Decision Making

INDEX

Page no

Introduction 2

1.1 create a plan for the collection of primary and secondarydata for a given business problem 2

1.2 present the survey methodology and sampling frame used 4

1.3 design a questionnaire for a given business problem 6

2.1 create information for decision making by summarising datausing representative values 7

2.2 analyse the data to draw valid conclusions in a business context 10

2.3 analyse data using measures of dispersion to inform a givenbusiness scenario 12

2.4 explain how quartiles, percentiles and the correlation coefficient areused to draw useful conclusions in a business context 13

3.1 produce graphs using spreadsheets and draw valid conclusions basedon the information derived 15

3.2 create trend lines in spreadsheet graphs to assist in forecasting forspecified business information 16

3.3 Prepare a business presentation using suitable software and techniques to disseminate information effectively 17

3.4 Prepare a formal business report 18

4.1 use appropriate information processing tools 18

4.2 Prepare a project plan for an activity and determine the critical path 19

4.3 Use financial tools for decision making 21

Conclusion 22

References 23

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Introduction:

In business, making good decisions requires the effective use of information. Business

Decision Making provides the opportunity of learning a variety of sources and develops

techniques in four aspects of information: data gathering, data storage, tools available

to create useful information and presenting.

Moreover, using appropriate IT software and spreadsheets for data analysis and the

preparation of information provides the advantages of using information systems which

is currently used at all levels in every organisation.

Everpia London, a company with 100% Korean invested capital is the owner of high-

grade Everon bedding- a reputable brand for lots of consumer in London. It has already

3 factories in Luton and Essex and now wants to establish one more factories in order

to expand its activity.

Business Decision Making Purpose and aim of this assessment will give the author

opportunity to examine a variety of data sources. For any of the given scenarios, he will

collect data from different sources by using variety of methods, and will use

spreadsheets and other software for data analysis and the preparation of information in

an effective manner. Conclusions on the basis of data analysis are required to clarify

the importance and use of different data analysis techniques.

1.1 Prepare and implement a plan for the collection of primary and secondary

data

The Evepia’s criteria in choosing the most appropriate location for the new factory

embraced a plenty of small and medium English enterprises (SMEs), the closest

geographical match, and the production capacity and behavior toward their partners

which specialize in textiles in that location are good. And in order to find out the most

suitable province, we have to collect both secondary and primary data.

Secondary data

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The secondary data are data which have already been collected elsewhere, for some

other purpose, but which can be used or adapted for the survey being conduct (Bpp,

2004, p.7). So that the author can use the secondary data to assess the first two criteria

of Everpia: the province which having a large number of textiles companies and short

distances between Everpia and those companies. These secondary data below are

used:

• The geographical location of each province: find out location of the province which is

nearest to Everpia Office in Luton (Bradfordshire). We can localize it within 50km from

Luton and then searching on Google or from the Atlas Geography of London to

determine the province that reach the condition.

• The area of each province: we need to find information about this to know if it suitable

for the construction of the factory or not. We can find it on the General Statistics Office

of London (GSO)’s website, in Statistics data: land used by province. These data bring

us the information of the land use on different purposes so that we can know how many

areas have been used and if Everpia can build a factory there or not.

• The number of SMEs which specialized in textiles: find out the province that has textile

is the leading economic power or which province has the big concentration of small and

medium textile companies. This kind of information can be found from the Department

of Planning and Investment (DPI)’s website of each province. For example: the website

hungyenbusiness.gov.uk, use function “Finding enterprises by branch”. It will provide us

the accuracy source on registered firms and their kind of business. And a very important

thing that we need to know is the legitimacy of the company. So we must contact a

Chamber of Commerce or Government Trade Office to verify their legitimacy.

•Population of each province: this data help us to figure out where the human resource

is abundant and favorable for employees seeking for the factory. We can search on

GSO’s website; there is the data of average population by province there.

With all the secondary data above we can choose out 3 cities that have the best fits with

the first two criteria that are provided by Everpia.

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Besides, it is better that we can see first-hand the reality, by observation we will know

clearer about the factors that can influence our decision in choosing the province.

Primary data

From the data that we have searched from the secondary data the number of SMEs

which specialized in textiles, we can list out the textile companies of each province with

this information: Name of the company, the location and kinds of textile manufacturing

that they do.

In order to investigate the production capacity and the firm behavior we need to collect

primary data. Primary data are collected especially for the purpose of whatever survey

is being conducted (Bpp, 2004, p7).

In this case, we will do a survey to investigate the companies' features to satisfy the

third criteria by finding the information about fixed and operating capital, number of

employees, their education and skills, management skills and the credibility. The survey

methodology is presented below.

1.2 Present the survey methodology and sampling frame used

The list of textiles companies in 3 cities is called the sampling frame. After having the

sampling frame we continue to pick out sample for the investigation of firm’s production

capacity and their behavior towards clients. Because of the unnecessary and wasting

time and money, we cannot evaluate all the companies that have in the list, we just

select some of the companies to represent for the rest by using sampling method or in

other words we use the sampling method to narrow the range of the surveyed firm. Here

we have the list of all textile companies that have common conditions like: all located

within 50km from London, all are textile companies, etc but different in province where

they located in. So the stratified method is the most suitable method that we can use.

Take an example in using stratified method to pick out the sample:

As we have 3 strata are 3 provinces named A, B and C.

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Province A has 15 textile companies

Province B has 15 textile companies

Province C has 30 textile companies.

Total: 60 textile companies

Assume that we are taking 12 from 60 textiles companies to investigate.

The first step is we have to calculate the percentage of each group (each cities)

% textile company in province A: 15/60.100% = 25%

% textile company in province B: 15/60.100% = 25%

% textile company in province C: 30/60.100% = 50%

So that our 12 samples must be:

20% of the textile company in province A = (25x12)/100 = 3 companies

40% of the textile company in province B= (25x12)/100= 3 companies

40% of the textile company in province C= (50x12)/100= 6 companies.

Now we can choose 3 companies from province A, 3 companies from province B and 6

companies from province C to investigate by survey method.

Furthermore, because Everpia wants to choose companies are belonging to three-digit

sub-industries of textile: Spinning, weaving and fishing of textiles (171), Manufacture of

other textiles (172) and Manufacture of knitted and crocheted fabric and articles (173)

so firstly, we need to divide all the companies in each province to 3 part. Part 1, part 2

and part 3 that are belonged to three-digit sub-industries of textile: 171, 172, 173,

respectively. Secondly, we choose the company based on these conditions: in each

province we need to choose 3 types of sub-industries of textile and exactly the number

of company that we have calculated above. For example: in province A we have to

choose 3 companies and those 3 companies are from different kind of sub-industries of

textile, it means that we will choose 3 companies from province A, 1 company is (171)

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type, 1 company is (172) type and 1 company is (173) type. It’s similar with the two

remaining cities.

1.3 design a questionnaire for a given business problem

Next, our task is to find out firm’s production capacity and company’s behavior towards

clients. In order to collect information from those companies, the questionnaire is used.

Depending on the purpose we design the question relevant. Furthermore, we also need

to identify the targeting respondent for the questionnaire to get the accurate information

and we will decide which is the best method to collect the information from the

questionnaire.

Here we have to investigate about the company capacity as well as their behavior

toward the clients so we need to ask questions about the capital (include fixed and

operating capital) of the company, their profit every year, their liquidity, debts, the official

employees that the company have, level education of their employees, about their

performance, the employees’ skill in textile, their amount of product that they produce in

a month (year), the manager’s skill, level education of the manager, their attitude about

the company’s responsibility with clients etc. So the targeting respondent for those

questions is the director or the CEO of the company who knows best about the

company situation as well as the data of everything in the company. And in this case,

the personal interview is the best choice although it may cost more of money. In a

personal interview the interviewer can avoid all the misunderstanding of the interviewee

and moreover, the interview can grasp the situation and more active in colleting the

necessary information for the survey, so it’s more efficient.

And because this questionnaire are designed for a personal interview so almost the

questions in there are open-ended questions.

The questionnaire has the structure as below

The first is the introduction to introduce about our company and questionnaire’s

purpose.

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The second is the content of the questionnaire:

About the company’s situation at present: 6 questions

About the employees and managers of the company, the assessment of their skill: 10

questions

About their attitude with clients: 3 questions

About the company’s equipment: 2 questions

About the company’s partnership: 2 questions.

The detailed questionnaire is in the appendix 1.

2.1 create information for decision making by summarising data using representative values

The representative values includes mean, median and mode, it can be calculated by

using the measure of location. By using formula in Excel, we have this histrogram:

Expected salary per year:

Mean 48,6997

Median 40,000

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Mode 40,000

First quartile 30,000

Third quartile 50,000

Skewness 8.862355137

With this variable, the median and the mode are the same but different with the mean.

The mean is 48.6997992

* The average salary that the students at the University of New South Wales, UK

expect each year is ≈£48,700 per year.

The median is 40,000

* It means that there are 50% students expect their salary each year above £40,000

and 50% of students expect their salary per year below £40,000.

The mode is 40,000

* £40,000 is the salary that has the highest choice for the expected salary of students

at University of New South Wales, UK.

The first quartile is 30,000

* 25% students at University of New South Wales, UK expect their salary equal or less

than £30,000/year.

The second quartile is the median.

The third quartile is 50,000

* 75% students of University of New South Wales, UK expect their salary equal or less

than £50,000 per year.

Age:

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Mean 22.48394

Median 21

Mode 22

First quartile 20

Third quartile 24

Skewness 6.565967484

Age Distribution of New South Wales students.

With this variable, the mean, mode and median are nearly the same.

The mean is 22.48394

* The average age of the students at University of New South Wales, UK is ≈ 22,5.

The median is 21

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* In the University of New South Wales there are 50% of students have the age above

21 and 50% of students have the age below 21.

The mode is 22

* The number of student aged 22 is the most popular in the University.

The first quartile is 20

* 25% students aged equal or less than 20.

The third quartile is 24

* 75% students aged equal or less than 24.

* When there are extreme values in a set of data, we prefer to use mode or median,

because the mean will be affected by the extreme values so it makes the result

inappropriate.

With the data of culture back-ground, because it’s qualitative data so we cannot find the

mean or median we just find out that UK is the culture back-ground that occur the most

in the data.

2.2 analyse the data to draw valid conclusions in a business context

To calculate the skewness of data distribution, we use the Coefficient of Skewness

formula.

If C of S is nearly +1 or -1, the distribution is highly skewed.

In this case, we can see that both C of V of age and expected salary are positive

* The distribution is skew to the right.

Because the skewness of expected salary is higher than the skewness of age so the

expected salary is more spread out.

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We can see the histograms which are drew below to check the data distribution that we

have commented.

Salary:

Salary Frequency Cumulative %

100,000-200,000 9 99.20%

>200,000-800,000 4 100.00%

>800,000 0 100.00%

A suitable survey methodology in terms of population, sample and sampling methods

that could be used to collect the New Wales University’s studentss salary, wages about

their opinions on the different range available on the market is the different types of

sampling methods, which are used to gathering information about a studentss. The

alternative would be to test, measure or question every member of the students, this

might be impractical because It could take too long, difficult to access all items in

students such as their national insurance and tax contribution, it’s too expensive and

total students size may be unknown.

Advantages of sampling; is that it saves time and money, and sometimes can be the

only option. Disadvantages are that sampling error, this is when sample is not

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representative of total university’s expenditure, this bias can be computed and

analysed. Non sampling errors, this is when missing data, defective questionnaires etc,

these cannot be computed and analysed so sampling must be planned and carried out

well.

2.3 analyse data using measures of dispersion to inform a given business

scenario

Cross table showing the distribution of data by cultural background and expected salary

Count of expected salary Cultural background

Expected salary English Chinese Germanic Indian Latin Slavonic Other

1000-20.000 53 6 0 0 0 0 2

>20.000-40.000 163 26 3 4 2 0 23

>40.000-60.000 92 23 1 8 0 4 10

>60.000-80.000 20 6 3 4 0 1 7

>80.000-100.000 15 3 1 0 1 1 2

>100.000-200.000 2 3 0 1 0 1 2

>200.000-800.000 0 4 0 0 0 0 0

Total 350 67 8 17 3 7 46

Look at the table above, we can see that almost the culture back-ground of students at

University of New South Wales, United Kingdom. With 350 students out of total 499

students, the number of English students will influence the number of the other culture

back-ground so we cannot see the relationship between the culture back-ground and

the expected salary of the students correctly.

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Cross table showing the distribution of data by gender and expected salary

Count of expected salary Gender

Expected salary Male Female

20.000-40.000 97 125

>40.000-60.000 53 85

>60.000-80.000 19 22

>80.000-100.000 7 16

>100.000-200.000 5 4

>200.000-800.000 0 4

Total 206 292

Look at the table above, we can see that at the different salary from less than £20,000

to £100,000 the number of male and female is similar (because there are more female

than male here). But the female are tend to expect the salary higher than the male.

There are 8 females have the expected salary from over £100,000 to £800,000 per year

while there’re only 5 males who want to have the salary over £100,000 per year. May be

the male are much more realistic than the female so they just expect the lower salary

than the female.

2.4 explain how quartiles, percentiles and the correlation coefficient are used to

draw useful conclusions in a business context

Quartile: ‘Quartile represents the middle value between two quarters of a distribution’

(Dransfield, 2003). The lower quartile is the value between the first and second quarter

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of the distribution. The upper quartile is the value between the third and fourth quarter of

the distribution. The middle quarter is called median.

Percentile: Percentiles are values that divide a sample of data into one hundred groups

containing equal numbers of observations. For example, 30% of the data values lie

below the 30th percentile (Easton and McColl, 2010).

Coefficient: the coefficient of variation measures the spread of a set of data as a

proportion of its mean. It is the ratio of the sample standard deviation to the sample

mean. It is often expressed as a percentage (Easton and McColl, 2010).

Quartiles, deciles, and percentiles divide a frequency distribution into a number of parts

containing equal frequencies. According to the 50% students expect their salary each

year above £40,000 and 50% of students expect their salary per year below £40,000.

The items are first put into order of increasing magnitude. Quartiles divide the range of

values into four parts, each containing one quarter of the values. Again, if an item

comes exactly on a dividing line, half of salary of students counted in the group above

and half is counted below. Similarly, deciles divide into ten parts, each containing one

tenth of the total frequency, and percentiles divide into a hundred parts, each containing

one hundredth of the total frequency. If we think again about the median, it is the

second or middle quartile, the fifth decile, and the fiftieth percentile. If a quartile, decile,

or percentile falls between two items in order of size, for our purposes the value halfway

between the two items will be used. Other conventions are also common, but the effect

of different choices is usually not important.

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3.1 produce graphs using spreadsheets and draw valid conclusions based on the

information derived

2003 2004 2005 20060

102030405060708090

DomesticInternational

The line chart shows the trend which took place in sales of domestic and international

markets during the four-year period from 2003-2006. As we can see in the chart, the

trends of two markets were contradictory. Firstly, in 2003 there was a big different

between the sales of domestic and export markets because the export sales was 10

times higher than the domestic sales with £80,5m and £8,4 m, respectively. However, in

2004 the export sales sudden plunged significantly from £80,5m to £37,4m and

continued to go down in subsequent years and remarkable decrease to £1,8 m in 2006

while the domestic sales from 2003-2006 were erratic a little bit but in general it still

remained stable, from £8,4 m in 2003 to £13,8 m in 2006. It can be said that Everpia

Company has found the stability in domestic market but they were losing their place in

the international markets although they used to be successful before with the high

sales. So it’s necessary that the company need to attach more special importance to the

international market by some prosper strategy and plan in marketing or in the quality of

product in order to affirmed the company’s brand and attract more foreign partner.

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3.2 create trend lines in spreadsheet graphs to assist in forecasting for specified business information

(This tread line chart has drawn by J. Scott Armstrong is quite hypothetical http://bit.ly/bj8IKv)

The chart above illustrates the use of a third order polynomial and projects a

significantly higher 30-period outcome of the sales information.

The forecasting problem is integral to successful enterprise such as Everpia Company.

Yet, many senior executives, managers, and administrators have difficulty interpreting

the meaning of a given time-series forecast based on methodology alone in the

business information.

We have used the forecasts generated by each method are quite different from each

other. Moreover, the methods depicted above illustrate only a small sampling of the

most common time-series forecasting techniques in use today. Other forecasting

methods include such techniques as autoregressive moving averages, generalized

autoregressive conditional heteroskedastic methods, multivariate forecasting methods,

and a long list of other advanced techniques in frequent use by companies.

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3.3 Prepare a business presentation using suitable software and techniques to disseminate information effectively

Power Point, Excel will be the medium for the presentation to the CEO and other high

ranking officers of the company. The author chose this medium because Power Point is

powerful, easy-to-use presentation software that is part of the Microsoft Office suite of

products. We can use Power Point to create presentations for a wide variety of

audiences and for a wide variety of purposes. PowerPoint tenders a number of

advantages over traditional methods for presentations. Some advantages include the

following:

--Easy to edit

--Professional appearance

--Can be used in a small classroom up to a large auditorium

--Flexible

--Slides can't get lost

--Allows for dynamic content on slides, in the form of animations, multi-media inserts,

etc.

--Can easily be exported to the web for viewing

The image the author wants to portray is strong confidence, business capability, and

wide-ranging knowledge of the distance learning market, including the current demand

of that market. It is essential that the author speak with confidence and belief, so that

the CEO and other high ranking officers of the company will see that the author really

believe in what speaking of. The information the author will present will have the exact

data which are usually required for a research paper (Introduction, Body, and

Conclusion).

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As a final point, the image the author will portray would most likely encompass a

positive reflection of distance learning and how my company will undeniably be a

valuable and profitable business endeavor.

3.4 Prepare a formal business report

February 3, 2011

Ms. Leonore Fielding

Vice-President of Operations

Everpia Group, London,

UK

Dear Ms. Fielding

The attached report, which you requested on January 1, represents our findings

regarding the survey publications at bedding Manufacturing.

Our report includes an assessment of current publications at London as well as an

analysis of the current and future communication needs of your company.

The communications action plan outlined in our report reflects the results of our

research both within the company and in the national and international marketplace. We

are especially grateful to the Everpia staff, in particular the members of the

communications group, for their input.

I look forward to discussing our recommendations with you and will be happy to meet

with you and your staff regarding our report and its exciting implications for Pemberton.

Sincerely

Mr. X

4.1 use appropriate information processing tools

All the business organisations require information for following purposes;

* Planning

* Controlling

* Recording transactions

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* Performance measurement and

* Decision making

In order to fulfil those purposes, good quality information is needed. There are three

types of information. They are Strategic, Tactical and Operational information.

Strategic information is used for planning the organisation’s long term objectives and

goals and the senior managers are involved. It is both quantitative and qualitative but

the future cannot be predicted.

Tactical information is short and medium term planning in which productivity

measurements are included. It is generated internally and external component are

limited. It based on quantitative measures and prepared regularly.

Operational information is used to ensure specific tasks properly within a factory or

office. It is relevant to day-to-day plans which involve all managers. It is largely

quantitative and task-specific.

In Management Information System (MIS), the installation of new IT will be identified as

Operational decision.

4.2 Prepare a project plan for an activity and determine the critical path

This section shall contain, either directly or by reference, plans for the supporting

functions of the software project. Supporting functions include (but may not be limited

to):

• Software quality assurance,

• Verification and validation plans,

• Production support and operational support functions.

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Work Packages, Schedules, and Budget

The Gantt Chart shows the a project plan analysis dateline.

This section of the Project Management Plan will specify the work packages, identify the

dependency relationships among them, state the project resource requirements, provide

the allocation of budget and resources to work packages, and establish a project

schedule.

1 Work Packages

This subsection will define the work packages (work breakdown structure (WBS)) for the

activities and tasks that must be completed in order to satisfy the project agreement.

Each work package must be uniquely identified; identification may be based on a

numbering scheme and descriptive title. A diagram depicting the breakdown of activities

(Gantt Chart) may be used to depict a hierarchical relationship among work packages.

2 Dependencies

This section will state the ordering relations among work packages to account for

interdependencies among them and dependencies on external events. Techniques

such as dependency lists, activity networks, and the critical path method may be used

to depict dependencies among work packages.

3 Resource Requirements

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Identifies, as a function of time, is estimated of total resources required to complete the

project. Numbers and types of personnel, computer time, hardware, software, office

facilities, travel, training, and maintenance requirements are typical resources that

should be specified.

4 Budget Requirements

Identifies, as a function of time, is estimated of total budget dollars required to complete

the project.

4.3 Use financial tools for decision making

Financial tools underlie any process of intelligent decision making. Most families

seeking to reform their financial habits focus on tactics rather than strategy. These are

two different terms that are often confused. Tools refer to a long-term plan with set

criteria for success. Tactics are shorter term plans that are used to push forward to the

goals laid out by the strategy. A tactic might be something like deciding to cut down on

energy usage to reduce electricity bills.

Changing Habits

Improving financial decision making can be the accumulation of small choices made

over a longer period of time combined with some major decisions, such as a career

change or returning to school. In some cases, a decision to save money may result in

higher risk incurred to the household. For example, anyone can save money by

dropping their health insurance plan, but it exposes them to more financial risk from

illness or injury.

Getting Help

Learning how to make better financial decisions can be made easier by getting

assistance from others. Professional financial advisers can assist households in

constructing sensible budgets, coming up with debt repayment plans and allocating

resources for retirement. Self-education in matters of investment, better spending

practices and reforming deleterious habits are also quite useful.

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Big Choices

Adopting more frugal habits such as eating at home, paying down credit card debt and

negotiating down cell phone bills are all beneficial financial decisions, but their benefits

pale in comparison to the potential benefits of making major life changes. Moving into a

smaller house, taking time to get additional education to qualify for better jobs or

perhaps starting a new business are all examples of major--and risky--financial

decisions with life-changing effects.

Conclusion:

In Business Decision Making, using a variety of sources for data collection in order to

analyse the different costs of business is presented. It also applies a range of

techniques for analysing data for the purpose of business. By using different kind of

graphs show the business how to draw valid conclusions based on the information and

leads to prepare a formal business report. Moreover, management information systems

suggest suitable information tools for the different levels of the organisation through

calculation and a diagram.

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References:

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Cagan, M. (2008). Inspired: How To Create Products Customers Love. SVPG Press; 1st edition

Hahn, G. J., Hill, W. J., Hoerl, R. W. and Zinkgraf, S. A. (1999) The Impact of Six Sigma Improvement-A Glimpse into the Future of Statistics, The American Statistician, Vol. 53, No. 3, pp. 208-215.

Haines, S (2008). The Product Manager's Desk Reference. McGraw-Hill; 1 edition

Lawley, B. (2009). The Phenomenal Product Manager: The Product Manager's Guide to Success, Job Satisfaction and Career Acceleration. Happy About Press.

Turban, Efraim (2002), Electronic Commerce: A Managerial Perspective, Prentice Hall . Pp. 56-62

Peppers, D. and Rogers, M. Ph.D. (2008), Rules to Break and Laws to Follow, Wiley. Pp. 23-29

Pine, B. J. II; Gilmore, J. (7/1/98), "Welcome to the Experience Economy", Harvard BusinessReview. http://www.itu.dk/courses/DIDE/E2006/downloads/welcome_to_the_experience_economy.pdf[Accessed 26th Jan, 2012]

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http://www.itu.dk/courses/DIDE/E2006/downloads/welcome_to_the_experience_economy.pdf

http://www.itu.dk/courses/DIDE/E2006/downloads/welcome_to_the_experience_economy.pdf

Appendix 1:

Company’s current situation

1. Who are your key customers and where are they (current and prospective)?

A. What are their problems, needs and wants

2. What benefit can your company provide these customers that they can’t obtain

elsewhere?

3. Where are you now?

A. Where do you want to be in 1 year, 3 years, 5 years and beyond?

4. Why do you want to be there?

5. What problems must you overcome to get there?

6. What methods, tools and strategies are now being used to get there?

Client questionnaires

7. Who are your (key) competitors?

8. What is is your assessment of their apparent goals and strategies relative to

their product characteristics?

B. Pricing?

C. Distribution?

D. Service?

E. Communication with their customers and other publics?

F. Strengths?

G. Weaknesses?

9. Is there any current marketing research available?

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Partnership and equipment related questionnaires:

10. Use three equipments to describe how the company should be perceived by the

audience.

(examples: conservative, progressive, friendly, formal, casual, serious, energetic,

humorous,professional)

11. Are these different equipments than current image perception?

12. What do you feel is the biggest challenge in getting this image across to

partnership?

13. How is your company currently perceived partnership relation? Do you wish to carry

the same kind of message through this?

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Decision Making

Documents

Transcript of Decision Making