52310542 decision theory

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Assignment No.2

Quantitative Techniques

(5564)

Col MBA/MPA

DECISION THEORY

Fayyaz Ahmed Kayani

Roll No. AD593483

Semester: Autumn 2009

F a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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ACKNOWLEDGEMENT

No one writes alone. So I would like to thanks all those who

helped and assisted a great source in completion of

assignment. Assigned topic was a new for me and it was not

possible to accomplish it without their magnificent support.

They have been a source of knowledge for me as they helped

me much in understanding the assigned Topic. I especially

thank to my honorable tutor who guided me in every juncture. I

also pay my gratitude to Department of Business

Administration, AIOU, Islamabad for their marvelous selection

of issues for MBA students through which they are gaining

treasure of knowledge after completion of given task for their

future.

DECISION THEORYF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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INTRODUCTION

Every day we, are humans, make many decisions; and occasionally we make an

important decision that can have immediate and/or long-term effects on our lives.

Such decisions as where to attend school, whether to rent or buy, whether your

company should accept a merger proposal, and so on, are important decisions for

which we would prefer to make correct choice.

The success or failure that an individual or organization experiences, depends

to a large extent on the ability of making appropriate decisions. Making of a decision

requires an enumeration of feasible and viable alternatives (courses of action or

strategies), the projection of consequences associated with different alternatives,

and the measure of effectiveness (or an objective) to identify best alternative to be

used.

Everyone engages in the process of making decisions on a daily basis. Some of

these decisions are quite easy to make and almost automatic. Other decisions can be

very difficult to make and almost debilitating. Likewise, the information needed to

make a good decision varies greatly. Some decisions require a great deal of

information whereas others much less. Sometimes there is not much if any

information available and hence the decision becomes intuitive, if not just a guess.

Many, if not most, people make decisions without ever truly analyzing the situation

and the alternatives that exist. There is a subjective and intrinsic aspect to all

decision making, but there are also systematic ways to think about problems to help

make decisions easier. The purpose of decision analysis is to develop techniques to

aid the process of decision making, not replace the decision maker.

Earlier, the decisions were taken subjectively based on the skill, experience

and intuition of the decision maker. But in todays world of dynamism, the decision

making has become very complex, particularly in business, marketing and

management because they involve a number of interactive variables (factors) whose

values and relationships cannot be determined accurately. In such situations, mere

intuition and expertise of the decision maker are inadequate and we require well

considered judgment and analysis based on the use of several quantitative techniques

and even computers in solving problems. It is in this context that we need a full-


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fledged decision theory which provides a sound and scientific basis for improved

decision making.

Decision making is the essence of management. In general, the process of

making decisions calls for (i) identifying the alternatives, (ii) gathering all the

relevant information about them, and (iii) selecting the best alternative on the

basis of some criterion.The decision theory, also called the decision analysis, is used to determine

optimal strategies where a decision-maker is faced with several decision alternatives

and an uncertain, or risky, pattern of future events. To recapitulate, all decision-

making situations are characterized by the fact that two or more alternative courses

of action are available to the decision-maker to choose from. Further, a decision may

be defined as the selection by the decision-maker of an act, considered to be best

according to some pre-designated standard, from among the available options.

When analyzing the decision making process, the context or environment of the

decision to be made allows for a categorization of the decisions based on the nature

of the problem or the nature of the data or both. There are two broad categories of

decision problems: decision making under certainty and decision making under

uncertainty.

THEORETICAL QUESTIONS ABOUT DECISIONS

The following are examples of decisions and of theoretical problems that they give

rise to.

Shall I bring the umbrella today? The decision depends on something which I do not

know, namely whether it will rain or not.

I am looking for a house to buy. Shall I buy this one? This house looks fine, but

perhaps I will find a still better house for the same price if I go on searching. When

shall I stop the search procedure?

Am I going to smoke the next cigarette? One single cigarette is no problem, but if I

make the same decision sufficiently many times it may kill me.

The court has to decide whether the defendant is guilty or not. There are two

mistakes that the court can make, namely to convict an innocent person and to acquit

a guilty person. What principles should the court apply if it considers the first of these

mistakes to be more serious than the second?


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A committee has to make a decision, but its members have different opinions.

What rules should they use to ensure that they can reach a conclusion even if they are

in disagreement? Almost everything that a human being does involves decisions.

Therefore, to theorize about decisions is almost the same as to theorize about human

activities. However, decision theory is not quite as all-embracing as that. It focuses

on only some aspects of human activity. In particular, it focuses on how we use ourfreedom. In the situations treated by decision theorists, there are options to choose

between, and we choose in a non-random way.

Our choices, in these situations, are goal-directed activities. Hence, decision

theory is concerned with goal-directed behaviour in the presence of options.

A Truly Interdisciplinary Subject

Modern decision theory has developed since the middle of the 20th

century throughcontributions from several academic disciplines. Although it is now clearly an

academic subject of its own right, decision theory is typically pursued by researchers

who identify themselves as economists, statisticians, psychologists, political and

social scientists or philosophers. There is some division of labour between these

disciplines. A political scientist is likely to study voting rules and other aspects of

collective decision-making. A psychologist is likely to study the behaviour of

individuals in decisions, and a philosopher the requirements for rationality in

decisions. However, there is a large overlap, and the subject has gained from the

variety of methods that researchers with different backgrounds have applied to the

same or similar problems.

Normative and Descriptive Theories

The distinction between normative and descriptive decision theories is, in principle,

very simple. A normative decision theory is a theory about how decisions should be

made, and a descriptive theory is a theory about how decisions are actually made.

The should in the foregoing sentence can be interpreted in many ways. There is,

however, virtually complete agreement among decision scientists that it refers to the

prerequisites of rational decision-making. In other words, a normative decision theory

is a theory about how decisions should be made in order to be rational. This is a very

limited sense of the word normative. Norms of rationality are by no means the only


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or even the most important norms that one may wish to apply in decision-making.

However, it is practice to regard norms other than rationality norms as external to

decision theory. Decision theory does not, according to the received opinion, enter

the scene until the ethical or political norms are already fixed. It takes care of those

normative issues that remain even after the goals have been fixed. This remainder of

normative issues consists to a large part of questions about how to act in when thereis uncertainty and lack of information. It also contains issues about how an individual

can coordinate her decisions over time and of how several individuals can coordinate

their decisions in social decision procedures.

If the general wants to win the war, the decision theorist tries to tell him how to

achieve this goal. The question whether he should at all try to win the war is not

typically regarded as a decision-theoretical issue. Similarly, decision theory provides

methods for a business executive to maximize profits and for an environmentalagency to minimize toxic exposure, but the basic question whether they should try to

do these things is not treated in decision theory.

Although the scope of the normative is very limited in decision theory, the

distinction between normative (i.e. rationality-normative) and descriptive

interpretations of decision theories is often blurred. It is not uncommon, when you

read decision-theoretical literature, to find examples of disturbing ambiguities and

even confusions between normative and descriptive interpretations of one and thesame theory. Probably, many of these ambiguities could have been avoided. It must

be conceded, however, that it is more difficult in decision science than in many other

disciplines to draw a sharp line between normative and descriptive interpretations.

This can be clearly seen from consideration of what constitutes a falsification of a

decision theory. It is fairly obvious what the criterion should be for the falsification

of a descriptive decision theory.

ELEMENTS OF DECISION MAKINGDecision Maker: The entity responsible for making the decision. This may be a single

person, a committee, company, and the like. It is viewed here as a single entity, not

a group.

Alternatives: A finite number of possible decision alternatives or courses of action

available to the decision maker. The decision maker generally has control over the


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specification and description of the alternatives. These alternatives are also called

courses of action (actions, acts or strategies) and are known to the decision-maker.

States of Nature: The scenarios or states of the environment that may occur but are

not under control of the decision maker. These are the circumstances under which a

decision is made. The states of nature are mutually exclusive events and exhaustive.

This means that one and only one state of nature is assumed to occur and that all

possible states are considered.

Payoff or Outcome: Outcomes are the measures of net benefit, or payoff, received

by the decision maker. This payoff is the result of the decision and the state of

nature. Hence, there is a payoff for each alternative and outcome pair. The measures

of payoff should be indicative of the decisions makers values or preferences. The

payoffs are generally given in a payoff matrix in which a positive value represents net

revenue, income, or profit and a negative value represents net loss, expenses, or

costs. This matrix yields all alternative and outcome combinations and their

respective payoff and is used to represent the decision problem.

General form of payoff matrix

1 2 n

1

2

Courses of Action

(Alternatives)

States of Nature Probability S S S

N

N

L

1 11 12 1n

2 21 22 2n

m m m1 m 2 mn

p p p p

p p p p

N p p p p

L

L

M M M M L M

L

STEPS OF DECISION MAKING PROCESS

The decision making process involves the following steps:

1. Identify and define the problem.

2. Listing of all possible future events, called states of nature, which can occur in

the context of the decision problem. Such events are not under the control of

decision-maker because these are erratic in nature.

3. Identification of all the courses of action (alternatives or decision choices)

which are available to the decision-maker. The decision-maker has control over

these courses of action.


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4. Expressing the payoffs resulting from each pair of course of action and state of

nature. These payoffs are normally expressed in a monetary value.

5. Apply an appropriate mathematical decision theory model to select best course

of action from the given list on the basis of some criterion (measure of

effectiveness) that results in the optimal (desired) payoff.

TYPES OF DECISION-MAKING ENVIRONMENTSTo arrive at a good decision it is required to consider all available data, an exhaustive

list of alternatives, knowledge of decision environment, and use of appropriate

quantitative approach for decision-making. In this section four types of decision-

making environments: Certainty, uncertainty, risk and conflict have been described.

The knowledge of these environments helps in choosing appropriate quantitative

approach for decision-making.

Type 1 - Decision-Making under Certainty

The process of choosing an act or strategy when the state of nature is completely

known is called decision making under certainty. The decision-maker has the

complete knowledge (perfect information) of consequence of every decision choice

(course of action or alternative) with certainty. Obviously, he will select an

alternative that yields the largest return (payoff) for the known future (state of

nature). In such situation, each act will only result in one event and the outcome of

the act can be predetermined with certainty. Hence, such situations are also termed

as deterministic situations. For example, the decision to purchase either National

Saving Certificate (NSC); or deposit in National Saving Scheme is one in which it is

reasonable to assume complete information about the future because there is no

doubt that the Pakistani government will pay the interest when it is due and the

principal at maturity. In this decision-model, only one possible state of nature

(future) exists.

Type 2 - Decision-Making under Risk

In this case the decision-maker has less than complete knowledge with certainty ofthe consequence of every decision choice (course of action) because it is not

definitely known which outcome will occur. This means there is more than one state

of nature (future) and for which he makes an assumption of the probability with

which each state of nature will occur. For example, probability of getting head in the

toss of a coin is 0.5. Decision-making under risk is a probabilistic decision situation, in

which more than one state of nature exists and the decision-maker has sufficientF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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information to assign probability values to the likely occurrence of each of these

states. The probabilities of various outcomes may be determined objectively from the

past data. Knowing the probability distribution of the states of nature, the best

decision is to select that course of action which has the largest expected payoff

value. The expected (average) payoff of an alternative is the sum of all possible

payoffs of that alternative weighted by the probabilities of those payoffs occurring.However, past records may not be available to arrive at the objective probabilities. In

many cases the decision-maker may, on the basis of his experience and judgment, be

able to assign subjective probabilities to the various outcomes. The problem can then

be solved as decision problem under risk.

Under conditions of risk, the most popular decision criterions for evaluating the

alternative is the expected monetary value/expected opportunity loss of the

expected payoff.

(i) Expected monetary value (EMV)

More generally, the decision-making in situations of risk is on the basis of the

expectation principle, with the event probabilities assigned, objectively or

subjectively as the case may be, the expected pay-off for each strategy is

calculated by multiplying the pay-off values with their respective probabilities

and then adding up these products. The strategy with the highest expected

pay-off represents the optimal choice. It goes without saying that in problems

involving pay-off matrix in terms of costs, optimal strategy is that

corresponding to which the expected value is the least.

(ii) Expected Opportunity Loss (EOL)

An alternative approach to maximizing expected monetary value (EMV) is to

minimize the expected opportunity loss (EOL), also called expected value of

regret. The EOL is defined as the difference between the highest profit (or

payoff) for a state of nature and the actual profit obtained for the particular

course of action taken. In other words, EOL is the amount of payoff that is lostby not selecting the course of action that has the greatest payoff for the state

of nature that actually occurs. The course of action due to which EOL is

minimum, is recommended.

Since EOL is an alternative decision criterion for decision-making under

risk, therefore, the results will always be the same as those obtained by EMV

criterion discussed earlier.F a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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The steps for calculating EOL are summarized as follows:

(a) Prepare a profit (cost) table for each course of action and state of nature

combination along with the associated probabilities.

(b) For each state of nature calculate the opportunity loss (OL) values by

subtracting each payoff from the maximum payoff for that outcome. (For

each state of nature calculate the opportunity loss (OL) values bysubtracting the minimum payoff for that outcome from each payoff.)

(c) Calculate EOL for each course of action by multiplying the probability of

each state of nature with the OL value and then adding the values.

(d) Select a course of action for which the EOL value is minimum.

Expected value of perfect information (EVPI)

The expected profit with perfect information is the expected return, in the

long run, if we have perfect information before a decision is made. The

Expected Value of Perfect Information (EVPI) may be defined as the maximum

amount one would be willing to pay, to acquire perfect information as to which

event would occur. EPPI represents the maximum obtainable EMV with perfect

information as to which event will actually occur (as calculated before

information is received). If EMV represents the maximum obtainable EMV

without perfect information, perfect information would increase expected

profit from EMV up to the value of EPPI, so the amount of that increase would

be equal to EVPI. Thus, we have

EVPI = EPPI EMV

Type 3 - Decision-Making under Uncertainty

In this case the decision-maker is unable to specify the probabilities with which

the various states of nature (futures) will occur. However, this is not the case of

decision-making under ignorance, because the possible states of nature are known.

Thus, decisions under uncertainty are taken even with less information than decisionsunder risk. For example, the probability that Mr. X will be the prime minister of the

country 15 years from now is not known.

The decision situations where there is no way in which the decision-maker can

assess the probabilities of the various states of nature are called decisions under

uncertainty. In such situations, the decision-maker has no idea at all as to which of

the possible states of nature would occur nor has he a reason to believe why a givenF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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state is more, or less, likely to occur as another. With probabilities of the various

outcomes unknown, the actual decisions are based on specific criteria. The several

principles which may be employed for taking decisions in such conditions include (i)

Laplace Criterion, (ii)Maximin or Minimax Criterion, (iii)Maximax or Minimin

Criterion, (iv)Savage Criterion, (v)Hurwicz Criterion (or Criterion of Realism).

Such situations are frequent in business and management. Will the new plant orindustrial unit be successful? Will the new product be able to compete with others in

the market? How much to produce and stock to get maximum returns?

(i) Optimism (Maximax (Profit) or Minimin (Cost)) Criterion

In this criterion the decision-maker ensures that he should not miss the

opportunity to achieve the largest possible profit (maximax) or lowest possible

cost (minimin). Thus, he selects the alternative (decision choice or course of

action) that represents the maximum of the maxima (or minimum of the

minima) payoffs (consequences or outcomes). The working method is

summarized as follows:

(a) Locate the maximum (or minimum) payoff values corresponding to each

alternative (or course of action), then

(b) Select an alternative with best anticipated payoff value (maximum for

profit and minimum for cost).

Since in this criterion the decision-maker selects an alternative with largest (or

lowest) possible payoff value, it is also called an optimistic decision criterion.

(ii) Pessimism (Maximin (Profit) or Minimax (Cost)) Criterion

This principle is adopted by pessimistic decision-makers who are conservative

in their approach. Using this approach, the minimum pay-offs resulting from

adoption of various strategies are considered and among these values the

maximum one is selected. It involves, therefore, choosing the best (the

maximum) profit from the set of worst (the minimum) profits.

When dealing with the costs, the maximum cost associated with eachalternative is considered and the alternative which minimizes this maximum

cost is chosen. In this context, therefore, the principle is used minimax-the

best (the minimum cost) of the worst (the maximum cost).

The working method is summarized as follows:

(a) Locate the minimum (or maximum in case of profit) payoff value in case of

loss (or cost) data corresponding to each alternative, thenF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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(b) Select an alternative with best anticipated payoff value (maximum for

profit and minimum for loss or cost).

Since in this criterion the decision-maker is conservative about the future and

always anticipates worst possible outcome (maximum for profit and minimum

for loss or cost), it is called a pessimistic decision criterion. This criterion is

also known as Walds criterion.(iii) Equal probabilities (Laplace) Criterion

Since the probabilities of states of nature are not known, it is assumed that all

states of nature will occur with equal probability, i.e. each state of nature is

assigned an equal probability. As states of nature are mutually exclusive and

collectively exhaustive, so the probabilities of each of these must be

1

number of states of nature. The working method is summarized as follows:

(a) Assign equal probability value to each state of nature by using the formula:

1

number of states of nature.

(b) Compute the expected (or average) payoff for each alternative (course of

action) by adding all the payoffs and dividing by the number of possible

states of nature or by applying the formula:

(Probability of state of nature j) (Payoff value for the combination of alternative, i

and state of nature j)

(c) Select the best expected payoff value (maximum for profit and minimum

for cost).

This criterion is also known as the criterion of insufficient reason because,

except in a few cases, some information of the likelihood of occurrence of

states of nature is available.

(iv) Coefficient of optimism (Hurwicz) Criterion

This criterion suggests that a rational decision-maker should be neither

completely optimistic nor pessimistic and, therefore must display a mixture of

both. Hurwicz, who suggested this criterion, introduced the idea of a

coefficient of optimism (denoted by ) to measure the decision-makers degree

of optimism. This coefficient lies between 0 and 1, where 0 represents a


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In the case of costs, the principle works like this.

(a) From the given payoff matrix, develop an opportunity loss (or regret)

matrix as follows:

(i) Find the worst payoff corresponding to each state of nature, and

(ii)Subtract all other entries (payoff values) corresponding to each state of

nature from this value.(b) For each course of action (strategy or alternative) identify the best or

minimum regret value. Record this number in a new row.

(c) Select the course of action (alternative) with the greatest anticipated

opportunity loss value.

Type 4 - Decision-Making under Conflict

In many situations, neither states-of-nature are completely known nor are they

completely uncertain. Partial knowledge is available and therefore it may be termed

as decision-making under partial uncertainty. An example of this is the situation of

conflict involving two or more competitors marketing the same product.

Some Examples related to Different Decision-Making Environments

Example 1: A food product company is contemplating the introduction of a

revolutionary new product with new packaging or replace the existing product atmuch higher price (S1) or a moderate change in the composition of the existing

product with a new packaging at a small increase in price (S2) or a small change in the

composition of the existing product except the word New with a negligible increase

in price (S3). The three possible states of nature or events are: (i) high increase in

sales (N1), (ii) no change in sales (N2) and (iii) decrease in sales (N3). The marketing

department of the company worked out the payoffs in terms of yearly net profits forF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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each of the strategies of three events (expected sales). This is represented in the

following table:

States ofNature

Strategies

S1 S2 S3N1 7,00,000 5,00,000 3,00,000

N2 3,00,000 4,50,000 3,00,000

N3 1,50,000 0 3,00,000

Which strategy should the concerned executive choose on the basis of the following?

(a) Maximin criterion (b) Maximax criterion

(c) Minimax regret criterion (d) Laplace criterion

Solution: The payoff matrix is rewritten as follows:

(a) Maximin Criterion

States of Nature Strategies

S1 S2 S3N1 7,00,000 5,00,000 3,00,000

N2 3,00,000 4,50,000 3,00,000N3 1,50,000 0 3,00,000

Column (minimum) 1,50,000 0 3,00,000 MaximinThe maximum of column minima is 3,00,000. Hence, the company should adopt

strategy S3.

(b) Maximax Criterion


S1 S2 S3N1 7,00,000 5,00,000 3,00,000

N2 3,00,000 4,50,000 3,00,000N3 1,50,000 0 3,00,000

Column (maximum) 7,00,000

Maximax

5,00,000 3,00,000

The maximum of column maxima is 7,00,000. Hence, the company should adopt

strategy S1.

(c) Minimax Regret Criterion (opportunity loss in case of profits)

States ofNature

Strategies

S1 S2 S3

N1 7,00,000

7,00,000 =0 7,00,000

5,00,000 =2,00,000 7,00,000

3,00,000 =4,00,000

N2 4,50,000 3,00,000 =1,50,000

4,50,000 4,50,000 =0

4,50,000 3,00,000 =1,50,000

N3 3,00,000 1,50,000 =1,50,000

3,00,000 0 =3,00,000

3,00,000 3,00,000 =0

Column(maximum)

1,50,000

Minimax regret

3,00,000 4,00,000

Hence, the company should adopt minimum opportunity loss strategy, S1.


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(d)Laplace Criterion

Since, we do not know the probabilities of states of nature, assume that they are

equal. For this example, we would assume that each state of nature has a probability

1/3 of occurrence. Thus,

Strategy Expected Return (Rs)

S1 (7,00,000 + 3,00,000 + 1,50,000)/3 = 3,83,333.33

S2 (5,00,000 + 4,50,000 + 0)/3 = 3,16,666.66S3 (3,00,000 + 3,00,000 + 3,00,000)/3 = 3,00,000

Since, the largest expected return is from strategy S1; the executive must select

strategy S1.

Example 2:A Super Bazaar must decide on the level of supplies it must stock to meet

the needs of its customers during Eid days. The exact number of customers is not

known, but it is expected to be in one of the four categories; 300, 350, 400 or 450

customers. Four levels of supplies are thus suggested with level j being ideal (from

the viewpoint of incurred costs) if the number of customers falls in category j.

Deviations from the ideal levels results in additional costs either because extra

supplies are stocked needlessly or because demand cannot be specified. The table

below provides these costs in thousands of rupees.

Customer categorySupplies level

A1 A2 A3 A4E1 7 12 20 27

E2 10 9 10 25E3 23 20 14 23

E4 32 24 21 17

(a) Which level of inventory is chosen on the basis of (i) Laplace criterion (ii) minimax

criterion (iii) minimin criterion?

(b) Now consider payoff matrix as profit matrix then which level of inventory is

chosen on the basis of Hurwicz criterion

Solution: (a) (i) Laplace Criterion

Since, we do not know the probabilities of states of nature, assume that they areequal. For this question, we would assume that each state of nature has a probability

1/4 of occurrence. Thus,

Strategy Expected Return (Rs)

A1 (7 + 10 + 23 + 32)/4 = 18

A2 (12 + 9 + 20 + 24)/4 = 16.25

A3 (20 + 10 + 14 + 21)/4 = 16.25

A4 (27 + 25 + 23 + 17)/4 = 23


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Since, the lowest expected return is from strategy A2 and A3; the executive must

select strategy A2 or A3.

(ii)Minimax Criterion


A1 A2 A3 A4E1 7 12 20 27

E2 10 9 10 25E3 23 20 14 23

E4 32 24 21 17

Column(maximum)

32 24 21

Minimax27

The minimum of column maxima is 21. Hence, the company should adopt strategy A3.

(iii) Minimin Criterion


A1 A2 A3 A4E1 7 12 20 27

E2 10 9 10 25E3 23 20 14 23

E4 32 24 21 17

Column(minimum)

7

Minimin

9 10 17

The minimum of column minima is 7. Hence, the company should adopt strategy A1.

(b) In the context of profit data, Hurwicz Criterion, HC = (Max Value) + (1 ) (Min

Value). Its value for various strategies is as follows:

State ofNature

Profit from optimal Course of Action(thousand Rs)

(1) (2) (3) (4) (5) (6) (7) (8)

A1 A2 A3 A4 Profit (Max incolumns (1, 2,3 & 4))

0.5 x(5)

Profit (Min incolumns (1, 2,3 & 4))

0.5x (7)

(6) +(8)

E1 7 12 20 27 32 16 7 3.5 19.5

E2 10 9 10 25 24 12 9 4.5 16.5

E3 23 20 14 23 21 10.5 10 5 15.5

E4 32 24 21 17 27 13.5 17 8.5 22Since, maximum is 22, so, it is optimal to adopt strategy A4.

Example 3: Al Abbas Ltd has installed a machine costing Rs 4 lacs and is in the

process of deciding on an appropriate number of a certain spare parts required for

repairs. The spare parts cost Rs 4000 each but are available only if they are ordered

now. In case the machine fails and no spares are available, the cost to the companyF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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of mending the plant would be Rs 18000. The plant has an estimated life of 8 years

and the probability distribution of failures during the time, based on experience with

similar machines, is as follows:

No. of failures during 8-yearly period 0 1 2 3 4 5

Probability 0.1 0.2 0.3 0.2 0.1 0.1

Ignoring any discounting for time value of money, determine the following:

(a) The expected number of failures in the 8-year period.

(b) The optimal number of units of the spare part on the basis of Hurwicz principle

(taking =0.7).

(c) EVPI.

Solution: Since the availability of number of spares at the time of the failure of any

machine is under the control of decision-maker, no. of spares per year is considered

as course of action (decision choice) and the no. of failures of machines is uncertain

and only known with probability, therefore, it is considered as a state of nature(event).

Let S be the quantity (number of spares to be available). And F is the no. of failures

within one year. It is given that cost of storing a spare is Rs. 4000. Cost of not storing

the spare is Rs. 18000.

Cost function =4,000S, S F

4,000S + 18000 (F S), S < F

(a) The expected number of failures in the 8 year period, is given by

6

i i

i 1

E(F) p F 0.1 0 0.2 1 0.3 2 0.2 3 0.1 4 0.1 5 2.3=

= = + + + + + =

State ofNature(F)

Probability Cost (thousand Rs) Due to Courseof Action (purchase)

Expected Cost (thousand Rs) Due toCourse of Action

(1) (2) (3) (4) (5) (6) (7) (1) x(2)

(1) x(3)

(1) x(4)

(1) x(5)

(1) x(6)

(1)x(7)

0 1 2 3 4 5 0 1 2 3 4 5

0 0.10 0 4 8 12 16 20 0 0.4 0.8 1.2 1.6 2

1 0.20 18 4 8 12 16 20 3.6 0.8 1.6 2.4 3.2 42 0.30 36 22 8 12 16 20 10.8 6.6 2.4 3.6 4.8 6

3 0.20 54 40 26 12 16 20 10.8 8 5.2 2.4 3.2 4

4 0.10 72 58 44 30 16 20 7.2 5.8 4.4 3 1.6 2

5 0.10 90 76 62 48 34 20 9 7.6 6.2 4.8 3.4 2

Expected Cost (EC) 41.4 29.2 20.6 17.4 17.8 20

(b) In the context of cost data, Hurwicz Criterion, HC = (Min Value) + (1 ) (Max

Value). Its value for various strategies is as follows:

Stateof

Probability Cost (thousand Rs) Due toCourse of Action

Cost from optimal Course ofAction(thousand Rs)


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Nature

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

0 1 2 3 4 5 Cost (Minin columns(2, 3, 5, 6& 7))

0.7x (8)

Cost (Maxin columns(2, 3, 5, 6& 7))

0.3x(10)

(9) +(11)

0 0.05 0 4 8 12 16 20 0 0 90 27 27

1 0.10 18 4 8 12 16 20 4 2.8 76 22.8 25.6

2 0.20 36 22 8 12 16 20 8 5.6 62 18.6 24.2

3 0.30 54 40 26 12 16 20 12 8.4 48 14.4 22.84 0.20 72 58 44 30 16 20 16 11.2 34 10.2 21.4

5 0.15 90 76 62 48 34 20 20 14 20 6 20

Since, minimum is 20, so, it is optimal to keep 5 spare parts.

(c)

State of Nature

Probability Cost (thousand Rs) Due to Course ofAction

Cost from optimal Course ofAction(thousand Rs)

(1) (2) (3) (4) (5) (6) (7) (8) (1) x (8)

0 1 2 3 4 5 Cost (Min in (2, 3,5, 6 & 7))

WeightedCost

0 0.05 0 4 8 12 16 20 0 0

1 0.10 18 4 8 12 16 20 4 0.8

2 0.20 36 22 8 12 16 20 8 2.4

3 0.30 54 40 26 12 16 20 12 2.4

4 0.20 72 58 44 30 16 20 16 1.6

5 0.15 90 76 62 48 34 20 20 2

Expected Cost with Perfect Information (ECPI) 9.2

Now, EVPI = EC* ECPI

= 17.4 9.2

= 8.2 thousand rupees

Example 4:An investor is given the following investment alternatives and percentage

rates of return.Investmentalternatives

State of Nature (Market Conditions)

Low Medium High

Regular Shares 7% 10% 15%

Risky Shares -10% 12% 25%

Property -12% 18% 30%

Over the past 300 days, 150 days have been medium market conditions and 60 days

have had high market increases. On the basis of these data, state the optimum

investment strategy for the investment.

Solution: According to the given information, the probabilities of low, medium and

high market conditions would be 0.30 (300 (150 + 60) = 90/300), 0.50 (150/300) and

0.20 (60/300) respectively. The expected pay-offs for each of the alternatives are

calculated and shown in the table below:

MarketConditions

Probability Profit (Rs) Due to Course ofAction

Expected Payoff (Rs) Due to Courseof Action


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(1) (2) (3) (4) (1) x (2) (1)x (3) (1) x (4)

Regularshares

Riskyshares

Property Regularshares

Riskyshares

Property

Low 0.30 0.07 0.10 0.15 0.021 0.03 0.045

Medium 0.50 0.10 0.12 0.25 0.05 0.06 0.125

High 0.20 0.12 0.18 0.30 0.024 0.036 0.06

Expected monetary value (EMV) 0.053 0.126 0.230

Since the expected return of 23% is the highest for property, the investor shouldinvest in this alternative.

Example 5:A company manufactures goods for a market in which the technology of

the product is changing rapidly. The research and development department has

produced a new product which appears to have potential for commercial exploitation.

A further Rs 60,000 is required for development testing.

The company has 100 customers and each customer might purchase at the most one

unit of the product. Market research suggests that a selling price of Rs 6000 for each

unit with total variable costs of manufacturing and selling estimate are Rs 2,000 for

each unit.

From previous experience, it has been possible to derive a probability distribution

relating to the proportion of customers who will buy the product as follows:

Proportion of customers 0.04 0.08 0.12 0.16 0.20

Probability 0.10 0.10 0.20 0.40 0.20

Determine the expected opportunity losses, given no other information than that

stated above, and state whether or not the company should develop the product.

Solution: If p is the proportion of customers who purchase the new product, the profit

is:

(6,000 2,000) x 100p 60,000 = Rs (4,00,000p 60,000).

Let Ni (I = 1, 2, , 5) be the possible states of nature, i.e. proportion of the customers

who will buy the new product and S1 (develop the product) and S2 (do not develop the

product) be the two courses of action.

The profit values (payoffs) for each pair of N is and Sjs are shown in the following

table:

State of Nature Ni(Proportion ofCustomers, p)

Probability

Profit = Rs(4,00,000p 60,000)Course of Action

Opportunity Loss (Rs) (1) x(2)

(1) x(3)

(1) (2) (3)

S1 S2 S1 S2 S1 S20.04 0.1 44,000 0 0 (44,000) = 44,000 0 0 = 0 4,400 0

0.08 0.1 28,000 0 0 (28,000) = 28,000 0 0 = 0 2,800 0


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0.12 0.2 12,000 0 0 (12,000) = 12,000 0 0 = 0 2,400 0

0.16 0.4 4,000 0 4,000 4,000 = 0 4,000 0 = 4,000 0 1,600

0.20 0.2 20,000 0 20,000 20,000 = 0 20,000 0 = 20,000 0 4,000

Expected Opportunity Loss (EOL) 9,600 5,600

(Note: All the entries of column S2 would be 0. Since, we are not developing anything

then no profit will be earned)

Since, the company seeks to minimize the expected opportunity loss, the company

should select course of action S2 (do not develop the product) with minimum EOL.

Example 6:A retailer purchases cherries every morning at Rs 50 a case and sells them

for Rs 80 a case. Any case remaining unsold at the end of the day can be disposed of

next day at a salvage value of Rs 20 per case (thereafter they have no value). Past

sales have ranged from 15 to 18 cases per day. The following is the record of sales for

the past 120 days:

Cases sold 15 16 17 18Number of days 12 24 48 36

Find how many cases the retailer should purchase per day to maximize his profit.

Solution: Since number of cherries (in cases) purchased is under the control of

decision-maker, purchase per day is considered as course of action (decision choice)

and the daily demand of the cherries is uncertain and only known with probability,

therefore, it is considered as a state of nature (event).

Let P be the quantity (number of cases of cherries to be purchased). And D is the

demand within a day.

Profit = (80-50) P, D>=P

(80-50)D (50-20) (P-D), D < P

The resulting profit values and corresponding expected payoffs are computed in the

following table:

States ofNature D(Demandper week)

Probability Profit (Rs) Due to Courses ofAction P (Purchase per day)

Expected Payoff (Rs) Due to Courses ofAction (Purchase per Day)

15 16 17 18 15 16 17 18

(1) (2) (3) (4) (5) (1)x(2) (1)x(3) (1)x(4) (1)x(5)15 12/120 =

0.1450 420 390 360 45 42 39 36

16 24/120 =0.2

450 480 450 420 90 96 90 84

17 48/120 =0.4

450 480 510 480 180 192 204 192

18 36/120 =0.3

450 480 510 540 135 144 153 162

Expected monetary value (EMV) 450 474 486 474


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Since the highest EMV of Rs 486 is corresponding to course of action 17, the retailer

must purchase 17 cases of cherries every morning.

Example 7:A company needs to increase its production beyond its existing capacity.

It has narrowed the alternatives to two approaches to increase the production

capacity: (a) expansion, at a cost of Rs 8 million, or (b) modernization at a cost of Rs5 million. Both approaches would require the same amount of time for

implementation. Management believes that over the required payback period,

demand will either be high or moderate. Since high demand considered being

somewhat less likely than moderate demand, the probability of high demand has been

set at o.35. If the demand is high, expansion would gross estimated additional Rs 12

million but modernization only additional Rs 6 million, due to lower maximum product

capability. On the other hand, if the demand is moderate, the comparable figures

would be Rs 7 million for expansion and Rs 5 million for modernization.

(a) Calculate the profit in relation to various action and outcome combinations and

states of nature.

(b) If the company wishes to maximize its EMV, should it modernize or expand?

(c) Calculate the EVPI.

(d) Construct the conditional opportunity loss table and also calculate EOL.

Solution: Defining the states of nature: high demand and moderate demand (over

which the company has no control) and courses of action (companys possible

decisions): Expand and Modernize.

Since the probability that the demand is high estimated at 0.35, the probability of

moderate demand must be (1 0.35) = 0.65. The resulting profit values,

corresponding expected payoffs and Expected Opportunity Loss (EOL) values are

computed in the following table:

Stateof

Nature(Demand)

Probabilit

y

Profit (millionRs) Due to

Course of Action

ExpectedPayoff

(million Rs)Due to Courseof Action

Profit fromoptimal Course

ofAction(millionRs)

OpportunityLoss (million

Rs) Due toCourse of Action

(1) x(5)

(1) x(6)

(1) (2) (3) (1) x(2)

(1) x(3)

(4) (1) x(4)

(5) (6)

Expand(S1)

Modernize(S

2)

Expand (S1)

Modernize(S2)

Profit(Max in(2 &3))

WeightedProfit

S1 S2 S1 S2


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HighDemand

(N1)

0.35 12 8 =4

6 5 =1

1.4 0.35 4 1.40 4 4 =0

4 1= 3

0 1.05

ModerateDemand

(N2)

0.65 7 8 =1

5 5 =0

0.65 0 0 0 0(1) =1

0 0= 0

0.65 0

Expected monetary value (EMV) 0.75 0.35Expected Profit with Perfect Information (EPPI) 1.40Expected Opportunity Loss (EOL) 0.65 1.05

(b) Since the highest EMV of Rs 0.75 million is corresponding to course of action

Expand, the company must expand it.

(c) EVPI = EPPI EMV

=1.40 0.75

= Rs. 0.65 Million

(d)Since, the company seeks to minimize the expected opportunity loss (EOL), the

company should select course of action S1 (Expand).

Example 8:A toy manufacturer is considering a project of manufacturing a dancing

doll with three different movement designs. The doll will be sold at an average of Rs

10. The first movement design using gears and levels will provide the lowest tooling

and set up cost of Rs 1,00,000 and Rs 5 per unit of variable cost. A second design with

spring action will have a fixed cost of Rs. 1, 60,000 and variable cost of Rs 4 per unit.

Yet another design with weights and pulleys will have a fixed cost of Rs. 3, 00,000 and

variable cost of Rs 3 per unit. One of the following demand events can occur for the

doll with the probabilities:Demand (units) Probability

Light demand 25,000 0.10

Moderate demand 1,00,000 0.70

Heavy demand 1,50,000 0.20

(a) Construct a payoff table for the above project.

(b) Which is the optimum design?


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(c) How much can be decision-maker afford to pay to obtain perfect information

about the demand?

Solution: Payoff (Profit) = Revenue Cost

= (Selling Price x no. of units demanded) (fixed cost + variable cost)

= (Selling Pricexno. of units demanded)(fixed cost+(no. of units demandedxper unit

cost))

State of

Nature

(Demand)

Probability Profit (Rs) Due to Course of Action Expected Payoff (Rs) Due to Course

of Action

(1) (2) (3) (4) (1) x (2) (1) x (3) (1) x (4)

Gears &

Levels

Spring

Action

Weights &

Pulleys

Gears &

Levels

Spring

Action

Weights &

Pulleys

Light 0.10 25,000 10,000 1,25,000 2,500 1,000 12,500

Moderate 0.70 4,00,000 4,40,000 4,00,000 2,80,000 3,08,000 2,80,000

Heavy 0.20 6,50,000 7,40,000 7,50,000 1,30,000 1,48,000 1,50,000

Expected monetary value (EMV) 4,12,500 4,55,000 4,17,500

Since, EMV is largest for spring action, it must be selected.

State of Nature

(Demand)

Probability Profit (Rs) Due to Course of Action Profit from optimal Course of

Action(Rs)

(1) (2) (3) (4) (4) (1) x (4)Gears &

Levels

Spring

Action

Weights &

Pulleys

Profit (Max in

(2, 3 & 4))

Weighted

Profit

Light 0.10 25,000 10,000 1,25,000 25,000 2,500

Moderate 0.70 4,00,000 4,40,000 4,00,000 4,40,000 3,08,000

Heavy 0.20 6,50,000 7,40,000 7,50,000 7,50,000 1,50,000

Expected Profit with Perfect Information (EPPI) 4,60,500

The maximum amount of money that the decision-maker would be willing to pay to

obtain perfect information regarding demand for the doll will be EVPI = EPPI EMV

=4,60,000 4,55,000 = Rs 5,500

DECISION TREE ANALYSIS

Decision-making problems discussed so far have been limited to a single

decision over one period of time, because the payoffs, states of nature, courses of

action and probabilities associated with the occurrence of states of nature are not

subject to change.


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However, situations may arise when a decision-maker needs to revise his previous

decisions on getting new information and make a sequence of several interrelated

decisions over several future periods. Thus he should consider the whole series of

decisions simultaneously. Such a situation is called a sequential or multi period

decision process.

Decision tree is a network which exhibits graphically the logical relationshipbetween the different parts of the complex decision process. It is a graphic model of

each combination of various acts and states of nature {S i, Aj}; (I = 1, 2, , m; j = 1, 2,

, n) along with their payoffs, the probability distribution of the various states of

nature and the EMV or EOL for each act.

Decision tree is a very effective device in making decisions in various

diversified problems relating to personnel, investment, portfolios, project

management, new project strategies, etc.

Each combination (Si, Aj) is depicted by a distinct path through the decision

tree. An essential feature of the decision tree is that the flow should be from left to

right in a chronological order.

Standard symbols are used in drawing a decision tree.

(i) A square ( ) is used to represent a decision point or decision node at which

the decision maker has to decide about one of the various acts or alternatives

available to him.

(ii) Each act or alternative is shown as a line, representing a branch of the tree

emanating from the square.

(iii) A circle ( ) is used to represent a chance event or chance node at which

various events or states of nature are represented by lines, which depict the

sub-branches of the tree emanating from the circle.

(iv) Each branch of the tree (corresponding to each act or strategy) has as

many sub-branches as the number of events or states of nature.

(v) Along the branches/sub-branches are also shown the probabilities of variousstates of nature and the payoffs for each combination (Si, Aj); I = 1, 2, , m; j =

1, 2, , n along with the EMV or EOL for each act.

(vi) As a branch can sub-branch again, we obtain a tree like structure, which

represents the various steps in a decision problem.

Roll Back Technique of Analyzing a Decision Tree


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27/40

Produc

tX

-30000

ProductY-50000

HighDem

and(0.4)

75000

Medium Demand (0.4)

55000LowDemand(0.2)

35000

HighDem

and(0.3)

100000

Medium Demand (0.4)

80000

LowDemand(0.3)7

Example 2:A businessman has two independent investments A and B available to him

but he lacks the capital to undertake both of them simultaneously. He can choose to

take A first and then stop, or if A is successful then take B, or vice versa. The

probability of success for A is 0.7 while for B it is 0.4. Both investments require aninitial capital outlay of Rs. 2000; and both return nothing if the venture is

unsuccessful. Successful completion of A will return Rs. 3000 (over cost), and

successful completion of B will return Rs. 5,000 (over cost). Draw and evaluate the

decision tree by the roll back technique and determine the best strategy.

Solution:

Net Payoff (Rs.) Expected Payoff (Rs.)75000-30000=45000 450000.4=1800055000-30000=25000 250000.4=1000035000-30000=5000 50000.2=1000Total 29000 (EMV)

100000-50000=50000 500000.3=1500080000-50000=30000 300000.4=1200070000-50000=20000 200000.3=6000Total 33000 (EMV)


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AcceptA

(Cost2

000)

Do Nothing

AcceptB

EMV = 2060

EMV = 1400

Succ

ess

Failure

Stop

EMV = 800

EMV = 1500

(Cost2000)

(0)D1

Succ

ess

Succ

ess

Success

Failu

Failure

Failure

Stop

AcceptA

(Cost2000)

(Cost2000)AcceptB

-2000

(0.3)

3000

(0.7)

5000

(0.4)

-2000

3000(0.7)

5

(0.

-200(0.6

D2

D3

Decision Node Event Probability

(p)

Conditional Payoff (in

Rs.) P

Expected Payoff (Rs.)

p PD3 (i) Accept A Succes

s

0.7 3000 2100

Failure 0.3 -2000 -600

EMV = 1500

(ii) Stop 0

D2 (i) Accept B Succes

s

0.4 5000 2000

Failure 0.6 -2000 -1200

EMV = 800

(ii) Stop 0

D1 (i) Accept A Succes

s

0.7 3000 + 800 = 3800 2660

Failure 0.3 -2000 -600

EMV = 2060

(ii) Accept B Succes 0.4 5000 + 1500 = 6500 2600F a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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s

Failure 0.6 -2000 -1200

EMV = 1400

(iii)Do Nothing 0

From the above table we conclude that the best strategy is to accept investment A

first and if it is successful, then accept the investment B.


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PRACTICAL STUDY OF THE ORGANIZATION

WITH RESPECT OF THE TOPIC

ORGANIZATION: GLAXOSMITHKLINE Pakistan Limited

SYSTEM STUDIED: RISK MANAGEMENT SYSTEM

In GSK, the Risk Management System is used as proactive approach to eliminate /

reduce the potential risks associated with their business. Decision theory is used

extensively in Risk Management System for scoring the risks on the basis of likelihood

and consequences.

Note : This is only the overview of Risk Management System. Original documents

could not be part of assignment due to their confidentiality.


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COMPANY INTRODUCTION

GlaxoSmithKline Pakistan Limited was created on January Ist 2002 through the

merger of SmithKline and French of Pakistan Limited, Beecham Pakistan (Private)

Limited and Glaxo Wellcome (Pakistan) Limited- standing today as the largest

pharmaceutical company in Pakistan.

As leading international pharmaceutical company they make a real difference

to global healthcare and specifically to the developing world. Company believes this is

both an ethical imperative and key to business success. Companies that respond

sensitively and with commitment by changing their business practices to address such

challenges will be the leaders of the future. GSK Pakistan operates mainly in two

industry segments: Pharmaceuticals (prescription drugs and vaccines) and consumer

healthcare (over-the-counter- medicines, oral care and nutritional care).

GSK leads the industry in value, volume and prescription market share.

Company is proud of their consistency and stability in sales, profits and growth. Some

of their key brands include Augmentin, Panadol, Seretide, Betnovate, Zantac and

Calpol in medicine and renowned consumer healthcare brands include Horlicks,

Aquafresh, Macleans and ENO.

In addition, company is also deeply involved with our communities and

undertakes various Corporate Social Responsibility initiatives including working with

the National Commission for Human Development (NCHD) for whom GSK was one of

the largest corporate donors. GSK consider it their responsibility to nurture the

environment we operate in and persevere to extend their support to our community

in every possible way. GSK participates in year round charitable activities which

include organizing medical camps, supporting welfare organizations and donating to /

sponsoring various developmental concerns and hospitals. Furthermore, GSK maintainsstrong partnerships with non-government organizations such as Concern for children,

which is also extremely involved in the design, implementation and replication of

models for the sustainable development of children with specific emphasis on primary

healthcare and education.


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GSKs MISSION STATEMENT

Excited by the constant search for innovation, we at GSK undertake our quest

with the enthusiasm of entrepreneurs we value performance achieved with

integrity. We will attain success as a world class global leader with each and every

one of our people contributing with passion and an unmatched sense of urgency.

Our mission is to improve the quality of human life by enabling people to do more,

feel better and live longer.

Quality is at the heart of everything we do-from the discovery of a molecule to the

development of a medicine.

RISK MANAGEMENT SYSTEM


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Risk management is an essential component of the system of internal control and

governance and is regarded as good management practice throughout GSK. A

systematic, standardized and effective approach to risk management is required in

order to:

Establish a common language and protocols for communicating risks in order to

take right decisions at right time.

Ensure that responsibilities for managing risks are clearly stated, understood

and accepted.

Establish appropriate mechanisms for communication, reporting and escalation

of risks.

Ensure that business objectives are achieved.

SCOPE OF RISK MANAGEMENT PROCESS


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PROCESS STEP ACTIVITIES

Following are the different steps involved in the risk management system:

Establish the Risk Management Organization for the risk assessment area.

Identify, Record and Priorities Scored Risks.

Confirm and Approve Risk Mitigation plans.

Implementation, monitoring and of risk mitigation plans.

Governance and Maintenance.

Figure Risk Management Process

Decision Theorycomes into play when a risk is going to be scored (Analyse the

risks). Risks are scored on the basis of likelihood and consequences.

INFORMATION STRUCTURE IN RISK MANAGEMENT SYSTEMF a y y a z A h m e d K a y a n i R o l l N o . 5 9 3 4 8 3

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A Risk is the basic record.

Risk requirements now split into three components.

Mandated requirements to progress risks through workflow.

A number ofRisk Mitigation Plans may be attached to Risk. A Risk must have at

least one Risk Mitigation Plan.

A number ofAction Plans may be attached to each Risk Mitigation Plan. A Risk

Mitigation Plan must have at least one Action Plan.

The diagram below depicts the structure of a Risk Record.

RISK SCORING

Risk scoring is subjective there is no right or wrong answer it is based on personal

judgment or consensus.

Review the consequence of a risk first and only when this is agreed review the

associated likelihood of the scored consequence.

The subjectivity on assessment of likelihood is inherently higher than that for

consequence and influenced by individual perception, background, and local

objectives a team based approach is always used to reach consensus on

likelihood.

The key requirement for the risk management process is that the significant risks

are identified and managed appropriately the precise scoring is a secondary

consideration.

It is essential that risks assessment area are consistently scored and prioritized and

a group view is required by the Quality management process to avoid personal bias

in scoring.

The scoring supports the prioritization of risks but, even then, judgment is

required where several risks all have the same score and decisions are required in

terms of resource allocation.


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The scoring supports the prioritisation of risks but, even then, judgment is

required where several risks all have the same score and decisions are required in

terms of resource allocation.

Comparisons of numbers of risks on aggregation of risk assessment areas are of

little value any analysis and trending should focus on topics and not scores.

Differences in number and ratings of risks across risk assessment areas should be

explored in terms of processes, resources and approach to generate them.

As with risk description, scoring is based on the current environment taking into

account all controls.

A control can impact the consequence or likelihood. A control should be

considered as something which impacts how severe a risk can become and not be

limited to physical controls, written procedures or failsafe controls.

Risks should be assessed and scored from a GSK perspective. Hence, the

consequence and likelihood Matrix has been changed, to focus on the impact of

the Regulators detecting risks e.g. observations.

***************************************************


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RISK MANAGEMENT SYSTEM (HOME PAGE)


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RISK MANAGEMENT SYSTEM

WORKFLOW


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RISK IDENTIFICATION TOOLS

5 Whys

Brainstorming

Surveys

Interviews

FMEA (Failure Mode Effect Analysis)

SWOT (Strengths, Weaknesses, Opportunities & Threats) Analysis

PEST (political, Economic, Socio-Cultural, Technological) Analysis

Kaizen (Continuous Improvement)

GEMBA (Go and See)

Affinity & Fishbone diagrams

Reality Trees

Process flowcharts

Potential Problem Analysis (Kepnor Tregoe)

Benchmarking

Mind maps

IPO


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REFERENCES

1. Quantitative Techniques (AIOU)

2. www.infra.kth.se/~soh/decisiontheory.pdf

3. en.wikipedia.org/wiki/Decision_theory

4. www.answers.com/topic/decision-theory

5. www.mendeley.com/.../decision-theory-a-brief-introduction

6. books.google.com

7. www.stat.tamu.edu/~hart/632/Bayes2

8. www.rapidmore.com/rapidshare.php?...decision+theory...brief+introduction

9. darwin.eeb.uconn.edu/eeb310/lecture.../decision/decision.html

10.www.morehouse.edu/facstaff/ajohnson/ai.../6.825-lecture-19.pdf

11.www.springerlink.com/index/R456425111457PK7.pdf

12.www.cse.unr.edu/~bebis/CS679/Handouts/DHS2.11Revised.pdf

13.www.envisionsoftware.com/.../Normative_Decision_Making_Theory.html

14.economics.stanford.edu/.../normative-decision-theory

15.home.ubalt.edu/ntsbarsh/opre640a/partix.htm

16.www.mindtools.com Decision Making

17.www.businessdictionary.com/definition/decision-theory.html

18.encyclopedia2.thefreedictionary.com/decision+theory

19.Lectures delivered by worthy Tutors in the class
http://www.infra.kth.se/~soh/decisiontheory.pdfhttp://www.answers.com/topic/decision-theoryhttp://www.mendeley.com/.../decision-theory-a-brief-introductionhttp://www.stat.tamu.edu/~hart/632/Bayes2http://www.rapidmore.com/rapidshare.php?...decision+theory...brief+introductionhttp://www.morehouse.edu/facstaff/ajohnson/ai.../6.825-lecture-19.pdfhttp://www.springerlink.com/index/R456425111457PK7.pdfhttp://www.cse.unr.edu/~bebis/CS679/Handouts/DHS2.11Revised.pdfhttp://www.envisionsoftware.com/.../Normative_Decision_Making_Theory.htmlhttp://home.ubalt.edu/ntsbarsh/opre640a/partix.htmhttp://www.google.com/url?url=http://www.mindtools.com/pages/main/newMN_TED.htm&rct=j&ei=3mXeS4DwJYv80wSVyZHIBw&sa=X&oi=breadcrumbs&resnum=10&ct=result&cd=1&ved=0CCsQ6QUoAA&q=decision+analysis+problems&usg=AFQjCNFP6VJVi1dR1dZYfZLDZFrY6pKi-ghttp://www.businessdictionary.com/definition/decision-theory.htmlhttp://www.infra.kth.se/~soh/decisiontheory.pdfhttp://www.answers.com/topic/decision-theoryhttp://www.mendeley.com/.../decision-theory-a-brief-introductionhttp://www.stat.tamu.edu/~hart/632/Bayes2http://www.rapidmore.com/rapidshare.php?...decision+theory...brief+introductionhttp://www.morehouse.edu/facstaff/ajohnson/ai.../6.825-lecture-19.pdfhttp://www.springerlink.com/index/R456425111457PK7.pdfhttp://www.cse.unr.edu/~bebis/CS679/Handouts/DHS2.11Revised.pdfhttp://www.envisionsoftware.com/.../Normative_Decision_Making_Theory.htmlhttp://home.ubalt.edu/ntsbarsh/opre640a/partix.htmhttp://www.google.com/url?url=http://www.mindtools.com/pages/main/newMN_TED.htm&rct=j&ei=3mXeS4DwJYv80wSVyZHIBw&sa=X&oi=breadcrumbs&resnum=10&ct=result&cd=1&ved=0CCsQ6QUoAA&q=decision+analysis+problems&usg=AFQjCNFP6VJVi1dR1dZYfZLDZFrY6pKi-ghttp://www.businessdictionary.com/definition/decision-theory.html

52310542 decision theory

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