# Business Decision Making At Ocean Limited Accounting Essay

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This case study is based on the implementation of a new project at the Ocean Limited, a UK company specialised in corporate dressing.

Currently the company has 50 employees and operating 100% in the domestic market. The company designs the clothes by taking clients' body-measurements by manually at a rate of 5 persons per hour with 2 employees. The new project is based on the use of body-scan machines to take measurements. The General Director of Ocean Limited has been in contact with a company that develops hi-tech body-scan machines and was offered a new invention based on ultra-sonic sensor technology. He is interested in the project for the benefits of the company.

As project managers, we are assigned to work on the new project by carrying out research using a variety of statistical and financial tools; write a report and present it both in writing and verbally to the Director so that he can make the right decision whether to invest in the project or go against it.

## The Project Management Team

The Project Managers of our team are:

Mala D Rugoonaut - ID: 164139109

Hyacinth Blake - ID: 161223109

Preston Muzangaza - ID:

## Project Planning

The estimated Time to implement the project: 6 months (24 weeks).

Our team is working on the following plan:

## Activity

## No of weeks

## A

Draw up the requirements study

## 2

## B

Review management information systems

## 2

## C

Collect secondary data

## 2

## D

Calculate representative values, illustrate and evaluate the project

## 1

## E

Make forecast for sales, expenditure and profit & loss account for the next 5 years

## 2

## F

Calculate of correlation between sales and marketing expenditure

## 1

## G

Evaluate the inventory control systems and calculate the Economic Order Quantity

1

## H

Evaluate project investment using varieties of financial tools

## 2

## I

Write a report of the project

## 3

## J

Present project to the Managing Director

## 2

## K

Implement project

## 6

## Table 1

## Precedence table

## Activity

## Preceding Activities

A

Draw up the requirements study

None

B

Review management information systems

A

C

Collect secondary data

B

D

Calculate representative values, illustrate and evaluate the project

C

E

Make forecast for sales, expenditure and profit & loss account for the next 5 years

C

F

Calculate of correlation between sales and marketing expenditure

E

G

Evaluate the inventory control systems and calculate the Economic Order Quantity

C

H

Evaluate project investment using varieties of financial tools

D, F

I

Write a report of the project

H, G

J

Present project to the Managing Director

I

K

Implement project

J

## Table 2

## Project complete network with duration

## 5

E 2 F 1

7

6

4*

4

3

2

1

10

9

8

A2 B 2 C 2 D 1 H 2 I 3 J 2 K 6

## ................

G 1

The network consists of a uniqueness dummy.

## Complete project network with earliest and latest event times

Earliest event times

Latest event times

## 8

## 5

E 2 8 F 1

## 2 4 6 7 9 11 14 16 22

7

6

4*

4

3

2

1

10

9

8

A2 B 2 C 2 D 1 H 2 I 3 J 2 K 6

## ................

2 4 6 9 9 11 14 16 22

G 1

## Floats of Ocean Limited project

## Activity

## Earliest starting time

## Latest finishing time

## Duration

## Float

A

0

2

2

2 - 0 - 2 = 0

B

2

4

2

4 - 2 - 2 = 0

C

4

6

2

6 - 4 - 2 = 0

D

6

9

1

9 - 6 - 1 = 2

E

6

8

2

8 - 6 - 2 = 0

F

8

9

1

9 - 8 - 1 = 0

G

6

11

1

11 - 6 - 1 = 4

H

9

11

2

11 - 9 - 2 = 0

I

11

14

3

14 - 11 - 3 = 0

J

14

16

2

16 - 14 - 2 = 0

K

16

22

6

22 - 16 - 6 = 0

## Table 3

Activities A, B, C, E, F, H, I, J and K are critical because they have zero floats. Therefore the critical path of Ocean Ltd. project is ABCEFHIJK.

## Gantt chart for Ocean Ltd. Project

## 1

## 2

## 3

## 4

## 5

## 6

## 7

## 8

## 9

## 10

## 11

## 12

## 13

## 14

## 15

## 16

## 17

## 18

## 19

## 20

## 21

## 22

## A

## B

## C

## E

## F

## H

## I

## J

## K

## D

## G

Critical activities A, B, C, E, F, H, I, J and K are found on top of the chart by solid areas.

Non- critical activities are found at the bottom of the chart by areas with solid outline for duration and dotted outline for float.

## Information Systems

## Types of Information Systems

## 1. Operational management - Transaction Processing System (TPS)

For the operational side of the business, TPS helps with the business planning. As the name implies, this system processes the routine transactions in the business efficiently and accurately. The business may have many TPS, including:

Production and accounting systems.

Sales and purchase order processing

Systems to calculate payroll and tax payments.

Billing systems to send invoices to customers.

Stock control systems.

Human resource management system.

## 2. Tactical management - Management Information System (MIS)

For the tactical level of the organisation, MIS mainly focuses on the internal sources of information and takes data from the TPS and summarises it into a series of management reports. MIS reports tend to be used by middle management and operational supervisors. It is designed to serve the monitoring, controlling, decision-making, and administrative activities of middle managers.

## 3. Strategic management - Decision Support System (DSS)/Executive Information System (EIS)

Finally for the strategic level of the business, DSS is especially designed to help management make decisions in situations where there is uncertainty about the possible outcomes of those decisions.

DSS/EIS employ advanced graphics software to provide highly visual and easy-to-use representations of complex information and current trends. DSS/EIS address unstructured decisions and create a generalised computing and communications environment.

Information processing tools: Computer hardware and software are information processing tools used for the operational, tactical and strategic level of an organisation to store manipulate and analyse collected data with relative ease.

## Computer hardware

Input devices: keyboard, mouse

Processing unit: CPU

Storage: hard drive, CDs, memory stick

Output devices: monitor, speakers, printers

## Computer Software:

System software: Operating System, antivirus software

Communication software: Microsoft Word, Excel, PowerPoint.

Application software: organisation and productivity software

## Information system that our team is operating

Our team is operating in the Tactical and Strategic levels of Information Systems (MIS, DSS/ EIS).

MIS - as middle managers we are focusing on internal events, providing information for planning and decision making when the company needs to take decision on new project.

Strategic level of management - as we are helping management to tackle and address strategic issues and long-term trends, both within the organisation and in the external environment, e.g., forecast sales, profit & lost account for the next 5 years, using financial tools to evaluate project.

DSS/EIS - they address non-routine decisions requiring judgement and evaluation. Various tools and techniques have to be used to help gather relevant information and analyses the options and alternatives. Spreadsheets have to be used to create "what-if" models to help strategic decision-making.

## Collection of Secondary Data

To work on this new project, secondary data provided by Ocean Limited, books and report/articles from websites have been used to carry out research, as data from these sources are relatively cheap, quickly achievable and easily accessible. The reports were collected from trusted websites (see reference), which we consider reliable, relevant and compatible enough to work out this project.

## Information available from Ocean Limited

Currently the company:

Has 50 employees.

Takes the body-measurements of clients by manually, 5 persons per hour with 2 employees.

The new body-scan machine has the following features:

Body-scan is handled by one operator.

Machine can scan 60 persons per hour.

Total costs involved will be approximately £ 150,000.

Other relevant information about the project:

Operator will earn £ 60 per hour, other employees £ 40 per hour each.

Average total cost of one outfit will be £ 400 with a gross profit of 40% of sales value.

Sales are 2,000 outfits per month now, and are expected to grow to 5,000 outfits per month next year.

The Return on Investment (ROI) of one competitor who adopted a similar machine 2 years ago are:

Year 1

## ROI

Year 2

## ROI

## Month

## %

## Month

## %

1

2.36

13

3.46

2

5.73

14

2.64

3

6.6

15

3.63

4

10.05

16

3.44

5

5.13

17

9.46

6

1.88

18

4.9

7

2.52

19

7.45

8

2

20

20.23

9

4.69

21

3.91

10

1.91

22

1.7

11

6.75

23

16.29

12

3.92

24

5.52

25

1.44

## Table 4

## Report/articles from websites:

Economic climate in UK: Monday 21 December 2009

Prime minster Gordon Brown was given a helping hand today ahead of the forthcoming general election as a leading business organisation said that Britain's battered economy would finally exit recession by the end of the year. However, it cautioned that recovery would remain "sluggish" for at least two years.

The economy has been mired in recession for six consecutive quarters - the longest slump in history - but the CBI (Confederation of British Industry) now expects output to grow by 1.2% in 2010 and by 2.5% in 2011. Its growth forecasts are less optimistic than those of Chancellor Alistair Darling. In the pre-budget report, the chancellor forecast growth of 1.25% in 2010 and 3.5% the following year.

Ian McCafferty, CBI chief economic adviser, said: "The UK economy faces a number of structural hurdles over the coming two years, and this recovery - like that of the 1980s - will be relatively drawn out. Credit conditions will remain difficult as the banks slowly nurse themselves back to health, consumer spending will be shaped by the need to rebuild savings, and the public sector will soon have to tighten its belt. All three factors will act as headwinds to growth."

Business Intelligence 2009 / Recession Strategy - an insight from the SME market

Royal Bank of Scotland Group (October 2009)

Almost one in three SME leaders (30%) estimate the value of their market has decreased a lot in the last 12 months, while nearly four in 10 (38%) say the value of their market has been stable or even showing growth.

There has been deterioration in market conditions in the last six months.

Most companies were ready for this downturn, or even worse conditions (70% performing about the same or better than expected).

A number of SMEs have exceeded expectations through proactive marketing, innovations and efficiency drives.

A minority have been taken by surprise by the severity of conditions (29% performing worse than expected).

For most SMEs the most serious impact directly resulting from the current economic conditions has been on the level of demand (43%), but there have been issues around finance, cash flow, costs, exchange rate and staffing.

## Statistical data analysis of Ocean Ltd competitor

Calculations of representatives values: Mean, Median, Mode and quartiles are used to summarise the data set by using Microsoft Excel to make these calculations fairly simple.

## 1. Calculation of Mean

The mean () of the sample is calculated by the sum of the values (âˆ‘) divided by number of values (n).

= âˆ‘x /n

## Months

## ROI (%)

## 1

## 2.36

## 2

## 5.73

## 3

## 6.6

## 4

## 10.05

## 5

## 5.13

## 6

## 1.88

## 7

## 2.52

## 8

## 2

## 9

## 4.69

## 10

## 1.91

## 11

## 6.75

## 12

## 3.92

## 13

## 3.46

## 14

## 2.64

## 15

## 3.63

## 16

## 3.44

## 17

## 9.49

## 18

## 4.9

## 19

## 7.45

## 20

## 20.23

## 21

## 3.91

## 22

## 1.7

## 23

## 16.29

## 24

## 5.52

## 25

## 1.44

## Sum

## 137.64

## Mean

## 5.5056Table 5

Value of n = 25

## Mean = 5.5%

## 2. Calculation of Mode

Table 5 shows that the data set does not have a most frequently occurring value, therefore the mode is undefined.

## 3. Calculation of Median and the Quartiles

To find the median and the quartiles, the values are arranged in the ascending order.

## ROI (%)

## 1

## 1.44

## 2

## 1.7

## 3

## 1.88

## 4

## 1.91

## 5

## 2

## 6

## 2.36

## 7

## 2.52

## 8

## 2.64

## 9

## 3.44

## 10

## 3.46

## 11

## 3.63

## 12

## 3.91

## 13

## 3.92

## 14

## 4.69

## 15

## 4.9

## 16

## 5.13

## 17

## 5.52

## 18

## 5.73

## 19

## 6.6

## 20

## 6.75

## 21

## 7.45

## 22

## 9.49

## 23

## 10.05

## 24

## 16.29

## 25

## 20.23Table 6

The value of the middle item of the ordered list represents the median of the sample. Hence,

Median = (n + 1) th item

2

= (25 +1) / 2 = 13th item

## Median = 3.92%

Lower quartile = 0.25 * (n + 1) th item

= 0.25 * (25 + 1) th item

= 6.5th item

6.5h item lies between 2.36 and 2.52, therefore

## Lower quartile = 0.5 * (2.52 - 2.36) + 2.36 = 2.44%

Upper quartile = 0.75 * (n + 1) th item

= 0.75 * (25 +1) th item

= 19.5th item

19.5th item lies between 6.6 and 6.75, therefore

Upper quartile = 0.5 * (6.75 - 6.6) + 6.6 = 6.675%

## Inter-quartile range = 6.675 - 2.44 = 4.235%

From the above measures we can conclude that:

The extreme values in the data set give a high mean value, which is misleading and not truly representative value of the whole data set.

The mode does not prove to be an efficient measure because no distinct modal values occur in the data set.

Because of the extreme values the median proves to be the more appropriate summary measure.

The median is less than the mean, this provides evidence that the data is positively skewed (skewed to the right).

## Calculation of Variance and Standard Deviation

Variance measures the spread of the set of data. The variance (S2) is calculated by using the shortcut formula:

S2 = âˆ‘x2 - (âˆ‘x)2/n

n - 1

x x2

1

2.36

5.57

2

5.73

32.83

3

6.6

43.56

4

10.05

101

5

5.13

26.32

6

1.88

3.53

7

2.52

6.35

8

2

4

9

4.69

21.99

10

1.91

3.65

11

6.75

45.56

12

3.92

15.37

13

3.46

11.97

14

2.64

6.97

15

3.63

13.18

16

3.44

11.83

17

9.49

90.06

18

4.9

24.01

19

7.45

55.5

20

20.23

409.25

21

3.91

15.29

22

1.7

2.9

23

16.29

265.36

24

5.52

30.47

25

1.44

2.07

Sum =

137.64

1248.59Table 7

Variance of sample = 1248.59 - 137.642/25 = 20.45%

25 - 1

Standard deviation (S) is the square root of variance, therefore

Standard deviation = âˆšS2 = âˆš20.25 = 4.52%

As the data set is skewed, the variance / standard deviation is influenced by the extreme values, which give it a high value (4.52%).

As a consequence, the median (3.92%) and the inter-quartile range (4.235%) are providing more suitable measures of dispersion.

## Construction of Histogram

To help in the decision- making process, a histogram is drawn to illustrate the distributional shape of the data.

## Group tabulated data with unequal width

## ROI %

## Frequency

## Class width

## Frequency density

0 to < 2

4

2

2

2 to < 4

9

2

4.5 (highest)

4 to < 6

5

2

2.5

6 to < 8

3

2

1.5

8 to < 12

2

4

0.5

12 to <17

1

5

0.2

17 to < 22

1

5

0.2

## Table 8

The modal group is 2 to < 4, as this group has the largest frequency density.

## Histogram to show the distribution of data

## Frequency density

ROI %The histogram clearly shows that the data set is positively skewed. The median is less than the mean. This means the high percentages of ROI have low frequencies.

## The relationship between the mean, median and mode

## (See reference for source of this graph)

## Project evaluation

Statistical analysis of Ocean Ltd's competitor proves that during the 25 months most of the ROI values were low. However, the competitor used a less advanced machine than the scan machine our company is interested to invest on. Therefore, we believe that with the sophisticated hi-tech body-scan machines and if the economic climate is favourable, our ROI will be higher.

## Sales forecast for the next 5 years

Number of outfits for sales in the 1st year = 5000 * 12 = 60,000

Cost of one outfit = £ 400

Gross profit = 40% of sales value

Then, cost of production (60%) = 400 * 60,000 = £ 24 m, hence

## 1st year: Sales (100%) = 24 * 100 = £ 40 m

## 60

1st year: gross profit = 40 - 24 = £ 16 m

From the secondary data collected on the economic climate in UK, output is expected to grow by 1.2% in 2010 and by 2.5% in 2011. Therefore, we are assuming that in the following year sales may rise from 5000 outfits to 6000 monthly and,

Gross profit to be 40%,

Then, cost of production (60%) = 400 * 6000 * 12 = £ 28.8 m

## 2nd year: Sales (100%) = 28.8 * 100 = £ 48 m

## 60

2nd year: gross profit = 48 - 28.8 = £ 19.2 m

% increase in sales = 48 - 40 * 100 = 20%

40

To estimate the sales for next years, multiplied by (100 + 20) = 1.2, that is, increase

100

sales by 20% each year. Therefore,

## 3rd year: sales = 48 *1.2 = £ 57.6 m

## 4th year: sales = 57.6 * 1.2 = £ 69.12 m

## 5th year sales: = 69.12 *1.2 = £ 82.94 m

## Year

## 1

## 2

## 3

## 4

## 5

## Sales in millions £

40

48

57.6

69.12

82.94

## Table 9

The above graph shows a line sloping upwards, showing that every year the value of sales will increase.

## Sales and marketing expenditure for the next 5 years

1st year: Gross profit = £ 16 m

Assuming marketing expenditure = 5% of gross profit, as more money should be spent on marketing to keep the demands of goods high in the market.

## 1st year: Marketing expenditure = 5% * 16 = £ 0.8 m

2nd year: Gross profit = £ 19.2 m

Let assume marketing expenditure to increase to 5.4%, then

## 2nd year: Marketing expenditure = 5.4% * £ 19.2 m = £ 1.04 m

% increase in marketing expenditure = 1.04 - 0.8 * 100 = 30%, therefore

0.8

## 3rd year: Marketing expenditure = (100 + 30) * 1.04 = £ 1.35

## 100

## 4th year: Marketing expenditure = 1.3 * 1.35 = £ 1.76

## 5th year: Marketing expenditure = 1.3 * 1.76 = £ 2.28

## Year

## Sales (in millions £)

## Marketing expenditure

## (in millions £)

## 1

## 40

## 0.8

## 2

## 48

## 1.04

## 3

## 57.6

## 1.35

## 4

## 69.12

## 1.76

## 5

## 82.94

## 2.28

## Table 10

The scatter diagram indicates that the more money spent on marketing, the greater the value of sales. It also suggests that there is a relationship between sales and marketing expenditure. This is because the pattern of the points roughly forms a straight line sloping upwards, suggesting that there is possibly a linear association between the two variables.

## Correlation between sales and marketing expenditure

## Year

## Sales

## Marketing

## Expenditure

## x

## y

## xy

## x2

## y2

1

40

0.8

32

1600

0.64

2

48

1.04

49.9

2303

1.08

3

57.6

1.35

77.8

3317.8

1.82

4

69.12

1.76

121.7

4777.6

3.1

5

82.94

2.28

189.1

6879

5.2

Sum (âˆ‘)

297.66

7.23

470.5

18877.4

11.84

## Table 11

Correlation can be calculated by the formula:

r = sxy / âˆšsxxsyy

Where r = -1â€¹ r â€º +1

sxy = âˆ‘xy - âˆ‘xâˆ‘y/ n = 470.5 - 297.66 * 7.23 = 40.08

5

sxx = âˆ‘x2 - (âˆ‘x)2/n = 18877.4 - 297.662 = 1157.1

5

syy = âˆ‘y2 - (âˆ‘y)2/n = 11.84 - 7.232 = 1.39

5

r = sxy / âˆšsxxsyy = 40.08 /âˆš1157.1 * 1.39

=40.08 / 47.28

= 0.85

The value of r = +0.85 lies between -1 and +1 and it is close to +1. Therefore it can be said that there is a strong positive correlation between sales and marketing expenditure.

## Profit & loss account forecast for next 5 years

Based on the secondary data collected,

- The company has 50 employees.

- Machine operator will earn £ 60 per hour, other employees £ 40 per hour each.

- The machine can scan 60 persons per hour.

We assume that the company employs 10 machine operators, 40 employees and each worker works 40 hours per week.

Annual wages for operators will be = 10 * 40 hr * £ 60 * 52 weeks = £ 1,248,000

Annual wages for employees will be = 40 * 40 hr * £ 40 * 52 weeks = £ 3,328,000

Assuming overtime payments to be £ 424,000

Total expense on wages = £ 5 m

Other expenses (electricity, gas, water, maintenance, etc.) = £ 1m

1st year: Marketing expenditure (as calculated before) = £ 0.8 m, therefore

1st year: Total expenses = 5 + 1+ 0.8= £ 6.8 m

1st year: Gross profit = £ 16 m

Based on the above assumptions,

1st year: Profit before tax = 16 - 6.8 = £ 9.2 m

Tax = 20%

Tax to be paid = 20% * 9.2 = £ 1.84 m

## 1st year: Net profit (cash flow) = 9.2 - 1.84 = £ 7.36 m

2nd year: Gross profit = £ 19.2 m

2nd year: Marketing expenditure = £ 1.04 m

Assuming wages and other expenses to be the same

2nd year: Total expenses = 5 +1 + 1.04 = £ 7.04 m

2nd year: Profit before tax = 19.2 - 7.04 = £ 12.16 m

## 2nd year: Net profit (cash flow) = 12.16 - (20% * 12.16) = £ 9.73 m

% increase in net profit = 9.48 - 7.36 * 100 = 32.2 %, therefore

7.36

## 3rd year: Net profit = 1.322 * 9.73 = £ 12.86 m

## 4th year: Net profit = 1.322 * 12.86 = £ 17 m

## 5th year: Net profit = 1.322 * 17 = £ 22.47 m

## Year

1

2

3

4

5

## Net profit (cash flow) in £ m

7.36

9.73

12.86

17

22.47

## Table 12

## Investment valuation of project using financial tools

## 1. Calculation of Accounting Rate of Return (ARR)

ARR = Average annual profit before tax / Average capital invested

As calculated before,

1st year: Profit before tax = £ 9.2 m

2nd year: Profit before tax = £ 12.16 m

% increase in profit = 12.16 - 9.2 * 100 = 32%, therefore

9.2

3rd year: Profit = 1.32 * 12.16 = £ 16.05 m

4th year: Profit = 1.32 * 16.08 = £ 21.22 m

5th year: Profit = 1.32 * 21.19 = £ 28.01 m

## Year

## Profit before tax (£ m)

## 1

## 9.2

## 2

## 12.16

## 3

## 16.05

## 4

## 21.22

## 5

## 28.08

## Sum

## 86.71

## Table 13

Machine's life span = 5 years

Average annual profit before tax = Sum of all annual profit before tax

No of years of project life

= 86.71 = £ 17.34 m

5

Average capital employed = (Initial capital employed + Residual value) / 2

Initial capital employed (I0) = £ 0.15 m

Taking residual value to be 0,

Average capital employed = 0.15 + 0 = £ 0.075 m

2

## ARR = 17.34 = 231.2 %

## 0.075

## 2. Calculations of Payback (PB) and Discounted payback (DPB)

Initial investment (I0) = £ 150.000 = £ 0.15 m

Required rate of return = 8%

Future value (FV) = Payback

Present value (PV) = Discounted payback, which is calculated by the formula:

PVn = FV/ (1 + k)n, where

k: required rate of return

n: number of years

1 / (1 + k)n: present value interest factor.

Therefore,

1st year: PV1 = 7.36 / (1 + 0.08) = 6.81

2nd year: PV2 = 9.73 / (1 + 0.08)2 = 8.34

3rd year: PV3 = 12.86 / (1 + 0.08)3 = 10.2

4th year: PV4 = 17 / (1 + 0.08)4 = 12.5

5th year: PV5 = 22.47 / (1 + 0.08)5 = 15.3

## Year

## Net cash flow (£ m)

## Cumulative cash flow

## PB

## DPB

## PB

## DPB

0

- 0.15

- 0.15

- 0.15

- 0.15

1

7.36

6.81

7.21

6.66

2

9.73

8.34

16.94

15

3

12.86

10.2

29.8

25.2

4

17

12.5

46.8

37.7

5

22.47

15.3

69.27

## 53 (= NPV)

Payback period

0.074 year

0.79 year

## Table 14

## 3. Calculation of Net Present Value (NPV)

NPV is calculated by:

NPV = âˆ‘ [CFt / (1 + k)t] - I0

CF: cash flow

I0: Initial investment

NPV = (7.36 / 1.08) + (9.73 / 1.082) + (12.86 / 1.083) + (17 / 1.084) + (22.47 / 1.085) - 0.15

## Hence NPV of the investment =£ 53 m

NPV is a positive value; therefore we can accept the investment.

## 4. Calculation of Internal Rate of Return (IRR)

IRR = rate that makes the NPV equal the investment

IRR = positive rate + [positive rate / (positive NPV - negative NPV)] * range of rate)

When rate of return is 8 %, NPV = £ 53 m

By trial and error:

When k1 = 4900%

NPV1 = (7.36 / 50) + (9.73 / 502) + (12.86 / 503) + (17 / 504) + (22.47 / 505) - 0.15

= 0.151 - 0.15 = 0.001

When k2 = 5000%

NPV2 = (7.36 / 51) + (9.73 / 512) + (12.86 / 513) + (17 / 514) + (22.47 / 51 5) - 0.15

= 0.148 - 0.15 = - 0.098

Range of rate: 4900% - 5000%

IRR = k1 + [NPV1 / (NPV1 - NPV2)] * (k2 - k1)

= 4900 + [0.001 / (0.001 + 0.098)] * (5000 - 4900)

= 4901.01%

## Cost of capital

## Present value of cash flow

## I0

## NPV

8%

53.15

0.15

53

4900%

0.151

0.15

0.001

5000%

0.148

0.15

-0.098

## Table 15

The IRR is very high as compared to the required rate of return; it just shows the high profitability of the project.

## Selection of financial tool for the project

## Financial tools

## Value

DPB period

0.79 year

NPV

£53 m

IRR

4901%In practice: IRR>NPV>DPB

IRR is selected because it has the highest value. The investment of £ 0.15 m can be paid back in the 1st year. The company will benefit a cumulative cash flow of around £ 53 m in five years.

## Inventory control systems in an organisation

Inventory control systems deal with the maintenance of information about activities within an organisation that ensures the ordering and delivery of materials. The systems include:

Costs of keeping inventory - unit cost, ordering and delivery cost, holding cost, shortage cost.

The basic Economic Order Quantity (batch size).

Other inventory models include:

Lead time - deliveries take a certain lead time to arrive. Orders must be placed lead time units before stocks reach zero.

Allowing shortages - shortages saves ordering cost and holding cost but increases shortage costs. Shortage costs arise with unmet and backlogged demand.

Allowing quantity discount.

These functions need to be performed in sequence to result in a well run inventory control system.

In the present business environment all businesses small and mid size rely on computerised inventory management systems.

## Calculation of Economic Order Quantities (EOQ)

EOQ can be calculated by:

q = âˆš2KD / h, where

q: quantity of units ordered per batch.

Given that 5000 outfits will be produced per month in the 1st year and each outfit requires 2 units of raw material.

D = constant rate of demand = 2 * 5000 = 10,000 units

K = ordering cost/set-up cost = £ 5,000

h = holding cost per units = £ 0.30

Therefore,

q = âˆš2 * 5,000 *10,000 = 18257.42 units

0.30

Cycle length = q / D = 18257 = 1.8257 month

10,000

This means 18,257 units of material will be ordered per batch every 1.8 months.

2nd year: 6,000 outfits / month

% increase of outfits/month each year = 6,000 - 5000 * 100 = 20%

5,000

3rd year: 1.2 * 6,000 = 7,200 outfits/month

4th year: 1.2 * 7200 = 8,640 outfits/month

5th year: 1.2 * 8640 = 10,368 outfits/month

## EOQ for next 5 years

## Year

## Â

## Â

## Â

## No of

## Outfits /month

## Â

## Â

## Units of

## material

## required

## D

## Ordering

## cost (£)

## Â

## K

## Holding

## cost (£)

## Â

## h

## EOQ

## (units per

## batch)

## q

## Cycle

## Length/

## month

## Â

## 1

## 5,000

## 10,000

## 5,000

## 0.3

## 18,257

## 1.8

## 2

## 6,000

## 12,000

## 5,000

## 0.3

## 20,000

## 1.6

## 3

## 7,200

## 14,400

## 5,000

## 0.3

## 21,909

## 1.5

## 4

## 8,640

## 17,280

## 5,000

## 0.3

## 24,000

## 1.4

## 5

## 10,368

## 20,736

## 5,000

## 0.3

## 26,290

## 1.3

## Table 15

## Conclusion

Based on our assumptions and forecast, we are expecting the UK economy to exit from recession and returning to growth, and an increase in consumer buying behaviours. If this is the trend then the company can invest on the new project and benefit a cumulative cash flow of around £ 53 m in five years. However if the economic climate deteriorates or remains the same, we believe the company can still invest in the project as based on our assumptions, financial tools provide evidence that the investment can be paid back in the first year.

## Reference

## Module Tutor Lecture notes:

Hai Le., 2009. Business Decision Making (unit 6) H2, HND in Business. London: Guildhall College

## Websites:

## http://www.idatservices.com/images/services.jpg

## http://www.guardian.co.uk/business/2009/dec/21/cbi-economic-growth-recession

http://www.guardian.co.uk/business/2009/dec/23/uk-economy-still-vulnerable-bank-of-england

http://cashflow.rbs.co.uk/?DCMP=KNC-RBSCSHFLWPPC&gclid=CMSr7uze7J4CFUQA4wodx0iCIA

http://tutor2u.net/business/ict/intro_information_system_types.htm

http://images.google.co.uk/imgres?imgurl=http://onlineacademics.org/CA670/positiveskew.jpg&imgrefurl=http://onlineacademics.org/CA670/&usg=__2OmqlHCC9-CQh_aHWHubkRwGKfE=&h=360&w=480&sz=22&hl=en&start=57&um=1&tbnid=080MxkMhClOXeM:&tbnh=97&tbnw=129&prev=/images%3Fq%3Dpositively%2Bskewed%2Bdistribution%26ndsp%3D18%26hl%3Den%26client%3Dfirefox-a%26rls%3Dorg.mozilla:en-US:official%26sa%3DN%26start%3D54%26um%3D1