to do what is necessary to succeed and accept the responsibility for allowing
your success, then you won't be disappointed. Success can be yours if you think smart and
constantly use the techniques outlined in this book.
Risk Factors/Motivation in Planning
Generally speaking, people who aim higher, do better - to a certain point. Some aim higher and
fail. You must set goals of how you're going to do and then strive for the goal or objective.
When we buy or sell anything we must put the transaction into perspective. That is, we must
review the real estate world in perspective to what's going on today and then decide: Would this
property or product be of value to the homebuyer or any buyer today? In other words, will it suit
him, or to put it another way, we don't sell the horse property to the boat enthusiast or the estuary
property to the horse set.
Planning is Power
Planning pays off. Planning pays off very quickly in the negotiation arena. Before the encounter
takes place, go through it in your mind; rehearse it in advance. Be sure to state clearly and in
precise words what you want to accomplish. Next, it's important to set the stage by visualizing
where the encounter will take place; standing up, sitting down, office, home, desk, private office,
whose? The chances are your opponent will not go through such a mental process. The actual
situation will be new for the other person but not for you. This will give you an advantage. Your
opponent will make mistakes but you will have rehearsed and corrected your behavior.
Plan your meeting and then meet according to your plan. You'll have the advantage of knowing
what your plan allows you to get through the first few minutes of your encounter. You'll know
where to start precisely and what steps to take to get you to your next objective. You put yourself
into a trap by not considering possible alternative positions and alternative situations. Find out as
much as possible about your opponent in advance.
You should consider your opponent's likely opening position and what he or she will or will not
want to pay or accept. Your plan should not only be to change your opponent's aspiration level,
but to get him or her to re-evaluate the minimum he or she will accept or the minimum he or she
will pay.
Your overall plan should include how to visualize the negotiation process moving towards your
desired conclusion. To achieve this, you must consider the basis of your opponent's position and
arguments your opponent will use. You must plan not only support for your position, but
arguments to weaken the position of your opponent. You should identify the obstacles you
anticipate in negotiations and plan how to overcome them.
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Decide on what benefits you want to offer the other side and what benefits you want to use as
bargaining chips to hold or later give up in negotiating. Planning should include more than just
arguments; it should include the actual language of the presentation.
Steps to Successful Planning
* You need to gain information - you want to know as much as possible about the
property/product or similar products.
* Set goals/objectives based on your perception of strengths and needs. Plan the tactics you will
use. Identify mutual interest of the parties. Analyze your strengths and weaknesses and those of
your opponent. Define the issues of contention and consider alternatives; the more in number, the
better your chances to resolve the issues.
* Prioritize before you begin; rank your priorities in "must have" and "want but not a must". Be
flexible; you must be willing to give something up. Don't lose sight of what you are negotiating.
Make a checklist.
Price is always obvious but what about this?
* Defects
* Inspections
* Financing
* Due on sale clause
* Assumptions
* Date of possession
* Who is responsible for maintenance?
* Who pays the closing cost?
* What about earnest money?
* What about liquidated damages?
* Will the need come up for increased earnest money?
* Insurance
* Personal property
* Will it be "subject to"?
Before the encounter takes place, go through it in your mind, rehearsing it in advance. Play a
little script writing game with yourself, although preferably not word-for-word. Plan your
meeting then meet according to your plan. Having the advantage of knowing what your plan is
allows you to get over the first few very important minutes or seconds of your encounter. You
know how to start because you already know precisely what the outcome is to be and what the
steps are that will get you there. It is easier if you set off in the correct direction.
Listen
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Most people know how to talk but they don't know how to listen. Not only should you know
what's being said, you should also be aware of what's being implied. Don't assume!! Ask
questions and verify facts; take notes. If your opponent gives false or wrong information, don't
call him or her on it or call them a liar; just let them know that you know otherwise and that they
may have bad information. This will keep them at the negotiating table; the door will remain
open.
Dumb is Smart and Smart is Dumb
When reviewing a product of property you really like, be sure the seller understands you are
looking at other options. This tactic should get the sellers into a selling mode.
Your objective is to get the sellers to accept a less than asking price offer without being
offended. Low offers will reduce the sellers expectations and prepare them for a lower price.
You Don't Want It or Need It
The best prices are usually obtained by people who don't want the property. Your power as a
buyer is usually greatest when you don't want to buy. As your motivation and desire to buy
increases, your power to negotiate decreases. When you want to buy something, you must give
the appearance that you are a reluctant buyer or you will lose all of your ability to negotiate.
Try To Interview Questions
During negotiations, find out as much about your opponent as possible. Knowing his needs and
motivations will help you in structuring the responses. Your opponent will want as much
information as possible about you so try to restrict your information flow as much as possible.
Be The Investigative Reporter
Open questions creates a conversational tone. They eliminate the sense of interrogation typically
associated with closed questions. In fact, the person may not be aware the questions are even
being asked. Open questions encourage the other person to think about the answer. By asking a
question, you have invited the other person to offer his views, i.e.:
* What would you like to see happen as a result?
* Where do you think your agency fell short?
* What message do you want to get across to the public?
* What do you think are the benefits of your product?
* Why do you think someone should buy your product instead of your competitor's?
With open questions you gain more than factual information; you get a good take on thoughts,
attitudes and emotions that influence the other person's actions. Open questions also help the
other person clarify his thinking as he states his needs in his own words.
Creating Smart Questions
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A closed question is easily turned into an open question by adding one or two important words;
what, how and could are perfect examples.
Problem Solving
What seems to be the problem?
What solutions do you see?
Taking The Sting Out Of Criticism
How do you think ______ affects ______? (Fill in the blanks to suit the situation)
Establishing a give and take atmosphere lets you learn a great deal. Ask, "is there anything more
I can do to clarify before you begin?', or "Why don't you give it some thought and get back to me
with questions before we begin."
Basic Concepts
* Negotiate only with those in Authority
* Satisfy the needs of ALL parties
* Be Prepared to Trade
* Be Calm
* Sell
* Don't compromise your objectives
* Deal from Strength
* Tell Your Story Yourself
* Sleep on It
* Don't Oversell
* Keep a poker face
* Don't underestimate others
* Be Personal
* Don't be too exclusive
* Respect Confidentiality
* Be Confident
* Never Let you Guard Down
* Be reasonable
* Always End on a Positive Note
Strategy
* Sit at the "Head of the Table" in meetings
* Take Command of Each Meeting
* Have a Total Plan
* Carefully consider the effect of Meetings in Public
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* The fewer the participants, the earlier the Agreement
* Whenever possible, Phrase Questions for a Positive Answer
* Be Flexible
* Go No More than Halfway
* Make an Early concession
* Don't wait to Spill Bad News
* Defer Discussions of Key Issues
* Each Day is a New Ball Game
* Know the Needs of the Other side
* Make Promises with Caution
* Don't waste people's time - including your own
* Don't Keep Worrying about the End Results
* Don't Work Others
* Make ALL terms Specific
Tactics
* Avoid Marathon Sessions
* Be the Aggressor
* Caucus Often
* Interruptions Turn People Off
* Silence is Golden
* Be the First to bring up Major Terms
* Break the Tension
* Defer Discussion about Sensitive Points
* Don't end a Meeting on a Negative Tone
* Get Agreement on Next Steps
* Make it Easy
* Disagree on a Positive Note
* Be Courteous
* Keep the Meeting on the Track
* Don't React too Unfavorably to Your Own Mistakes
* Don't Rush the Other Side
* When the Mission is Accomplished - Leave!
Disciplines
* Don't Retrade
* Be a Team Member
* Don't Drink
* Be Right the First Time
* Don't Slouch
* Don't be In A Hurry
* Don't Brag
* Concentrate
* Tell it Like It Is
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* Don't be a Nitpicker
* Be On Time
* Say What you Mean
* Be Organized
* Be Well Groomed
* Don't Appear Up-Tight
* Think Ahead
* Avoid Smoke Signals
* When in Rome, Do as the Romans do
* Never say "I Told You So"
Analysis
* Represent Yourself
* Be sure the Chemistry is Right
* Eyeball to Eyeball - discuss Terms Only in Person
* Listen! You've Heard This One Before
* Spot Their Leader
* Analyze Office Deor
* A Negative Statement may be a "Go" signal
* Don't be Too Critical
* Evaluate Others' Success
* Be Wary of Ignorance
* Observe Associates
* Look for Ways to Verify What you are Told
* Is He With You?
* Reconnaissance is Valuable
* The Early Bird Gets the Worm
* Reluctance Means Problems or Weakness
* Absence is a Red Flag
Psychology
* Be Yourself
* Don't Knock Others
* Be Positive When Discussing Other's Problems
* Don't Embarrass Other People
* Be Cautious about Expressing Unrelated Opinions
* Don't be Unpleasant
* Respect Other's Personal Preferences
* Show Interest in Others
* Be Sensitive to Other's Moods
* Be Patient
* Don't Push Too Far
* Expect Negative Reactions
* Think Before You Speak
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* Be Understanding
* Acknowledge Others' Contributions
* Respect Identity
* Show Interest
Details
* Be Prepared
* Document
* Keep the Numbers Even
* Select your Team Carefully
* Organize the Meeting Room Ahead of Time
* Clarify Each Point of Agreement
* Avoid Disappearing Acts
* Delegate Only with Control
* Negotiate in Your Territory
* Keep it Simple
* Site Selection is a Critical Factor
* Breakfast Meetings are Often Disappointing
* Be a Good Host
* Timing is a Critical Factor
Beware
* Observe Office Furniture Strategy
* Watch the Windows
* "I'm Really a Good Guy"
* You'll Never Get the Whole Story
* Be Wary of the Flatterer
* Beware of Provocation
* Be Alert for Strained Eyeballs
* Be Cautious When You are Not Wanted
* Find Out what's REALLY on Their Mind
* Look Out for the Procrastinator
* Be Sure You have All The Facts
* Watch Out for the Faker
* Don't Get Taken by the Pack Rat
* Don't be Fooled by the Cover
* Don't be Taken by the Soft-Soaper
* Watch Out for Snow Jobs
The Last Word
* Be Absolutely Sure there are No Surprises in the Fine Print
Guidelines
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The guidelines offered here will work but they are just that, guidelines. These are not foolproof
scripts that will produce identical outcomes.
Overcoming Objectives
When confronted with "yes", but "ask", "what are your major concerns about this project, idea,
product?" "What other choices do you see?" "How can I help you?".
Getting Cooperation
When faced with a blank wall, ask "Have you ever made an exception?".
Clarifying Statements
"How do you plan to do it?".
Stemming Anxiety
"Which of these is more important and what are the time limits?".
Defusing Volatile Emotions
"Can you tell me more about what you are feeling?".
Open-Ended Questions
The beauty of open questions is that they allow the other person to become involved to
participate in the exchange and come up with solutions of his or her own, i.e.:
* How would you handle this situation?
* What kind of people get ahead in this company?
* What kind of feedback are you getting from your people in this field?
* How to you feel about this?
* What is most important to you?
* What is it you don't like about Brand X?
* What are your priorities for this assignment?
Negotiation Priorities
There are many techniques, but these two are absolutely essential:
Know what you want to accomplish
Determine what steps are needed to accomplish it
Articulate What You Want
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You must decide, before any contact is made, exactly what you want. Then in very simple terms,
state the desire clearly and in a manner that will allow you to observe your success or your
failure so you can learn from your experience. If you don't articulate exactly what you want,
you'll never know how to go about getting it. Further, if you fail in a given situation, without
articulation you'll be unable to identify what you did wrong. Therefore, you won't know how to
improve your performance the next time the same situation arises.
Judging Books By Their Covers
We are all victims of this observational shorthand. Most of us use it without even thinking.
Stereotypes could be way off base, however people make those judgments all the time.
The Impression You Make
You want to plan the first impression you want to make. Since we expect certain people to dress
a certain way, when we see a particular type of appearance we automatically identify that person
as a particular type. We then expect certain behaviors and actions from that person. It's a quick
system and most of us use it. When we do this, it means that we instantly reach a conclusion
about someone we have not seen before. If the initial impression was positive, fine. But if it was
negative, the person must overcome an obstacle. Furthermore, they may not realize they have the
obstacle to overcome.
Ask yourself, what do you look for when you are planning a face-to-face meeting? You already
know about yourself but the confrontation isn't with yourself, it's with someone else. You have to
win over that someone. The first rule is to determine what is important to your adversary. This is
much more significant than being concerned with what makes you feel good. Once you know
what is significant to your opponent, you can determine more thoughtfully the way you want to
present yourself. You'll probably have many choices. Think, what will impress that person?
Overpower that person? Intimidate that person?
This is a good place to talk about dress code...
Remember, determine what is most important to you; what do you want? If you want to win, do
the advance planning and take the necessary steps to be successful.
Planning How You Look
In most situations, you improve your chances of winning if you are more like than unlike your
adversary, and it is easy to find out what your adversary is like. Just visit the environment before
your meeting or talk to someone who is familiar with the opponent.
Territory
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Never enter into a negotiation without being familiar with the territory. Always reconnoiter the
area before engaging in any conflict; in other words, eliminate or minimize surprises. The more
you see, hear, touch, smell, about a meeting location, the better.
Props - Life Is Just Like A Play
Characters in a play need costumes to support and enhance their positions. Baseball and football
players need uniforms to support their positions and enhance their status. You should use notes
in a very obvious manner as props. Notes can focus attention. If during the discussion you wish
to emphasize one of your ideas, you can refer to your notes. Your adversary will become aware
of its significance as you point out the significant item. Make sure your opponent is aware that
you are being careful, thorough and meticulous. If you keep meticulous notes, your open's
perception of your strength as an adversary will heighten. You will be demonstrating that you are
both well informed and well prepared.
Data collection is a powerful tool. It not only demonstrates knowledge but it also effectively
counters an opponent's use of phrases such as I think, or I feel, or it seems to me. For maximum
effectiveness, your notes should consist of documents, policies, contracts, copies and volumes of
actual handwritten notes (in your own handwriting of course).
Use Notes Like Attorneys
In the courtroom situation, you'll notice the attorneys slow the opposition down by referring to
notes and asking for repeats of what was said. So you see, they can be used to focus your
attention or they can be used to slow the opposition down and keep them off base. Notes will
give you time to think about new questions and gather your thoughts.
Know exactly what you want. Preparation is very important. Write it down and have it
prominently visible in your notes. If you don't know what you want, you won't know if you ever
get it. Review. If you review progress and state what you want, this will make your opponent
uncomfortable because you are so well prepared it will give you a significant increase in the
chances you will win your points.
Using Your Notes and Preparation
Don't try to commit too much to memory. Use your list and your plans and use them openly.
This will create a certain amount of intimidation for your opponent. Use large sized pieces of
paper, not scratch pads. Refer to your list and make notes during the conversation. Be careful and
deliberate. Refer to your notes regularly. Take your time. When the opposition sees you're using
notes, they will become intimidated and concerned that you are better prepared than they are. If
you don't know what to say, refer to your notes. DON'T TALK IF YOU ARE
UNPREPARED. Take your time and know what you want to say.
Keep Your Sights on What You Want
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Never lose sight of exactly what you want. Before the negotiation begins, write out a simple
statement of what you want the outcome to be. This will enable you to direct the conversation
toward your goal. You will not be distracted by inappropriate material. In order to win, you must
know what you want and be able to tell when you have acquired it.
No Preparation
The chances are excellent that your opponent will not have taken time or care in the planning, so
you have an advantage. The size of the advantage will vary during the negotiation.
Inconsistencies
Listen for inconsistencies. Attention to details when your opponent is talking will often alert you
to changes in the opponent's position. If your opponent becomes confused and inaccurate
concerning an issue or problem, you can assume your opponent is on soft ground. If a person has
confidence is the facts, their position will be strong and solid.
When the opponent falters and changes facts, he or she is vulnerable. This is when you carefully
review your notes and then use them to your advantage. The facts that you have written down
will help you develop a strong argument for your position, especially if you can read back your
opponent's words from your notes. Pay attention to the language of your adversary. Find out
what is important to that person. Learn something about their business before you make the
contact. A little preparatory research will be of help. Again, never lose sight of your goal. You
want to win the confrontation and in order to do so you must have supporting information.
Concentrate and focus your search.
Preparation
The same skills are available to your opponent. If you prepare your position knowing what the
other person might do, you can win by planning ahead and selecting your action carefully. If you
simply let things happen and let nature take its course, you reduce your chances of winning. Let's
face it, losing makes no sense.
Remote communications Negotiations
In my opinion, the most dangerous type of negotiation is by the telephone. It's the ultimate jumpstart, quickie deal. Don't do it, is my recommendation, and here's why:
The following are a few of the many things that can go wrong:
* No Planning
* No visible body language
* No agenda - very dangerous
* Other activities going on in the office (distractions)
* Interruptions
* It's easy for the other party to say no
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* The caller is always better prepared
* It's easy for the party receiving the call to make up excuse
Prior Planning Precludes
Poor Performance
* Schedule an appointment
* Make an agenda
* Have a plan to use, a checklist
* Make small talk to slow it down
* You'll lose money if you shoot from the hip
* Know what limits the opponent's power
* Have notepaper and calculation equipment handy
* Have reason to make or not make the deal right away
* Have time limits
* Check with higher authority if pressured
Buying Pressure/Selling Pressure
Sellers usually have more pressure than buyers. Let's review ways to limit the buyer's ability to
negotiate, using a house sale as an example. Think about the following:
* Unusual features
* Location
* Conditions
* Service
* Terms
* Prestige
* Size and shape
* Time and quality
* Track record
* Quality and history
* Technical services
* Warranties
* Perceptions
Buyers can limit the seller's ability to exploit their sole position by:
* Threaten to do without - make your own
* Re-design or re-engineer the product or house
* Take another look at how much you buy
* Go direct to the builder and pass you by
* Timing is always a limitation
* Specifications don't meet your standards
* Track record - reliability, delivery
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Feel-Felt-Found System To Avoid Controversy
FEEL - I know how you feel
FELT - I've felt the same way myself
FOUND - But I've found when I examine the situation...
Don't argue; that forces them to defend their position. Agree and then turn it around.
Remember, smart is dumb and dumb is smart. Instead of the opposition competing with you,
they help you if you are dumb.
The Call Girl Principal
Value of service always diminishes after the service is performed.
Concessions
Anytime you make a concession, be sure and get a concession, otherwise the opposition will
keep asking for concessions. If you don't stop them, they will continue to request a concession
until you do. The answer is to ask for a concession every time you give one, this way they will
stop asking. Ask for something in return right away. Use the Trade-Off Principal: If I can do that
for you, what can you do for me? Never give anything away.
Funny Money
Remember the real estate commission as an example: The agent will say, "Oh, it's only 6%",
which sounds small on the surface but if the property was worth a million dollars, the small 6%
is $60.000.
React To costs
When given a price or a quote, always react or the price will increase, or they will automatically
add the freight or the packaging. People watch your response.
Squeeze or Vice Technique
"I'm sorry, you'll have to do better than that." If someone says that to you, you should say "How
much better than that do I have to do?"
Withdraw Offer Principal
"I'm embarrassed about this..."
"The committee decided last night..."
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Negotiation: The Reality
You are negotiating all the time
Everything you want is owned or controlled by someone else
Three critical factors
1. Power - tendency to want to retain
2. Information - he who has...has power
3. Time - Is it on your side?
The Negotiation Issues
Never narrow down to only one issue Different people want different things
o Establish the needs of the employer
o Establish the needs of the one you are negotiating with
o Look at the "package" value
Stages of Every Negotiation
1. Learn your opponent’s goals (Ask and do your homework)
2. Establish what you want - Know your bottom line
3. Gather information about opponent and his/her needs
4. Reach for compromise
Good Negotiators...
* ...know that both sides are under pressure
* Don't feel intimidated
* ...Practice negotiation to get better at it
* ...Don't take it personal or get emotional. They are not offering "such and such" to offend you
* Be willing to create a Fair/Fair situation. Win / win may NOT be realistic
Power Distribution in Negotiation
The opposite negotiator
* Title, reward, punish, reverent, charismatic, expertise
You can retain....
o Situation and information power...
o Time (buy it): " This is embarrassing but I need to discus this with..."
Skills in Negotiating
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* Refer to a higher authority
* Never say yes to the first offer
* The value of a service diminishes after services have been performed
* Always maintain walk-away power
* Make a big deal out of any concession you make and get a counter concession
* Don't be first to name a price
* Be the one who writes the contract
* The person under the greatest time constraint generally loses. Never reveal you have a
deadline
* Try not to negotiate using remote non-visual communications (body language cues)
* Stay positive and unemotional
* Keep looking for creative concessions and trade
* Be patient and respectful - People make concessions to those they like
* Crunch the numbers before you go out - Know what you need
* Start high to avoid "I'll bet I could have gotten more..." syndrome
* Leave the other side thinking, "I have done well"...
* Don't surprise the other party when you show up
* Before countering a bad offer...Ask...Would you reconsider?
* Principle bargaining is better that loud or hard bargaining
* Don't state you final offer first
Arguments
An argument is any disagreement - from the most polite discussion to the loudest brawl.
Defensive argument
The essence of defensive argument is simple: Assume everyone is out to get you!
Warnings
* If an opposer is very attached to a position and you are not, back off. It's not worth it.
* Don't Be obnoxious!
Super-Rule I
Never admit defeat unless you are absolutely convinced, and even then keep your mouth shut
and wait till Monday.
How to Build an Argument
* Always know what You Are Arguing About!
* A Very Good way of getting out of an argument you seem to be losing is to ask something like
"What do you think we are arguing about?" Whatever the answer is returned, say, "Oh, I see. I
thought you meant something else."
* Should someone ask you to state the conclusion, especially if there is an audience, say, "I had a
feeling that you didn't know what we were arguing about. Why don't you try taking a guess?"
* Always attack the reasons for a conclusion, not the conclusion itself
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The Principle of Rationality
We always assume that people have reasons for their beliefs.
First Rule for Dealing with a Fanatic
Don't.
When stuck, ask "What would it take to prove you are wrong?"
The Principle of Similar Cases
Where two cases or situations are similar, a reason must be offered for not treating them the
same.
The Principle Principle
Virtually every position can be expressed in terms of a general principle: for everything there is a
principle.
Always know the principles to which you are committed, and always know the principles to
which your opposer is committed.
Whenever possible, embrace the consequences of your position.
Super-Rule II
Listen!
The only way to deal with a non-listener is with patience and repetition.
The Twofold Path of Argument
The first path is learning the tools and moves. The second path is concentration and relaxation.
One without the other does not work.
Ring around the Argument
* An argument is circular or begs the question when one of the reasons assumes what it I
supposed to prove.
* Reasons and points may hurt your position, but names will never harm you: Don't fight about
labels unless you must.
* Treat a dismissal like "nonsense!" as a conclusion and not as an argument.
* When the circularity is not blatant, identify the circular reason and demand that it be justified.
* Pointing out your opposer's fallacy can make him or her look foolish or sneaky, but be certain
that your audience will see it immediately
What Were We Talking About?
* When suddenly you no longer know what you are arguing about, check to see if the subject
was changed.
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* If you do not know what the topic is, you cannot expect your opposer to stay on it.
* Trust your instincts; if you are confused there must be a reason. Check it out.
* Be firm and obvious with an habitual subject-switcher
Everyone's doing it
* Popularity alone is not enough
* If your opposer says that everyone knows....and you don't know, then what he said was wrong.
An Expert
* An expert is anyone who knows more than we do when we want to know it
* Remember - you are an expert, too, and you know how little you know
* No one is simply an expert - an expert must be an expert in something
* If the expert appealed to is not appropriate, then a fallacy is committed
* Is the Authority giving you generally accepted facts or an unusual personal opinion? Find out.
* Know Your Experts: Do they hold embarrassing beliefs? Do they make rash predictions?
* Never agree with an expert unless you really do know what he is talking about, no matter how
stupid you feel.
The Refuge of Scoundrels
* If someone attacks a person's character, insist that he put up or shut up
* Labels apply to people, not their arguments
The Straw-man Argument
* When given a radical position, ask yourself, Does anyone REALLY hold this view?
* Given any position, no matter how crazy or extreme, you can always find someone who holds
it.
* Always be suspicious of positions that are too easy to attack. They have very likely been
distorted.
The Slippery Slope
* You will slide down the slippery slope unless you remember that different statements need
different reasons
* There are always two questions to be asked about a slippery slope:
1. Is the slope truly slippery?
2. Should the first step be taken?
* Always keep track of what assumptions you have granted for the sake of argument, because
you may want to take one of them back.
Haste Makes Waste
* A statement needs more than reasons for acceptance - it needs good reasons
* Believe nothing.
* Don't think that because one thing MIGHT be a cause of another that it is.
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* An explanation is a false-cause if other explanations are easily found.
* Attack a false cause in two ways:
1. Find other causes
2. Find other false correlations
* There is no such thing as THE cause of something
* One exception falsifies a generalization
* Never make a general statement stronger than you need to - you may be forced to retract.
Sneaky Moves
* Be suspicious of choices: are there really more than you have been offered?
* Replies appealing to common practice are almost always irrelevant
* The use of "two wrongs" is an admission of guilt.
* A threat is never a good reason to believe something, but it may be a good reason to do
something.
* When looking at an advertisement always ask yourself what the ad is really selling.
* Is the threat something to be feared?
Judgment
The Three Factors of Judging
A MAN of good judgment in a given set of affairs is a man in so far educated, trained, whatever
may be his literacy. To know what is good judgment we need first to know what judgment is.
That there is an intimate connection between judgment and inference is obvious enough. The
aim of inference is to terminate itself in an adequate judgment of a situation, and the course of
inference goes on through a series of partial and tentative judgments. What are these units, these
terms of inference when we examine them on their own account? Their significant traits may be
readily gathered from a consideration of the operations to which the word judgment was
originally applied: namely, the authoritative decision of matters in legal controversy -- the
procedure of the judge on the bench. There are three such features:
(I) A controversy, consisting of opposite claims regarding the same objective situation
(II) A process of defining and elaborating these claims and of sifting the facts adduced to support
them
(III) A final decision, or sentence, closing the particular matter in dispute and also serving as a
rule or principle for deciding future cases.
I. Unless there is something doubtful, the situation is read off at a glance; it is taken in on sight,
i.e. there is merely apprehension, perception, recognition, not judgment. If the matter is wholly
doubtful, if it is dark and obscure throughout, there is a blind mystery and again no judgment
occurs. But if it suggests, however vaguely, different meanings, rival possible interpretations,
there is some point at issue, some matter at stake. Doubt takes the form of dispute, controversy;
different sides compete for a conclusion in their favor. Something in the total situation suggests
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one of many possible meanings. Only one of them can possibly be sound; perhaps none of them
is appropriate; yet some meaning the thing in question surely has. How is it to be interpreted,
estimated, appraised, and placed? Every judgment proceeds from some such situation.
2. The hearing of the controversy divides into two branches, either of which, in a given case,
may be more conspicuous than the other. In judgment they are
(a) The determination of the data that are important in the given case
(b) The elaboration of the conceptions or meanings suggested by the crude data
These questions are strictly correlative; the answer to each depends upon the answer to the other.
We may, however, for convenience, consider them separately.
(a) In every actual occurrence, there are many details which are part of the total occurrence, but
which nevertheless are not significant in relation to the point at issue. All parts of an experience
are equally present, but they are very far from being of equal value as signs or as evidences. Nor
is intensity, or vividness or conspicuousness, a safe measure of indicative and proving value.
Hence, judgment is required even in reference to the situation or event that is present to the
senses; elimination or rejection, selection, discovery, or bringing to light must take place.
Till we have reached a final conclusion, rejection and selection must be tentative or conditional.
We select the things that we hope or trust are cues to meaning. But if they do not suggest a
situation that accepts and includes them, we reconstitute our data, the facts of the case; for we
mean, intellectually, by the facts of the case those traits that are used as evidence in reaching a
conclusion or forming a decision. No hard and fast rules for this operation of selecting and
rejecting, or fixing upon the facts, can be given. To be a good judge is to have a sense of the
relative indicative or signifying values of the various features of the perplexing situation; to
know what to let go as of no account; what to eliminate as irrelevant; what to retain as conducive
to outcome; what to emphasize as a clue to the difficulty.
True judgments are based on intelligent selection and estimation, with the solution of a problem
as the controlling standard. Possession of this capacity makes the difference between the artist
and the intellectual bungler.
Such is judging ability, in its completest form, as to the data of the decision to be reached. But in
any case there is a certain feeling along for the way to be followed; a constant tentative picking
out of certain qualities to see what emphasis upon them would lead to; a willingness to hold final
selection in suspense; and to reject the factors entirely or relegate them to a different Position in
the evidential scheme if other features yield more solvent suggestions. Alertness, flexibility,
curiosity are the essentials; dogmatism, rigidity, prejudice, caprice, arising from routine, passion,
and flippancy are fatal.
(b) This selection of data is, of course, for the sake of controlling the development and
elaboration of the suggested meaning in the light of which they are to be interpreted. An
evolution of conceptions thus goes on simultaneously with the determination of the facts; one
possible meaning after another is held before the mind, considered in relation to the data to
which it is applied, is developed into its more detailed bearings upon the data, is dropped or
tentatively accepted and used. We do not approach any problem with a wholly naive or virgin
mind; we approach it with certain acquired habitual modes of understanding, with a certain store
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of previously evolved meanings, or at least of experiences from which meanings may be educed.
If the circumstances are such that a habitual response is called directly into play, there is an
immediate grasp of meaning. If the habit is checked, and inhibited from easy application, a
possible meaning for the facts in question presents it. No hard and fast rules decide whether a
meaning suggested is the right and proper meaning to follow up. The individual's own good (or
bad) judgment is the guide. There is no label on any given idea or principle that says
automatically, "Use me in this situation " -- as the magic cakes of Alice in Wonderland were
inscribed " Eat me." The thinker has to decide, to choose; and there is always a risk, so that the
prudent thinker selects warily, subject, that is, to confirmation or frustration by later events. If
one is not able to estimate wisely what is relevant to the interpretation of a given perplexing or
doubtful issue, it avails little that arduous learning has built up a large stock of concepts. For
learning is not wisdom; information does not guarantee good judgment. Memory may provide an
antiseptic refrigerator in which to store a stock of meanings for future use, but judgment selects
and adopts the one used in a given emergency -and without an emergency (some crisis, slight or
great) there is no call for judgment. No conception, even if it is carefully and firmly established
in the abstract, can at first safely be more than a candidate for the office of interpreter. Only
greater success than that of its rivals in clarifying dark spots, untying hard knots, reconciling
discrepancies, can elect it or prove it a valid idea for the given situation.
3. The judgment when formed is a decision; it closes (or concludes) the question at issue. This
determination not only settles that particular case, but it helps fix a rule or method for deciding
similar matters in the future; as the sentence of the judge on the bench both terminates that
dispute and also forms a precedent for future decisions. If the interpretation settled upon is not
controverted by subsequent events, a presumption is built up in favor of similar interpretation in
other cases where the features are not so obviously unlike as to make it inappropriate. In this
way, principles of judging are gradually built up; a certain manner of interpretation gets weight,
authority. In short, meanings get standardized, they become logical concepts.
The Origin and Nature of Ideas
This brings us to the question of ideas in relation to judgments. Something in an obscure
situation suggests something else as its meaning. If this meaning is at once accepted, there is no
reflective thinking, no genuine judging. Thought is cut short uncritically; dogmatic belief, with
all its attending risks, takes place. But if the meaning suggested is held in suspense, pending
examination and inquiry, there is true judgment. We stop and think, we de-fer conclusion in
order to in-fer more thoroughly. In this process of being only conditionally accepted, accepted
only for examination, meanings become ideas. That is to say, an idea is a meaning that is
tentatively entertained, formed, and used with reference to its fitness to decide a perplexing
situation, -- a meaning used as a toot of judgment.
Let us recur to our instance of a blur in motion appearing at a distance. We wonder what the
thing is, i.e. what the blur means. A man waving his arms, a friend beckoning to us, are
suggested as possibilities. To accept at once either alternative is to arrest judgment. But if we
treat what is suggested as only a suggestion, a supposition, a possibility, it becomes an idea,
having the following traits: (a) As merely a suggestion, it is a conjecture, a guess, which in cases
of greater dignity we call a hypothesis or a theory. That is to say, it is a possible but as yet
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doubtful mode of interpretation. (b) Even though doubtful, it has an office to perform; namely,
that of directing inquiry and examination. If this blur means a friend beckoning, then careful
observation should show certain other traits. If it is a man driving unruly cattle, certain other
traits should be found. Let us look and see if these traits are found. Taken merely as a doubt, an
idea would paralyze inquiry. Taken merely as a certainty, it would arrest inquiry. Taken as a
doubtful possibility, it affords a standpoint, a platform, method of inquiry.
Ideas are not then genuine ideas unless they are tools in a reflective examination that tends to
solve a problem. Suppose it is a question of having the pupil grasp the idea of the sphericity of
the earth. This is different from teaching him its sphericity as a fact. He may be shown (or
reminded of) a ball or a globe, and be told that the earth is round like those things; he may then
be made to repeat that statement day after day till the shape of the earth and the shape of the ball
are welded together in his mind. But he has not thereby acquired any idea of the earth's
sphericity; at most, he has had a certain image of a sphere and has finally managed to image the
earth after the analogy of his ball image. To grasp sphericity as an idea, the pupil must first have
realized certain perplexities or confusing features in observed facts and have had the idea of
spherical shape suggested to him as a possible way of accounting for the phenomena in question.
Only by use as a method of interpreting data so as to give them fuller meaning does sphericity
become a genuine idea. There may be a vivid image and no idea; or there may be a fleeting,
obscure image and yet an idea, if that image performs the function of instigating and directing
the observation and relation of facts.
Logical ideas are like keys that are shaping with reference to opening a lock. Pike, separated by
a glass partition from the fish upon which they ordinarily prey, will -so it is said -- butt their
heads against the glass until it is literally beaten into them that they cannot get at their food.
Animals learn (when they learn at all) by a " cut and try " method; by doing at random first one
thing and another thing and then preserving the things that happen to succeed. Action directed
consciously by ideas -by suggested meanings accepted for the sake of experimenting with them is the sole alternative both to bull-headed stupidity and to learning bought from that dear teacher
-- chance experience. It is significant that many words for intelligence suggest the idea of
circuitous, evasive activity -- often with a sort of intimation of even moral obliquity. The bluff,
hearty man goes straight (and stupidly, it is implied) at some work. The intelligent man is
cunning, shrewd (crooked), wily, subtle, crafty, artful, designing -the idea of indirection is
involved. An idea is a method of evading, circumventing, or surmounting through reflection
obstacles that otherwise would have to be attacked by brute force. But ideas may lose their
intellectual quality as they are habitually used. When a child was first learning to recognize, in
some hesitating suspense, cats, dogs, houses, marbles, trees, shoes, and other objects, ideas -conscious and tentative meanings -intervened as methods of identification. Now, as a rule, the
thing and the meaning are so completely fused that there is no judgment and no idea proper, but
only automatic recognition. On the other hand, things that are, as a rule, directly apprehended
and familiar become subjects of judgment when they present themselves in unusual contexts: as
forms, distances, sizes, positions when we attempt to draw them; triangle, squares, and circles
when they turn up, not in connection with familiar toys, implements, and utensils, but as
problems in geometry.
Analysis and Synthesis
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Through judging confused data are cleared up, and seemingly incoherent and disconnected facts
brought together. Things may have a peculiar feeling for us, they may make a certain
indescribable impression upon us; the thing may feel round (that is, present a quality which we
afterwards define as round), an act may seem rude (or what we afterwards classify as rude), and
yet this quality may be lost, absorbed, blended in the total value of the situation. Only as we need
to use just that aspect of the original situation as a tool of grasping something perplexing or
obscure in another situation, do we abstract or detach the quality so that it becomes
individualized. Only because we need to characterize the shape of some new object or the moral
quality of some new act, does the element of roundness or rudeness in the old experience detach
itself, and stand out as a distinctive feature. If the element thus selected clears up what is
otherwise obscure in the new experience, if it settles what is uncertain, it thereby itself gains in
positiveness and definiteness of meaning. This point will meet us again in the following chapter;
here we shall speak of the matter only as it bears upon the questions of analysis and synthesis.
Even when it is definitely stated that intellectual and physical analyses are different sorts of
operations, intellectual analysis is often treated after the analogy of physical; as if it were the
breaking up of a whole into all its cQn3tituent parts in the mind instead of in space. As nobody
can possibly tell what breaking a whole into its parts in the mind means, this conception leads to
the further notion that logical analysis is a mere enumeration and listing of all conceivable
qualities and relations.
The influence upon education of this conception has been very great. Every subject in the
curriculum has passed through-or still remains in-what may be called the phase of anatomical or
morphological method: the stage in which understanding the subject is thought to consist of
multiplying distinctions of quality, form, relation, and so on, and attaching some name to each
distinguished element. In normal growth, specific properties are emphasized and so
individualized only when they serve to clear up a present difficulty. Only as they are involved in
judging some specific situation is there any motive or use for analyses, i.e. for emphasis upon
some element or relation as peculiarly significant.
The same putting the cart before the horse, the product before the process, is found in that over
conscious formulation of methods of procedure so current in elementary instruction. The method
that is employed in discovery, in reflective inquiry, cannot possibly be identified with the method
that emerges after the discovery is made. In the genuine operation of inference, the mind is in the
attitude of search, of hunting, of projection, of trying this and that; when the conclusion is
reached, the search is at an end. The Greeks used to discuss: " How is learning (or inquiry)
possible? For either we know already what we are after, and then we do not learn or inquire; or
we do not know, and then we cannot inquire, for we do not know what to look for." The dilemma
is at least suggestive, for it points to the true alternative: the use in inquiry of doubt, of tentative
suggestion, of experimentation. After we have reached the conclusion, a reconsideration of the
steps of the process to see what is helpful, what is harmful, what is merely useless, will assist in
dealing more promptly and efficaciously with analogous problems in the future. In this way,
more or less explicit method is gradually built up. It is, however, a common assumption that
unless the pupil from the outset consciously recognizes and explicitly states the method logically
implied in the result he is to reach, he will have no method, and his mind will work confusedly or
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anarchically; while if he accompanies his performance with conscious statement of some form of
procedure (outline, topical analysis, list of headings and subheadings, uniform formula) his mind
is safeguarded and strengthened. As a matter of fact, the development of an unconscious logical
attitude and habit must come first. A conscious setting forth of the method logically adapted for
reaching an end is possible only after the result has first been reached by more unconscious and
tentative methods, while it is valuable only when a review of the method that achieved success in
a given case will throw light upon a new, similar case. The ability to fasten upon and single out
(abstract, analyze) those features of one experience that are logically best is hindered by
premature insistence upon their explicit formulation. It is repeated use that gives a method
definiteness; and given this definiteness, precipitation into formulated statement should follow
naturally. But because teachers find that the things that they themselves best understand are
marked off and defined in clear-cut ways, our schoolrooms are pervaded with the superstition
that children are to begin with already crystallized formulae of method.
As analysis is conceived to be a sort of picking to pieces, so synthesis is thought to be a sort of
physical piecing together; and so imagined, it also becomes a mystery. In fact, synthesis takes
place wherever we grasp the bearing of facts on a conclusion, or of a principle on facts. As
analysis is emphasis, so synthesis is placing; the one causes the emphasized fact or property to
stand out as significant; the other gives what is selected its context, or its connection with what is
signified. Every judgment is analytic in so far as it involves discernment, discrimination,
marking off the trivial from the important, the irrelevant from what points to a conclusion; and it
is synthetic in so far as it leaves the mind with an inclusive situation within which the selected
facts are placed.
Educational methods that pride themselves on being exclusively analytic or exclusively
synthetic are therefore (so far as they carry out their boasts) incompatible with normal operations
of judgment. Discussions have taken place, for example, as to whether the teaching of geography
should be analytic or synthetic. The synthetic method is supposed to begin with the partial,
limited portion of the earth's surface already familiar to the pupil, and then gradually piece on
adjacent regions (the county, the country, the continent, and so on) till an idea of the entire globe
is reached, or of the solar system that includes the globe, The analytic method is supposed to
begin with the physical whole, the solar system or globe, and to work down through its
constituent portions till the immediate environment is reached. The underlying conceptions are
of physical wholes and physical parts. As matter of fact, we cannot assume that the portion of the
earth already familiar to the child is such a definite object, mentally, that he can at once begin
with it; his knowledge of it is misty and vague as well as incomplete. Accordingly, mental
progress will involve analysis of it -- emphasis of the features that are significant, so that they
will stand out clearly. Moreover, his own locality is not sharply marked off, neatly bounded, and
measured. His experience of it is already an experience that involves sun, moon, and stars as
parts of the scene he surveys; it involves a changing horizon line as he moves about; that is, even
his more limited and local experience involves far-reaching factors that take his imagination
clear beyond his own street and village. Connection, relationship with a larger whole, is already
involved. But his recognition of these relations is inadequate, vague, and incorrect. He needs to
utilize the features of the local environment that are understood to help clarify and enlarge his
conceptions of the larger geographical scene to which they belong. At the same time, not till he
has grasped the larger scene will many of even the commonest features of his environment
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become intelligible. Analysis leads to synthesis; while synthesis perfects analysis. As the pupil
grows in comprehension of the vast complicated earth in its setting in space, he also sees more
definitely the meaning of the familiar local details. This intimate interaction between selective
emphasis and interpretation of what is selected is found wherever reflection proceeds normally.
Hence the folly of trying to set analysis and synthesis over against each other.
Diplomatic Advisor Job Description
What a Diplomatic Advisor does is go out and look for Houses that might be good allies to their
client House, then report back so that the Master can consider them, another the Diplomatic
Advisor does is, help sign treaties, declare war, however a Diplomatic Advisor has to be able to
make well informed decisions at all times, so that only the right one can be made, so the person
with this rank has to compile information about organizations, then report about them, not just "I
went to their channel and they lots of members" . A Diplomatic Advisor will have to find out
important information about the subject of investigation.
Location in the Hierarchy
The Mentat Advisor fits within his Master's overall organization along with middle level
diplomats and diplomatic advisors, high-level representatives of NGOs, university professors,
middle level military officers, community representatives, and other individuals.
Expert Advisors
Each Advisor stores valuable information and disseminates it in an informational and interactive
framework. The Advisor interacts with his client to solve a problem. The Advisor should give
advice and/or provide additional information on a specific subject based on the response to his
questions.
The Advisor must be easy to use and understand. An Advisor can provide more detailed
information that may be helpful to the user, such as sections of the law related to the topic being
discussed. Additional information on publications and other organizations are also provided.
The Advisor is intended to provide general information, but is not intended to provide definitive
advice without adequate prior preparation.
Expert Advisors enable businesses and others to answer a questions and receive reliable answers
on how regulations apply to their unique situation. The Expert Advisors combine the expertise
of many professionals into a single source of expert help.
Attributes of Advisors
Subject Knowledge
* Demonstrates expertise in subject;
* Shows genuine interest in subject;
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* Has interesting ideas; is someone you can learn from.
Work Habits
* Organized;
* Attentive to detail;
* Efficient: gets things done; attends to deadlines.
Personal Attributes
* Bright;
* Enthusiastic;
* Patient;
* Compassionate; empathetic;
* Displays integrity;
* Flexible;
* Sensitive;
* Trustworthy;
* Forthright when dealing with conflict
Advising Practices
* Provides clear expectations;
* Recommends readings;
* Makes time for the client; reviews client work in a timely fashion;
* Creates an atmosphere conducive to learning; engages clients' ideas; knows how to inspire and
encourage clients;
* Challenges clients to think more deeply and to understand different perspectives;
* Provides constructive comments and appropriate feedback, including positive feedback when
appropriate;
* Provide advice, wise counsel and direction to clients;
* Mutually negotiates tasks and schedules;
* Helps clients to negotiate the system;
* Encourages participation in professional organizations;
* Provides letters of recommendation;
* Guides clients in making grant applications.
Attitudes toward Clients
* Wants client to succeed;
* Believes in the client's ability;
* Trusts the client will do what needs to be done;
* Respectful of clients needs, efforts, interests and choices;
* Nurtures the client's self-image as an emerging leader:
* Supports clients' interests and passions;
* Nurtures clients' sense of ownership of their work;
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* Fosters an egalitarian relationship that is neither intrusive nor presumptuous;
* Appropriately acknowledges clients' contributions and accomplishments;
* Sees the client as a colleague, not a competitor and uses authority and power to serve client
interest
* Maintains appropriate role boundaries:
* Client's role as an emerging Leader is clearly defined;
* Advisor's self-image is not that of a parent, but a colleague who expresses support and
Confidence in the client's abilities;
* Does not expect to be 'parented' by the client;
* Able/willing to negotiate a compromise in the face of disagreement or conflict;
* Assumes responsibility for political or interpersonal issues that arise among committee
members and intervenes on client's behalf;
* Shows respect for the multiple role demands placed on him Master.
Other factors that contribute to positive relationships with Advisors include sharing common
interests, shared perspectives of about problem paradigms, a mutually flexible approach to the
relationship in which both Advisor and client are able to accommodate a range of tasks and a
mutual respect for one another that culminates in a relationship that is professional, collegial and
egalitarian.
Ineffective Advisors
Attributes of advisor/client relationships that added stress to their experiences that may be
classified into three categories, including personal attributes, advising practices and relationship
management.
Ineffective Advisors
Personal Attributes
* Cold; impersonal
* Autocratic
* Pompous; overbearing
* Gruff
Ineffective Advisors
Advising Practices
* Hypercritical
* Unavailable; does not respond in a timely way to client requests or messages
* Uses client work for personal benefit
Ineffective Advisors
Attitudes Toward Clients
* Manipulative
* Lack of respect for alternate perspectives of research paradigms
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* Wants to shape client thinking in accordance with one's own views
* Controlling, resulting in friction when clients speak their minds
* Abusive and cruel: belittles clients; makes snide remarks
* Intimidating: attacks clients' beliefs and is constantly testing the client
* Uses positional power and authority to silence the client
* View emotions as a weakness
* Blurred role boundaries in which the client provides an audience for the advisor's personal
and/or departmental issues
* Creates conflict among committee members
Mentat Dysfunction
A Mentat is not a freak. There are, however, certain characteristics typical of a Mentat: Ego,
inquisitive, distant, serious, logical, etc.
Sapho use at this point in the timeline is rather extensive as a mind-clarifying and enhancing
drug. It is NOT required and neither are overly bushy-eyebrows. :) The reddened lips, however,
are a side-effect of sapho use.
Overall, a Mentat is a reflection of a highly organized mind with a thirst of for data.
There are times when you will resent the straight-line necessities imposed on Mentat
performance.
Mentats share the fallibilities of those who use them. The human mind, as is the case of any
animal mind, is a resonator. It responds to the resonances in the environment. The Mentat has
learned to extend his awareness across many parallel loops of causality and to proceed along
those loops for long chains of consequences. There is a danger in inciting a Mentat to compute.
Processor Naiveté
Their training stresses the unquestioning acceptance of the direction of others, and they are
therefore totally dependant on the good-will of those around them.
Generalist pride
Generalist knowledge, when combined with confidence-building Mentat training, leads many to
annoy their comrades with an overblown sense of their own superiority, making them very
difficult to work with.
Mentat freeze
Although taught to transcend the narrowness of specialization, no human being can be entirely
free from the element of doubt. Repeated and strenuous questioning of a Mentat's computations
do not lead to new computations but to anxiety about the base of those calculations. The
resulting state halts all Mentat functions permanently unless the doubt can be removed and
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confidence restored. A strategy for avoiding self-doubt is a reliance on absolutes, as long as they
are not abused and no hypothesis is overlooked or option unexplored or incorrect assumption
accepted.
Memorizer babble
There is a risk of being overwhelmed by the minutiae of data. The best defense against Babble is
to categorize the data.
Caffeine
Caffeine is a poison: it messes up the digestion, raises cholesterol levels, may cause severe
withdrawal symptoms such as migraines and with extensive use can lead to condition not all too
different from anxiety neurosis.
Sapho addiction
Sapho amplifies extrapolation as well as being a basic energizing liquid, but it subjects its users
to unpredictable outbursts of emotion and/or long periods of passivity. This lethargy MAY led a
Mentat to neglect the constant updating upon which his accuracy depends.
Rhajia
The nature of this music is widely disagreed, lient;
s a death trap. Most commonly, those who become immersed in this music become comatose
and die, with those who survive having no memory of what occurred.
Verbal dependence
A Mentat relies totally on discursive symbolic systems. The resulting computational thoughts
have clean edges, sharp relief. There are no blurred between-places. While this is excellent for
our purposes, it does not necessarily correlate to Reality.
Medication
Some medicines can cause loss of memory: tranquilizers, muscular relaxants, sleep pills, and
anti-anxiety drugs, particularly the benzoadiazepinics that include the diazepan (valium) and the
lorazepan. Some medicines for the control of high blood pressure (hypertension) may cause
memory problems and depression.
Ginko Biloba
There are no reported side effects in the medical literature, buncludingsers have complained
about stomach troubles at high doses.
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Abruptly, his mental sensorium clicked into full awareness and his mind leaped into the frozen
trance where Time did not exist; only the computation existed.... He gave himself personnel
computation.
Pain is a function of nerves. Pain comes as light to the eyes. Effort comes from the muscles, not
the nerves. It is an old Mentat drill. Completed in the space of one breath.
...a deep Mentat mode. Data streamed through the computer inside his skull, a human brain that
simulated the clarity the es of the ancient, hated enemies of mankind.
...stood in a trance sorting through veiled regions of logic and analysis.
Other schools
The elite schools make enough profits off their training to live comfortably, although none have
sufficient wealth to trade on an interstellar level. Economic and pan optio neutrality as well as a
healthy self-restraint have allowed these entities to survive for thousands of years. [Suks,
Mentats]
Twisted Mentats
There is no school associated with "twisted" Mentats.
Some centuries ago, the Bene Tlielax were able to cultivate a certain level of perversion into a
branch of their own mimicked Mentat training, creating what became known in some circles as
the Twisted Mentat.
The Twisted Mentat is often a trained assassin in this phase of his/her work.
Twisted Mentats may be purchased at any of the three Mentat levels for the additional costs
noted in 'Mentat Costs'. Additionally, all Twisted Mentats will be purchased through the Bene
Tlielax.
Assassin training for a Twisted Mentat will cost additional.
Long amongthe best of Landsraad society, a Twisted Mentats give a House that extra boost that
you simply can't get with an ordinary, run-of-the-mill Mentat. Twisted Mentats are more
cunning, more devious, and more deceptive--more of everything you love in a Mentat! Twisted
Mentats cost no more than the normal kind but last up to twice as long. In addition, if you wish,
you can pre-select the qualities you want your Mentat to have, down to the tiniest detail, and
have a custom Twisted Mentat in less than a year from the Bene Tlielax.
All Tleilaxu are to remember that, as an autonomous society and are not automatically rewarded
in any respect. Many Tleilaxu on Kaitain are, since they have been purchased, of the slave class,
and are not awarded respect based on position. If you are respected at all, it is because you are a
valuable and expensive commodity. If you are a twisted Mentat, the respect you receive will be
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because of your skill and your skill only; the same applies for all other expensive and valuable
constructs.
Bene Gesserit
Bene Gesserit is the ancient school of mental and physical training established primarily for
female students after the Butlerian Jihad destroyed the so-called "thinking machines" and robots.
The Bene Gesserit sisterhood is a mysterious school that educates primarily female students in
the mental and physical arts. Its g the hor shrouded in secrecy, and very little is know about
them. Bene Gesserit spouses and concubines are much sought after in the Imperium, for their
grace, poise, inherent nobility, and allure. Internally the Sisterhood is the only thing that is
preserving the continuity of humankind and nothing must stand in its way to produce the
Kwisatz Haderach is uppermost in the agenda of the breeding portion of the Sisterhood. We
cannot over look the fact that the Bene Gesserit is almost exclusively a political entity wrapped
in a quasi-religious semi-mystical shroud. No one trusts the Bene Gesserit, they have little reason
to, y; or we e end the Bene Gesserit have always proved to be the strong rudder in the stormy
millennia.
The Bene Gesserits are as they should be, servants of the Landsraad. No more, no less. They are
not to be trusted as pry where they are not wanted and scheme to destroy the stability that the
Guild has established for humanity.
Wealth
The BG receive income from all manner of secret sources, and are said to have vast wealth,
although it isn't obvious. They do not extensively trade in the worldwide economy, but they do
have economic resources.
History
The Bene Gesserit Sisterhood, from here on out referred to as the Sisterhood, has existed from
before the Butlerian Jihad in early Terran civilization. Its purpose over the years has been to
serve the Landsraad
The Sisterhood can be felt in many aspects of daily life throughout the upper echelons of the
Landsraad. From the use of Truthsayers, to the concubines of the Siridari, to the training
provided to young Noble Born females, the Bene Gesserit name is synonymous with beauty,
intelligence, and mystical power. Their. avowed purpose is to serve, though many of the
Landsraad chose to believe otherwise.
Status
Majority of the Sisterhood seen to the public on a continual basis are the concubines that serve
the various Houses. The other intendance that is common to see a Sister in is that of a
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Truthsayer, especially inwards deerial Court. In both functions, the Sisterhood holds the position
of servant to the Imperium and the Landsraad.
Discussion of Chapter House
Currently, the Sisterhood has 12 Chapter Houses throughout the known universe. The main
Chapter House is located on Wallach IX. Within the walls of Wallach IX is the most extensive
library known to the universe. It is unclear as to what all the contents are in the library as no one
outside of the Reough douothers has complete access to the library.
Another Chapter House, and the one most concerned with in the Landsraad, is the one located on
Kaitain. Generally, after a Sister is trained in the basics on Wallach IX, she is sent to different
Chapter Houses to serve the Reverend Mothers there until a position n merelyound for her with a
Great House.
Economy
Since the Sisterhood does not hold any contracts or participate in the CHOAM, on the surface, it
doesn't seem to earn any money. However, it is rich enough to support the many Chapter Houses
through the universe as well as the additional spice needed to enhance thee it is or truthsaying.
Group positions
Group Employment
Almost all Bene Gesserits present at this time are to be concubines, assigned to serve at a
particular Great House. Not all Sisters are attached to House heads or potential heads.
Group Protocols
Internal Protocols
Regardless of what level the Sister acquires within the Landsraad, the Reverend Mother is still
someone to be respected, if for nothing else but the abundance of wisdom that she contains
because of the memories.
As the purpose of the Sisterhood is to serve, a Sister that I found to be disagreeable is treated
with extreme harshness, to the point in which she would be taken back to Wallach IX for
additional deep training. The Bene Gesserit would overall reframe from killing one of their own,
the as it might jeopardize the breeding program. It is much more acceptable to train out the
undesirable traits or force an encounter in which a child can be conceived and the bloodline is
not lost.
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It is unacceptable for a Sister to teach anyone the Ways of the Sisterhood without the approval
and full knowledge and concurrence is being learned by the Reverend Mothers. Doing so could
result in serious disciplinary actions by the Reverend Mothers.
Bene Tleilaxu
They live on the planet Tleilax. The capital city is Bandalong.
Perhaps the Bene Tleilaxu are best known for their three primary exports. Among these are
artificial ell invol as those provided to the victims of a stone-burner. Second, the Bene Tleilaxu
are the source of twisted Mentats, human-computers who directed their tremendous skill to evil
purposes. Finally, the axolotl tanks on Tleilax were the destination of corpses who were to see
new life as gholas.
The Sisterhood has relations with the Bene Tleilaxu because the Landsraad is dependent upon
them. However, the Sisterhood, reacting as one would to a foreign religion that risks to
undermine its own, the have deep seated reservations about the dirty Bene Tleilaxu.
The Bene Tleilaxu are the perfect spies. The Face Dancers have the ability to assume the
appearance and manners of anyone. Their deceptiveness and ability to control the game without
direct use of force is near that of the Benk for peit.
As the proprietors of the axolotl tanks, the Bene Tleilaxu are similar to the Guild. Their primary
source of income stems largely from death in battle.
The Bene Tleilaxu can be valuable in alliance for any of the players because of your ability to
revive dead leaders. From the Tleilaxan point of view clients and allies are likely to be the
enemies of the Emperor or the Guild.
The Bene Tleilaxu is just another group who, like the Bene Gesserits, believes they know what is
better for humanity. They are to be trusted no more than necessary.
History
The Bene Tleilax brotherhood has continued to serve the nee issues perial society today as we
have in the past. Both societies have benefited greatly from the harmonious relations, and profits
have steadily increased since a slight downturn in 10,031.
Some nasty rumors have been circulating, and we are determined to set the record straight. For
the record, the Bene Tleilaing drugad something to do with the following events, and whoever
says we did is a bald-faced liar.
o We had absolutely nothing to do with the assassination of Galeazzo V Moritani.
o We have had nothing to do with the recent upheavals in Houses Rastanyev or Venhei.
o We did not recently sell a Genetic Purification System 808-3A to House Sivaramanian. They
must have obtained it from someone else.
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o The catastrophic plague that recently wiped out the fief of the resong did not originate with us.
o The Bene Tleilax are not, and have never been, in negotiations with the Imperial Church
involving immeasurable sums of money.
o The Garamond insurrection was not funded by solaris from Tleilaxu coffers.
o The recent abduction of Reverend Mother Xula Caduveo was not our doing
Character
Summary
The Bene Tleilax are a brotherhood of scholars, scientists, and philosophers dedicated to
furthering the gradual but inevitable perfection of the human race. From our utopian society on
the planet Tleilax, we seek to unravel the mysteries of life and consciousness, of God and his
Language, and of the universe and its inhabitants.
Due to the foolish conservatism of powindah society, we of the Brotherhood are, shall we say,
"distrusted" among the mainstream of Imperial society. Across the universe, we Tleilaxu are
despised and persecuted for their origins, and live in constant fear of pogroms, which are
common even in today's "modern" Empire. As a result, our society has become secretive and
closed to outsiders.
Among the many skills of the Bene Tleilax is an unsurpassed mastery of genetic manipulation.
While this often riles the ethical scruples of the reactionary powindah, we insist that we only use
our expertise for the betterment of the human race.
Views on Religion
The Bene Tleilax are, first and foremost, a religious order dedicated to the One True God and
His plans for His creation. The Tleilaxu Way is God's tool to achieve His earthly paradise, in
which His immortal favorites bask forever in gardens of unearthly delight. And although we are
opposed by many other groups who have grossly misinterpreted His word, we are assured that, in
the end, only we will prevail.
Products and Services
This list, while by no means comprehensive, will give you an idea of the range of Tleilaxu
products and the depth to which we will go to satisfy your refined desires. And while the
products and services listed below remain our most popular items, we also accept custom orders
and special requests to satisfy the most finicky of patrons. Contact your local importer of
biological novelties or, if you're in the Greater Kaitain area, visit the Monasterium Tleilaxu in the
Foothills District.
Faction Protocols
Internal Protocol
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A note on terms: The term "Bene Tleilax" refers to the brotherhood itself, while the word
Tleilaxu refers to origins. The Bene Tleilax are an organization, the Tleilaxu are an "ethnic"
group, if you will. You can be Tleilaxu without being a part of the Bene Tleilax brotherhood,
but not the other way around: all Bene Tleilax are Tleilaxu. Certain sorts of Tleilaxu constructs-many pleasure slaves, for example--can be considered Tleilaxu without necessarily being a part
of the Brotherhood.
Spacing Guild
As for the Spacing Guild, as far as Rastanyev is concerned, the ties are slightly closer. Viewed as
a group that provides a vital service (that of transporting the exports of the different products that
the House subsists on), most have always been careful not to take any course that might alienate
the Guild.
We do not believe the Guild is a threat. On the contrary, the Guild needs the Landsraad as much
as it is needed. In such a marriage, the two will not destroy the other without knowingly risk
destroying itself. We do believe that the Guild is based upon the study and application of pure
mathematics and suspect that in some way the Guild's prescient abilities limits itself in its
actions.
Wealth
CHOAM and the Guild take a cut from all trade that goes on. It is rumored that most of the
CHOAM profits are divided among the Directors and their allies.
History
The power of the Guild extends far. Time itself is determined by the Guild, hence the accepted
designations of "Before Guild" and "After Guild". Guild members function in many important
roles throughout the Landsraad: serving as bankers, transporters and protectors of the weak.
Without the Guild, the Landsraad would fall into turmoil and destruction. The history of the
Guild is long, though few outside of the upper stage navigators share it.
Recently, the Guild has been fairly quiet, making few, if any, demands upon the Landsraad. In
doing so, it has developed an... "agreement". The Landsraad shall provide the Guild with the
necessary spice it asks for and the Guild will provide for the Landsraad the stability it needs to
continue to exist.
Training
None have seen an actual Guilds Navigator. However, the presence of the Guild is not
transparent. Throughout the Landsraad, the Guild has paid money to have trained agents that
serve as their voice to the Landsraad. These agents, selected carefully by other trusted Guild
agents, are taught the basics of business, economy, and politics. Though the use of spice, they
are linked to the Navigator, serving as the eyes, ears, and mouth of the Guild. As such, no
expense is spared in training these agents.
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View on Religion
The Guild takes no official stance on Religion. While it has been heard in public some of its
members quoting from the accepted Orange Catholic Bible, it is uncertain if the Guild even has
an established religion on their Homeworld Tupile.
Imperial Citizenry Status
Guild members are to be respected, if not revered.
Group positions
Guild members serve a variety of functions on their selected planet. Examples of positions
commonly held by Guild members are: banker, CHOAM representatives, Investigators,
Auditors, secretaries, and negotiators.
Group Protocols
When seen together, Guild members are often commented as "sharing a mind" and thinking
along the same lines. In public, they always act as one.
Official Code of Conduct
The Guild is modest. Modesty, after all, deters curiosity and allows for the Guild's continued
secrecy. They do not interfere publicly with the affairs, conflicts, or situations of the Landsraad
or Imperium. In fact, it seems that many times, they have an attitude of "Business much go on".
They never seem to be phased by changes in leadership among the Houses. Their attitude is
almost... cold.
Instructions for Interacting with Specific Houses Major
The Guild does not publicly get involved in any affairs, conflicts, or situations that could
jeopardize the sense of neutrality the Guild maintains.
Swordsman Schools
Several Great Houses operate Sword schools, most notably the recently destroyed House Ginaz.
Each house teaches Swordplay, leadership, shield repair, small craft piloting, and other sword
related skills, but schools teach other things as well, that are the direct result of their philosophy,
and these are reflected in the behavior of the Swordmaster. A student is either taught at a school,
which is an apprenticeship that takes many years, or is schooled over the course of years by a
House Swordmaster. Although a player is not bound by the teachings of his/her school (or
his/her teacher's school) a good student will follow those teachings wherever possible.
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The following Sword schools exist. All players with sword training should either have attended
one of these schools, (having been apprenticed there by their parent house at an early age) or
been taught by a House Swordmaster who would teach you a blend of the House's philosophy
and his school's.
Ginaz
By far the most famous of the Sword schools, it is also the best. It is the only one that can train
Swordmasters of the tenth level. Its teachings emphasize honor, loyalty, and pure
swordsmanship.
Wallach
The oldest sword school in the Imperium. Emphasizes chivalry and fair play - though its
graduates tend to be haughty and distant.
Samarama
A school based on the House's Japanese tradition. Its students tend to be very reflective,
honorable, and almost loners, though they tend to make excellent advisors.
Thorgod
Only a few hundred years old, the Thorgod school students tend to be cruel and merciless, prone
to go berserk in battle, though loyal when their loyalty is earned
Forbino
The Forbino School is both despised and treasured by Great Houses of the Landsraad. The
Forbino swordsmen are well trained to be sure, but their loyalty extends only as far as their pay
checks.
Suk
The Rules governing Suks are divided among the following subcategories:
1. Suk Hiring
2. Suk Technology
3. Suk Training
Suk Technology
Medical technology is an exotic mixture of the advanced and the primitive. A Suk takes
advantage of available technological advances, while not administering unthematic medicine.
They have extraordinary skill and artistry.
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Suks also have access to more advanced techniques. Examples: a standard medical facility
includes bone and organ banks. Also, the rich variety of plants from Ecaz has led to an
understanding of pharmacology, and heavy reliance on drugs (stimulants, sedatives, mood
enhancers, and of course melange) in everyday life.
However, religious proscription has stunted development in other areas. For example, the Suk
cannot, under any circumstances, use a treatment requiring a computer, or delve into areas of
genetic engineering, artificial insemination, or abortion.
Suk Hiring
Every Great House is provided with a Suk medic. The medic is trained in basic, outpost level
medicine, but is not capable of performing complex procedures. However, the medic's skill
would not be up to organ repair or replacement surgery, or identifying a poison and
administering the antidote. Ideally the medic will serve the House Suk's assistant, and will be
accessible when the Suk is not available.
In addition to the medic, each Great House may purchase a Suk of the Inner School. House
Heads are urged not to rely on the medic in lieu of purchasing a Suk physician. Not only do the
medics fall short of the Suk's advanced skill, they totally lack the Suk's loyalty and non-violence
conditioning. Because of the innate paranoia of the noble born, it would be extremely unthematic
for a non-conditioned medic to serve as a Great House's only doctor.
Suk Employment
(or, The Care and Feeding of
Your Suk)
Imperial Conditioning makes your Suk a valuable addition to a House. Remember that there is
no reason for you to doubt the Suk School's claims about their conditioning. A Suk is the only
member of a House staff whose obedience and trustworthiness is unquestionable. As such, s/he
can serve as much more than a "splint 'n' pill man." Guardian and tutor of your heir, personal
assistant, courier of sensitive messages, goodwill emissary: these are all appropriate functions for
the Suk.
The only caution on involving the Suk is non-violence. Your Suk is conditioned for two
principles:
1. To abhor violence
2. To obey you.
Placing your Suk in a position where s/he might, in following your orders, be a party to violence
could put an intolerable strain on the psyche. The prudent House Head will take care not to risk
the Suk in this way.
Suk Training
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Candidates for the Inner School are taken from their families and subjected to rigorous screening
and conditioning processes from earliest infancy. Suk training requires approximately 30 years
of full-time study. The training provides the candidate for a full range of medical, surgical, and
pharmaceutical skill. Imperial Conditioning, which all Suks must master, has two points of
focus:
1. Pyretic Conscience
The pyretic conscience, or "trial by fire," refers to the indoctrination of the physician to espouse
total non-violence. Through this cond
o The , a Suk is rendered incapable of taking human life, and finds any violent behavior
disgusting.
2. Loyalty
As well as non-violence, Suks are conditioned to value loyalty and obedience to their
employers, and to despise betrayal. The Suk finds the concept of disobedience almost as
repellant as the conciveté Turder.
When the Suk graduates from the Inner School at age 30, s/he is tattooed with a red diamond on
the forehead. Each point of the diamond represents one tenet of the Suk School oath: "I will give
Loyalty, I will seek Knowledge, I will practice Healing, I will prolong Life."
Mentat Training
The tsense of a Mentat begins in early childhood and continues into adolescence at which point
the pubescent is made aware of the potential for this avenue of education. The young protoMentat must then choose the path of the Mentat. During the ensuing years, training becomes
quite intense, taking many years and proceeding through many rankings.
The Mentats hired by Houses Major are of three levels or ranks:
Mentat Generalist
Mentat Simulationist
Mentat Advisor
Each of these ranks indicates a development of the mind of the Mentat.
Twisted Mentats can be trained at each of the above levels but are more expensive due to their
additional "talents".
In addition, a Mentat will often be ordered with additional training, such as assassin or sword
training - both for self-defense, and for use as offensive weapons.
..........................
Mentat training should began as early as possible, even in infancy if strong potential was noted.
Early training stimulated sensory awareness through sound, color, texture, odor, and taste;
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kinetics' awareness through spinning, rocking, warmth, cold; emotional awareness through fear,
joy, anger, love, hate, and security.
For potential Mentat "in the wild" their development is assisted along the way with special
training - mnemonics, the focusing of awareness, the muscle control and sharpening of
sensitivities, the study of languages and nuances of voices. This will increase the likelihood of
their acceptance into the School and prepare them for the rigors of the training.
During childhood, the future Mentats develop mentally and physically in rigorous, year-round
programs. The aim is to broaden the youngster's cognition and to resist specialization. Severe
punishment will meet the child who neglects one study in favor of another: "Everything is
important, and nothing is more important than everything" is the motto of the Mentat training
school. A strict and unforgiving disciplinary code promotes Albans' goal that every child be
completely self-directed by fifteen. Campus construction and maintenance, the evening silence,
the weekly fast, all tasks performed by lower classmen and directed and enforced by
upperclassmen, who punished breaches with a severity they had learned in their turn from their
predecessors. Sports developed strategy as well as physical skill; some, long-distance running,
for example, aided the disciplinary code and the six-day-a-week curriculum in either producing a
fully ready candidate for the novitiate or in washing him out of the program.
In the final preparatory year, at about fourteen, clients are grounded in prepositional and
predicate logic, inference, modal deduction, transfinite induction, statistics, multivalent analysis,
conceptual synthesis, N-dimensional geometry, formal linguistics, and transcendental
phenomenology. These studies provided the mental linkages to accept subsequent Mentat
training should the client succeed in mastering them.
To be trained as a Mentat -you have to learn how to work your own mind. You learn first that
the mind must work itself. That's very strange. You can work your own muscles, exercise them,
strengthen them, but the mind acts of itself. Sometimes, when you have learned this about the
mind, it shows you things you did not want to see.
A Mentat will learn the integrated communication methods as he complete the next step in your
mental education. This is a gestalten function, which will overlay data paths in your awareness,
resolving complexities and masses of input from the Mentat index-catalogue techniques that you
already have mastered. Your initial problem will be the breaking tensions arising form the
divergent assembly of minutiae/data on specialized subjects. Be warned. Without Mentat
overlay integration, you can be immersed in the Babel Problem, which is the label we give to
omnipresent dangers of achieving wrong combinations from accurate information.
Education is no substitute for intelligence. That elusive quality is defined only in part by puzzlesolving ability. It is in the creation of new puzzles reflecting what your senses report that you
round out the definition.
Many things we do naturally become difficult only when we try to make the intellectual subjects.
It is possible to know so much about a subject that you become totally ignorant.
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Ready comprehension is often a knee-jerk response and the most dangerous form of
understanding. It blinks an opaque screen over your ability to learn. The judgmental precedents
of law function that way, littering your path with dead ends. Be warned. Understand nothing.
All comprehension is temporary.
Logical Reasoning
Logic is the science of reasoning, proof, thinking, or inference. Logic allows us to analyze a
piece of reasoning and determine whether it is correct or not. To use the technical terms, we
determine whether the reasoning is valid or invalid. The projection of logic onto all things is
unnatural, but suffered to continue for its usefulness. A Mentat is the embodiment of logic.
Problem solutions are concepts that, in a very real sense, are projected outside of a Mentat, there
to be studied and rolled around - to be examined from all sides.
Logical argument
What is an argument?
An argument is a connected series of statements to establish a definite proposition. There are
three stages to an argument: premises, inference, and conclusion.
Stage one: Premises
One or more propositions will be are necessary for the argument to continue. They must be
stated explicitly. They are called the premises of the argument. They are the evidence (or
reasons) for accepting the argument and its conclusions.
Premises (or assertions) are often indicated by phrases such as because, since, obviously and so
on. (Obviously is often viewed with suspicion, as it can be used to intimidate others into
accepting dubious premises.
Stage two: Inference
The premises of the argument are used to obtain further propositions. This process is known as
inference. In inference, we start with one or more propositions that have been accepted. We then
derive a new proposition. There are various forms of valid inference. The propositions arrived at
by inference may then be used in further inference. Inference is often denoted by phrases such as
implies that or therefore.
Stage three: Conclusion
The conclusion is often stated as the final stage of inference. It is affirmed on the basis the
original premises, and the inference from them. Conclusions are often indicated by phrases such
as therefore, it follows that, we conclude and so on.
Types of argument
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There are two traditional types of argument, deductive and inductive. A deductive argument
provides conclusive proof of its conclusions; if the premises are true, the conclusion must also be
true. A deductive argument is either valid or invalid. A valid argument is defined as one where if
the premises are true, then the conclusion is true.
An inductive argument is one where the premises provide some evidence for the truth of the
conclusion. Inductive arguments are neither valid nor invalid.
There are forms of argument in ordinary language that are neither deductive nor inductive.
Recognizing an argument
Sometimes an argument will not follow the order just described. This is perfectly valid, if
sometimes a little confusing. Arguments are harder to recognize than premises or conclusions.
Many people shower their positions with assertions without ever producing anything which one
might reasonably describe as an argument.
Implication in detail
The fact that a deductive argument is valid does not imply that its conclusion holds.
Obviously a valid argument can consist of true propositions. However, an argument may be
entirely valid even if it contains only false propositions. The conclusion is not true because the
argument's premises are false. If the argument's premises were true, however, the conclusion
would be true. The argument is thus entirely valid. More subtly, we can reach a true conclusion
from one or more false premises. However, the one thing we cannot do is reach a false
conclusion through valid inference from true premises. A sound argument is a valid argument
whose premises are true. A sound argument therefore arrives at a true conclusion. Be careful not
to confuse sound arguments with valid arguments.
Bias and Logical Errors
As you're reviewing the sources, you should also look for evidence of bias and logical problems.
Remember that all arguments reflect the originator's position in some way. We often reject
arguments that we think are biased, but defining bias is difficult. Sometimes, we think that
anyone with an opinion different from our own is biased. Usually, though, having an opinion and
even feeling strongly about that opinion doesn't make someone's argument biased. An argument
IS biased when the reasons why the originator takes a certain position are suspect or when they
are based on assumptions that aren't widely shared.
Fallacies
The term fallacy is used to refer to mistaken beliefs as well as to the faulty reasoning that leads
to those beliefs. This is fair enough, but in logic the term is generally used to refer to a form of
technically incorrect argument, especially if the argument appears valid or convincing. We
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define a fallacy as a logical argument which appears to be correct, but which can be seen to be
incorrect when examined more closely. By studying fallacies we aim to avoid being misled by
them. Below is a list of some common fallacies, and also some rhetorical devices often used in
debate. The list is not intended to be exhaustive.
Argumentum ad baculum
Appeal to force
The Appeal to Force is committed when the arguer resorts to force or the threat of force in order
to try and push the acceptance of a conclusion. It is often used by politicians, and can be
summarized as "might makes right." The force threatened need not be a direct threat from the
arguer.
Argumentum ad misericordiam Appeal to Pity
This is the Appeal to Pity, also known as Special Pleading. The fallacy is committed when the
arguer appeals to pity for the sake of getting a conclusion accepted.
Argumentum ad populum
This is known as Appealing to the Gallery or Appealing to the People. To commit this fallacy is
to attempt to win acceptance of an assertion by appealing to a large group of people. This form
of fallacy is often characterized by emotive language
Argumentum ad numerum
This fallacy is closely related to the argumentum ad populum. It consists of asserting that the
more people who support or believe a proposition, the more likely it is that that proposition is
correct.
The fallacy of accident: The Fallacy of Accident is committed when a general rule is applied to a
particular case whose "accidental" circumstances mean that the rule is inapplicable. It is the error
made when one goes from the general to the specific. This fallacy is often committed by
moralists and legalists who try to decide every moral and legal question by mechanically
applying general rules.
Converse accident
Hasty generalization
This fallacy is the reverse of the Fallacy of Accident. It occurs when one forms a general rule by
examining only a few specific cases that are not representative of all possible cases
Dicto simpliciter
Sweeping generalization
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A sweeping generalization occurs when a general rule is applied to a particular situation in
which the features of that particular situation render the rule inapplicable. A sweeping
generalization is the opposite of a hasty generalization.
Non causa pro causa
Post hoc ergo propter hoc
These are known as False Cause fallacies. The fallacy of Non Causa Pro Causa occurs when one
identifies something as the cause of an event but it has not actually been shown to be the cause.
The fallacy of Post Hoc Ergo Propter Hoc occurs when something is assumed to be the cause of
an event merely because it happened before the event
Cum hoc ergo propter hoc
This fallacy is similar to Post Hoc Ergo Propter Hoc. It asserts that because two events occur
together, they must be causally related, and leaves no room for other factors that may be the
cause(s) of the events.
Circulus in demonstrando
This fallacy occurs when one assumes as a premise the conclusion which one wishes to reach.
Often, the proposition will be rephrased so that the fallacy appears to be a valid argument
Complex question
Fallacy of interrogation
Fallacy of presupposition
This is the interrogative form of Begging the Question. The question presupposes a definite
answer to another question, which has not even been asked. This trick is often used by lawyers in
cross-examination. Another form of this fallacy is to ask for an explanation of something which
is untrue or not yet established.
Equivocation
Fallacy of four terms
Equivocation occurs when a key word is used with two or more different meanings in the same
argument.
Amphiboly
Amphiboly occurs when the premises used in an argument are ambiguous because of careless or
ungrammatical phrasing.
Accent
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Accent is another form of fallacy through shifting meaning. In this case, the meaning is changed
by altering which parts of a statement are emphasized.
Fallacies of composition
One Fallacy of Composition is to conclude that a property shared by the parts of something must
apply to the whole. The other Fallacy of Composition is to conclude that a property of a number
of individual items is shared by a collection of those items.
Fallacy of division
The fallacy of division is the opposite of the Fallacy of Composition. Like its opposite, it exists
in two varieties. The first is to assume that a property of some thing must apply to its parts. For
The slippery slope argument
This argument states that should one event occur, so will other harmful events. There is no proof
made that the harmful events are caused by the first event.
A is based on B fallacies
...is a type of... fallacies
Fallacy of the Undistributed Middle
These fallacies occur when one attempts to argue that things are in some way similar without
actually specifying in what way they are similar
Affirmation of the consequent
This fallacy is an argument of the form A implies B, B is true, therefore A is true. To understand
why it is a fallacy, examine the truth table for implication given earlier.
Denial of the antecedent
This fallacy is an argument of the form A implies B, A is false, therefore B is false. The truth
table for implication makes it clear why this is a fallacy. Note that this fallacy is different from
Non Causa Pro Causa. The latter has the form A implies B, A is false, therefore B is false, where
A does not in fact imply B at all. Here, the problem is not that the implication is invalid; rather it
is that the falseness of A does not allow us to deduce anything about B.
Converting a conditional
This fallacy is an argument of the form If A then B, therefore if B then A.
Argumentum ad antiquitatem
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This is the fallacy of asserting that something is right or good simply because it is old, or because
"that's the way it's always been."
Argumentum ad novitatem
This is the opposite of the Argumentum ad Antiquitatem; it is the fallacy of asserting that
something is more correct simply because it is new or newer than something else.
Argumentum ad crumenam
The fallacy of believing that money is a criterion of correctness; that those with more money are
more likely to be right.
Argumentum ad lazarum
The fallacy of assuming that because someone is poor he or she is sounder or more virtuous than
one who is wealthier. This fallacy is the opposite of the argumentum ad crumenam.
Argumentum ad nauseam
This is the incorrect belief that an assertion is more likely to be true the more often it is heard.
An "argumentum ad nauseam" is one that employs constant repetition in asserting something.
Bifurcation / False Dilemma
Also referred to as the "black and white" fallacy, bifurcation occurs when one presents a
situation as having only two alternatives, where in fact other alternatives exist or can exist.
Plurium interrogationum
Many questions
This fallacy occurs when a questioner demands a simple answer to a complex question or a
single answer to a multipart question.
Non sequitur
A non sequitur is an argument where the conclusion is drawn from premises that are not logically
connected with it.
Red herring
This fallacy is committed when irrelevant material is introduced to the issue being discussed, so
that everyone's attention is diverted away from the points being made, towards a different
conclusion.
Reification
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Hypostatization
Reification occurs when an abstract concept is treated as a concrete thing.
Shifting the burden of proof
The burden of proof is always on the person making an assertion or proposition. Shifting the
burden of proof, a special case of Argumentum ad Ignorantiam, is the fallacy of putting the
burden of proof on the person who denies or questions the assertion being made. The source of
the fallacy is the assumption that something is true unless proven otherwise.
Straw man
The straw man fallacy is to misrepresent someone else's position so that it can be attacked more
easily, then to knock down that misrepresented position, then to conclude that the original
position has been demolished. It is a fallacy because it fails to deal with the actual arguments that
have been made.
The extended analogy
The fallacy of the Extended Analogy often occurs when some suggested general rule is being
argued over. The fallacy is to assume that mentioning two different situations, in an argument
about a general rule, constitutes a claim that those situations are analogous to each other.
Tu quoque
This is the famous "you too" fallacy. It occurs when an action is argued to be acceptable because
the other party has performed it. This is a personal attack, and is therefore a special case of
Argumentum ad Hominem.
Audiatur et altera pars
Often, people will argue from assumptions that they do not bother to state. The principle of
Audiatur et Altera Pars is that all of the premises of an argument should be stated explicitly. It is
not strictly a fallacy to fail to state all of one's assumptions; however, it is often viewed with
suspicion.
Appeal to Tradition
Sometimes we do things for good reasons; sometimes we do things simply because we have
always done them. Such is the nature of appeal to tradition.
Ad Hoc
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There is a difference between argument and explanation. If we're interested in establishing A,
and B is offered as evidence, the statement A because B is an argument. If we're trying to
establish the truth of B, then A because B is not an argument, it is an explanation.
Advanced Training
With his advanced training, Jericho is able to conceal his own motives, moreover it his forte to
decipher the motives of others and how to use those against them. Using the subtle techniques of
observation and perception, Jericho is able influence others by understanding their wants and
desires and using that knowledge to his advantage. The secrets and intrigues of the other houses
occupy a great deal of his efforts, and he strives to discern their strengths and weaknesses for the
good of House Mentat.
Emotions
...proper mental calm for an assessment. He had to be as precise as possible. At the same time,
he knew that precise thinking contained undigested absolutes. Nature was not precise. The
universe was not precise when reduced to his scale; it was vague and fuzzy, full of unexpected
movements and changes. Mankind as a whole had to be entered into his computation as a natural
phenomenon. And the whole process of precise analysis represented a chopping off, a remove
from the ongoing current of the universe. He had to get at that current, see it in motion.
... own emotional balance depended upon a retreat into Mentat coldness.
Troubled, frowned, hesitant, ... [evident emotions]
If we can recognize the automatic thought and think about it rationally, we are usually on the
way to overcoming it. But emotional reasoning turns this process on its head. In emotional
reasoning, I continue to take for granted the automatic thought that causes my negative feeling
and try to reason on the basis of my feelings. Thus emotional reasoning amplifies the effects of
other cognitive distortions.
The basic assumption behind emotional reasoning is "Where there's smoke, there's fire." Let's
say you're preparing for a big test. It's natural that you'll be a little "nervous" about a challenging
event. And if you're over generalizing on the basis of your last test and fortune telling that you
will fail on this one, you'll be more anxious and nervous than you need to be. In this state of
mind, it's easy to fall into emotional reasoning and think along these lines: "Hey, I'm nervous.
I'm afraid. I must not understand the material. If I did, why would I be afraid?" Where there's
smoke, there's fire.
The trouble with emotional reasoning is that smoke is not firm evidence of fire. If you're scared
about your upcoming test, it's probably because you're rubbing two automatic thoughts together
and scaring yourself. People who allow themselves to get caught up in emotional reasoning can
become completely blinded to the difference between feelings and facts.
Anger
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Anger is "an emotional state that varies in intensity from mild irritation to intense fury and
rage,". Like other emotions, it is accompanied by physiological and biological changes; when
you get angry, your heart rate and blood pressure go up, as do the levels of your energy
hormones, adrenaline, and noradrenaline.
Anger Control Methods
Relaxation
Simple relaxation tools, such as deep breathing and relaxing imagery, can help calm down angry
feelings. There are books and courses that can teach you relaxation techniques, and once you
learn the techniques, you can call upon them in any situation. If you are involved in a
relationship where both partners are hot-tempered, it might be a good idea for both of you to
learn these techniques.
Some simple steps you can try
* Breathe deeply, from your diaphragm; breathing from your chest won't relax you. Picture your
breath coming up from your "gut."
* Slowly repeat a calm word or phrase such as "relax," "take it easy." Repeat it to yourself while
breathing deeply.
* Use imagery; visualize a relaxing experience, from either your memory or your imagination.
* Nonstrenuous, slow yoga-like exercises can relax your muscles and make you feel much
calmer.
Practice these techniques daily. Learn to use them automatically when you're in a tense situation.
Cognitive Restructuring
Simply put, this means changing the way you think. Angry people tend to curse, swear, or speak
in highly colorful terms that reflect their inner thoughts. When you're angry, your thinking can
get very exaggerated and overly dramatic. Try replacing these thoughts with more rational ones.
Logic defeats anger, because anger, even when it's justified, can quickly become irrational. So
use cold hard logic on yourself. Remind yourself that the world is "not out to get you,". Do this
each time you feel anger getting the best of you, and it'll help you get a more balanced
perspective. Angry people tend to demand things: fairness, appreciation, agreement, and
willingness to do things their way. As part of their cognitive restructuring, angry people need to
become aware of their demanding nature and translate their expectations into desires. When
you're unable to get what you want, you will experience the normal reactions-frustration,
disappointment, hurt-but not anger. Some angry people use this anger as a way to avoid feeling
hurt, but that doesn't mean the hurt goes away.
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Problem Solving
Sometimes, our anger and frustration are caused by very real and inescapable problems in our
lives. Not all anger is misplaced, and often it's a healthy, natural response to these difficulties.
There is also a cultural belief that every problem has a solution, and it adds to our frustration to
find out that this isn't always the case. The best attitude to bring to such a situation, then, is not to
focus on finding the solution, but rather on how you handle and face the problem.
Make a plan, and check your progress along the way. Resolve to give it your best, but also not to
punish yourself if an answer doesn't come right away. If you can approach it with your best
intentions and efforts and make a serious attempt to face it head-on, you will be less likely to
lose patience and fall into all-or-nothing thinking, even if the problem does not get solved right
away.
Better Communication
Angry people tend to jump to-and act on-conclusions, and some of those conclusions can be very
inaccurate. The first thing to do if you're in a heated discussion is slow down and think through
your responses. Don't say the first thing that comes into your head, but slow down and think
carefully about what you want to say. At the same time, listen carefully to what the other person
is saying and take your time before answering.
Listen, too, to what is underlying the anger. For instance, you like a certain amount of freedom
and personal space, and your "significant other" wants more connection and closeness. If he or
she starts complaining about your activities, don't retaliate by painting your partner as a jailer or
a warden. It's natural to get defensive when you're criticized, but to what's underlying the words:
the message that this person might feel neglected and unloved. It may take a lot of patient
questioning on your part, and it may require some breathing space, but don't let your anger-or a
partner's-let a discussion spin out of control. Keeping your cool can keep the situation from
becoming a disastrous one.
Changing Your Environment
Sometimes it's our immediate surroundings that give us cause for irritation and fury. Problems
and responsibilities can weigh on you and make you feel angry at the "trap" you seem to have
fallen into and all the people and things that form that trap.
Give yourself a break
Make sure you have some "personal time" scheduled for times of the day that you know are
particularly stressful.
Some Other Tips for
Easing Up on Yourself
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Timing: If you tend to fight when you discuss things at a particular time or place-perhaps you're
tired, or distracted, or maybe it's just habit-try changing the times when you talk about important
matters so these talks don't turn into arguments.
Avoidance: If something makes you furious every time you experience it, avoid it. Don't make
yourself look at what infuriates you. The point is to keep yourself calm.
Finding alternatives: If your some action leaves you in a state of rage and frustration, give
yourself a project-that doesn't involve it. Or find another alternative.
Do You Need Counseling?
If you feel that your anger is really out of control, if it is having an impact on your relationships
and on important parts of your life, you might consider counseling to learn how to handle it
better. A Professional Counselor at the Home School can work with you in developing a range of
techniques for changing your thinking and your behavior. When you talk to a prospective
therapist, tell her or him that you have problems with anger that you want to work on, and ask
about his or her approach to anger management. Make sure this isn't only a course of action
designed to "put you in touch with your feeling and express them"-that may be precisely what
your problem is. With counseling, psychologists say, a highly angry person can move closer to a
middle range of anger in about 8 to 10 weeks, depending on the circumstances and the
techniques used.
Depression
Depression is a mood state that can be brought upon by overly negative interpretations of
ourselves and of events. Negative thinking is not the only cause of depression; biological
changes can cause depression, as can catastrophic events. However, when depression is present,
regardless of cause, negative thinking is always present. And what is particularly insidious about
depression is that negative thinking left unchecked automatically spirals depression deeper and
deeper.
Symptoms of depression are not just by-products, but actually serve to strengthen and prolong
the depressive state. Though depression is a self-perpetuating state, the symptoms that worsen
the state are tangible, and modifying them ceases the self-fueling mood state, thus weakening the
depression, leading to mood improvement. Negative thinking is certainly one of the most
powerful fuels of depression. However, when depressed people learn to identify cognitive
distortions and then to replace them with more realistic interpretations, depression can be
reduced. Moreover, when people become adept at altering negative thoughts and beliefs, their
likelihood of experiencing episodes of depression in the future decreases. Cognitive therapy also
focuses on the other symptoms of depression, working to help the Mentat reduce isolation,
increase pleasurable activities and improve social skills. This often requires "putting the cart
before the horse", in other words helping patients to engage in behaviors that do not feel
potentially pleasurable. With depression, motivation does not typically occur until after the
patient has initiated the behaviors. This is incorporated into the confidence building exercises
every Mentat undergoes that helps fight Mentat freeze.
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One fact is that just "thinking positively" is not going to decrease depression in any lasting way.
Though depressed people do not engage in a great deal of positive thinking, it is less the absence
of positive thoughts and more the frequency of negative thoughts that perpetuate depressed
mood. Positive thinking alone just doesn't seem to be reducing depression in a lasting way. In
reality, it will have little effect on a depression for you to say to yourself "I'm doing a great job"
when for the majority of the day your automatic thoughts are self-critical and hopeless. The
reason is that even though you're telling yourself positive things, you are still believing only
negative things.
Anxiety
Anxiety is unlike depression, which sort of creeps in, and more like anger because it can
essentially "take over" in seconds. The emotional component is what we are typically most aware
of; the feelings of fear, apprehension and dread. The physical symptoms of anxiety include
increased heart rate, rapid breathing, shaking, even dizziness. Anxiety is by nature intense and
quick to escalate.
Anyone who has experienced intense anxiety is aware of the deficits in thinking and
concentration that can occur. Anxiety seems to cause a narrowing of attention. Anxious
individuals typically say they block or just can't think. In actuality they are thinking at full
throttle, but only about what is causing the anxiety! We have a limited capacity in terms of how
much information we can attend to at once. When strong emotions are present, they monopolize
cognitive capacity. Like depression, cognitive distortions are very much a part of chronic
anxiety.
Cognitively, Anxiety is always about vulnerability. Anxious individuals typically overestimate
the danger and underestimate their ability to control it.
Though anxiety by design is adaptive, there are many people who are crippled by its frequent
occurrence. The above model is optimistic, in that any active reduction of a symptom is going to
slow down the cycle of anxiety. Knowing which symptoms are tangible and how to reduce their
intensity is what cognitive therapy for Anxiety is all about. Consider the three types of
symptoms; emotional, physical and cognitive. Some treatments focus on the physical symptoms.
Medications that sedate are in effect reducing the physiological component of anxiety and thus
turning down the cycle. Relaxation techniques do the same thing. Cognitive behavioral treatment
for anxiety always includes training in relaxation. There are books and tapes available as well
which can help you learn to bring about a relaxed state. Learning how to relax is an integral part
of managing anxiety, because without alternative means of bringing about a less aroused state,
the anxious person will be plagued with urges to engage in maladaptive escape behaviors.
Other treatments focus exclusively on the emotion of anxiety. Some medications, for example,
directly influence chemicals in the brain believed to be related to anxiety.
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A particularly effective way to control anxiety is to modify distorted thinking. Cognitive
techniques are very usefully, in that with practice they can become quite automatic, thus making
you less vulnerable to anxiety in the future, increasing your anxiety armor as it were.
The most common anxiety provoking cognitive distortion is "CATASTROPHIC
EXAGGERATION." This is when the disastrousness of an event (particularly an expected event)
is exaggerated. Black and white, disastrous thoughts almost always accompany strong anxiety
states. Catastrophic thoughts can be about events in our lives, or, as is the case with panic
disorder, be about physical arousal (any normal increase in arousal is often catastrophized as a
serious medical condition or as the onset of a panic episode).
Identifying a catastrophic thought and modifying it so that it is more balanced and realistic can
have a profound effect on anxiety, certainly as much as techniques which focus on directly on
physical or emotional symptoms.
A decatastrophizing dialog proved very helpful in reducing this fellow's anxiety such that he
could go to his interview. Remember, decatastrophizing isn't just considering the evidence
against a purely negative prediction, but also considering what the big deal is even IF THE
WORST POSSIBLE OUTCOME DID HAPPEN.
Walking through the coping steps of a worst-case scenario is different than worrying about the
worst-case scenario. The latter is typically a preoccupation with the disastrousness of an event,
and mental energy placed on preventing its occurrence. De-catastrophizing is considering the
worst-case scenario, and then coming to the awareness that you could cope. If you can convince
yourself that you can tolerate the worst case, then all possible outcomes become manageable, by
default!
After convincing yourself that you could cope with the worst-case scenario, you should feel
considerably less overwhelmed. Now consider BEST CASE SCENARIOS, then REALISITIC
SCENARIOS. They will seem more possible after you have de-catastrophized.
As long as maladaptive escape responses are utilized, the anxiety cycle will endure.
EXPOSURE is never comfortable, and in cognitive therapy attempts are made to create stepwise
exposure schedules for people so that they are not overwhelmed and abandon change efforts.
However, it is important that the steps not be to "easy" as managing anxiety involves helping the
patient tolerate mild to moderate levels of anxiety and recognize that these states ebb, and do not
necessarily lead to intense panic. Systematic desensitization is a gradual exposure technique for
the treatment of phobia, in which the individual is taught relaxation skills that are applied to
gradually increasing levels of exposure. Further steps are not encouraged until the patient has
mastered previous steps.
Brain boosting substances
Smart drugs are basically of three different varieties: drugs, nutrients and herbs. Many nutrients
are classified as drugs when they are potent enough and in some cultures the difference between
a medicine (usually synthetic) and an herb (natural) is very hazy.
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Foods
Some vitamins are essential for the proper working of memory: tiamin, folic acid, and B12
vitamin. They are found in bread and cereal, vegetable and fruits. Some experts say that
synthesized vitamins improve memory, but others have doubts about this, arguing that the
studies have not confirmed these nutrients do work.
Water
Water help maintain the memory systems working, especially in older persons. Lack of water in
the body has an immediate and deep effect on memory; dehydration can generate confusion and
other thought difficulties.
Sleep
To be able to have a good memory, it is essential that we allow the brain to have enough sleep
and rest. While sleeping, the brain disconnects from the senses, and proceeds to revising and
storing memory. Insomnia would produce a chronic fatigue and would impair the ability of
concentration and the storing of information.
Smart Drugs
Piracetam
The most common smart drug is probably Piracetam, probably because it's not the most recent; it
has a wide variety of uses and is quite inexpensive. It is used to treat several illnesses, like
alcoholism, dementia and stroke, but should also improve memory and learning in healthy
humans. It is supposed to increase the flow of information between the right and left hemispheres
of the brain, thus helping in creative problem solving. It is sold as pills and the effective dose is
2400-4800 mg in three divided doses although some sources report significantly smaller dosages
ranging from 800 mg to 2400 mg. It has no know serious side effects, although insomnia,
headaches, nausea and stomach disturbances are possible. As with any other smart drug it is the
best to try and find out the dose that is good for you while keeping in mind the possible toxicity
of the drug (Piracetam has no know toxicity meaning that one probably can't overdose it).
Piracetam has a synergistic effect with DMAE, centrophenoxine, choline and Hydergine, which
means that the effects of Piracetam are amplified when taken at the same time with these drugs.
Hyderbine
Another well-known smart drug is Hydergine, which is used to treat senility. It is also supposed
to increase intelligence, memory and recall, and prevent various type of brain deterioration.
Furthermore it is supposed to repair some of the damage done by free radicals. One of the
strongest effects Hydergine has is its ability to prevent damage to the brain caused by too little
oxygen and therefore it is used as an emergency treatment for stroke patients. Known side effects
are mild nausea, dizziness and headaches, but Hydergine is considered virtually non-toxic. A
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danger of adverse reactions still exists at very high doses and people suffering from psychosis
should not use it. An effective dose can be anything from 3 mg to 9 mg, even though doses as
high as 12 mg have been tried on healthy humans with no side effects. Hydergine pills range
usually from 1 mg to 5 mg per pill. It is notable that the daily dose should be divided to three
equal doses and that the effects may not be noticeable until after several months of use (unless a
high dosage is taken).
Diapid
Another prescription drug called Diapid (a trade name for Vasopressin) is widely known for its
nootropic effects. Diapid is a brain hormone that is naturally present in your body and which
helps in learning new information. It has been used to treat a form of diabetes, because it reduces
the need to urinate. It has also been used to treat several conditions leading to memory
impairment. Vasopressin is taken in the form of a nasal spray - 2 to four sniffs three times a day.
Its effects are imminent and noticeable; clear-headed feeling and increased attention are among
reported effects. It is usually sold in c. 12 ml bottles and runs out very quickly if used
continuously. Continuous use is also discouraged; because it may cause headaches, nose
irritation or abdominal cramps.
Centrophenoxine (Lucidril)
Centrophenoxine is know for its anti-ageing effect (increases the life-span up to 30% in
laboratory animals) and for its intelligence boosting properties. It clears out cellular waste
product called liposfucin that prevents the normal functioning of neurones. When taken (usually
as pills) it breaks down to DMAE in your blood. The effects of these two drugs are believed to
be velly a prar. A suggested dosage is anything between 1000 and 3000 mg daily, although the
dose should be reduced if side effects occur (excitability, muscle stiffness or headaches).
DMAE (Dimethylaminoethanol)
DMAE increases intelligence, memory, energy levels and learning, extends the life span and
even elevatesnue to its effects are usually noticeable within half an hour after ingestion (more
quickly when taken as a liquid) and continue for a few hours. Some people have reported a build
up of tolerance to DMAE after several weeks of use. If tolerance builds up it can be handled by
discontinuing the use for a few weeks. Adverg for a aindications are rare, but minor side effects
include muscle tension or hypertension. Overdosing may cause insomnia or dull-headedness, so
it is better to start with a low dose first. A suggested dose is from 300 mg up to 1000 mg daily in
two divided doses (usually morning and afternoon). Determining the correcasoning should be
easy: just start with a low enough dose and gradually build up until you notice no improvement.
It is important to notice that DMAE may cause the opposite of the desired effect (dullheadedness) when overdosed. So this time its up to you whether this drug is a smart or a dumb
one.
Smart nutrients
Antioxidants
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There are several vitamins that are classified as antioxidants, namely vitamin E, C and A (betacarotene). Reported benefits from antioxidants are anti-ageing effects and protection from
damage tos.
Anells
Recommended dosages vary greatly, but here's general dosage suggestion: water soluble vitamin
E (100-500 IU daily), Vitamin C (200-500 mg daily) and beta-carotene (25 000 - 30 000 IU
daily). Note that Vitamin A is toxic even if not lethal when overdosed, so taking beta-carotene
(which your body turns intoradrenal A) instead is recommended.
B vitamins
There are twelve different B vitamins, of which four have been shown to have positive effects on
the nervous system. Thiamine (vitamin B1) is also considered an antioxidant and the
recommended dosage is between 25 and 150 mg daily although some sources report doses
asvolved i 1 000 mg.
Niacin (B3)
Niacin (B3) helps to improve memory and to combat stress. Recommended dosage is 100-200
mg daily taken with an antacid. Doses exceeding 50 mg may first cause flushing i.e. a feeling of
blood rushing to the head. Some people have also reported itching as a side effect. These
effectscalm worgo away after continued use.
Pyridoxine (B6)
Pyridoxine (B6) helps your brain to manufacture neurotransmitters and as such is vital for your
brain to function properly. It also aids Melange in increasing life span and to decrease stress.
Recommended dosage is 50-100 mg daily. Doses over 125 mg can be neurotoxic over longer
periods of time and should be avoided.
Cyanocobalamin (B12)
Cyanocobalamin (B12) is useful when fighting fatigue as it hey you threlease of energy from
food and to increase learning in laboratory animals. A daily amount of 100-200 mcg is suggested
along with 400 mcg of folic acid. All of these vitamins are best taken as a B-complex, so that
supplementing one type of vitamin B will not cause a deficiency of another type.
Choline and Lecithin
Lecithin and choline are precursors of asetylcholine which transmits electric impulses in your
brain. They have been show to improve short-term memory in normal humans. Both of the
nutrients offer basically the same benefits, although you can get away with taking smaller
amounts of choline as all of lecithindo thingtransformed into asetylcholine. Suggested intake is 3
grams of choline four times a day (that means 12 grams/day) and a bit more for lecithin in two
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doses. Both should be taken with a large amounts of B5 (c. 1 gram per dose) to help the
conversion to asetylcholine. Choline can cause a fishy odor that can be avose this eating yogurt.
In large doses it can also cause diarrhea, which is a sure sign to cut down the dosage. Both can be
bought at health food stores as liquid or as capsules. Both should be stored chilled in an airtight
container.
Amino acids
Amino acids are essential in building neurotransmitters in your brain and low levels of amino
acids in one's diet can result in tiredness and lack of concentration. Phenylalanine is the most
common of brain boosting bring cids; it will help one to fight off stress and it may also elevate
one's mood and increase alertness. A compound called DL-phenylalaninen taken daily at the
dose of 1 000 to 1 500 mg should be enough, followed by 50mg of vitamin B5 and half a gram of
vitamin C. Phenylalanine is best taken on an empty stomach, b intentit competes with proteins to
cross the blood brain barrier. As phenylalanine competes with tryptophan (a protein) in crossing
the blood brain barrier these substances should not be taken together. If phenylalanine prevents
tryptophan from crossing the blood brain barrier, then you may end up with lower serotonine
very i which in severe cases can lead to depression and aggressiveness. Foods rich in Ltryptophan include: Cottage cheese, milk, meat, fish, turkey, bananas, dried dates, peanuts or
generally all foods rich in protein. Avoid taking phenylalanine with these foods. Take on an
empty stomach.
There are also several time befino acids, such as Glutamine, Arginine, Tryptophan and Taurine,
but as the safety and usefulness of all these have not been settled.
Herbs
Mixing of herbs is considered essential as herbalists claim that many herbs have little effect on
their own, but combined they're supposedly very potent. Mentats unable to pick their own herbs
two forms of preserved herb essences remain, mainly freeze-dried and alcohol based extracts.
These two preserving methodsted and posed to retain the power of the herbs for long periods.
Melange
The "spice of spices," the crop for which Arrakis is the unique source. The spice, chiefly noted
for its geriatric qualities, is mildly addictive when taken in small quantities, severely addictive
when imbibed in quantities above two grams daiediate seventy kilos of body weight. (See Ibad,
Water of Life, and Pre spice Mass.) Muad'Dib claimed the spice as a key to his prophetic powers.
Guild navigators make similar claims. Its price on the Imperial market has ranged as high as
620,000 solaris the decagram.
Ginkgo Biloba
It increases blood circulation of the tiny blood vessels of the brain and effects usually attributed
to it include improved memory, reasoning and alertness. Ginkgo is also an antioxidant and it
helps your brain to build its own fuel called ATP. The suggested dosage is 120-160 mg of ginkgo
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extract that contains 24% active ingredients ginkgo flavonoid don'xtract should be taken in three
divided doses as gingko leaves the body within six hours of ingestion. Extracts are available
from health food stores almost everywhere, but the potency may not be that great. The ingredient
to keep an eye on when choosing gingko products is gingko flavonoids or gingko heterosides.
The more extract has this the better it is. If only low potency extracts are available one should up
the dosage even up to 1000 mg.
Ginseng
The medicine has used ginseng root successfully for thousands of years and during that time it
has had several medical uses. Ginseng has been used to treat fatigue, abnormal blood pressure
and quite oddly even insomnia and cancer. It is generally thought of as an all around medicine
that has no specific use, so pend in co it to get various different results. Stress and fatigue relief
are among the most commonly give reasons for taking ginseng extract. It works by regulating the
blood sugar levels and heart beat, increasing blood flow and metabolism - to name just a few.
Tea and extracts are the best forms, because the active in these ss get into your blood faster from
these forms. Both products have a distinct bitter taste, as does the root itself. If you plan to use
the root, you're better of chewing than swallowing it, because ginseng is very hard to digest.
Dosage is anything from 500 to 4000 mg daily in divided doses.
Gotu-kola
A mastereastern medicine-wonder, gotu-kola is a plant that has been used to improve wound
healing and different types of skin conditions. It is also believed to affect brain functioning by
reducing stress and anxiety. Gotu-kola has a mild tranquillizing effect. Study shows it to improve
concentration. A dose of two leaves a day (chewed not swallowed) should give the desired
effect. A plant very similar to gotu-kola in its effects and use if fo-ti-tieng, which can b, vegetan
place of gotu-kola.
Caffeine
Caffeine is used and claimed by many people to be the only thing that gets them going in the
morning, thus it is generally considered to improve performance. What is not so often mentioned
are the side effects of caffeine, namely that it makes its users anxious and irritable. Caffeine is
also very addictive and should be considered a drug when taken as potent pills. Research on
caffeine's benefits is divided: some claim it improves performance while others proclaim it
actually decreases performance. What is for sure is that several million people swear by it daily.
Coffee and tea have a very positive effect to maintain attention and to end sleepiness, but the
excitation promoted by these drinks may interfere with the memory function.
Rachag
Rachag is a caffeine-type stimulant from the yellow berries of akarso, a plant native to Sikun (of
70 Ophiuchi A) characterized by almost oblong leaves. Its green and white stripes indicate the
constant multiple condition of parallel active and dormant chlorophyll regions.
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Sapho
Sapho is a high-energy liquid extracted from barrier roots of Ecaz. Commonly used by Mentats
since it amplifies mental powers. Users develop deep ruby stains on mouth and lips. Ecaz is the
fourth planet of Alpha Centauri B.
It is by will alone I set my mind in motion.
It is by the juice of sapho that thoughts acquire speed,
the lips acquire stains.
The stains become a warning.
It is by will alone I set my mind in motion.
The sapho taste triggered responses in his brain, firing his neurons, stoking his mental
capabilities.
Perfect Your Thinking
Incorrect Thinking that Bypasses Intelligence
1. Filtering: You take the negative details and magnify them while filtering out all positive
aspects of a situation.
2. Discounting the positives: You insist that your accomplishments or positive qualities don't
count.
3. Polarized Thinking: Things are black or white, good or bad. You have to be perfect or you're a
failure. There is no middle ground.
4. Over Generalization: You come to a general conclusion based on a single incident or piece of
evidence. If something bad happens once, you expect it to happen over and over again.
5. Jumping to conclusions: You conclude things are bad without any definite evidence. Two
instances of this particular problem are:
i. Mind reading: Without their saying so, you know what people are feeling and why they act the
way they do. In particular, you are able to divine how people are feeling toward you..
ii. Fortune telling: You predict things will turn out badly
6. Magnification or minimization: You blow things way out of proportion or you shrink their
importance.
7. Catastrophizing: You expect disaster. You notice or hear about a problem and start "what if's:"
What if tragedy strikes? What if it happens to you?"
8. Personalization: Thinking that everything people do or say is some kind of reaction to you.
You also compare yourself to others, trying to determine who's smarter, better looking, etc.
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9. Control Fallacies: If you feel externally controlled, you see yourself as helpless, a victim of
fate. The fallacy of internal control has you responsible for the pain and happiness of everyone
around you.
10. Fallacy of Fairness: You feel resentful because you think you know what's fair but other
people won't agree with you.
11. Blame: You blame yourself for something you weren't entirely responsible for, or you blame
other people and overlook ways that you contributed to a problem. You hold other people
responsible for your pain, or take the other tack and blame yourself for everyone's problem or
reversal.
12. Shoulds: You have a list of ironclad rules about how you and other people should act. People
who break the rules anger you and you feel guilty if you violate the rules. You criticize yourself
or other people with "shoulds", "shouldn'ts","musts","oughts", and "have-tos".
13. Emotional Reasoning: You believe that what you feel must be true-automatically. If you feel
stupid and boring, then you must be stupid and boring.
14. Fallacy of Change: You expect that other people will change to suit you if you just pressure
or cajole them enough. You need to change people because your hopes for happiness seem to
depend entirely on them.
15. Global Labeling: You generalize one or two qualities into a negative global judgment.
Instead of saying "I made a mistake" you tell yourself "I'm a jerk" or "a loser".
16. Being Right: You are continually on trial to prove that your opinions and actions are correct.
Being wrong is unthinkable and you will go to any length to demonstrate your rightness.
17. Heaven's Reward Fallacy: You expect all your sacrifice and self-denial to pay off, as if there
were someone keeping score. You feel bitter when the reward doesn't come.
18. Know better:
19. Chicken little syndrome:
20. Believing your press agent:
21. Believing your critics:
22. Perfectionism:
23. Comparisonitis:
24. Yes-butism:
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Correct Thinking that Activates Intelligence
1. Ask Questions: Be willing to wonder.
2. Define Your Terms: Be precise about what is being considered. Operational definitions are the
precise definitions in terms of how the variables are actually being observed and measured.
3. Examine the Evidence: What evidence supports or refutes the argument being made?
4. Analyze Assumptions and Biases: We must be aware of how our assumptions might bias our
conclusions.
5. The principle of falsifiability: This means that scientific predictions are made to expose the
hypothesis to the possibility of disconfirmation.
6. Avoid Emotional Reasoning: Emotional reasoning can replace clear thinking.
7. Don't Oversimplify: Resist easy generalizations and "either-or thinking".
8. Resist arguing by anecdote: This means generalizing from a few examples to everyone.
9. Consider Other Interpretations: Formulate hypotheses that offer explanations of the topic. The
goal is to arrive at a theory which is a system of principles that tries to explain the phenomena
and their interrelationships. Be careful not to shut out alternative explanations too soon.
10. Tolerate Uncertainty: Many questions have no easy answers. We have to be willing to be
uncertain when new evidence questions our conclusions.
11. Replication is important before firm conclusions can be drawn.
12. Identify the distortion: write down which distortion is twisting your thinking
13. The straightforward Approach: Substitute a more positive and realistic thought
14. The cost-benefit analysis: List the advantages and disadvantages of a negative thought, belief
or behavior.
15. Examine the Evidence: Instead of assuming that a negative thought is true, examine the
actual evidence for it.
16. The Survey method: Do a survey to find out if your thoughts and attitudes are realistic
17. The Experimental Method: Do an experiment and test the accuracy of your Negative
Thought
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18. The Double-Standard Technique: Talk to yourself with the same compassionate way you
might talk to a dear friend who was upset
19. The Pleasure-Predicting Method: Predict how satisfying activities will be, from 0% to 100%.
Record how satisfying they turn out to be.
20. The Vertical Arrow Technique: Draw a vertical arrow under your Negative Thought and ask
why it would be upsetting if it were true.
21. Thinking in Shades of Grey: Instead of thinking about your problems in black-and-white
categories, evaluate things in shades of gray.
22. Define terms: When you label yourself as "inferior" or "a loser", ask yourself what you mean
by these labels.
23. Be specific: Stick with reality and avoid judgments about reality
24. The Semantic Method: Substitute language that is less emotionally loaded for "should"
statements and labeling.
25. Reattribution: Instead of blaming yourself for a problem, think about all the factors that may
have contributed to it.
26. The Acceptance Paradox: Instead of defending yourself against your own self-criticisms find
truth in them and accept them.
27. Questioning your evidence: This is important in dealing with all mistakes in thinking.
28. Analyze the consequences: The first step in thinking about your particular list of shoulds is to
analyze the consequences of giving them up or modifying them.
29. Perfection: Each of us has come to an individual conclusion about how important a personal
standard of perfection is. But that conclusion should be drawn only after we fairly consider the
reasons for our choice.
30. Assign responsibility
31. De-catastrophising
32. Develop alternatives in thought
33. Develop alternatives in feeling
34. Develop alternatives in actions
35. Labeling your mistakes
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36. Then what?
37. Super exaggeration
38. Scaling 1 to 10
39. Turning adversary to advantage
40. Developing replacements
41. Rehearsing positive images
42. Self-instruction
43. Self-distraction
44. Playing Defense Attorney
This has been
The Mentat Handbook
James W. Meritt
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