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Risk and Uncertainty

Risk and Uncertainty

 

 

Risk and Uncertainty

Chapter 11 Risk and Uncertainty

1.      Objectives

1.1       Suggest research techniques to reduce uncertainty, e.g. focus groups, market research.
1.2       Explain the use of expected value, sensitivity and simulation.
1.3       Apply expected values and sensitivity to decision-making problems.
1.4       Apply the techniques of maximin, maximax and minimax regret to decision-making problems including the production of profit tables.
1.5       Draw a decision tree and use it to solve a multi-stage decision problem.
1.6       Calculate the value of perfect information.


2.      Risk and Uncertainty

2.1

Risk and Uncertainty

 

Risk involves situations or events which may or may not occur, but whose probability of occurrence can be calculated statistically and the frequency of their occurrence predicted from past records. Thus insurance deals with risk.

Uncertain events are those whose outcome cannot be predicted with statistical confidence.

2.2

Risk Preference

 

A risk seeker is a decision maker who is interested in the best outcomes no matter how small the chance that they may occur.

A decision maker is risk neutral if he is concerned with what will be the most likely outcome.

A risk averse decision maker acts on the assumption that the worst outcome might occur.

3.      Allowing for Uncertainty

3.1       The role of market research

3.1.1

Market Research

 

Market research is the systematic process of gathering, analyzing and reporting data about markets to investigate, describe, measure, understand or explain a situation or problem facing a company or organization.

3.1.2    Market research enables organizations to understand the needs and opinions of their customers and other stakeholders. Armed with this knowledge they are able to make better quality decisions and provide better products and better services.
3.1.3    Thus, research influences what is provided and the way it is provided. It reduces uncertainty and monitors performance. A management team which possesses accurate information relating to the marketplace will be in a strong position to make the best decisions in an increasingly competitive world.

3.2       Types of data collected

3.2.1    Data can be either:
(a)        primary – collected at first hand from a sample of respondents, or
(b)      secondary – collected from previous surveys, other published facts and opinions, or from experts. It is also known as desk research, because it can be carried out from one’s desk.
3.2.2    More importantly for research practice and analysis, data can be either:
(a)        quantitative data usually deals with numbers and typically provides the decision maker with information about how many customers, competitors, etc act in a certain way. Quantitative data can, for example, tell the researcher what people need or consume, or where, when and how people buy goods or consumer services.
(b)       qualitative data tell us why consumers think/buy or act the way they do. Qualitative data is used in consumer insight (e.g. understanding what makes consumers prefer one brand to another), media awareness (e.g. how much of an advertisement is noticed by the public), new product development studies and for many other reasons.
3.2.3    Qualitative research has as its specific purpose the uncovering and understanding of thought and opinion. It is carried out on relatively small samples and unstructured or semi-structured techniques, such as individual in depth interviews and group discussions (also known as focus group), are used.

3.3       Conservatism

3.3.1    This approach simply involves estimating outcomes in a conservative manner in order to provide a built-in safety factor.
3.3.2    A more scientific version of conservatism is to measure the most likely outcome form a decision, and the worst and best possible outcomes. This will show the full range of possible outcomes from a decision, and might help managers to reject certain alternatives because the worst possible outcome might involve an unacceptable amount of loss. This requires the preparation of pay-off tables.
3.3.3    Pay-off tables identify and record all possible outcomes (or pay-offs) in situations where the action taken affects the outcomes.

 

3.3.4

Example 1

 

ABC Co is trying to set the sales price for one of its products. Three prices are under consideration, and expected sales volumes and costs are as follows.


Price per unit

$4

$4.30

$4.40

Expected sales volume (units)

 

 

 

Best possible

16,000

14,000

12,500

Most likely

14,000

12,500

12,000

Worst possible

10,000

8,000

6,000

Fixed costs are $20,000 and variable costs of sales are $2 per unit.

Which price should be chosen?

Solution:

Here we need to prepare a pay-off table showing pay-offs (contribution) dependent on different levels of demand and different selling prices.

Price per unit

$4

$4.30

$4.40

Contribution per unit

$2

$2.30

$2.40

Total contribution

$

$

$

Best possible

32,000

32,200

30,000

Most likely

28,000

28,750

28,800

Worst possible

20,000

18,400

14,400

(a)     The highest contribution based on most likely sales volume would be at a price of $4.40 but arguably a price of $4.30 would be much better than $4.40, since the most likely profit is almost as good, the worst possible profit is not as bad, and the best possible profit is better.
(b)    However, only a price of $4 guarantees that the company would not make a loss, even if the worst possible outcome occurs. (Fixed costs of $20,000 would just be covered.) A risk averse management might therefore prefer a price of $4 to either of the other two prices.

 

 

4.      Probabilities and Expected Values

4.1

Expected Values

 

(a)    Expected values indicate what an outcome is likely to be in the long run with repetition. Where probabilities are assigned to different outcomes, we can evaluate the worth of a decision as the expected value, or weighted average, of these outcomes.
(b)    The principles is that when there are a number of alternative decisions, each with a range of possible outcomes, the optimum decision will be the one which gives the highest expected value.

4.2

Example 2

 

Suppose a manager has to choose between mutually exclusive options A and B, and the probable outcomes of each option are as follows.

Option A

Option B

Probability

Profit ($)

Probability

Profit ($)

0.8

5,000

0.1

(2,000)

0.2

6,000

0.2

5,000

 

 

0.6

7,000

 

 

0.1

8,000

The expected value (EV) of profit of each option would be measured as follows.
Option A


Probability

Profit ($)

EV of profit ($)

0.8 ×

5,000 =

4,000

0.2 ×

6,000 =

1,200

 

EV =

5,200

Option B


Probability

Profit ($)

EV of profit ($)

0.1 ×

(2,000) =

(200)

0.2 ×

5,000 =

1,000

0.6 ×

7,000 =

4,200

0.1 ×

8,000 =

800

 

EV =

5,800

In this example, since it offers a higher EV of profit, option B would be selected in preference to A, unless further risk analysis is carried out.

4.4       Limitations of expected values
(a)        The expected value is merely a weighted average of all possible outcomes, it has severe limitations as a decision rule by which to judge preference. The expected value will never actually occur.
(b)       Expected values are used to support a risk-neutral attitude. A risk-neutral decision maker will ignore any variability in the range of possible outcomes and be concerned only with the expected value of outcomes.
(c)        Expected values are more valuable as a guide to decision making where they refer to outcomes which will occur many times over.

5.       Decision Rules

5.1       In some situations it might not be possible to assign meaningful estimates of probabilities to possible outcomes. Where this situation occurs managers might use any of the following criteria to make decisions: maximin, maximax or the criterion of regret.

5.2

Decision Rules

 

(a)    Maximin basis (小中取大原則) The ‘play it safe’ basis for decision making is referred to as the maximin basis. This is short for ‘maximise the minimum achievable profit’.
(b)    Maximax basis (大中取大原則) – A basis for making decisions by looking for the best outcome is known as the maximax basis, short for ‘maximise the maximum achievable profit’.
(c)    Minimax regret (大中取小遺憾準則) – The ‘opportunity loss’ basis for decision making is known as minimax regret .

 

5.3       The maximin decision rule

5.3.1    The assumption underlying the maximin criterion is that the worst possible outcome will always occur and the decision-maker should therefore select the largest payoff under this assumption. This would mean choosing the alternative that maximizes the minimum profits.

5.3.2

Example 4

 

Suppose a businessman is trying to decide which of three mutually exclusive projects (互斥項目) to undertake. Each of the projects could lead to varying net profit which the businessman classifies as outcomes. I, II and III. He has constructed the following profit table or matrix.

 

Net profit in $000s of outcome turns out to be

Project

I (Worst)

II (Most likely)

III (Best)

A

50

85

130

B

70

75

140

C

90

100

110

The maximin decision rule suggests that he should select the ‘smallest worst result’ that could happen. This is the decision criterion that managers should ‘play safe’ and either minimize their losses or costs, or else go for decision which gives the higher minimum profits. If he selects project A the worst result is a net profit of 50. Similarly, the best results for B and C are 70 and 90 respectively. The best worst outcome is 90 and project C would therefore be selected (because this is a better ‘worst possible’ than either A or B).

5.3.3    Criticisms of maximin
(a)        It is defensive and conservative, being a safety first principle of avoiding the worst outcomes without taking into account opportunities for maximizing profits.
(b)       It ignores the probability of each different outcome taking place. In the previous example, we ignored the fact that outcome II was the most likely outcome.


5.4       Maximax

5.4.1    The maximax criterion is the opposite of maximin, and is based on the assumption that the best payoff will occur. The maximax criterion looks at the best possible results. Maximax means ‘maximise the maximum profit’.

5.4.2

Example 5

 

Here is a profit or payoff table showing the profits that will be achieved depending upon the action taken (D, E or F) and the circumstances prevailing (I, II or III).

 

Profits
Actions

Circumstances

D

E

F

I

100

80

60

II

90

120

85

III

(20)

10

85

 

 

 

 

Maximum profit

100

120

85

Action E would be chosen if the maximax rule is followed.

5.4.3

Exercise 1

 

A company is considering which one of three alternative courses of action, A, B and C to take. The profit or loss from each choice depends on which one of four economic circumstances, I, II, III or IV will apply. The possible profits and losses, in thousands of dollars, are given in the following payoff table. Losses are shown as negative figures.

 

Profit/(loss) ($000)
Actions

Circumstances

A

B

C

I

70

60

70

II

(10)

20

(5)

III

80

0

50

IV

60

100

115

Required:

State which action would be selected using each of the maximax and maximin criteria.

5.4.4    Criticisms of maximin
(a)        It ignores probabilities.
(b)       It is over-optimistic.

5.5       Minimax regret rule

5.5.1    The minimax regret rule aims to minimize the regret from making the wrong decision. Regret is the opportunity lost through making the wrong decision.

5.5.2

Example 6

 

A manager is trying to decide which of three mutually exclusive projects to undertake. Each of the projects could lead to varying net costs which manager calls outcomes I, II and III. The following payoff table or matrix has been constructed.

Outcomes

Project

(Net profit)

A

B

C

I (Worst)

50

70

90

II (Most likely)

85

75

100

III (Best)

130

140

110

Which project should be undertaken?

Solution:

A table of regrets can be compiled, as follows, showing the amount of profit that might be foregone for each project, depending on whether the outcome is I, II or III.

 

Project

Outcome

A

B

C

I (Worst)

40 *

20 **

0

II (Most likely)

15 ***

25

0

III (Best)

10

0

30

* 90 – 50
** 90 – 70
*** 100 – 85, etc.

The maximum regret is 40 with project A, 25 with B and 30 with C. The lowest of these three maximum regrets is 25 with B, and so project B would be selected if the minimax regret rule is used.

4.3

Example 3

 

BBC Newsagents stocks a weekly lifestyle magazine. The owner buys the magazines for $0.30 each sells them at the retail price of $0.50 each.

At the end of the week unsold magazines are obsolete and have no value. The estimated probability distribution for weekly demand is shown below.

Weekly demand in units

Probability

20

0.20

30

0.55

40

0.25

Required:

What is the expected value of demand? If the owner is to order a fixed quantity of magazines per week, how many should that be?

Solution:

EV of demand (units per week) = (20 × 0.20) + (30 × 0.55) + (40 × 0.25) = 30.5 units per week.

The next step is to set up a decision matrix of possible strategies (numbers bought) and possible demand.

The ‘pay-off’ from each combination of action and outcome is then computed.

No sale = cost of $0.30 per magazine
Profit per magazine = $0.20 ($0.50 – $0.30)

Probability

Outcome

Decision

 

(No. demanded)

(No. bought)

 

 

20

30

40

 

 

$

$

$

0.20

20

4.00

1.00 *

(2.00)

0.55

30

4.00

6.00

3.00

0.25

40

4.00

6.00

8.00

 

 

4.00

5.00**

3.25

* Buy 30 and sell only 20 gives a profit of (20 × $0.5) – (30 × $0.3) = $1
** (0.2 × 0.1) + (0.55 × 6) + (0.25 × 6) = 5
The strategy which gives the highest expected pay-off is to stock 30 magazines each week.

 

5.6       Contribution tables

5.6.1    Questions requiring application of the decision rules often incorporate a number of variables, each with a range of possible values. For example these variables might be:
(i)        Unit price and associated level of demand
(ii)       Unit variable cost
Each variable might have, for example, three possible values.
5.6.2    Before being asked to use the decision rules, exam questions could ask you to work out contribution for each possible outcomes.
5.6.3    The number of possible outcomes = no. of value of variable 1 × no. of value of variable 2 × no. of value of variable 3, etc. So, for example, if there are three variables, each with three possible values, there are 3 × 3 = 9 outcomes.

5.6.4

Example 7

 

Suppose the budgeted demand for project X will be 11,500 units if the price is $10, 8,500 units if the price is $12 and 5,000 units if the price is $14. Variable costs are estimated at either $4, $5 or $6 per unit. A decision needs to be made on the price to be charged.

Here is a contribution table showing the budgeted contribution for each of the nine possible outcomes.

Demand

Price

Variable cost

Unit contribution

Total contribution

 

$

$

$

$000

11,500

10

4

6

69.0

11,500

10

5

5

57.5

11,500

10

6

4

46.0

8,500

12

4

8

68.0

8,500

12

5

7

59.5

8,500

12

6

6

51.0

5,000

14

4

10

50.0

5,000

14

5

9

45.0

5,000

14

6

8

40.0

Once the table has been drawn up, the decision rules can be applied.

Solution:

Maximin

We nee to maximize the minimum contribution.

Demand/price

Minimum contribution

11,500/$10

$46,000

8,500/$12

$51,000

5,000/$14

$40,000

Set a price of $12.

Maximax

We need to maximize the maximum contribution.

Demand/price

Minimum contribution

11,500/$10

$69,000

8,500/$12

$68,000

5,000/$14

$50,000

Set a price of $10.

Minimax

We need to minimize the maximum regret (lost contribution) of making the wrong decision.

Variable cost

 

Price

 

$

$10

$12

$14

4

-

$1,000

$19,000

5

$2,000

0

$14,500

6

$5,000

0

$11,000

 

 

 

 

Maximax regret

$5,000

$1,000

$19,000

Mimimax regret strategy (price of $12) is that which minimizes the maximum regret ($1,000).

Sample working
At a variable cost of $4, the best strategy would be a price of $10. Choosing a price of $12 would mean lost contribution of $69,000 – $68,000, while choosing a price of $14 would mean lost contribution of $69,000 – $50,000.

Decision Trees

6.1

Decision Trees

 

A decision tree is a pictorial method of showing a sequence of interrelated decisions and their expected outcomes. Decision trees can incorporate both the probabilities of, and values of, expected outcomes, and are used in decision-making.

6.2

Example 8

 

A company can choose to launch a new product XYZ or not. If the product is launched, expected sales and expected unit costs might be as follows.

Sales

Unit costs

Units

Probability

$

Probability

10,000

0.8

6

0.7

15,000

0.2

8

0.3

6.3

Exercise 2

 

ABC Co has a new wonder product, the vylin, of which it expects great things. At the moment the company has two courses of action open to it, to test market the product or abandon it.

If the company test markets it, the cost will be $100,000 and the market response could be positive or negative with probabilities of 0.60 and 0.40.

If the response is positive the company could either abandon the product or market it full scale.

If it markets the vylin full scale, the outcome might be low, medium or high demand, and the respective net gains/(losses) would be (200), 200 or 1,000 in units of $1,000 (the result could range from a net loss of $200,000 to a gain of $1,000,000). These outcomes have probabilities of 0.20, 0.50 and 0.30 respectively.

If the result of the test marketing is negative and the company goes ahead and markets the product, estimated losses would be $600,000.

If, at any point, the company abandons the product, there would be a net gain of $50,000 from the sale of scrap. All the financial values have been discounted to the present.

Required:

(a)       Draw a decision tree.
(b)       Include figures for cost, loss or profit on the appropriate branches of the tree.

Solution:

 

 

 

 

 

 

 

 

6.4       Evaluating the decision with a decision tree

6.4.1

Rollback Analysis

 

Rollback analysis evaluates the EV of each decision option. You have to work from right to left and calculate EVs at each outcome point.

The EV of each decision option can be evaluated, using the decision tree to help with keeping the logic on track. The basic rules are as follows.
(a)       We start on the right hand side of the tree and work back towards the left hand side and the current decision under consideration. This is sometimes known as the 'rollback' technique or 'rollback analysis'.
(b)       Working from right to left, we calculate the EV of revenue, cost, contribution or profit at each outcome point on the tree.

6.4.2

Example 9

 

In the Exercise 2 above, the right-hand-most outcome point is point E, and the EV is as follows.

 

Profit (x)

Probability (p)

px

 

$000

 

$000

High

1,000

0.3

300

Medium

200

0.5

100

Low

(200)

0.2

(40)

 

 

EV =

360

This is the EV of the decision to market the product if the test shows positive response. It may help you to write the EV on the decision tree itself, at the appropriate outcome point (point E).

(a)       At decision point C, the choice is as follows,
(i)         Market, EV = +360 (the EV at point E)
(ii)        Abandon, value = +50
The choice would be to market the product, and so the EV at decision point C is +360.
(b)       At decision point D, the choice is as follows.
(i)         Market, value = – 600
(ii)        Abandon, value = +50
The choice would be to abandon, and so the EV at decision point D is +50.

The second stage decisions have therefore been made. If the original decision is to test market, the company will market the product if the test shows positive customer response, and will abandon the product if the test results are negative.

The evaluation of the decision tree is completed as follows.
(a)       Calculate the EV at outcome point B.
EV = 0.6 × 360 + 0.4 × 50 = 236
(b)       Compare the options at point A, which are as follows.
(i)         Test: EV = EV at B minus test marketing cost = 236 – 100 = 136
(ii)        Abandon: Value = 50
The choice would be to test market the product, because it has a higher EV of profit.

7.      The Value of Information

7.1       When a decision-maker is faced with a series of uncertain events that might occur, he or she should consider the possibility of obtaining additional information about which event is likely to occur. Here we consider how we can calculate the maximum amount it would be worth paying to acquire additional information from a particular source.

7.2

The Value of Perfect Information

 

(a)       Perfect information is guaranteed to predict the future with 100% accuracy. Imperfect information is better than no information at all but could be wrong in its prediction of the future.
(b)       The value of perfect information is the difference between the EV of profit with perfect information and the EV of profit without perfect information.

 

Sensitivity Analysis

8.1

Sensitivity Analysis

 

(a)       Sensitivity analysis can be used in any situation so long as the relationships between the key variables can be established. Typically this involves changing the value of a variable and seeing how the results are affected.
(b)       It is used to describe any technique whereby decision options are tested for their vulnerability to changes in any “variable” such as expected sales volume, sales price per unit, material costs, or labour costs.

8.2       Here are three useful approaches to sensitivity analysis.
(a)        To estimate by how much costs and revenues would need to differ from their estimated values before the decision would change.
(b)       To estimate whether a decision would change if estimated costs were x% higher than estimated, or estimated revenues y% lower than estimated.
(c)        To estimate by how much costs and/or revenues would need to differ from their estimated values before the decision maker would be indifferent between two options.

8.3

Example 11

 

BBB Co has estimated the following sales and profits for a new product which it may launch on to the market.

 

$

$

Sales (2,000 units)

 

4,000

Variable costs: materials

2,000

 

labour

1,000

3,000

Contribution

 

1,000

Less: incremental fixed costs

 

800

Profit

 

200

Required:

Analyse the sensitivity of the project.

Solution:
(a)       If incremental fixed costs are more than 25% above estimate, the project would make a loss.
(b)       If unit costs of materials are more than 10% above estimate, the project would make a loss.
(c)       Similarly, the project would be sensitivity to an increase in unit labour costs of more than $200, which is 20% above estimate, or else to a drop in the unit selling price of more than 5%.
(d)       The margin of safety, given a breakeven point of 1,600 units, is (400/2,000) × 100% = 20%

Management would then be able to judge more clearly whether the product is likely to be profitable. The items to which profitability is more sensitive in this example are the selling price (5%) and material costs (10%). Sensitivity analysis can help to concentrate management attention on the most important factors.

 

9.      Simulation Models

9.1

Simulation Models

 

Simulation models can be used to deal with decision problems involving a number of uncertain variables. In other words, the model allows the company to change more than one variable in one time for the decision making. Random numbers are used to assign values to the variables.

9.2       One of the chief problems encountered in decision making is the uncertainty of the future. Where only a few factors are involved, probability analysis and expected value calculations can be used to find the most likely outcome of a decision. Often, however, in real life, there are so many uncertain variables that this approach does not give a true impression of possible variations in outcome.


Examination Style Questions

Question 1 – CVP Analysis and Uncertainty
The accountant of Laburnum Ltd is preparing documents for a forthcoming meeting of the budget committee. Currently, variable cost is 40% of selling price and total fixed costs are £40,000 per year.

The company uses an historical cost accounting system. There is concern that the level of costs may rise during the ensuing year and the chairman of the budget committee has expressed interest in a probabilistic approach to an investigation of the effect that this will have on historic cost profits. The accountant is attempting to prepare the documents in a way which will be most helpful to the committee members. He has obtained the following estimates from his colleagues:

 

Average inflation rate over ensuing year

Probability

Pessimistic

10%

0.4

Most likely

5%

0.5

Optimistic

1%

0.1

 

 

1.0

 

Demand at current selling prices

Probability

Pessimistic

£50,000

0.3

Most likely

£75,000

0.6

Optimistic

£100,000

0.1

 

 

1.0

The demand figures are given in terms of sales value at the current level of selling prices but it is considered that the company could adjust its selling prices in line with the inflation rate without affecting customer demand in real terms.

Some of the company’s fixed costs are contractually fixed and some are apportionments of past costs; of the total fixed costs, an estimated 85% will remain constant irrespective of the inflation rate.

You are required to analyse the foregoing information in a way which you consider will assist management with its budgeting problem. Although you should assume that the directors of Laburnum Ltd are solely interested in the effect of inflation on historic cost profits, you should comment on the validity of the accountant’s intended approach. As part of your analysis you are required to calculate:

(a)     the probability of at least breaking even, and
(b)     the probability of achieving a profit of at least £20,000.                                    (16 marks)
(c)     It can be argued that the use of point estimate probabilities (as above) is too unrealistic because it constrains the demand and cost variables to relatively few values. Briefly describe an alternative simulation approach which might meet this objection.                                         (6 marks)
(Total 22 marks)
(ACCA Level 2 Management Accounting)

Question 2 - Maximax, Maximin and Expected Value
Shifters Haulage (SH) is considering changing some of the vans it uses to transport crates for customers. The new vans come in three sizes; small, medium and large. SH is unsure about which type to buy. The capacity is 100 crates for the small van, 150 for the medium van and 200 for the large van.

Demand for crates varies and can be either 120 or 190 crates per period, with the probability of the higher demand figure being 0·6.

The sale price per crate is $10 and the variable cost $4 per crate for all van sizes subject to the fact that if the capacity of the van is greater than the demand for crates in a period then the variable cost will be lower by 10% to allow for the fact that the vans will be partly empty when transporting crates.

SH is concerned that if the demand for crates exceeds the capacity of the vans then customers will have to be turned away. SH estimates that in this case goodwill of $100 would be charged against profits per period to allow for lost future sales regardless of the number of customers that are turned away.

Depreciation charged would be $200 per period for the small, $300 for the medium and $400 for the large van.

SH has in the past been very aggressive in its decision-making, pressing ahead with rapid growth strategies. However, its managers have recently grown more cautious as the business has become more competitive.

Required:

(a)     Explain the principles behind the maximax, maximin and expected value criteria that are sometimes used to make decisions in uncertain situations.                                                             (4 marks)
(b)     Prepare a profits table showing the SIX possible profit figures per period.         (9 marks)
(c)     Using your profit table from (b) above discuss which type of van SH should buy taking into consideration the possible risk attitudes of the managers.                                                           (6 marks)
(d)     Describe THREE methods other than those mentioned in (a) above, which businesses can use to analyse and assess the risk that exists in its decision-making.                                           (6 marks)
(25 marks)
(ACCA F5 Performance Management December 2008 Q2)

Question 3 – Payoff Tables, Maximin, Maximax and Expected Values
Cement Co is a company specialising in the manufacture of cement, a product used in the building industry. The company has found that when weather conditions are good, the demand for cement increases since more building work is able to take place. Last year, the weather was so good, and the demand for cement was so great, that Cement Co was unable to meet demand. Cement Co is now trying to work out the level of cement production for the coming year in order to maximise profits. The company doesn’t want to miss out on the opportunity to earn large profits by running out of cement again. However, it doesn’t want to be left with large quantities of the product unsold at the end of the year, since it deteriorates quickly and then has to be disposed of. The company has received the following estimates about the probable weather conditions and corresponding demand levels for the coming year:

Weather

Probability

Demand

Good

25%

350,000 bags

Average

45%

280,000 bags

Poor

30%

200,000 bags

Each bag of cement sells for $9 and costs $4 to make. If cement is unsold at the end of the year, it has to be disposed of at a cost of $0·50 per bag.

Cement Co has decided to produce at one of the three levels of production to match forecast demand. It now has to decide which level of cement production to select.

Required:

(a)     Construct a pay off table to show all the possible profit outcomes.                      (8 marks)
(b)     Decide the level of cement production the company should choose, based on the following decision rules:
(i)      Maximin                                                                                                      (1 mark)
(ii)     Maximax                                                                                                      (1 mark)
(iii)    Expected value                                                                                           (4 marks)
You must justify your decision under each rule, showing all necessary calculations.
(c)     Describe the ‘maximin’ and ‘expected value’ decision rules, explaining when they might be used and the attitudes of the decision makers who might use them.                                          (6 marks)
(20 marks)
(ACCA F5 Performance Management June 2011 Q1)

Question 4 – Pricing and purchase contract decisions based on uncertain demand and calculation of maximum price to pay for perfect information
Z Ltd is considering various product pricing and material purchasing options with regard to a new product it has in development. Estimates of demand and costs are as follows:

If selling price per unit is

 

£15 per unit

£20 per unit

 

 

Sales volume

Sales volume

Forecasts

Probability

(000 units)

(000 units)

Optimistic

0.3

36

28

Most likely

0.5

28

23

Pessimistic

0.2

18

13

Variable manufacturing costs (excluding materials) per unit

 

 

£3

 

£3

Advertising and selling costs

 

£25,000

£96,000

General fixed costs

 

£40,000

£40,000

Each unit requires 3kg of material and because of storage problems any unused material must be sold at £1 per kg. The sole suppliers of the material offer three purchase options, which must be decided at the outset, as follows:

(i)      any quantity at £3 per kg, or
(ii)     a price of £2.75 per kg for a minimum quantity of 50 000 kg, or
(iii)    a price of £2.50 per kg for a minimum quantity of 70 000 kg.

You are required, assuming that the company is risk neutral, to

(a)     prepare calculations to show what pricing and purchasing decisions the company should make, clearly indicating the recommended decisions;                                                              (15 marks)

(b)     calculate the maximum price you would pay for perfect information as to whether the demand would be optimistic or most likely pessimistic.                                                                    (5 marks)
(Total 20 marks)

Question 5 – Selling price decision based on expected values and value of additional information
Warren Ltd is to produce a new product in a short-term venture which will utilize some obsolete materials and expected spare capacity. The new product will be advertised in quarter I with production and sales taking price in quarter II. No further production or sales are anticipated.

Sales volumes are uncertain but will, to some extent, be a function of sales price. The possible sales volumes and the advertising costs associated with each potential sales price are as follows:


The resources used in the production of each unit of the product are:


Production labour:

Grade 1

2 hours

 

Grade 2

1 hour

Materials: X

1 unit

 

Y

2 units

 

The normal cost per hour of labour is:


Grade 1

£2

Grade 2

£3

However, before considering the effects of the current venture, there is expected to be 4,000 hours of idle time for each grade of labour in quarter II. Idle time is paid at the normal rates.

Material X is in stock at a book value of £8 per unit, but is widely used within the firm and any usage for the purposes of this venture will require replacing. Replacement cost is £9 per unit.

Material Y is obsolete stock. There are 16,000 units in stock at a book value of £3.50 per unit and any stock not used will have to be disposed of at a cost, to Warren, of £2 per unit. Further quantities of Y can be purchased for £4 per unit.

Overhead recovery rates are:


Variable overhead

£2 per direct labour hour worked

Fixed overhead

£3 per direct labour hour worked

Total fixed overheads will not alter as a result of the current venture.

Feedback from advertising will enable the exact demand to be determined at the end of quarter I and production in quarter II will be set to equal that demand. However, it is necessary to decide now on the sales price in order that it can be incorporated into the advertising campaign.

Required:

(a)     Calculate the expected money value of the venture at each sales price and on the basis of this advise Warren of its best course of action.                                                                     (12 marks)
(b)     Briefly explain why the management of Warren might rationally reject the sales price leading to the highest expected money value and prefer one of the other sales prices.
(4 marks)
(c)     It will be possible, for the sales price of £40 per unit only, to ascertain which of the four levels of demand will eventuate. If the indications are that the demand will be low then the advertising campaign can be cancelled at a cost of £10,000 but it would then not be possible to continue the venture at another sales price. This accurate information concerning demand will cost £5,000 to obtain.

Indicate whether it is worthwhile obtaining the information and ascertain whether it would alter the advice given in (a) above.                                                                                                 (4 marks)
(Total 20 marks)
(ACCA Level 2 Management Accounting)

Question 6 – Decision Tree
In the market for one of its product, MD and its two major competitors (CN and KL) together account for 95% of total sales.

The quality of MD’s products is viewed by customers as being somewhat better than that of its competitors and therefore at similar prices it has an advantage.

During the past year, however, when MD raised its price to £1.2 per litre, competitors kept their prices at £1.0 per litre and MD’s sales declined even though the total market grew in volume.

MD is now considering whether to retain or reduce its price for the coming year. Its expectations about its likely volume at various prices charged by itself and its competitors are as follows:

Prices per litre

 

MD

CN

KL

MD’s expected sales

(£)

(£)

(£)

Million litres

1.2

1.2

1.2

2.7

1.2

1.2

1.1

2.3

1.2

1.2

1.0

2.2

1.2

1.1

1.2

2.4

1.2

1.1

1.0

2.2

1.2

1.0

1.0

2.1

1.1

1.1

1.1

2.8

1.1

1.1

1.0

2.4

1.1

1.0

1.0

2.3

1.0

1.0

1.0

2.9

Experience has shown that CN tends to react to MD’s price level and KL tends to react to CN’s price level. MD therefore assesses the following probabilities:

 

 

 

If MD’s price per litre is

there is a probability of

that CN’s price per litre will be

(£)

 

(£)

1.2

0.2

1.2

 

0.4

1.1

 

0.4

1.0

 

1.0

 

 

 

 

1.1

0.3

1.1

 

0.7

1.0

 

1.0

 

 

 

 

1.0

1.0

1.0

If CN’s price per litre is

there is a probability of

that KL’s price per litre will be

(£)

 

(£)

1.2

0.1

1.2

 

0.6

1.1

 

0.3

1.0

 

1.0

 

 

 

 

1.1

0.3

1.1

 

0.7

1.0

 

1.0

 

 

 

 

1.0

1.0

1.0

Costs per litre of the product are as follows:


Direct wages

£0.24

Direct materials

£0.12

Departmental expenses:


Indirect wages, maintenance and supplies

16 2/3% of direct wages

Supervision and depreciation

£540,000 per annum

General works expenses (allocated)

16 2/3% of prime cost

Selling and administration expenses (allocated)

50% of manufacturing cost

You are required to state whether, on the basis of the data given above, it would be most advantageous for MD to fix its price per litre for the coming year at £1.2, £1.1 or £1.0.

 

 

7.3

Example 10

 

The management of ABC Co must choose whether to go ahead with either of two mutually exclusive projects, A and B. The expected profits are as follows.

 

Profit if there is strong demand

Profit/(loss) if there is weak demand

Option A

$4,000

$(1,000)

Option B

$1,500

$500

Probability of demand

0.3

0.7

Required:

(a)       Ascertain what the decision would be, based on expected values, if no information about demand were available.
(b)       Calculate the value of perfect information about demand.

Solution:

(a)
If there were no information to help with the decision, the project with the higher EV of profit would be selected.

 

Project A

Project B

Probability

Profit

EV

Profit

EV

 

$

$

$

$

0.3

4,000

1,200

1,500

450

0.7

(1,000)

(700)

500

350

 

 

500

 

800

Project B would be selected.

This is clearly the better option if demand turns out to be weak. However, if demand were to turn out to be strong, project A would be more profitable. There is a 30% chance that this could happen.

(b)
Perfect information will indicate for certain whether demand will be weak or strong. If demand is forecast weak, project B would be selected. If demand is forecast as strong, project A would be selected, and perfect information would improve the profit from $1,500 (project B) to $4,000 (project A).

Forecast demand

 

Probability

 

Project chosen

 

Profit

 

EV of profit

 

 

 

$

$

Weak

0.7

B

500

350

Strong

0.3

A

4,000

1,200

 

EV of profit with perfect information

1,550

 

$

EV of profit without perfect information

800

EV of profit with perfect information

1,550

Value of perfect information

750

Provided that the information does not cost more than $750 to collect, it would be worth having.

Source: https://hkiaatevening.yolasite.com/resources/PMNotes/Ch11-Risk.doc

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