RISK CONTROL & MITIGATION

Lesson : Week 4-5

RISK CONTROL

RISK CONTROL is a method by which a company identifies

potential losses and devise strategies to reduce or terminate the
losses.
It is a technique for identifying potential risks in the operation of a
firm, its technical and non-technical aspects.
In order to identify the potential losses, they assess the company’s
assets, loans, and investment which is called Risk Assessment. It’s
an important procedure to determine the worth of an investment and
how to reduce risks.
THE PURPOSE OF CONTROL
MEASURE
The purpose of control measure is to reduce the risk via impact on
likelihood, consequence or magnitude. Example of which may
include, but not limited to the following:
 A prevailing management policy
 Work procedure and practices
 Technical system
 Training program
 Contract management planning guidelines
CONTROL VALUES
Code Description

HE The control happens to be highly effective as it lowers the

(Highly Effective ) chances of the risk-taking place and /or it lessens the
consequences if the risk does strike

ME The control happens to be moderately effective as it only partly

(Moderately Effective ) decreases the odds of the risk transpiring and or somewhat
eases the magnitudes if the risk does occur

IE The control happens to be ineffective as it does not lower the

( Ineffective ) possibility of the risk occurring and /or it does not diminish the
consequences if the risk does not take place.
DEFINING LIKELIHOOD AND CONSEQUENCE.

Analyzing Likelihood /Consequence for Risk Taking.

 Risk analysis is about:
-Determining the likelihood of events
-The magnitude of their consequence and
-The mitigating factors that would reduce the
nature, frequency or damaging effects of the
consequences.
DEFINING LIKELIHOOD AND
CONSEQUENCE
When evaluating likelihood and consequences, you may consider asking
the following usual questions:
-How prone is this risk to occur?
-What will be the circumstances in case it does
happen?
-By and large, what will be the overall risk level?
- Is the risk Acceptable or Unacceptable?
The formula for the risk matrix is clear enough for all to comprehend.

Likelihood + Consequence - Controls in Place =

VULNERABILITY
LIKELIHOOD AND CONSEQUENCE MATRIX
 CONSEQUENCES
LIKELIHOOD Insigni Catas-
Minor Moderate Major
ficant trophic
A
Almost Certain S S H H H
(expected to happen)
B
Likely (probably to M S S H H
occur)
C
Possible (sometimes L M S H H
occur)
D
Unlikely (will/will not L L M S H
happened)
E
Rare (occurred in
L L M S S
exceptional
circumstances)
Unacceptable Risks
 H = a High Risk, Attention, Time and Resources required
 S = a Significant Risk, Attention required.
Acceptable Risks
 M = a Moderate Risk, Monitor
 L = a Low risk, Standard Operating Procedures to handle
 LIKELIHOOD
RANK CATEGORY DESCRIPTION
A
The event is expected to occur
Almost Certain
in most circumstance

B
The event will probably occur
Likely
in most circumstances

C The event should occur at

Possible
some time
D The event could occur at some
Unlikely
time
E
The event may occur only in
Rare
exceptional circumstances
PRIORITY CRITERIA
PRIORITY CRITERIA

a. Grievance to injury and casualty aftermaths

b. Damage to persona, reputation and integrity

c. Damage to private property

d. Damage to structural resources

e. Environmental damage
 CONSEQUENCES

Rank Category Description

1 Insignificant Slight financial deficit, effect of which may only be minor no

brunt on general program or operative sequels; may be
considered as isolated case with very minor impact that
necessitates no adverse external criticism or publicity.

2 Minor There is a small financial loss with corresponding minimal

impact on the overall program or functional outcomes as well as
those directly affected by the situation. There may be criticisms
towards the managers and staff that may affect the overall
morale of the personnel. There is also some level of impact on
the customers.

3 Moderate There is considerable amount of financial loss with significant

bearing on overall program or functional outcomes. A sizable
portion of goods or services maybe damage or tainted resulting
in external criticism directed at the executive and board levels as
well as the key stakeholders .there is a noticeable degree in terms
of change in morale .
CONSEQUENCES
CONSEQUENCES

Rank Category Description

4 Major There is excessive financial loss resulting in
restrained commodities and services
attributable to failure to deliver and with
severe external criticism. Extensive blow in
totality including members’ morale and
performance which maybe trigger increase
in stress related issues.

5 Catastrophic May result in the closure of the

company, removal of an executive from
office, substantial irreversible impact due to
malpractice. Harsh and serious impact in
totality .
 RISK MITIGATION: (RISK MANAGEMENT TOOLS)

 Risk Avoidance or removal is where a circumstance around the risk has been
changed, so the risk no longer exists
 Example:
- Cancellation of project
- pursuing another approach of service distribution
 Risk Reduction is also known as mitigation. This action is taken to lessen the
chance or impact of the risk.
 Example:
- buying generators to back-up in case of power outage
- Buying two different cuisines in case the other is not
delicious.
RISK FINANCING :
Risk Reduction is also known as mitigation. This action is taken to lessen the
chance or impact of the risk.
 Risk Retention or Acceptance of the risk which involves drawing-up a ‘plan
B’ or contingency plan to deal with the impact. Preferred term for self-
insurance.
 Risk Transfer is shifting the risk and the impact to a third party. This means
that the accountability or problem for damage or loss is reallocated to another
party through contractual provision, insurance or other means.
 Example: the presence of contractors and sub-contractors in a project.
Preferred term for self-insurance

Self-insure is a risk management technique in which a company or individual sets aside a pool of
money to be used to remedy an unexpected loss. Theoretically, one can self-insure against any type
of damage (like from flood or fire) In practice, however, most people choose to purchase insurance
against potentially significant, infrequent losses.
Example of the Self-Insure Method
For example, the owners of a building situated atop a hill adjacent to a floodplain may opt against
paying costly annual premiums for flood insurance. Instead, they choose to set aside money for
repairs to the building if in the relatively unlikely event floodwaters rose high enough to damage
their building. If this occurred, the owners would be responsible to pay out-of-pocket for damages
caused by a natural disaster, like a flood.
Pros and Cons of the Self-Insured Method

When a person decides to self-insure, they run the risk of not having enough money to cover damages or
medical care. Experts recommend always carrying a form of automobile insurance, even if you live in the two
states that do not require it (Virginia and New Hampshire), insurance on your home, and medical insurance
for you and your family.

It is possible to carry a bond instead of auto insurance in some states, but you are still financially responsible
if you are in an accident, mainly if you are found at-fault. Paying for insurance is a safety net for you, your
possessions, and your family. If you choose to self-insure, you may save money over the years. The
downside? You must be willing to commit to saving a lot of money to protect yourself from emergencies—such
as fire, floods, accidents, and even death.

In its original form, the Affordable Care Act (ACA) mandated penalties for individuals and small businesses
that were not insured. According to some reports, this led to an increase in the number of self-insured
businesses. Leading insurance companies have also begun offering alternate funding mechanisms for
insurance. For example, one such plan calls for back-up insurance to stem losses from claims. Starting with
the 2019 plan year, people without healthcare insurance do not have to pay a "shared responsibility payment".
MANAGING RISK.
 Risk can be managed with proper discipline. The aim
should be that the firm incorporate risk management as:
 A practice
 A routing
 A way of life
 A way of depending and progressing manners and conducts
 The way the management conceive and executes activities
EVALUATION OF RISK

Evaluation of Risk

Critical Severe Importance Moderate Unimportant Modest

Financial Impact Financial Aspect Financial Impact

-losses that could result -losses that would -losses that could be met
in bankruptcy require resort to credit from existing assets or
cash flow
AREAS & SOURCES OF RISK
FINANCIAL HAZARD
Debt Management Accidents
Fraudulent Acts Unstable People
Accounting & taxation Unsafe Practices
Cash Flow Issues
Fund Raising

AREAS &
SOURCES OF
RISK

LEGAL OPERATIONAL
Contracts Data Assets
Duty of Care Personnel/People
States & Federal Action Consequential
Regulation Special Events
RISK MANAGEMENT STANDARD AS/NZS 4360.
STANDARDS AUSTRALIA AND STANDARDS NEW ZEALAND (2004)
AS/NZS 4360:2004, RISK MANAGEMENT, SYDNEY, NSW
 RISK MEASUREMENT AND
ANALYSIS
(DECISION ENVIRONMENTS)
Alicia N. Sulayon
DECISION ENVIRONMENTS
 The environment in which operations management decisions are
made can be classified according to the degree of certainty present.
There are three basic categories: certainty, risk, and uncertainty.
 Certainty implies that relevant parameters such as costs, capacity,
and demand have known values.
Example:
Profit per unit is $ 5. We have an order for 200 units. How much
profit will we make? (This is an example of certainty since unit of
profits and total demand are known.)
DECISION ENVIRONMENTS

 Consider these situations:

 Risk implies that certain parameters have probabilities outcomes.
Example:
 Profit is $ 5 per unit. Based on previous experience, there is a 50
percent chance of an order for 100 units and a 50 percent chance of
an order for 200 units. What is expected profit? (This is an example
of risk since demand outcomes are probabilistic.)
 Uncertainty implies that it is impossible to assess the
likelihood of various possible future events.

Example:
Profit per unit is $5. The probabilities of potential demands
are unknown. (This is an example of uncertainty.)
DECISION ENVIRONMENTS
 The importance of these three decision environment is that
they require different techniques of analysis. Some
techniques are better suited for one category than for
others. You should make note of the environment for
which each technique is appropriate.
DECISION THEORY
 Decision theory represents a general to decision making. It is suitable for a
wide range of operations management decisions. Among them are capacity
planning, product, and service design, equipment selection, and location
planning. Decisions that lend themselves to a decision theory approach tend to
be characterized by these elements:
 A set of possible future conditions exists that will have a bearing on the results
of the decision.
 The manager has a list of alternatives to choose from.
 There is a known payoff for each alternative under each possible future
condition.
DECISION THEORY
 In order to use this approach, a decision maker would employ this
process:
 Identify the possible future conditions (e.g. demand will be low, medium, or high; the number
of contracts awarded will be one, two, or three; the competitor will introduce a new product,
or the competitor will not introduce a new product). These are called states of nature.
 Develop a list of possible alternatives, one of which may be to do nothing.
 Determine or estimate the payoff associated with each alternative for every
possible future condition.
 If possible, estimate the likelihood of each possible future condition.
 Evaluate alternatives according to some decision criterion (e.g. maximize
expected profit), and select the best alternative.
PAYOFF TABLE
 The information for a decision is often summarized in a payoff table, which shows the
expected payoffs for each alternative under the various possible states of nature. These tables
are helpful in choosing among alternatives because they facilitate comparison of alternatives.
Consider the payoff table below, which illustrates a capacity planning problem.

Possible future demand

Low Moderate High

Alternatives
Small facility $10* $10 $10

Medium facility 7 12 12

Large facility (4) 2 16

DECISION THEORY
 The payoffs are shown in the body of the table. In this instance,
the payoffs are in terms of present values, which represent
equivalent current dollar values of expected future income minus
costs. This is a convenient measure because it places all
alternatives on a comparable basis.
 We see in the table that if a small facility is built, the payoff will be
the same for all three possible states of nature.
 For a medium facility, low demand will have present value of $7
million, whereas both moderate and high demand will have
present values of $12 million. A large facility will have a loss of $4
million if demand is low, a present value of $2 million if demand is
moderate, and a present value of $16 million if demand is high.
DECISION THEORY
 The problem for the decision maker is to select one of the
alternatives, taking the present values into account.
 Evaluation of the alternatives differs depending on the
degree of certainty associated with the possible future
conditions. Again, there are three possibilities to consider:
complete certainty, risk, and uncertainty.
 DECISION THEORY
 Decision Making under Certainty
When it is known which of the possible future conditions will actually happen, the
decision is usually relatively straightforward: Simply choose the alternative that has
the highest payoff under that state of nature.

EXAMPLE 1
Determine the best alternative in the payoff table, if it is known with certainty that
demand will be: (a) low, (b) moderate, (c) high.
Solution
Choose the alternative with the highest payoff. Thus, if we know demand will be
low, we would elect to build the small facility and realize a payoff of $10 million. If we
know demand will be moderate, medium facility would yield the highest payoff ($12
million versus either $10 or $2 million). For high demand, large facility will provide
the highest payoff.
 DECISION THEORY
 Decision Making under Uncertainty
 At the opposite extreme is complete uncertainty: no information is available on how
likely the various states of nature are. Under those conditions, four possible decision
criteria are maximin, maximax, Laplace, and minimax regret. These approaches can be
defined as follows.
 1. Maximin –Determine the worst possible payoff for each alternative, and then
choose the alternative that has the “best worst.”
 2. Maximax –Determine the best possible payoff, and choose the alternative with that
payoff.
 3. Laplace –Determine the average payoff for each alternative, and choose the
alternative with the best average.
 4. Minimax regret –Determine the worst regret for each alternative, and choose the
alternative with the “best worst.”
 The next two examples illustrate these decision criteria.
 Example 2 third row. Hence, the maximax criterion leads
Referring to the payoff table, determine which to building a large facility.
alternative would be chosen under each of these f. For the Laplace criterion, first find the row
strategies. totals, and then divide each of those amounts
a. Maximin by the number of states of nature (three in this
b. Maximax case). Thus, we have
c. Laplace Row total Row
average
Small facility 30 10.00
Solution
d. The worst payoffs for the alternatives are: Medium facility 31 10.33

Small facility $10 million Large facility 14 4.67

Since the
Medium facility $7 million medium
facility has
Large facility ( $4 ) million the highest
Hence, since $10 million is the best, choose to average, it
would be
build the small facility using the maximin strategy. chosen under
e. The best overall payoff is the $16 million in the the Laplace
criterion.
third row. Hence, the maximax criterion leads to
building a large facility.
f. For the Laplace criterion, first find the row totals,
and then divide each of those amounts by the
 The maximin approach is essentially a pessimistic one in
that it takes into account only the worst possible outcome
for each alternative. The actual outcome may not be as bad
as that, but this approach establishes a “guaranteed
minimum.”
 The maximax approach is an optimistic, “go for it”
strategy; it does not take into account any payoff other
than the best.
MINIMAX REGRET APPROACH
Payoff Table -
Possible future demand
Low Moderate High
Alternatives
Small facility
$10* $10 $10

Medium facility
7 12 12

Large facility
(4) 2 16
MINIMAX REGRET APPROACH

Example 3

Determine which alternative would be chosen using a to

the capacity planning problem.
Example 3 (concluded)

Solution
The first step in this approach is to prepare a table of opportunity losses, or regrets. To do this,
subtract every payoff in each column from the largest positive payoff in the column. For instance, in
the first column, the largest positive payoff is 10, so each of the three numbers in that column must be
subtracted from 10. Going down the column, the regrets will be 10 – 10 = 0, 10 – 7 = 3, and 10 – (-4) =
14. In the second column, the largest positive payoff is 12. Subtracting each payoff from 12 yields 2, 0,
and 10. In the third column, 16 is the largest payoff. The regrets are 6, 4, and 0. These results are
summarized in a regret table:

Regrets

Alternatives Low Moderate High Worst

Small facility 0 2 6 6
Medium facility 3 0 4 4
Large facility 14 10 0 14
MINIMAX REGRET APPROACH
 The second step is to identify the worst regret for each alternative. For the first
alternative, the worst is 6; for the second, the worst is 4; and for the third, the
worst is 14.
 The best of these “worsts” would be chosen using minimax regret. The
lowest regret is 4, which is for a medium facility. Hence, that alternative would be
chosen. Regrets
Alternatives Low Moderate High Worst
Small facility 0 2 6 6
Medium
3 0 4 4
facility
Large facility 14 10 0 14
 The second step is to identify the worst regret for each alternative. For the first
alternative, the worst is 6; for the second, the worst is 4; and for the third, the
worst is 14.
 The best of these “worsts” would be chosen using minimax regret The
lowest regret is 4, which is for a medium facility. Hence, that alternative would
be chosen.
 NOTE:

 The main weakness of these approaches (except for Laplace) is that

they do not take into account all the payoffs. Instead, they focus on the
worst or best, and so they lose some information. The weakness of
Laplace is that it treats all states of nature as equally likely. Still, for a
given set of circumstances, each has certain merits that can be helpful
to a decision maker.
DECISION MAKING UNDER RISK

 Between the two extremes of certainty and uncertainty lies the

case of risk: the probability of occurrence for each state of nature
can be estimated.
 (Note that because the states are mutually exclusive and
collectively exhaustive, these probabilities must add to 1.00.)
 A widely used approach under such circumstances is the expected
monetary value criterion. The expected value is computed for
each alternative, and the one with the highest expected value is
selected. The expected value is the sum of the payoffs for an
alternative where each payoff is weighted by the probability for the
relevant state of nature. Thus, the approach is:
EXPECTED MONETARY VALUE CRITERION (EMV) –determine the expected payoff
of each alternative, and choose the alternative that has the best expected payoff.

Example 4
Using the expected monetary value criterion, identify the best alternative for the previous
payoff table for these probabilities: low= .30, moderate = .50, and high =.20.

Solution
Find the expected value of each alternative by multiplying the probability of
occurrence fir each state of nature by the payoff fir that state of nature and
summing them:
EVsmall = .30($10) + .50 ($10) + .20 ($10) =$10
EVmedium = .30($7) + .50 ($12) + .20 ($12) =$10.5
EVlarge = .30(-$4) + .50 ($2) + .20 ($16) =$3
Hence, choose the medium-size facility because it has the highest expected
value.
 The expected monetary value approach is most appropriate when a decision
maker is neither risk-averse nor risk-seeking, but instead is risk-neutral.
 Typically, well established organizations with numerous decisions for this
nature tend to use expected value since it provides an indication if the long-run,
average payoff. That is the expected-value amount, (e.g., $10.5 million in the
last example) is not an actual payoff but an expected or average amount that
would be approximated if a large number of identical decisions were to be
made.
 Hence, if a decision maker applies this criterion to a large number of similar
decisions, the expected payoff for the total will equal the sum of the individual
expected payoffs.
EXPECTED MONETARY VALUE APPROACH
 The expected monetary value approach is most appropriate when a
decision maker is neither risk-averse nor risk-seeking, but instead is risk-
neutral. Typically, well established organizations with numerous decisions
for this nature tend to use expected value since it provides an indication
if the long-run, average payoff.
 That is the expected-value amount, (e.g., $10.5 million in the last
example) is not an actual payoff but an expected or average amount that
would be approximated if a large number of identical decisions were to
be made.
 Hence, if a decision maker applies this criterion to a large number of
similar decisions, the expected payoff for the total will equal the sum of
the individual expected payoffs.
DECISION TREES

 A decision trees is a schematic representations of the alternatives

available to a decision maker and their possible consequences.
The term gets its name from the treelike appearance .
 Although tree diagrams can be used in place of a payoff table,
they are particularly useful for analyzing situation that involves
sequential decisions.
 For instance, a manager may initially decide to build a small
facility only to discover that demand is much higher than
anticipated. In this case, the manager may then be called upon to
make a second decision on whether to expand or build an
additional facility.
EXPECTED VALUE OF PERFECT INFORMATION
 For instance, the choice of location for a restaurant may weigh heavily
on whether a new highway will be constructed or whether a zooning
permit will be issued.
 A decision maker may have probabilities for these states of nature;
however, it may possible to delay a decision until it is clear which state of
nature will exist.
 This might involve taking an option to buy the land. If the state of nature
is favorable, the option can be exercised; if the state is unfavorable, the
option can be allowed to expire. The question to consider is whether the
cost of the option will be less than the expected gain due to delaying the
decision (i.e., the expected payoff above the expected value). This is
known as the expected value of perfect information or EVPI.
EXPECTED VALUE OF PERFECT INFORMATION
 Expected value of perfect information – the difference between the expected
payoff under certainty and the expected payoff under conditions of risk.
 Other possible ways of obtaining perfect information depend somewhat on the
nature of the decision being made. For example, information about consumer
preferences might be come from market research; additional information about
a product could come from product testing; legal experts might be called on,
and so on.
 There are two ways to determine the EVPI. One is to compute the expected
payoff under certainty and subtract the expected payoff under the risk. Thus:
EXPECTED VALUE OF
PERFECT INFORMATION

Expected value Expected Expected

of perfect = payoff under - payoff under
information certainty risk
Example 6
Using information from Example 4, determine the expected value of perfect information using the
Figure 2-1.
Solution
First, compute the expected payoff under certainty. To do this, identify the best payoff under each
state of nature. Then combine these by weighting each payoff by the probability of that state of nature
and adding the amount. Thus, the best payoff under low demand is $10, the best under moderate
demand is $12, and the best under high demand is $16. The expected payoff under certainty is, then:

.30 ($10) + .50 ($12) + .20 ($16) = $12.2

The expected payoff under risk, as computed in Example 4, is $10.5. The EPVI is the difference between
these:
EVPI = $12.2 - $10.5 = $1.7
This figure indicates the upper limit on the amount the decision maker should be willing to spend to
obtain perfect information in this case. Thus, if the cost equals or exceeds this amount ( $1.7) ,
the decision maker would be better off not spending additional money and simply going with the
alternative that has the highest expected payoff.
A SECOND APPROACH is to use the regret table to compute the epvi. to do this, find
the expected regret for each alternative. the minimum expected regret is equal to the
EPVI.
Example 7

Determine the expected value of perfect information for the capacity-planning problem using the expected
regret approach.

Solution
Using information from Examples 2, 3, and 4, we can compute expected regret for each alternative.
Thus:

Small facility .30(0) + .50(2) + .20(6) = 2.2

Medium facility .30(3) + .50(0) + .20(4) = 1.7 [minimum]
Large facility .30(14) + .50(10) + .20(0) = 9.2

The lowest expected regret is 1.7, which is associated with the second alternative. Hence, the EPVI is $1.7
million, which agrees with the previous example using the other approach.
Merry Xmas !!!