V. WHY DECISIONS HARD?
What makes decisions hard? Certainly different problems may involve different and often special difficulties. Although
every decision may have its own special problems, there are four basic sources of difficulty.
First, a decision can be hard simply because of its complexity. Simply keeping all of the issues in mind at one time is
Second, a decision can be difficult because of the inherent uncertainty in the situation. In some decisions, the main
issue is uncertainty. For example, imagine a firm trying to decide whether to introduce a new product. The size of the market,
the market price, eventual competition, and manufacturing and distribution costs all may be uncertain to some extent, and
all have some impact on the firm's eventual payoff. Yet the decision must be made without knowing for sure what these uncertain
values will be.
Third, a decision maker may be interested in working toward multiple objectives, but progress in one direction may impede
progress in others. In such a case, a decision maker must trade off benefits in one area against costs in another. In investment
decisions, a trade-off that we usually must make is between expected return and riskiness.
Fourth, and finally, a problem may be difficult if different perspectives lead to different conclusions. Or, even from
a single perspective, slight changes in certain inputs may lead to different choices. This source of difficulty is particularly
pertinent when more than one person in involved in making the decision. Different individuals may look at the problem from
different perspectives, or they may disagree on the uncertainty or value of the various outcomes.
A. Behavioral Influences on Individual Decision Making
Several behavioral factors influence the decision making process. Some affect only certain aspects of the process, while
others influence the entire process. However, each may have an impact and therefore must be understood to fully appreciate
the decision making process in organizations. Four individual behavioral factors: values, personality, propensity for risk,
and potential for dissonance are discussed here. Each has a significant impact on the decision making process.
In the context of decision making, values are the guidelines a person uses when confronted with a situation in which a
choice must be made. Values are acquired early in life and are a basic (often taken for granted) part of an individual's thoughts.
Values; influence on the decision making process is profound:
In establishing objectives, value judgments must be made regarding the selection of opportunities and the assignment of
In developing alternatives, value judgments about the various possibilities are necessary.
In choosing an alternative, the values of the decision maker influence which alternative is chosen.
In implementing a decision, value judgments are necessary in choosing the means for implementation.
In the control and evaluation phase, value judgments cannot be avoided when corrective action is decided on and taken.
Clearly, values pervade the decision making process, encompassing not only the individual's economic and legal responsibilities
but his ethical responsibilities as well. They are reflected in the decision maker's behavior before making the decision,
in making the decision, and in putting the decision into effect. Indeed, some researchers state that alternatives are relevant
only as a means of achieving managerial values.
Decision makers are influenced by many psychological forces, both conscious and subconscious. One of the most important
of these forces is personality. Decision maker's personalities are strongly reflected in their choices. Studies that have
examined the effect of personality on the process of decision making have generally focused on three types of variables:
*Personality variables: the attitudes, beliefs, and needs of the individual.
*Situational variables; external, observable situations in which individuals find themselves.
*Interactional variables: the individual's momentary state that results from the interaction of a specific situation
with characteristics of the individual's personality.
The most important conclusions concerning the influence of personality on the decision making process are:
1. One person is not likely to be equally proficient in all aspects of the decision making process. Some people do better
in one part of the process, while others do better in another part.
2. Certain characteristics, such as intelligence, are associated with different phases of the decision making process.
3. The relationship of personality to the decision making process may vary for different groups on the basis of such factors
as sex, social status, and cultural background.
4. Individuals facing important and ambiguous decisions may be influenced heavily by peers opinions.
An interesting study examined the importance of cultural influences on decision making style differences between Japanese
and Australian college students. In Japan, a group orientation exists, while in Australia, the common cultural pattern emphasizes
and individual orientation. The results confirmed the importance of the cultural influence. Japanese students reported greater
use of decision processes or behaviors associated with the involvement and influence of others, while Australian students
reported greater use of decision processes associated with self-reliance and personal ability. In general, the personality
traits of the decision maker combine with certain situational and interactional variables to influence the decision making
3. Propensity for Risk
From personal experience, we are all undoubtedly aware that decision makers vary greatly in their propensity for taking
risks. This one specific aspect of personality strongly influences the decision making process. A decision maker with a low
aversion to risk establishes different objectives, evaluates alternatives differently, and selects different alternatives
than a decision maker in the same situation who has a high aversion to risk. The latter attempts to make choices where the
risk or uncertainty is low or where the certainty of the outcome is high. The best managers need to tread a fine line between
making ill-conceived, arbitrary decisions based purely on instinct (low aversion to risk) and becoming too obsessed with a
reliance on numbers, analyses, and reports (high aversion to risk). Many people are bolder and more innovative and advocate
greater risk taking in groups than as individuals. Apparently, such people are more willing to accept risk as members of a
4. Potential for Dissonance
Much attention has focused on the forces that influence the decision maker before a decision is made and that impact the
decision itself. Only recently has attention been given to what happens after a decision has been made. Specifically, behavioral
scientists have focused attention on post decision anxiety.
Such anxiety is related to what experts called cognitive dissonance over 35 years ago and what researchers today term
regret theory. This theory states that there is often a lack of consistency, or harmony, among an individual's various cognitions
(attitudes, beliefs, etc.) after a decision has been made. As a result, the decision maker has doubts and second thoughts
about the choice, In addition, the intensity of anxiety is likely to be greater in the presence of any of the following conditions:
* The decision is psychologically and/or financially important.
* There are a number of forgone alternatives.
* The forgone alternatives have many favorable features.
Dissonance can, of course, be reduced by admitting that a mistake has been made. Unfortunately, many individuals are reluctant
to admit that they have made a wrong decision These individuals are more likely to reduce their dissonance by using one or
more of the following methods:
* Seek information that supports the wisdom of their decisions.
* Selectively perceive (distort) information in a way that supports their decisions.
* Adopt a less favorable view of the forgone alternatives.
* Minimize the importance of the negative aspects of the decisions and exaggerate the importance of the positive aspects.
While each of us may resort to some of this behavior in our personal decision making, a great deal of such behavior could
easily harm organizational effectiveness.
Personality, specifically the level of self-confidence and persuasibility, heavily influences are closely interrelated
and are only isolated here for purposes of discussion.
VI. ETHICAL DECISION MAKING
1. What is Ethics?
Simply stated, ethics refers to standards of behavior that tell us how human beings ought to act in the many situations
in which they find themselves-as friends, parents, children, citizens, businesspeople, teachers, professionals, and so on.
It is helpful to identify what ethics is NOT:
* Ethics is not the same as feelings. Feelings provide important information for our ethical choices. Some people have
highly developed habits that make them feel bad when they do something wrong, but many people feel good even though they are
doing something wrong. And often our feelings will tell us it is uncomfortable to do the right thing if it is hard.
*Ethics is not religion. Many people are not religious, but ethics applies to everyone. Most religions do advocate high
ethical standards but sometimes do not address all the types of problems we face.
* Ethics is not following the law. A good system of law does incorporate many ethical standards, but law can deviate
from what is ethical. Law can become ethically corrupt, as some totalitarian regimes have made it. Law can be a function of
power alone and designed to serve the interests of narrow groups. Law may have a difficult time designing or enforcing standards
in some important areas, and may be slow to address new problems.
* Ethics is not following culturally accepted norms. Some cultures are quite ethical, but others become corrupt -or blind
to certain ethical concerns (as the United States was to slavery before the Civil War). "When in Rome, do as the Romans
do" is not a satisfactory ethical standard.
*Ethics is not science. Social and natural science can provide important data to help us make better ethical choices.
But science alone does not tell us what we ought to do. Science may provide an explanation for what humans are like. But ethics
provides reasons for how humans ought to act. And just because something is scientifically or technologically possible, it
may not be ethical to do it.
2. Why Identifying Ethical Standards is Hard
A. There are two fundamental problems in identifying the ethical standards we are to follow: On what do we base our
B. How do those standards get applied to specific situations we face?
If our ethics are not based on feelings, religion, law, accepted social practice, or science, what are they based on?
Many philosophers and ethicists have helped us answer this critical question. They have suggested at least five different
sources of ethical standards we should use.
3. Five Sources of Ethical Standards
A. The Utilitarian Approach
Some ethicists emphasize that the ethical action is the one that provides the most good or does the least harm, or, to
put it another way, produces the greatest balance of good over harm. The ethical corporate action, then, is the one that produces
the greatest good and does the least harm for all who are affected-customers, employees, shareholders, the community, and
the environment. Ethical warfare balances the good achieved in ending terrorism with the harm done to all parties through
death, injuries, and destruction. The utilitarian approach deals with consequences; it tries both to increase the good done
and to reduce the harm done.
B. The Rights Approach
Other philosophers and ethicists suggest that the ethical action is the one that best protects and respects the moral
rights of those affected. This approach starts from the belief that humans have a dignity based on their human nature per
se or on their ability to choose freely what they do with their lives. On the basis of such dignity, they have a right to
be treated as ends and not merely as means to other ends. The list of moral rights -including the rights to make one's own
choices about what kind of life to lead, to be told the truth, not to be injured, to a degree of privacy, and so on-is widely
debated; some now argue that non-humans have rights, too. Also, it is often said that rights imply duties-in particular, the
duty to respect others' rights.
C. The Fairness or Justice Approach
Aristotle and other Greek philosophers have contributed the idea that all equals should be treated equally. Today we use
this idea to say that ethical actions treat all human beings equally-or if unequally, then fairly based on some standard that
is defensible. We pay people more based on their harder work or the greater amount that they contribute to an organization,
and say that is fair. But there is a debate over CEO salaries that are hundreds of times larger than the pay of others; many
ask whether the huge disparity is based on a defensible standard or whether it is the result of an imbalance of power and
hence is unfair.
D. The Common Good (Caring) Approach
The Greek philosophers have also contributed the notion that life in community is a good in itself and our actions should
contribute to that life. This approach suggests that the interlocking relationships of society are the basis of ethical reasoning
and that respect and compassion for all others-especially the vulnerable-are requirements of such reasoning. This approach
also calls attention to the common conditions that are important to the welfare of everyone. This may be a system of laws,
effective police and fire departments, health care, a public educational system, or even public recreational areas.
E. The Virtue Approach
A very ancient approach to ethics is that ethical actions ought to be consistent with certain ideal virtues that provide
for the full development of our humanity. These virtues are dispositions and habits that enable us to act according to the
highest potential of our character and on behalf of values like truth and beauty. Honesty, courage, compassion, generosity,
tolerance, love, fidelity, integrity, fairness, self-control, and prudence are all examples of virtues. Virtue ethics asks
of any action, "What kind of person will I become if I do this?" or "Is this action consistent with my acting
at my best?"
Putting the Approaches Together
Each of the approaches helps us determine what standards of behavior can be considered ethical. There are still problems
to be solved, however.
The first problem is that we may not agree on the content of some of these specific approaches. We may not all agree to
the same set of human and civil rights.
We may not agree on what constitutes the common good. We may not even agree on what is a good and what is a harm.
The second problem is that the different approaches may not all answer the question "What is ethical?" in the
same way. Nonetheless, each approach gives us important information with which to determine what is ethical in a particular
circumstance. And much more often than not, the different approaches do lead to similar answers.
VII. DECISION MAKING TOOLS
The techniques in this module will help you to make the best decisions possible with the information you have available.
With these tools you will be able to map out the likely consequences of decisions, work out the importance of individual factors,
and choose the best course of action to take.
Tools to be discussed are:
* Pareto Analysis. Selecting the most important changes to make.
* Paired Comparison Analysis. Evaluating the relative importance of different options.
* Grid Analysis. Selecting between good options.
* Decision Trees. Choosing between options by projecting likely outcomes.
* PMI. Weighing the pros and cons of a decision.
*Force Field Analysis. Analyzing the pressures for and against change.
* Six Thinking Hats. Looking at a decision from all points of view.
* Cost/Benefit Analysis. Seeing whether a change is worth making.
In this module we will look at a set of good techniques hat help you to select between different options. These are very
useful when you have to take a go/no-go decision. This part finishes by discussing Decision Trees, which are excellent Decision
Making tools. If you are suffering from decidophobia, these tools will get you moving again.
Do remember, though, that the tools in this module exist only to assist your intelligence and common sense. These are
your most important assets in good Decision Making.
1. Pareto Analysis - Choosing the Most Important Changes to Make
Pareto analysis is a very simple technique that helps you to choose the most effective changes to make.
It uses the Pareto principle - the idea that by doing 20% of work you can generate 80% of the advantage of doing the entire
job. Pareto analysis is a formal technique for finding the changes that will give the biggest benefits. It is useful where
many possible courses of action are competing for your attention.
How to use tool:
To start using the tool, write out a list of the changes you could make. If you have a long list, group it into related
Then score the items or groups. The scoring method you use depends on the sort of problem you are trying to solve. For
example, if you are trying to improve profitability, you would score options on the basis of the profit each group might generate.
If you are trying to improve customer satisfaction, you might score on the basis of the number of complaints eliminated by
The first change to tackle is the one that has the highest score. This one will give you the biggest benefit if you solve
The options with the lowest scores will probably not even be worth bothering with - solving these problems may cost you
more than the solutions are worth.
A manager has taken over a failing service center. He commissions research to find out why customers think that service
is poor.He gets the following comments back from the customers:
1. Phones are only answered after many rings.
2. Staff seem distracted and under pressure.
3. Engineers do not appear to be well organized. They need second visits to bring extra parts. This means that customers
have to take more holidays to be there a second time.
4. They do not know what time they will arrive. This means that customers may have to be in all day for an engineer
5. Staff members do not always seem to know what they are doing.
6. Sometimes when staff members arrive, the customer finds that the problem could have been solved over the phone.
The manager groups these problems together. He then scores each group by the number of complaints, and orders the list:
* Lack of staff training: items 5 and 6: 51 complaints
* Too few staff: items 1, 2 and 4: 21 complaints
* Poor organization and preparation: item 3: 2 complaints
By doing the Pareto analysis above, the manager can better see that the vast majority of problems (69%) can be solved
by improving staff skills.
Once this is done, it may be worth looking at increasing the number of staff members. Alternatively, as staff members
become more able to solve problems over the phone, maybe the need for new staff members may decline.
It looks as if comments on poor organization and preparation may be rare, and could be caused by problems beyond the manager's
By carrying out a Pareto Analysis, the manager is able to focus on training as an issue, rather than spreading effort
over training, taking on new staff members, and possibly installing a new computer system.
Pareto Analysis is a simple technique that helps you to identify the most important problem to solve.
To use it:
* List the problems you face, or the options you have available
* Group options where they are facets of the same larger problem
* Apply an appropriate score to each group
* Work on the group with the highest score
Pareto analysis not only shows you the most important problem to solve, it also gives you a score showing how severe the
2. Paired Comparison Analysis - Working Out the Relative
Importance of Different Options
Paired Comparison Analysis helps you to work out the importance of a number of options relative to each other. It is particularly
useful where you do not have objective data to base this on.
This makes it easy to choose the most important problem to solve, or select the solution that will give you the greatest
advantage. Paired Comparison Analysis helps you to set priorities where there are conflicting demands on your resources.
It is also an ideal tool for comparing "apples with oranges" - completely different options such as whether
to invest in marketing, a new IT system or a new piece of machinery. These decisions are usually much harder than comparing
three possible new IT systems, for example.
How to use tool:
To use the technique, you will be needing a worksheet. You can use this to compare each option with each other option,
one-by-one. For each comparison, you will decide which of the two options is most important, and then assign a score to show
how much more important it is.
Follow these steps to use the technique:
1. List the options you will compare. Assign a letter to each option.
2. Mark the options as row and column headings on the worksheet.
3. Within the cells compare the option in the row with the one in the column. For each cell, decide which of the two options
is more important. Write down the letter of the more important option in the cell, and score the difference in importance
from 0 (no difference) to 3 (major difference).
4. Finally, consolidate the results by adding up the total of all the values for each of the options. You may want to
convert these values into a percentage of the total score.
3. Grid Analysis - Making a Choice Where Many Factors must be Balanced
Grid Analysis (also known as Decision Matrix analysis, Pugh Matrix analysis or MAUT which stands for Multi-Attribute Utility
Theory) is a useful technique to use for making a decision. Decision matrices are most effective where you have a number of
good alternatives and many factors to take into account.
How to use tool:
The first step is to list your options and then the factors that are important for making the decision. Then use a worksheet.
Lay the options out on the worksheet table, with options as the row labels, and factors as the column headings.
Next, work out the relative importance of the factors in your decision. Show these as numbers. We will use these to weight
your preferences by the importance of the factor. These values may be obvious. If they are not, then use a technique such
as Paired Comparison Analysis to estimate them.
The next step is to work your way across your table, scoring each option for each of the important factors in your decision.
Score each option from 0 (poor) to 3 (very good). Note that you do not have to have a different score for each option - if
none of them are good for a particular factor in your decision, then all options should score 0.
Now multiply each of your scores by the values for your relative importance. This will give them the correct overall weight
in your decision.
Finally add up these weighted scores for your options. The option that scores the highest wins!
Grid Analysis helps you to decide between several options, while taking many different factors into account.
To use the tool, lay out your options as rows on a table. Set up the columns to show your factors. Allocate weights to
show the importance of each of these factors. Score each choice for each factor using numbers from 0 (poor) to 3 (very good).
Multiply each score by the weight of the factor, to show its contribution to the overall selection. Finally add up the total
scores for each option. Select the highest scoring option.
Grid Analysis is the simplest form of Multiple Criteria Decision Analysis (MCDA), also known as Multiple Criteria Decision
Aid or Multiple Criteria Decision Management (MCDM). Sophisticated MCDA is involves highly complex modeling of different potential
scenarios and advanced mathematics.
6. Decision Tree Analysis - Choosing Between Options by Projecting Likely Outcomes
Decision Trees are excellent tools for helping you to choose between several courses of action. They provide a highly
effective structure within which you can lay out options and investigate the possible outcomes of choosing those options.
They also help you to form a balanced picture of the risks and rewards associated with each possible course of action.
How to use tool:
You start a Decision Tree with a decision that you need to make. Draw a small square to represent this towards the left
of a large piece of paper.
From this box draw out lines towards the right for each possible solution, and write that solution along the line. Keep
the lines apart as far as possible so that you can expand your thoughts.
At the end of each line, consider the results. If the result of taking that decision is uncertain, draw a small circle.
If the result is another decision that you need to make, draw another square. Squares represent decisions, and circles represent
uncertain outcomes. Write the decision or factor above the square or circle. If you have completed the solution at the end
of the line, just leave it blank.
Starting from the new decision squares on your diagram, draw out lines representing the options that you could select.
From the circles draw lines representing possible outcomes. Again make a brief note on the line saying what it means. Keep
on doing this until you have drawn out as many of the possible outcomes and decisions as you can see leading on from the original
Once you have done this, review your tree diagram. Challenge each square and circle to see if there are any solutions
or outcomes you have not considered. If there are, draw them in. If necessary, redraft your tree if parts of it are too congested
or untidy. You should now have a good understanding of the range of possible outcomes of your decisions.
Decision trees provide an effective method of Decision Making because they:
* Clearly lay out the problem so that all options can be challenged
* Allow us to analyze fully the possible consequences of a decision
* Provide a framework to quantify the values of outcomes and the probabilities of achieving them
* Help us to make the best decisions on the basis of existing information and best guesses.
As with all Decision Making methods, decision tree analysis should be used in conjunction with common sense - decision
trees are just one important part of your Decision Making tool kit.
Many other similar techniques are explained in the book Management Science by Wayne Winston and Christian Albright -
this is reviewed at the top of our right hand side bar.
5. PMI - Weighing the Pros and Cons of a Decision
PMI stands for 'Plus/Minus/Interesting'. It is a valuable improvement to the 'weighing pros and cons' technique used for
PMI is an important Decision Making tool: the mind tools used so far in this section have focused on selecting a course
of action from a range of options. Before you move straight to action on this course of action, it is important to check that
it is going to improve the situation (it may actually be best to do nothing!) PMI is a useful tool for doing this.
How to use tool:
To use PMI, download our free worksheet. In the column underneath 'Plus', write down all the positive results of taking
the action. Underneath 'Minus' write down all the negative effects. In the 'Interesting' column write down the implications
and possible outcomes of taking the action, whether positive, negative, or uncertain.
By this stage it may already be obvious whether or not you should implement the decision. If it is not, consider each
of the points you have written down and assign a positive or negative score to it appropriately. The scores you assign may
be quite subjective.
Once you have done this, add up the score. A strongly positive score shows that an action should be taken, a strongly
negative score that it should be avoided.
PMI is a good way of weighing the pros, cons and implications of a decision. When you have selected a course of action,
PMI is a good technique to use to check that it is worth taking.
To use the technique, draw up a table with three columns headed Plus, Minus and Interesting. Within the table write down
all the positive points of following the course of action, all the negatives, and all the interesting implications and possible
If the decision is still not obvious, you can then score the table to show the importance of individual items. The total
score should show whether it is worth implementing the decision.
6. Force Field Analysis- Understanding the Pressures For and Against Change
Force Field Analysis is a useful technique for looking at all the forces for and against a decision. In effect, it is
a specialized method of weighing pros and cons.
By carrying out the analysis you can plan to strengthen the forces supporting a decision, and reduce the impact of opposition
How to Use the Tool:
To carry out a force field analysis, first download our free worksheet and then use it to follow these steps:
* Describe your plan or proposal for change in the middle.
* List all forces for change in one column, and all forces against change in another column.
Assign a score to each force, from 1 (weak) to 5 (strong).
Force Field Analysis is a useful technique for looking at all the forces for and against a plan. It helps you to weigh
the importance of these factors and decide whether a plan is worth implementing.
Where you have decided to carry out a plan, Force Field Analysis helps you identify changes that you could make to improve
7. Six Thinking Hats- Looking at a Decision From All Points of View
'Six Thinking Hats' is a powerful technique that helps you look at important decisions from a number of different perspectives.
It helps you make better decisions by forcing you to move outside your habitual ways of thinking. As such, it helps you understand
the full complexity of the decision, and spot issues and opportunities to which you might otherwise be blind.
This tool was created by Edward de Bono in his book '6 Thinking Hats'.
Many successful people think from a very rational, positive viewpoint. This is part of the reason that they are successful.
Often, though, they may fail to look at a problem from an emotional, intuitive, creative or negative viewpoint. This can mean
that they underestimate resistance to plans, fail to make creative leaps and do not make essential contingency plans.
Similarly, pessimists may be excessively defensive, and more emotional people may fail to look at decisions calmly and
If you look at a problem with the 'Six Thinking Hats' technique, then you will solve it using all approaches. Your decisions
and plans will mix ambition, skill in execution, sensitivity, creativity and good contingency planning.
How to Use the Tool:
You can use the Six Thinking Hats technique in meetings or on your own. In meetings it has the benefit of blocking the
confrontations that happen when people with different thinking styles discuss the same problem.
Each 'Thinking Hat' is a different style of thinking. These are explained below:
* White Hat: With this thinking hat you focus on the data available. Look at the information you have, and see
what you can learn from it. Look for gaps in your knowledge, and either try to fill them or take account of them. This is
where you analyze past trends, and try to extrapolate from historical data.
* Red Hat: 'Wearing' the red hat, you look at problems using intuition, gut reaction, and emotion. Also try to think
how other people will react emotionally. Try to understand the responses of people who do not fully know your reasoning.
* Black Hat: Using black hat thinking, look at all the bad points of the decision. Look at it cautiously and defensively.
Try to see why it might not work. This is important because it highlights the weak points in a plan. It allows you to eliminate
them, alter them, or prepare contingency plans to counter them.
Black Hat thinking helps to make your plans 'tougher' and more resilient. It can also help you to spot fatal flaws and
risks before you embark on a course of action. Black Hat thinking is one of the real benefits of this technique, as many successful
people get so used to thinking positively that often they cannot see problems in advance. This leaves them under-prepared
* Yellow Hat: The yellow hat helps you to think positively. It is the optimistic viewpoint that helps you to see all
the benefits of the decision and the value in it. Yellow Hat thinking helps you to keep going when everything looks gloomy
* Green Hat: The Green Hat stands for creativity. This is where you can develop creative solutions to a problem. It is
a freewheeling way of thinking, in which there is little criticism of ideas. A whole range of creativity tools can help you
* Blue Hat: The Blue Hat stands for process control. This is the hat worn by people chairing meetings. When running into
difficulties because ideas are running dry, they may direct activity into Green Hat thinking. When contingency plans are needed,
they will ask for Black Hat thinking, etc.
A variant of this technique is to look at problems from the point of view of different professionals (e.g. doctors, architects,
sales directors, etc.) or different customers.
Six Thinking Hats is a good technique for looking at the effects of a decision from a number of different points of view.
It allows necessary emotion and skepticism to be brought into what would otherwise be purely rational decisions. It opens
up the opportunity for creativity within Decision Making. The technique also helps, for example, persistently pessimistic
people to be positive and creative.
Plans developed using the '6 Thinking Hats' technique will be sounder and more resilient than would otherwise be the case.
It may also help you to avoid public relations mistakes, and spot good reasons not to follow a course of action before you
have committed to it.
7. Cost/Benefit Analysis- Evaluating Quantitatively Whether to Follow a Course of Action
You may have been intensely creative in generating solutions to a problem, and rigorous in your selection of the best
one available. However, this solution may still not be worth implementing, as you may invest a lot of time and money in solving
a problem that is not worthy of this effort.
Cost Benefit Analysis or CBA is a relatively simple and widely used technique for deciding whether to make a change. As
its name suggests, you simply add up the value of the benefits of a course of action, and subtract the costs associated with
Costs are either one-off, or may be ongoing. Benefits are most often received over time. We build this effect of time
into our analysis by calculating a payback period. This is the time it takes for the benefits of a change to repay its costs.
Many companies look for payback over a specified period of time e.g. three years.
How to use tool:
In its simple form, cost-benefit analysis is carried out using only financial costs and financial benefits. For example,
a simple cost benefit ration for a road scheme would measure the cost of building the road, and subtract this from the economic
benefit of improving transport links. It would not measure either the cost of environmental damage or the benefit of quicker
and easier travel to work.
A more sophisticated approach to building a cost benefit models is to try to put a financial value on intangible costs
and benefits. This can be highly subjective - is, for example, a historic water meadow worth $25,000, or is it worth $500,000
because if its environmental importance? What is the value of stress-free travel to work in the morning?
These are all questions that people have to answer, and answers that people have to defend.
The version of the cost benefit approach we explain here is necessarily simple. Where large sums of money are involved
(for example, in financial market transactions), project evaluation can become an extremely complex and sophisticated art.
VIII. DECISION ANALYSIS
1. Why Study Decision Analysis?
The obvious reason for studying decision analysis is that carefully applying its techniques can lead to better decisions.
But what is a good decision? A simple answer might be that it is one that gives the best outcome. This answer, however, confuses
the idea of a lucky outcome with a good decision. Suppose that you are interested in investing an inheritance. After carefully
considering all options available and consulting with investment specialists and financial planners, you decide to invest
in stocks. If you purchased a portfolio of stocks in 1982, the investment most likely turned out to be a good one, because
stocks values increased dramatically during 1980s. On the other hand, if your stock purchase had been in early 1929, the stock
market crash and the following depression would have decreased the value of your portfolio drastically.
Was the investment decision a good one? It certainly could have been if it was made after careful consideration of the
available information and thorough deliberation about the goals and possible outcomes. Was the outcome a good one? For the
1929 investor, the answer is no. This example illustrates the difference between a good decision and a lucky outcome: You
can make a good decision but still have an unlucky outcome. Of course, you may prefer to have lucky outcomes rather than make
good decisions! Although decision analysis cannot improve your luck, it can help you to understand better the problems you
face and thus make better decisions. That understanding must include the structure of the problem as well as the uncertainty
and trade-offs inherent in the alternatives and outcomes. You may then improve your chances of enjoying a better outcome;
more important, you will be less likely to experience unpleasant surprises in the form of unlucky outcomes that were either
unforeseen or not fully understood. In other words, you will be making a decision with your eyes open.
The preceding discussion suggests that decision analysis allows people to make effective decisions more consistently.
This idea itself deserves discussion. Decision analysis is intended to help people deal with difficult decisions. It is a
prescriptive approach designed for normally intelligent people who want to think hard and systematically about some important
real problems according to experts.
This prescriptive view is the most appropriate way to think about decision analysis. It gets across the idea that although
we are not perfect makers, we can do better through more structure and guidance. We will see that decision analysis is not
an idealized theory for super rational and omniscient beings. Nor does it describe how people actually make decisions. In
fact, sufficient experimental evidence from psychology shows that people generally do not process information and make decisions
in ways that are consistent with the decision-analysis approach. (If they did, then there would be no need for decision analysis;
why spend a lot of time studying decision analysis if it suggest that you do what you already do?) Instead, using some fundamental
principles, and informed by what we know about human frailties in judgment and decision making, decision analysis offers guidance
to normal people working on hard decisions.
Although decision analysis provides structure and guidance for systematic thinking in difficult situations, it does not
claim to recommend an alternative that must be blindly accepted. Indeed, after the hard thinking that decision analysis fosters,
there should be no need for blind acceptance; the decision maker should understand the situation thoroughly. Instead of providing
solutions, decision analysis is perhaps best thought of as simply an information source, providing insight about the situation,
uncertainty, objectives, and trade-offs, and possibly yielding a recommended course of action. Thus, decision analysis does
not usurp the decision maker's job. According to another author,The basic presumption of decision analysis is not at all to
replace the decision maker's intuition, to relieve him or her of the obligations in facing the problem, or to be, worst of
all, a competitor to the decision maker's personal style of analysis, but to complement, augment, and generally work alongside
the decision maker in exemplifying the nature of the problem. Ultimately, it is of most value if the decision maker has actually
learned something about the problem and his or her own decision-making attitude through the exercise.We have been discussing
decision analysis as if it were always used to help an individual make a decision. Indeed, this is what it is designed for,
but its techniques have many other uses. For example, one might use decision-analysis methods to solve complicated inference
problems (that is, answering questions such as: What conclusions can be drawn from available evidence?. Structuring a decision
problem may be useful for understanding its precise nature, for generating alternative courses of action, and for identifying
important objectives and trade-offs. Understanding trade-offs can be crucial for making progress in negotiations settings.
Finally, decision analysis can be used to justify why a previously chosen judgment was appropriate.
Subjective Judgments and Decision Making
Personal judgments about uncertainty and values are important inputs for decision analysis. It will become clear through
this module that discovering and developing these judgments involves thinking hard and systematically about important aspects
Managers and policy makers frequently complain that analytical procedures from management science and operations research
ignore subjective judgments. Such procedures often claim to generate optimal actions on the basis of purely objective inputs.
But the decision-analysis approach allows the inclusion of subjective judgments. In fact, decision analysis requires personal
judgments; they are important ingredients for making good decisions.
At the same time, it is important to realize that human beings are imperfect information processors. Personal insights
about uncertainty and preferences can be both limited and misleading, even while the individual making the judgments may demonstrate
an amazing overconfidence. An awareness of human cognitive limitations is critical in developing the necessary judgmental
inputs, and a decision maker who ignores these problems can magnify rather than adjust for human frailties. Much current psychological
research has a direct bearing on the practice of decision-analysis techniques.
2. The Decision-Analysis Process
The first step is for the decision maker to identify the decision situation and to understand his or her objectives in
that situation. Although we usually do not have trouble finding decisions to make or problems to solve, we do sometimes have
trouble identifying the exact problem, and thus, we sometimes treat the wrong problem. Such a mistake has been called an error
of the third kind.Careful identification of the decision at hand is always important. For example, perhaps a surface problem
hides the real issue.
Understanding one's objectives in a decision situation is also important first step and involves some introspection. What
is important? What are the objectives? Minimizing cost? Maximizing profit or market share? What about minimizing risks? Does
risk mean the chance of monetary loss, or does it refer to conditions potentially damaging to health and the environment?
Getting a clear understanding of the crucial objectives in a decision situation must be done before much more can be accomplished.
In the next step, knowledge of objectives can help in identifying the alternatives, and beyond that the objectives indicate
how outcomes must be measured and what kinds of uncertainties should be considered in the analysis.
Many authors argue that the first thing to do is to identify the problem and then to figure out the appropriate objectives
to be used in addressing the problem. Others argue the opposite; it is far better, they claim, to spend a lot of effort understanding
one's central values and objectives, and then looking for ways decision opportunities to achieve those objectives. The debate
notwithstanding, the fact is that decisions come in many forms. Sometimes we are lucky enough to shape our decision-making
future in the way the latter suggests, and other times we find ourselves in difficult situations that we may not have anticipated.
In either case, establishing the precise nature of the decision situation (which we will later call the decision context)
goes hand in hand with identifying and understanding one's objectives in that situation.
With the decision situation and pertinent objectives established, we turn to discovery and creation of alternatives. Often
a careful examination and analysis of objectives can reveal alternatives that were not obvious at the outset. This is an important
benefit of a decision-analysis approach. In addition, research in the area of creativity has led to a number of techniques
that can improve the chance of finding new alternatives.
The next two steps, are called modeling and solution. Much of this module will focus in decomposing problems to understand
their structures and measure uncertainty and value; indeed, decomposition is the key to decision analysis. The approach is
to divide and conquer. The first level of decomposition calls for structuring the problem in smaller and more manageable pieces.
Subsequent decomposition by the decision maker may entail careful consideration of elements of uncertainty in different parts
of the problem or careful thought about different aspects of the objectives.
The idea of modeling is critical in decision analysis, as it is in most quantitative or analytical approaches to problems.
We will use influence diagrams or decision trees to create a representation or model on the decision problem. Hierarchical
and network models will be used to understand the relationships among multiple objectives, and we will assess utility functions
in order to model the way in which decision makers value different outcomes and trade off competing objectives. These models
are mathematical and graphical in nature, allowing one to find insights that may not be apparent on the surface. Of course,
a key advantage from decision-making perspective is that the mathematical representation of a decision can be subjected to
analysis, which can indicate a preferred alternative.
Decision analysis is typically an repetitive process. Once a model has been built, sensitivity analysis is performed.
Such analysis answers what if questions:If we make a slight change in one or more aspects of the model, does the optimal decision
change? If so, the decision is said to be sensitive to these small changes, and the decision maker may wish to reconsider
more carefully those aspects to which the decision is sensitive. Virtually any part of a decision is fair game for sensitivity
analysis. New alternatives may be identified, the model structure may change, and the models of uncertainty and preferences
may need to be refined. The term decision-analysis cycle best describes the overall process, which may go through several
iterations before a satisfactory solution is found.
In this repetitive process, the decision maker's perception of the problem changes, beliefs about the likelihood of various
uncertain eventualities may develop and change, and preferences for outcomes not previously considered may mature as more
time is spent in reflection. Decision analysis not only provides a structured way to think about decisions, but also more
fundamentally provides a structure within which a decision maker can develop beliefs and feelings, those subjective judgments
that are critical for a good solution.
3. Requisite Decision Models
In the early 1980s, the term requisite decision modeling was introduced. This marvelous term captures the essence of the
modeling process in decision analysis. In the proponent's words,a model can be considered requisite only when no new intuitions
emerge about the problem, or when it contains everything that is essential for solving the problem. That is, a model is a
requisite when the decision maker's thoughts about the problem, beliefs regarding uncertainty, and preferences are fully developed.
For example, consider a first-time mutual-fund investor who finds high, over-all long-term returns appealing. Imagine, though,
that in the process in researching the funds the investor begins to understand and become wary of highly volatile stocks and
mutual funds. For this investor, a decision model selected a fund by maximizing the average return in the long run would not
be requisite. A requisite model would have to incorporate a trade-off between the long-term returns and volatility.
A careful decision maker may cycle through the process shown in Figure 13.1 several times as the analysis is refined.
Sensitivity analysis at appropriate times can help the decision maker choose the next modeling steps to take in developing
a requisite model. Successful decision analysts artistically use sensitivity analysis to manage the iterative development
of a decision model. An important goal of this book is that you begin to acquire this artistic ability through familiarity
and practice with the concepts and tools of decision analysis.
4. Where Is Decision Analysis Used?
Decision analysis is widely used in business and government decision making. Perusing the literature reveals the applications
that include managing research-and-development programs, negotiating for oil and gas leases, forecasting sales for new products,
understanding the world oil market, deciding whether to launch a new product or new venture, and developing ways to respond
to environmental risks, to name a few. And some of the largest firms make use of decision analysis. A particularly important
arena for decision-analysis applications has been in public utilities, especially electric power generation. In part this
is because the problem utilities face (e.g., site selection, power generation methods, waste cleanup and storage, pollution
control) are particularly appropriate for treatment with decision-analysis techniques; they involve long time frames and hence
a high degree of uncertainty. In addition, multiple objectives must be considered when a decision affects many different stakeholders
In the literature, many of the reported applications relate to public-policy problems and relatively few to commercial
decisions, partly because public-policy problems are interest to such a wide audience. It is perhaps more closely related
to the fact that commercial applications often are proprietary; a good decision analysis can create a competitive advantage
of the firm, which may not appreciate having its advantage revealed in the open literature. Important public-policy applications
have included regulation in the energy (especially nuclear) industry and standard setting in a variety of different situations
ranging from regulations for air and water pollution to standards for safety features on new cars.
Another important area of application for decision analysis has been in medicine. Decision analysis has helped doctors
make specific diagnoses and individuals to understand the risks of different treatments. Institutional-level studies have
been done such as studying the optimal inventory or usage of blood bank or the decision of a firm regarding different kinds
of medical insurance to provide its employees. On a grander scale, studies have examined policies such as a widespread testing
for various forms of cancer or the impact on society of different treatment recommendations.
This discussion is by no means exhaustive; the intent is only to give you a feel for the breadth of possible applications
of decision analysis and a glimpse at some of the things that have been done. Many other applications are describe in cases
and examples throughout the book; by the time you have finished, you should have a good understanding of how decision analysis
can be (and is) used in many different arenas.
Because making decisions involves a degree of risk, it would be helpful to examine risk and risk analysis in this chapter
in order to gain an understanding of what is involved. Risk and uncertainty create anxiety, yet they are necessary components
of an active life.
General Comments on Risk Taking
1. Only the risk takers are truly free. All decisions of consequence involve risk. Without taking risks, you cannot grow
or improve or even live.
2. There is really no such thing as permanent security in anything on earth. Not taking risks is really not more secure
than taking them, for your present state can always be changed without action on your part. If you don't take the risk of
dying by driving to the store, your house could collapse on you and kill you anyway.
3. You are supposed to be afraid when you risk. Admit your fears--of loss, of rejection, of failure.
4. Risking normally involves a degree of separation anxiety--the anxiety you feel whenever you are removed from something
that makes you feel secure. Many children feel this when they first leave their parents for school. Some college students
feel this when they go off to college. Travelers sometimes feel it when they get homesick. The way to overcome separation
anxiety is to build a bridge between the familiar and secure and the new. Find out what the new place--school or country--is
like and how its elements compare to familiar and secure things at home. Take familiar things with you--books, teddy bear,
popcorn popper, whatever.
Advice on Risking
1. Decide whether the risk is necessary or desirable. Spend some careful thought before acting, so that you will not end
up taking unnecessary risks.
2. Risk for the right reasons and when you are calm and thoughtful. Don't take a risk because you are angry, hurt, depressed,
desperate, or frightened. Don't take risks just to get revenge or to harm someone else. Don't risk when you are incapable
of rational thought.
3. Have a goal. When you take a risk, have a clear purpose in mind so that you will know, after the fact, whether you
succeeded or not. What will taking the risk accomplish?
4. Determine the possible loss as well as the gain. That is, know exactly what the consequences of failure will be. Unless
you know pretty accurately what both loss and gain will be, you do not understand the risk. There is a tendency either to
underestimate or to overestimate the consequences of risk. Underestimation can result in surprising damage, cost, setbacks,
pain, whatever. But overestimation is just as problematic, because it can keep us from taking the risks we should be taking.
Many times, upon reflection, the worst case event of a failed risk is much less harmful or negative that we originally believed.
It's a good idea in fact to list all the good expected effects of a successful outcome and all the bad expected effects
of an unsuccessful outcome.
5. Try to make an accurate estimate about the probability of each case. Is the probability of success one in two, one
in ten, one in a hundred, one in a million? This can be sometimes difficult to do, but usually you can guess the probability
within an order of magnitude.
6. When possible, take one risk at a time. Divide your actions or goals wherever possible so that you are not combining
risks unless absolutely necessary. Simultaneous risking increases anxiety, creates confusion, and makes failure analysis very
7. Use imaging or role playing to work through the various possibilities, successes and failures, so that you will be
mentally prepared for any outcome. Think about what can go right and what can go wrong and how you will respond to or adjust
to each possibility.
8. Use a plan. Set up a timetable with a list of steps to take. Use the plan as a guideline, but be flexible.
9. Act decisively. When you have evaluated the risk and decided that it's worth it, act. Go for it. Don't hesitate at
the threshold or halfway through. Once you get going, be courageous. Grit your teeth and move forward. Don't procrastinate
and don't act half heartedly.
10. Don't expect complete success. You may get it, of course, but chances are the result of your risk will not be exactly
what you had imagined and there will be more a degree of success than absolute success or failure.
Risk Management Strategies
In order of precedence, the strategies are:
1. Dismiss extremely remote or unrealistic possibilities. For example, in the decision, Shall I go to the store? there
are risks like dying on the freeway, being shot by robbers, buying poisoned food, and so forth, but these should not normally
enter into the risk evaluation because they are highly if not extremely improbable. Remember that all life is accompanied
by risk. Ten thousand television sets catch fire each year, a hundred thousand people walk through plate glass each year,
125,000 do-it-yourselfers injure themselves with power tools each year, 70,000 children are injured by toys each year, ten
thousand people are poisoned by aspirin each year. But what are we willing to give up? Some of these are not really remote,
but we are willing to take the risk. E.g. automobile deaths. 1 chance in 4000 each year of dying.
And of course whenever you trust someone, you risk betrayal; when you open yourself, you risk exploitation or ridicule;
whenever you hand over a dollar, you risk being defrauded.
2. Insofar as possible, avoid catastrophes. If there is a small but significant chance for catastrophe, then the regular
expected value calculations may not apply.
A major principle of risk management is to avoid any real risk of catastrophe at any reasonable cost. The difficulty of
applying this principle comes from the uncertainty of what is a real risk and what is a reasonable cost.
3. Recognize the tradeoffs. Remember that every action of life has some risk to it. Even when we don't take the risk upon
ourselves, risk is often put upon us by the nature of life and society. Eating you risk food poisoning or choking, but you
have to eat or you'll die. Socializing you risk disease, driving or flying you risk crashing, but in some sense you have to
socialize and travel. Lying in the sun you risk skin cancer; smoking you risk lung cancer; eating French fries you risk heart
Don't deny the risks involved in living and don't worry excessively about the consequences of modern life.
4. Maximize Expected Values. Normally, the expected value of each alternative shows its relative preferability. That is,
you are opting for the greatest probability of the greatest good. Remember, though, that these calculations are guides, and
are based on what may be very subjective probabilities and rewards. You are not "required by law" to choose any
particular alternative. If you believe that the alternative with the highest EV is a poor choice, you should reconsider the
probabilities and rewards you have assigned to all the alternatives.
Decision Support System