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BUSINESS DECISION MAKING
HIGH NATIONAL DIPLOMA IN BUSINESS
STUDIES
Prepared By : D.D.C.Manori Wijerathna (104930,)
2
Acknowledgment
First and foremost I offer my sincerest gratitude to my lecture and supervisor, Ms Tamra as
her encouragement, guidance and support throughout the whole assignment enabled me to
develop an understanding of the subject and with her patience and knowledge I was allowed
to work in my own way. And also Mr Ibrahim lectured more general scenarios which
directed me to present the assignment precisely.
Lastly, I offer my regards and blessings to my parents who encouraged me through online,
and friends who supported me in any respect during the completion of the assignment
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Table of contents
Executive summary....................................................................................................................4
Company background................................................................................................................5
Introduction ...............................................................................................................................7
Chapter 1: Data collection and decision making......................................................................11
Chapter 2: Project management and Decision making............................................................29
Chapter 3: Financial decision making......................................................................................38
Chapter 4: Data presentation and interpretation for Decision making.....................................51
Conclusion and Recommendation............................................................................................67
References................................................................................................................................68
Appendix 1: The respondents profile.......................................................................................71
Appendix 2: Project planning...................................................................................................72
Appendix 3: Presentation.........................................................................................................75
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Executive summary
This report highlights the importance of finding, collecting, using, and analysing data,
information, facts and figures correctly, so that an organisations/ governments/ firms/sports
teams/ rock bands/ businesses etc, can make effective and efficient decisions. The author
also has discussed the necessity of business decision making is that business decision making
will affect competitive advantage. Poor decision making results in higher costs, less profit,
reduced brand strength, lack of understanding of internal/external factors which affect the
firm, and an inability to effectively and efficiently plan for the future. There are many
different reasons why they need to use data effectively.
The aim of this report is to develop techniques for data gathering and storage, an
understanding of the tools available to create and present useful information, in order to make
business decisions. Because in business, good decision making requires the effective use of
information. And this report also examines a variety of sources and develops techniques in
relation to four aspects of information: data gathering, data storage, and the tools available to
create and present useful information.
Information and communication technology is used in st. Patrick‟s college to carry out much
of this work and an appreciation and use of appropriate ICT software is central to completion
of this report. Specifically, the author used spreadsheets and other software for data analysis
and the preparation of information. The use of spreadsheets to manipulate of numbers, and
understanding how to apply the results, are seen as more important than the mathematical
derivation of formulae used. Finally the author was able to gain an appreciation of
information systems currently used at all levels in an organisation as aids to decision making.
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Company Background
St. Patrick's was established in 1803 as St. Patrick's School in oxford circus which is entirely
British government accredited and is a category A Licensed Sponsor with the UK Border
Agency. The College is an endorsed Edexcel centre for assessment and teaching. It has all the
facilities that students need for an effective and pleasant learning experience, which leads to
the success of their education. Students from over 50 countries including the Far East and
South Asia, Africa, the Caribbean, Latin America, and from the UK and other European
countries, take advantage from the high quality tuition offered by the College.
Figure 1: Partnership of St Patrick‟s, www.st.patrick‟s.co.uk
A Collaborative Partner of the University of Portsmouth
An Accredited Tutor Support Centre for the University of
Sunderland
A partner of the British Council’s
EducationUK
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According to figure 1, St Patrick‟s has built up strong collaborations and partnerships with
other universities to offer a variety of courses at different levels in Accounting, Business
Management, Technology, Healthcare Management, Hospitality Management, and Law. And
also, figure 2 clearly demonstrates the organizational structure of St Patrick‟s which allows
coordinating the diverse subjects effectively along with its mission which is to deliver world
class education with particular regard to their application in industry, commerce and
healthcare. The college foster multidisciplinary working internally and collaborate widely
externally.
Figure 2: Organization structure of St: Patricks, Field work
Accordingly, St Patrick's provides high quality education in a caring and friendly
environment where Students can study at the College for:
The External LLB from the University of London and the BSc (hons) International
Tourism and Hospitality Management from the University of Sunderland
The BSc (Hons) in Computing and Information Systems from the University of
Portsmouth
The BA (Hons) in Business Management from the University of Sunderland and the
MBA from the University of Sunderland.
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Introduction
Decision-making is a crucial for any organization in the world. The management can be
trained to make better decisions where they must need a supportive environment and should
receive proper support from their colleague and superiors. Accordingly decision-making
increasingly happens at all levels of a business (Refer figure 3).
Figure 3: Levels of decision making, Field work
According to figure 3 the Board of Directors may make the grand strategic decisions about
investment and direction of future growth, and managers may make the more tactical
decisions about how their own department may contribute most effectively to the overall
business objectives. But quite ordinary employees are increasingly expected to make
decisions about the conduct of their own tasks, responses to students and improvements to
business practice. This needs careful recruitment and selection, good training, and
enlightened management.
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Subsequently the author has examined that there are many types of business decisions in any
organization which clearly shown in figure 4.
Figure 4: Types of business decision making, Doyle, Kaner, Lind and Toldi 2007
1. Programmed Decisions These are standard decisions which always follow the same
routine. As such, they can be written down into a series of fixed steps which anyone can
follow. They could even be written as computer program
2. Non-Programmed Decisions. These are non-standard and non-routine. Each decision is not
quite the same as any previous decision.
3. Strategic Decisions. These affect the long-term direction of the business eg whether to take
over Company A or Company B
4. Tactical Decisions. These are medium-term decisions about how to implement strategy eg
what kind of marketing to have, or how many extra staff to recruit
5. Operational Decisions. These are short-term decisions (also called administrative
decisions) about how to implement the tactics e.g. which firm to use to make deliveries.
For an example, St Patrick‟s college which is a world leader in education private sector
always makes tactical decisions in order to compete with its competitors. So, figure 5 clearly
illustrates how the decision making process of St Patrick‟s college assists to maintain its
position in the education industry successfully.
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Figure 5: Decision making process of St .Patrick‟s, Davis (1974)
The model in Figure 5 above is a normative model which illustrates how a good decision
ought to be made. Beside there are other decisions making models too. Such as Linear
programming model which helps to explore maximising or minimising constraints, Spread-
sheets which are widely used to hold all the known information about, such as pricing and the
effects of pricing on profits. The different pricing assumptions can be fed into the spread-
sheet „modelling‟ different pricing strategies. This is a lot quicker and cheaper than actually
changing prices to see what happens. However the computer does not take decisions where
managers should do. But it helps managers to have quick and reliable quantitative
information about the business as it is and the business as it might be in different sets of
circumstances. There is, however, a lot of research into „expert systems‟ which aim to
replicate the way management of St.patrick‟s take decisions. And the management of St
Patrick‟s college also concerns about the constraints on decision-Making as this may can
generate in efficiency in college system (Refer figure 6).
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Figure 6: Constrains on business decision making, Robert A. Stine and Dean Foster
According to figure 6 constraints on Decision-Making are mainly divided into internal and
external. Internal constrains are constraints that come from within the college itself, such as
availability of finance where certain decisions will be rejected because they cost too
much, existing business policy which is not always practical to re-write business policy to
accommodate one decision and concern of students‟s abilities and feelings .External
constraints are constraints that come from the outside the college. Such as, National & EU
legislation, competitors‟ behaviour, etc.
Moreover by considering the factors explained above, the author has attempted to highlight in
further chapters that how college can deal with different scenarios to make decisions
effectively. This is well explained in chapter 1 via data collection and this links to other
chapters emphasizing the importance of planning.
existingbusiness policy
availability offinance
abilities and feelings
Internal constraints
National & EU legislation
competitors’ behaviour
External constraints
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Chapter 1: Data collection and decision making
1.1 Introduction
According to Taylor & Tillett (2004), information is data that has been processed into a form
that is significant to the receiver and is of perceived value in prospective decisions. Every
organization requires information as the basis for analysis. These required sources of can be
categorised as either primary or secondary data. For a better understanding, author presents
an overview of primary and secondary data diagram in figure 7.
Figure 7: Data sources, Field work
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1.2 Secondary data
Secondary data are existing data generated for a problem other than one at hand. Secondary
data consists of information that already exists somewhere, having been collected for another
purpose. Secondary data can usually be obtained more quickly and at a lower cost than
primary data. Also, secondary sources sometimes can provide data and Individual Company
cannot collect on its own, information that either is not directly available or would be too
expensive to collect. (Tylor,S.,(2007)
For an example, If St. Patrick‟s college attempts to evaluate student satisfaction on
organization of programmes and assessments, secondary research will be required to fabricate
upon previous records and information. It utilizes the wealth of data held in libraries and in
the government departments which assist to make decisions effectively and efficiently. This
can be divided into two sections as internal and external sources. (Refer figure 8)
Figure 8: sources of secondary data, Field work
Internal External
Database Marketing
The creation of large computerized files of
students‟ profiles and marketing strategies,
and it is the fastest-growing use of internal
database technology.
Government publications
Trade Associations - Newsletters,
special reports, annual reports, etc.
Website : www.st.patrick‟s.co.uk
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1.2.1 Benefits and limitations of secondary data
Secondary data can also present problems. The needed information may not exist; researchers
can rarely obtain all the data they need from secondary sources. Even when data can be
found, they might not be very usable. The researcher must evaluate secondary information
carefully to make certain it is relevant, accurate, current and impartial. Secondary data can
provide a good starting point for research and often can help to define problems and research
objectives. In most cases, however the company must also collect primary data.
According to figure 8 internal sources of St.patrick‟s college, can be covered the subjects in
variety. Such as to figure out the company‟s output by evaluating the sales costs, advertising
and other promotional expenses are marketing costs to be set against sales revenue. Whether
or not the functioning records are kept in such a way that they can be used to distribute
marketing costs to specific branded products ( different courses), and assist to monitor
marketing performance, specifies whether the St.patrick‟s college is truly focus on the
market.
Despite this, limitations can be occurred, if St.patrick‟s college does not have a broad student
database. And college can not engage in making observations and developing concept. And
because of this its own sales figures will not tell, how college need to increase the prospective
students in the future. The advantage of this method include time saving, provide a larger
data base comparing to primary data. Therefore the most productive source can be used for
St.patrick‟s college is the government statistics which are gathered for the purpose of
government, but college can utilize them to meet college requirements.
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1.3 Primary data
Primary data are the first hand information collected, compiled and published by organization
for some purpose. They are most original data in character and have not undergone any sort
of statistical treatment. When research is carried out to discover novel data, it is called
primary research. To do this, an inventive research plan must be developed which will
include, data collection, data input and then the production and analysis of the consequent
results. Despite, the research is at first hand, the results gathered will be more relevant to the
needs of the client organization. Primary data can be collected via personal investigation in
which the researcher conducts the survey him/herself and collects data from it. The data
collected in this way is usually accurate and reliable. This method of collecting data is only
applicable in case of small research projects and through investigation, trained investigators
are employed to collect the data. These investigators contact the individuals and fill in
questionnaire after asking the required information. Most of the organizations implied this
method. Beside collection through Questionnaire is quick but gives only rough estimate and
through telephone also, researchers can get information as this method is quick and give
accurate information.
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1.3.1 Advantages and dis advantages of primary data.
Primary data is more credible, which strengthens any argument researchers may be using
their research to effect. This highlights that every primary data has its own advantages and
disadvantages. (Refer figure 9)
Figure 9: Advantages and disadvantages of primary data, Field work
Advantages Disadvantages
1. It can be collected from a number of
ways like interviews, telephone
surveys, focus groups etc.
2. It can be also collected across the
national borders through emails and
posts.
3. It can include a large population and
wide geographical coverage.
Fourthly, it is relatively cheap and no
prior arrangements are required.
4. Primary data is current and it can
better give a realistic view to the
researcher about the topic under
consideration.
It has design problems like how to design the
surveys. The questions must be simple to
design a general lingo (understandable).
Some respondents do not give timely
responses. Sometimes, the respondents may
give fake, socially acceptable and sweet
answers and try to cover up the realities. In
some primary data collection methods there
is no control over the data collection.
Incomplete questionnaire always give a
negative impact on research.
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1.3.2 Limitations of primary data
Because of lengthy duration of the primary research it can often be expensive to perform.
Time needs to be consumed properly. As primary data collection needs the growth and
implementation of a research plan. Going from the beginning to undertake a research to have
the end results is often much longer than the time it takes to obtain secondary data. Primary
data is not always feasible. Because some information that could show quite valuable, but not
within the reach of a researcher. (Tylor,S.,(2007)
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1.4 Application of the scenario of St Patrick‟s college
1.4.1 Rationale of the questionnaire
As a mechanism for obtaining information and opinion, questionnaires is based on primary
data that have a number of advantages and disadvantages when compared with other
evaluation tools (Refer figure 11). In general, questionnaires are effective mechanisms for
efficient collection of certain kinds of information.
Figure 11: Advantages and disadvantages of questionnaire, Field work
Advantages Disadvantages
Cost: It is possible to provide
questionnaires to large numbers of students
simultaneously.
Uniformity: Each respondent receives the
identical set of questions. With closed-form
questions, responses are standardised,
which can assist in interpreting from large
numbers of respondents.
Can address a large number of issues and
questions of concern in a relatively
efficient way, with the possibility of a high
response rate.
Often, questionnaires are designed so that
answers to questions are scored and scores
summed to obtain an overall measure of the
attitudes and opinions of the respondent.
They may be mailed to respondents
(although this approach may lower the
response rate).
They permit anonymity. It is usually
argued that anonymity increases the rate of
response and may increase the likelihood
that responses reflect genuinely held
opinions.
It may be difficult to obtain a good
response rate. Often there is no strong
motivation for respondents to respond.
They are complex instruments and, if badly
designed, can be misleading.
They are an unsuitable method of
evaluation if probing is required – there is
usually no real possibility for follow-up on
answers.
Quality of data is probably not as high as
with alternative methods of data collection,
such as personal interviewing.
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1.4.2 Design a questionnaire
A well designed questionnaire motivates the respondent to provide complete and accurate
information. Questionnaire research design continues in a logical and specific way. Each item
in the flow chart depends upon the winning completion of all the preceding items.
Consequently, it is vital not to miss out a single stage. As part of St Patrick‟s college‟s
product Strategy, the questionnaire was designed to undertake a pilot survey of students‟
views of the quality of their studying experience in order to identify areas for enhancement.
To facilitate this process a Student Satisfaction Survey Steering Group was established
between the St Patrick‟s college and the Students‟ Union. As explained in 1.3, this
questionnaire has allowed collecting primary data regarding student satisfaction on
organization of programmes and assessments at St Patrick‟s College.
Figure 10: Questionnaire research flow chart, Simons, R. (1990),
19
Questionnaire
Dear students, this student satisfaction questionnaire is designed to provide an opportunity for
you to comment on your experience on lecture material and organized programmes including
assignmnets of St.patrick‟s collge
Section A: General information about you
20
21
Section B: Programme organization and assignments
please rate the extent to which you are satisfied with the following aspects of your
progrmmes/ courses and assignments and the rate how important they are o your experience
as a student(if applicable)
22
23
Section c: Your evaluation
Please write below an estimate of your satisfaction with the following aspects of
college education.
Do you think your lectures provide you enough materials to do your
assignments?
Yes
No
(If, no why?
comments.....................................................................................................................)
Can rate your overall satisfaction on doing assignments and scheduled
courses/programmes over 75%?
Yes
No
(If, no why?
comments.....................................................................................................................)
Thank you for taking time to complete this questionnaire
Figure 11: Questionnaire on student satisfaction at college, field work
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1.4.3 Aims and objectives of questionnaire
The overarching objectives of the survey are,
To develop a St Patrick‟s college-wide student satisfaction survey,
To agree a methodology for the data analysis,
To inform an effective strategy for the implementation of the findings.
Beside the overall aim of this work is to investigate student opinion on the experience of
dong assignments and organization of programmes at t St Patrick‟s college.
1.4.4 Methodology
An initial pilot student satisfaction survey was carried out to assess the reliability and validity
of this questionnaire. The development of the student satisfaction survey from student-
generated questions refined with input from administration department, marketing department
and from student union. This is a postal questionnaire was sent to all students who are in 2nd
year of college 2011. The questionnaire adopted the research methodology that was initially
developed by author.
A series of questions was presented using a 7-point satisfaction rating alongside a 7-point
importance rating. This allowed for analyses of strengths and areas for improvement,
identifying clear priority action targets for consideration. The questionnaire also included a
number of open questions that invited students to comment on any aspect of each particular
section. This information was analysed qualitatively and provides some contextual
information to accompany the ratings and in some cases also identifies suggestions for
improvement and possible solutions to problems. As such, the questionnaire was designed to
encourage respondents to consider responses so that any criticisms they had could be
constructive rather than simply negative responses. (Zapper,C,J.,(2006)
25
1.4.5 Sampling
Sampling is the act, process, or technique of selecting information from a portion of the
population by taking a sample of elements from the larger group and on the basis of the
information gathered from the subset, to infer something about the larger group. This can be
classified in to two broad categories of probability and non probability samples as shown in
figure 12.
Figure 12: classification of sampling, Pinson,L., (2002)
Sample Designs
Non probability Sampling
a. Convenience sampling
b.Judgement or purposive
sampling
c.Quota sampling.
d.Snowball sampling
probability Sampling
a. simple random sampling
b. systematic sampling.
c. stratified sampling.
d. cluster sampling
1.4.5.1 Sample size determination
Determining sample size includes both managerial and financial considerations. The sample
evaluates a certain population limitation. The sample size selected for St.patrick‟s college
will be 10% of the population of all undergraduate students who are in second year 2011. But
usually the larger the sample size, the less is the sampling error. The costs of larger samples
are likely to increase on a linear basis not so far sampling error. There are two major ways to
determine sample size, statistical method and non statistical method.
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1.4.6 Literature review
This chapter is concerned with research objectives where the role of student satisfaction
assurance within St Patrick‟s college. It begins with an evaluation of the components of
student satisfaction and the way which it can be obtain and so measured. Student loyalty
programmes are then discussed using examples to illustrate how college can impact on
student satisfaction.
The importance of education quality and student relationship management is then explored in
terms of the absolutes of quality management. In addition the basic elements of improvement
are illustrated that lead to build a continuous ladder of student retention as a result of student
satisfaction. And also it is concerned with the procedures and college management of student
complaints which assist to satisfy students effectively. Certain characteristics of former
students were associated with a high degree of reported satisfaction; for example, females and
older students tended to report somewhat higher levels. Also, students who attended
hospitality management courses and those in nursing or health-related programs were more
likely to give high ratings for satisfaction.
Although knowing student characteristics may not directly help institutions to improve
student assessments, it is important to examine their influence in the mix of factors that affect
satisfaction ratings. Four of the six dimensions were created from the ratings respondents
gave to questions about the opportunities provided by their programs for skill development
and personal growth are communication skills, social skills, analytical skills, and personal
growth. The other two factors are curriculum and teaching which emerged from respondents‟
program and course ratings. All the dimensions were positively correlated with the
satisfaction measure, that is, former students who gave high ratings to their courses or skill
development were likely to rate satisfaction high as well.3 While none of the six had a really
high correlation with the satisfaction measure, together the dimensions explained 30 percent
of the difference in satisfaction scores.4 That means that almost a third of the variability in
the satisfaction measure ratings can be attributed to the aspects of the educational experience
that are grouped into the dimensions shown in figure 13.
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Figure 13: Relationship between educational experience and student satisfaction, Waldmann (2001)
According to figure 13, whether the dimensions are considered together or independently,
curriculum, teaching, and analytical skills consistently exerted the most influence on
satisfaction ratings. The relationship between curriculum and overall satisfaction was the
strongest of the six dimensions, closely followed by teaching and analytical skills.
However, author suggests that this questionnaire should include questions that provided
numerous items relating to former students‟ educational experience and assessments of skills
development and ratings of various aspects of courses and programs that could be used to
explore satisfaction. To simplify the task of comparing a large number of variables to the
satisfaction measure, they were grouped into six factors.
28
Figure 14: Dimensions of educational experience, Abernethy2004)
According to figure 14, author argues that communication skills are the opportunities former
students should be given to develop the ability to speak, write, and read well and are not as
strongly related to the satisfaction measure. Likewise, personal growth and social skills are
less likely to affect overall satisfaction.
29
1.4.7 Ethical issues involved in questionnaire
Ethics of a research is of primary significance. The author assumes when carrying out a
research to measure the methods of improving student satisfaction, students who studying in
St.patrick‟s college are absolute respect, tact and diplomacy in responding to questionnaire.
Hence there will not be no ethical issues occurred during that period.
Thus when students in research are given appropriate information to make a properly
informed decision, students supposed author may ensure that they are genuinely happy to be
involved in research by protecting their rights.
The other main issue needed to be aware of is confidentiality, as students worry about what
sorts of restrictions are in place to make sure the information are accumulating isn't going to
go elsewhere. And also it is vital to demonstrate how to ensure the confidentiality. And also it
needs to consider hard about how to keep data anonymous but accessible. In addition it
should be believed that it is essential to get an ethical approval from students and all
participatory groups should be delighted similar, with consideration and respect. Students
with their permission should be involved in the research.
30
Chapter 2: Project management and decision making
2.1 Introduction
Project Management is a well-established approach to managing and controlling the
organizational changes to make decisions. A logical and systematic decision-making process
helps to address the critical elements that result in a good decision. Effective and efficient
decision making is at the heart of successful project teams, so it‟s critical for project leaders
to be aware of how decision making processes are really operating within the team. Breaking
decisions down into three distinct levels allows the project manager to better manage the
mission critical choices while providing a framework to align the hundreds of task specific
decisions made by team members on a daily basis. (Refer figure 15)
Figure 15: Levels of decision making in project management, Eisenstat, R.A. (2004),
Reflex decisions Conscious decisions Rigorous decisions
These are driven by the
values and priorities of the
company. Since these are
often delegated to others in
the organization it‟s essential
to ensure the project team has
a shared understanding of the
driving forces behind these
decisions. Establishing
“Team Agreements” is a
strategy for managing these
decisions to maximize
efficiency, reduce bottle-
necks, build trust and
reinforce desired behaviours
into everyday decisions.
These are at the heart of team
execution. Strategic
direction gets translated into
specific actions pertaining to
what and how choices that
will have profound impact on
the project team‟s results.
Collaborative processes
ensure that diverse interests
and perspectives are shared
to make the “best” decision
that the core team members
are willing to actively
support.
This defines the direction of
the project‟s activity. Major
investments of time and
money are at stake with
these, so it‟s important to
make sure the right people
are taking an objective look
at decision criteria and
sharing open, honest
perspectives on the risks and
impact these decisions will
have on the project and
company.
31
2.2 Application of St.patrick‟s scenario of Graduation
As explained in 2.1, author explains further, how a real organization makes decisions in
project planning. For an example, St Patricks College has decided to arrange a graduate
ceremony in year 2011. By the end of this event, students will get opportunities to
intermingle with lecturers, fellow students to discuss about their career path. However the
key to a successful project is creating a project plan that college should do when undertaking
a graduation ceremony. Beside, many educational companies fail to realise the value of a
project plan in saving time, money and many problems. Therefore, author attempted to
develop a project plan which explains in appendix 2.
Moreover while a project needs to be carefully planned, project management itself can also
benefit from a defined plan. In fact, effective project management involves four phases.
(Refer figure 16)
Figure 16: Project phases, van Lent, L. (2004)
Nevertheless, author needs to utilize project management tools and techniques such as Gantt
chart, pert and critical path analysis to draw project activities. (Kopeikina, L. (2005),
32
2.2.1 Gantt chart
Gantt Charts are constructive tools for analyzing and planning more complex projects. In
order to arrange a graduate ceremony Gantt chart,
assists college to sketch out the tasks that need to be completed
provides college a foundation for scheduling when these tasks will be carried out
permits college to plan the allocation of resources needed to complete the project, and
Facilitates college to work out the critical path for a project to complete it by a
particular date.
As shown in figure 17, author used Microsoft project 2010 to develop Gantt chart and then
attempted to list the tasks in project, and illustrated their relationship to one another and the
schedule using Gantt bars. Here author suggests that each project's tasks can be listed in the
grid portion on the left side of the Gantt Chart view, and then organize them into a hierarchy
of summary tasks and subtasks. Here tasks can be linked together, to show task dependencies.
In addition to the grid portion of the view, the Gantt chart view also gives a demonstrated
version of task list, with Gantt bars that illustrate the duration of project's tasks across a
timeline. For each task, the connected Gantt bar begins at the start date, and ends at the finish
date. If tasks were linked together, the Gantt bars are connected on the chart with link lines.
33
Figure 17: Gantt chart for graduation ceremony, Field work
34
2.2.2 Net work diagram (PERT chart)
A PERT chart is a project management tool (Program Evaluation Review) which presents a
graphic illustration of a project as a network diagram consisting of
numbered nodes representing events, or milestones in the project linked by directional lines
representing tasks in the project. The direction of the arrows on the lines indicates the
sequence of tasks. For an example, author attempted to draw a net work diagram as a next
step to schedule, organize, and coordinate tasks within a graduation ceremony project
according to in detail gant chart displayed in figure 17.
The author used Microsoft project to draw The Network Diagram (Figure 19) in Microsoft
Office Project 2010 and to show the dependencies between tasks in a graphical manner. A
box or a node represents each task, and a line connecting two boxes represents the
dependency between two tasks. Then the author attempted to create new tasks quickly in a
visual format using the Network Diagram and typed the name and duration for each task to
create it. (Figure 18)
On the other hand, author has identified that this network diagram can be much more difficult
to interpret, especially on when this project getting complex.
35
Figure 18: Activity network for graduation ceremony, Field work
Task Name Duration Start Finish Predecessors
1) Build up a project
proposal 1 day
Mon 23/05/11
Mon 23/05/11
a) Identifies the objectives 2 days Tue 24/05/11 Wed 25/05/11
1
b) Identifies the key
components 2 days Thu 26/05/11 Fri 27/05/11 2
c) Form the project team 3 days Mon 30/05/11
Wed 01/06/11
3
d) Approve with College 3 days Thu 02/06/11 Mon 06/06/11
4
e) Decorate the Hall or
Location 4 days Tue 07/06/11 Fri 10/06/11 5
f) Develop a Theme 5 days Mon 13/06/11
Fri 17/06/11 6
g) Rehearse the graduation
march and arrange
alphabetized seating
2 days Mon 20/06/11
Tue 21/06/11 7
h) Prepare a time plan for
the Master of
Ceremonies (MC),
ahead of time
1 day Wed 22/06/11
Wed 22/06/11
8
i) Arrange the table with
the diplomas- 1 day Thu 23/06/11 Thu 23/06/11 9
j) Arrange a spot for the
photographer 2 days Fri 24/06/11
Mon 27/06/11
10
k) Design a graduation
program 5 days Tue 28/06/11
Mon 04/07/11
11
l) Plan an Entertainment
Package with the
Students
4 days Tue 05/07/11 Fri 08/07/11 12
m) Choose an inspirational
featured speaker 2 days
Mon 11/07/11
Tue 12/07/11 13
n) Arrange refreshments
for the faculty and the
parents
o) Arrange Food service
3 days Wed 13/07/11
Fri 15/07/11 14
p) Event completion 1 day Tue 16/08/11 Tue 16/08/11
36
Figure 19: Activity network for graduation ceremony, Field work
2.2.3 Critical path analysis
Any project must be well planned, especially if a number of people are involved. Therefore
author suggests when undertake the planning and to ensure that the various tasks required in
the project are completed in time. As a result, author developed a method of scheduling
graduation ceremony project shortly which is called net work analysis, but is more usually
known as critical path analysis.
In this example of St Patrick’s graduation ceremony, there is a clear sequence of events that
have to happen in the right order. If any of the events on the critical path is delayed, then
graduation ceremony will not be ready as soon. However author has identified that the critical
path in the network diagram is identified as A-B-C-D-E-F-G-H-J-K-L-M-N-O-P. Any
stoppage on this path has no suppleness on the diagram to complete the project on time.
37
2.3 Importance of project management tools for decision making
Many managers base their decisions on data. In addition, to make planning and decision
making more accurate, a variety of techniques such as Gantt chart, pert chart based on the
scientific method, mathematics, and statistics have been developed. Beside software is
available to carry out most planning and decision-making technique.
However the author has identified that a Gantt chart graphically depicts the planned and
actual progress of work, and is also referred to as a time and activity chart. At any given time,
the project manager can see which activities have been completed on time. Because Gantt
charts are used to monitor progress, they also act as control devices. On the other hand
Project Gantt Charts and PERT charts are to be used as a tool to make decisions. They are
not to be used as a pretty graphic to show management at a monthly meeting. Because
Schedules help St.patrick‟s college to think, to plan, to change course as needed. They
change as the project progresses.
2.4 Importance of using software in project management
Project management basically involves managing of resources, to finish a specific attainable
task at a particular time frame. Project planning software has been one of the best things in
project management. Everything just becomes easier. There are a number of project
management software like Harvard Project Management, Primavera Project Planner, and
Microsoft Project Management. Depending on the complexity of the project and size
corresponding project management software could be selected from the various options
available. One of the simple and flexible project management software which is on the
middle scale should the author says is Microsoft Project. Some of the things that can be done
using Microsoft Project are creating project calendar, baseline plan, resources entry, Gantt
chart, project evaluation review technique (PERT) chart, and more. Beside there are so many
benefits of using software. They are creating table if need be. Also, that once information is
created on spreadsheets it is easily replicated, amended and communicated to
others. (Donaldson, G., Lorsch, J. (1983),
38
Chapter 3 Financial decision making
3.1 Introduction
The accounting function qualities the economic relationships of a business, the finance
function, on the other hand , manipulates those relationships in order to optimize the
company‟s liquidity and profitability. So the finance model is a diverse set of techniques that
are used to analyze and manage the future direction of the firm‟s investments and financing.
Management accounting is the primary source of accounting information for financial
decisions. These accountants handle the information directly relating to input costs, various
labour wages, facility overhead, sales revenues and other financial modelling. Management
accountants should act responsibly when reporting this information; positive and negative
aspects should be given to management. Providing a truthful assessment of financial
information and the impact of financial decisions can help companies understand the
potential economic impact of the decision. However managers at every level in company
should make difficult financial decisions continuously. Analytical tools are significant in
decision making, analysis, planning and control. The financing decision varies depending on
the size of the firm, the location of the firm. When making financial decisions, the manager
must determine the best financing mix or capital structure of the company. Beside al
managers use financial tools with accounting software and these tools aids a business in the
decision-making process. The financial tools are financial position analysis, profitability
trends, cash flow analysis, and equity cash flows, payback period, present value, net present
value and internal rate of return
39
3.2 Tools for Financial decision making
Investors use a number of methods to evaluate investment projects, rank them and select the
most attractive among them to finance. Those with money to lend will lend it provided the
rate of return (interest), the risk and responsibility (how quickly the money can be
repossessed) are consistence with their expectations. This section discusses three of the
most popular criteria applied.
•Payback period;
•Net present value;
•Internal rate of return.
Depending on the type of investment is anticipated, it may be advisable to work out these
criteria and include them in business plan.
40
3.2.1 Payback period
The payback period is defined as the number of years it will take to recover the original
investment from future net cash flows. The pay back method does not account for savings
that may continue from a project after the initial investment is paid back from the profits of
the project. But this is good for a first cut analysis of a project to make business decision.
Moreover advantages of payback period are that it is simple to compute and understand, it
handles investment risk effectively, it will give the exact period to pay back financing or loan
and it will outline the difference between cash out flow and inflow. On the other hand the
author argues that payback period method does not recognise the time value of money and
ignores the profitability of an investment.
However the calculation of the pay back period is the best illustrated with an example.
Consider Capital Budgeting project A which yields the following cash flows over its five year
life.
Year Cash Flow Net Cash
Flow
0 -1000 -1000
1 500 -500
2 400 -100
3 200 100
4 200 300
5 100 400
After entering above figures to Excel spread sheet, the author was able to get cumulative cash
flow or net cash flow. After two years the Net Cash Flow is negative (-1000 + 500 + 400 = -
100) while after three years the Net Cash Flow is positive (-1000 + 500 + 400 + 200 = 100).
Approximately 3 years required for an investment to recover its initial cost. But, if it is
assumed that the cash flows occur regularly over the course of the year, the Payback Period
can be calculated using the following equation, manually.
41
3.2.2 Present value
Present value is a fiscal term used to define the value of a certain amount of money at
present. The present value of £1 today is £1. If deposits £100 in the bank, that £100 will
become £105 in one year time at an interest rate of 5%. £105 is the Future Value (FV) of the
£100 in the first year, for an example Year 1. If Mr David continues to put the money (£105)
in the bank, it will earn another 5% interest. His bank account will have £110.25. That is the
future value of £100 today in year 2. And the future value depends on the interest rate offered
by the bank. If the interest rate is 10%, the future value of £100 in year 2 is higher. The
amount is £121(£100*1.1*1.1). It is equal to original sum of £100 plus the interest for 2
years. The author states that the interest David earns in the first year will also earn interest in
the second year too.
Assuming that David needs to save £121 for some expenses two years from now, and he is
interested to find out how much he would need to put into the bank today so that he will have
£121 in the bank. As the bank is paying an interest rate of 10%, he knows that he needs to put
in less today to obtain £121 in two years as a result of the interest his bank is paying him.
That amount he is going to put in today is known as the present value.
Microsoft Excel was able to help the author to find out what is that amount with its present
value formula. Here is the way to find out. First present the numbers as shown in the diagram.
It is known as the time line. It will help to clearly establish what he is going to calculate
42
In Cell C5, author entered the Excel formula “=PV (C3, 2, 0, E4)” excluding the inverted
commas. The formula calculated the amount David wanted to deposit into the bank today to
earn £121 in 2 years time. Then author entered the interest rate the bank is paying David
(C3), the number of years between now and the point he would like to receive the money
(i.e.£121), any payments or receipts between the beginning and the ending period/year.
Finally, the amount author expected to have some time in the future (in our case, it is £121 or
the value in E5). Once author has entered the formula (as shown in the formula bar in the
diagram above, author pressed enter. Then Excel returned the value negative £100 which was
the amount author had to put in today to make sure that it grows to £121 in two years‟ time.
The amount is negative to indicate that the money is taken from (and deposit into the bank)
while a positive amount shows the amount was received later. The results which was called
the present value would therefore showed the amount of money That Mr David wanted to put
in today in order to take back £121 in 2 years‟ time.
43
3.3.3 Net present value
The net present value (NPV) method is a useful method for evaluating investment projects.
The NPV is equal to the present value of future net cash flows discounted at the cost of
capital, minus the present value of the cost of the investment. The advantage of this method is
that it takes into account the time value of money and takes into consideration the potential of
the business over the entire planning period of the investment. The steps for obtaining the
NPV are as follows.
1. Find the present value of each net cash flow, including the initial outflow, discounted
at an appropriate percentage rate. The discount rate is based on the cost of capital for
the project. The latter depends on the level of interstates in the economy, the riskiness
of the project and several other factors.
2. Add up all discounted net cash flows over a defined planning period; their sum is
defined as the project's NPV.
3. If the NPV is positive, the project can be normally accepted; if negative, it has to be
rejected; and if two projects are mutually exclusive, the one with the higher positive
NPV should be chosen
The formula for this is,
.
44
For an example, Mr David invests £100,000 in a project. A year later he invests
another £50,000. From the second year onwards the net cash he receives is £45,000 per year
over a period of five years. The cash flow is as follows,
year Net cash flow £ Cumulative cash flow
0 -100000
-100000
1 -50000
-150000
2 45000
-105000
3 45000
-60000
4 45000
-15000
5 45000
30000
6 45000
75000
Assuming the cost of capital to be 9 % and a planning period of six years the NPV is
calculated to be as follows:
=£ 14,710.37.
45
In this example David‟s original wealth as an investor will increase by £14,710.37.Therefore,
it is probably a beneficial investment.
However the author provides a clear idea that how this was done in excel spreadsheet. First
author has equally entered above values having spaces in time and occurs at the end of each
period. Then author entered payment and income values in the correct sequence. Finally, the
author got the formula as follows.
Npv (discount rate, value2 ... value _n) - Initial Investment + value1
On the other hand the author argues that NPV is similar to the PV function (present value).
The main distinction between PV and NPV is that PV allows cash flows to commence either
at the end or at the beginning of the period. Unlike the variable NPV cash flow values,
Present value cash flows must be steady throughout the investment.
46
3.3.4 Internal rate of return
Internal rate of return is sometimes referred to as „economic rate of return‟ (ERR).The
internal rate of return is the discount rate that results in a net present value of zero for a series
of future cash flows. The major difference is that while net present value is expressed in more
units, the IRR is the true interest yield expected from an investment expressed as a
percentage,
1
2
3
4
5
6
7
A B
Data Description
-70,000 Initial cost of a business
12,000 Net income for the first year
15,000 Net income for the second year
18,000 Net income for the third year
21,000 Net income for the fourth year
26,000 Net income for the fifth year
Formula Description (Result)
=IRR(A2:A6) Investment's internal rate of return after four years (-2%)
=IRR(A2:A7) Internal rate of return after five years (9%)
According to above example Value is a reference to cells that contain numbers for which the
author wants to calculate the internal rate of return. Values must contain at least one positive
value and one negative value to calculate the internal rate of return. IRR uses the order of
values to interpret the order of cash flows. Just enter the cash flow values. So, if on a initial
investment of £-70,000, the net income of 5 years are 12000,15000,18000,21000 and 26000
and use the IRR function, as shown in excel spread sheet. so IRR of 5 years is 9%.
Finally the author states that IRR is closely related to NPV, the net present value function.
The rate of return calculated by IRR is the interest rate corresponding to a 0 (zero) net present
value.
47
3.5 Scenario examples
Manchester Investment
Period 0 1 2 3 4
Year 1 Year 2 Year 3 Year 4 Year 5
Revenue 40000 52000 61000 75000 90000
Investment -200000
TOTAL -160000 52000 61000 75000 90000
Discount rate 20 20 20 20 20
Discount factor 1.00 0.83 0.69 0.58 0.48
Discounted cash flows -160000 43333.33 42361.11 43402.78 43402.78 12500
NPV
IRR 23.70%
In order to decide the feasibility of the investment in Manchester, the discounted cash flow
should be calculated for each year. Based on 20% discount rate the discount factors are
obtained from the table and this allow to calculate the discounted cash flow for each year. At
the end of the year 5, the total discounted cash flow becomes optimistic value.
At the end of 5 years period the net present value is £12,500. The payback period is 3 years 3
months where the discounted cash flow becomes positive. Consequently the investment will
be economically viable with inside the 5 year period.
48
Exeter Investment
Period 0 1 2 3 4
Year 1 Year 2 Year 3 Year 4 Year 5
Revenue 32000 45000 65000 76000 89000
Investment -200000
TOTAL -168000 45000 65000 76000 89000
Discount rate 20 20 20 20 20
Discount factor 1.00 0.83 0.69 0.58 0.48
Discounted cash flows -168000 37500 45138.89 43981.48 42920.52 1540.895
NPV
IRR 20.43%
Likewise the investment in Exeter is calculated and found the total discounted cash flow is
still in negative. As a result the investment is viable at this period of 3.8 years. The Internal
Rate of Return is a discounted cash flow method which looks to find the discount rate at
which the present value of net cash inflows from a capital project exactly equal the capital
payout. IRR is the net present value is zero. For an instance, IRR is 20.43% when NPV is
zero.
49
Brighton Investment
Period 0 1 2 3 4
Year 1 Year 2 Year 3 Year 4 Year 5
Revenue 36000 51000 63000 74000 88000
Investment -190000
TOTAL -154000 51000 63000 74000 88000
Discount rate 20 20 20 20 20
Discount factor 1.00 0.83 0.69 0.58 0.48
Discounted cash flows -154000 42500 43750 42824.07 42438.27 7512.35
NPV
IRR 22.17%
The investment in Brighton is also feasible as the net present value is in optimistic at the end
of 5 year period. The payback period is 3 years and 5 months
50
3.6 Evaluate the Decision making at college
According to figure 20 Manchester is the best location that St. Patricks should go for, because
within 3 years and 3months college can handle the investment risk effectively. Though author
argues that within 3 years and 3 times, college will not be able to identify the time value of
money and ignores the profitability of investment. So, college can return 23.7% from an
initial investment which is profitable to make the decision on Manchester location. Net
present value of Manchester project measures the viability of a project by taking into account
the investments (outflow) and returns generated (inflow) from the investment, which are
12500.
Figure 20: Evaluation of 3 locations, Field work
Manchester Exeter Brighton
Payback period (yrs) 3.3 3.8 3.5
NPV (£) 12.,500 1540.895 7512.35
IRR (%) 23.7 20.43 22.17
The author also has noticed, if college go for Exeter and Brighton location, that will make an
average loss to their business. Because, within 3 years and 8months and 3 years and 5 months
college then can handle the investment risk, though college would return 20.43% from Exter
and 22.17% from Brighton. This does not make sound that college go for these 2 locations,
unless Manchester meets so many barriers in capitalization.
51
Chapter 4: Data presentation and interpretation for decision making
4.1 Data analysis
Data analysis is an exercise in which raw data is instructed and organized so that helpful
information can be taken out from it. Raw data can take a variety of forms, including
measurements, survey responses, and observations. Beside charts and graphs of data are all
forms of data analysis. These methods are designed to demonstrate the data so that readers
can gather information without needing to sort through all of the data on their own.
Summarizing data is often significant to supporting arguments made with that data, as is
presenting the data in a obvious and understandable way.
4.2 A Statistical analysis of Customer satisfaction at Egham wines Ltd
First Quench Retailing is the UK‟s leading independent specialist drinks retailer which brings
in Threshers, The Locals, Wine Rack and Haddows. Together First Quench Retailing
operates over 1500 outlets and employs over 12,000 people across the country. It‟s the UKs
13th largest private retailer and it serves over 150 million customers a year across the
different brands all over. Fundamentally, author attempts to discuss how the company makes
decisions by using data. (Refer appendix 3)
4.3 Measures of Central Tendency
While distributions provide an overall picture of some data set, it is sometimes desirable to
represent some property of the entire data set using a single statistic
There are different measures of central tendency that company follows,
The mode
The median
The mean
52
4.3.1 The mode
The mode is the average value, calculated by adding all the observations and dividing by the
number of observations.
Figure 21: Weekly shopping information, Field work
Weekly shopping Frequency Class width Frequency density
01 to 02
2
1
2 03 to 04
11
1
11
05 to 07
15
2
7.5 07+
12
7
1.7
As shown in figure 21 the highest frequency density is 11 which is the mode of shopping in a
week at the branch is 3- 4. To provide this scenario author has used Microsoft Excel
spreadsheet as it was quick and easy to measure the results of these outcome.
53
4.3.2 Mean and Median
4.3.2.1 The median
The two most common measures of central tendency are the median and the mean, which can
be illustrated with an example. Suppose Threshers draw a sample of five customers and
measure their purchasing behaviour which shows in figure 22.
Figure 22: Purchasing behaviour of customers, Field work
Number of customers Purchasing behaviour
1
100 2
100
3
130 4
140
5
150
According to figure 22, to find median, by using Microsoft Excel, the author arranged the
observations in order from smallest to largest value. If there are an odd number of
observations, the median is the middle value. If there is an even number of observations, the
median is the average of the two middle values. Thus, in the sample of five customers, the
median value would be 130 pounds; since 130 pounds is the middle price.
4.3.2.2 The mean
The mean of a sample or a population is computed in Excel by adding all of the observations
and dividing by the number of observations. Returning to the example of figure 22, the mean
of their purchasing behaviour would equal (100 + 100 + 130 + 140 + 150)/5 = 620/5 = 124
pounds. In the general case, the mean can be calculated, using one of the following equations:
Population mean = μ = ΣX / N OR Sample mean = x = Σx / n
Where ΣX is the sum of all the population observations, N is the number of population
observations, Σx is the sum of all the sample observations, and n is the number of sample
observations.
54
4.4 Measures of dispersion
Schwager (1986) illustrates that the important characteristic of a data set is how it is
distributed, or how far each element is from some measure of central tendency (average).
There are several ways to measure the variability of the data. Although the most common and
most important is the standard deviation, which provides an average distance for each
element from the mean, several others are also important.
The mainly used measures of dispersion are as follows.
Range
Standard deviation
Interquartile range
The information was generated from this basic question.
„What‟s the features that does not have on customers purchased wine‟, Opinion of customers,
Taste
Aroma
Body
Flavours
Blend
Other
Figure 23: customers preferred opinion on the wine features, Field work
Features Frequency
Cumulative 1 4
4
2 4
8 3 15
23
4 10
33 5 5
38
6 2
40
55
4.4.1 Range
Gegi (2006) the simplest measure of the spread of your data is its range, the range of a
distribution is defined as the difference between the largest and the smallest observed data
values. One of the simplest measures of variability to calculate depends only on extreme
values and provides no information about how the remaining data is distributed.
From the finding from the customers as shown in figure 23, the range is as below.
The lowest and highest data values respectively is 2 and 15
15 –2 = 13 is the range in the figure 21 this range falls in between the features 3 and 4 which
are body of the wine and flavors of the wine which are the features the customers feel lacking
in the present range of available wines which need to be taken in to considered in the new
product development of wines which will satisfy the customers‟ needs effectively.
4.4.2 Standard deviation
Greg(2002 ) defines standard deviation as the average difference between any values and the
mean of all the values, further he explains this statistics is a measure of the variation in a
distribution value.
Values = 4+4+15+10+5+2 = 40 / 6 = 6.6
As per the above calculation the standard deviation value is 6.6 which represent the
features of Aroma and Body of the wine which the customers think need to be
improved.
56
4.4.3 Inter quartile Range
Williams(2008) defines inter quartile as a measure of variability that overcomes the
dependency on extreme values is the Interquartile range .further he states these measure of
variability is the difference between the third quartile Q3 and the first quartile Q1, in related
in figure 23.
Q3-Q1= 30.75-10.25
=20.5
4.4.4 Lower quartile
Williams (2008) defines Interquartile as the value of the boundary at the 25th, 50th, or 75th
percentiles of a frequency distribution divided into four parts, each containing a quarter of the
population. The 25th
being the lower quartile 50th
being the median and the 75th
being the
upper quartile .
Author explains the lower and the upper quartile values for selected area, related to figure 23.
Formula Q1 = n + ¼
Q1 = 40 + ¼
Q1 = 10.25
In figure 23 the lower quartile value is represented by the feature is the aroma and the body of
the wine, which is one of the main and most sorted after feature by the customers.
57
Upper quartile
formula Q3 = 3(1+ 1/4)
Q3 = 40 (1+ ¼)
Q3 = 30.75
The above upper quartile value represent the feature body and flavor of the wine , where the
opinion reflects that the present features are that very well accepted by the customers where
they emphasize the fact that new wines with the selected features which they are interested
need to be developed by the organization to retain the present customer base.
One of the three numbers (values) that divide a range of data into four equal parts. The first
quartile (lower quartile) is the number below, which lays the 25 percent of the bottom data.
The second quartile (median) divides the range in the middle and has 50 percent of the data
below it. The third quartile (upper quartile) has 75 percent of the data below it and the top 25
percent of the data above it.
The formulas for the quartiles are as follows.
Q1 = n + ¼ 25th
percentile
Q2 = n + 1/2 50th
percentile
Q3 = 3(n+1/4) 75th
percentile
58
4.4.5 Percentile
As shown in figure 23, numbers (value) that represents a percentage position in a list (range)
of data. For example, if the performance of an entity is at 43rd percentile, then it performs
better than 43 percent of all entities within its group.
4.4.6 The correlation coefficient
The correlation coefficient is another measure of linear association between two variables
that takes on values between -1 and +1. Values near +1 indicate a strong positive linear
relationship, values near -1 indicate a strong negative linear relationship, and values near 0
indicate the lack of a linear relationship.
The above theoretical formulas are practically adopted for the following findings for the
customer‟s requirement of feature.
With the above use of measures of dispersion it‟s evident that the need of increasing
customer satisfaction for the organization is a must to compete in the market and to have
a competitive advantage over the others. However The need of measures of dispersion is
so important if a business is to be viable as identifying the short fall either from the
customer nor from its market share can is easy, but to identify the exact factor can be
done only through precise data identification and measuring those effectively using the
available methods and overcoming the issues is very much important. Further through
measures of dispersion the decision making in a business scenario is much effective to the
strategic level decision makers.
59
4.5 Data presentation and format
Data interpretation is a body of methods that help to describe facts, detect patterns, develop
explanations, and test hypotheses. The numerical results provided by a data presentation are
usually simple which finds the number that describes a typical value and it finds differences
among numbers. Beside data can be significant in decision making in strategic planning, in
developing operational plans and in implementation of operational plans.Current business
technology permits companies to utilize many software programs and designs or to create
business decision making. Information technology commonly used in businesses includes
computers, servers, business software such as Ms Office to draw spreadsheets, Gantt charts
and other histograms, pie charts. Companies may also use software technology to gather
external information that allows them to make more profitable decisions.
However the author attempts to provide fundamental attitude about Graphs and charts in
following figure 24.
Figure 24: Fundamentals of Graphs and charts, Field work
Chart/graph Purpose
1. Pie To show relative sizes of the components of a data-set, in comparison to
one another and to the whole set.
2. Bar To compare classes or groups of data. In bar charts, a class or group can
have a single category of data, or they can be broken down further into
multiple categories for greater depth of analysis.
3. Line To displaying data or information that changes continuously over time.
4. Histograms
To show Individual data points are grouped together in classes, so that
managers can get an idea of how frequently data in each class occur in
the data set. High bars indicate more points in a class, and low bars
indicate fewer points.
60
4.5.1 Statistics of shopping at Threshers
As shown in figure 23, the author attempted to draw a pie chart which is shown in figure 25
about the customers shopping frequency at the Threshers. 37% of customers were shopping
so frequently to full fill their needs, 30% of them shop on a daily basis which indicates that
the organisation has to build up a very strong customer base and effective product portfolio,
further through this analyse its evident that the customer‟s satisfaction is high.
Figure 25: Sopping frequency at Threshers, Field work
Moreover the author used Microsoft Excel to interpret the data in figure 23. In doing so at
first author highlighted the data in figure 23 and Inserted menu at the top of Excel and located
the Chart panel, and the Pie item.
Then again author clicked the down arrow and selected the first Pie chart.
1- 2 times5%
3- 4 times28%
5- 7 times 37%
7 + times 30%
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4.5.2 Analysis of the weekly spending at Threshers.
The author attempted to analyse the consumers spending pattern in Excel spreadsheet by
entering the data in figure 26, to demonstrate the clear picture.
Figure 26: Consumer spending pattern, Field work.
Money spent on
wines
Frequency Class width Frequency density
1- 19 1 18 0.05
20 - 39 5 19 0.26
40 - 69 6 29 0.20
70 - 99 13 29 0.44
100 + 15 100 0.15
By using the same method as explained in above, (entering bar chart function) author was
able to draw a bar chart.
Figure 27: Spending pattern of customers, Field work
0 5 10 15 20
White
Red
Rose
Frequency
62
According to figure 27, this bar chart indicates that 37.5% of customers spending more than
£ 100 on a weekly basis, most of the customers purchase high end wines which unique to the
organisation and the competitors haven‟t been able to gain on , which also has high
margins,32.5% of customers spend between £70 - £99 whom are the regular customers of the
organisation , altogether 70 % of the customers are regular and permanent customers, which
is a positive factor considering the present economic condition.
On the other hand, the same data in figure 26 can be entered in excel spreadsheet by clicking
on line graph which is a different function and then can have a different conclusion.
Figure 28: Statistics on wine purchased, Field work
As shown in figure 28, this line graph indicates the amount of money that been spend on a
week. So the highest frequency density is 0.44 and the mode is 70 – 99.which is continuous
data.
0
2
4
6
8
10
12
14
16
18
20
1 2 3 4 5 6
Preferred wine Frequency
63
4.5.3 Statistics on consumer behavior
As explained in above, the author highlights the importance on analyzing the consumer
behavior in order to identifying the market position of Threshers. Hence, author used
Excel as usual to interpret data in figure 30 and obtained a fine conclusion.
Figure 30: Most preferred wine, Field work
Preferred wine Frequency
White 19
Red 14
Rose 7
Figure 31: Variety of wine purchased, Field work
According to figure 31, the most selling wine of the organisation is white , which is 47% of
the total sales and Rose wines amount for 35% of the sales, the organisation should adopt
strategies to increase the sales of Red wines .
47%
35%
18%
0% 10% 20% 30% 40% 50%
White
Rose
Red
64
4.6 Time Series Forecasting
As illustrated in figure 32, author utilized Excel to provide the set of evenly spaced
numerical data of the above wine company obtained by observing response variable at
regular time periods. This forecast based only on past values that assumes that factors
influencing past and present will continue influence in future
Figure 32: Components of Demand at the company, Field work
65
4.7 Marketing Strategy of Egham wines Ltd
Pinson (2001) marketing strategy integrates the activities involved in the product
development, promotion, distribution, and pricing approach, identifies firm marketing goals
and identifies how they will be achieved in a limited time frame. The marketing strategy of
the Egham wines Ltd is to increase the market share by 4% from the present share, as well as
to increase the sales of wines from 60% presently to 70% in two years time by (2011). This
would pave the way to them financially stabilize their position in the market.
Figure 33: Increased sales of wine, www.igham.co.uk
In figure 33 its been clearly defined the marketing strategy to increase sales of wines at
Threshers Egham branch by 10% from 2009 to 2011 which is an achievable target on the
present market share of the above organisation in the market.
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4.7.1 The present profit margins on sales of products
The figure 34 states the present profit margins of products at the above organisation which
shows 45% is gained from the sales of wine with 60% of sales and by achieving the
marketing strategy by 2011 would give the organisation the much needed assistance with the
economical constrains which is predicted by world over for next couple of years.
Figure 34: Profit margins, Field work
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Conclusion and Recommendation
From the above report it can be seen that there are many factors a company should consider
in making decisions. For an example, the author attempted to discuss these in depth via
evaluating the student satisfaction of St.patrick‟s college and arranging graduation ceremony.
And factors like strategies they are going to use against their other education establishments
what kind of courses does the market actually need, long term viability of the project and
many more. Answers for most of these can be found by conducting research and making
effective use of the information gathered.
Beside the authors took St Patrick‟s college as an example and showed how the college was
able to use a variety of sources for the collection of data, both primary and secondary. And
the author has discussed about a range of techniques to analyse data effectively for business
purposes. More over the author was able to produce information in appropriate formats for
decision making in an organisational context by using software-generated information to
make decisions in an organisation.
To be successful in today's business environment, the author recommends that organizations
need rapid and easy access to information about their finances, customers, and external
market conditions. According to the scenarios of St. Patrick‟s college author recommends to
use Microsoft's team collaboration and business intelligence solutions in which that not
only college but also other companies can achieve greater efficiency by easily and securely
sharing information with employees, stakeholders, and customers. And also the author
recommend for any company to Improve productivity and decision-making throughout
organization by integrating critical information with intuitive business operations
applications.
68
References
1. Albright,S,C.,Winston,W,L.,Zapper,C,J.,(2006) data analysis & Decision making :
with Microsoft Excel (3rd
edition) south western cengage leaning
2. Brue,G.,(2002) six sigma for managers ,Mc graw hill professional publication
3. Barnard, C. (1938), The Function of the Executive, Harvard University Press,
Cambridge, MA, .
4. Bass, B.M. (1990), Bass & Stogdill's Handbook of Leadership, Free Press, New York,
NY
5. Beer, M. (1997), "Conducting a performance appraisal interview", Class room note,
Harvard Business School case study, Boston, MA
6. Brown, J., Courtney, N., Hendry, C. (2006), "Innovation and the performance
management system", paper presented at Performance Measurement and Management
2006: Public and Private, Cranfield School of Management, Cranfield,
7. Crouch,S.,Housden,M., (2003) marketing research for managers (3rd
edition)
Butterworth – Heinemann publication
8. Clarck,M., (1998) researching and writing dissertations in hospitality & tourism,
Cenage learning
9. Donaldson, G., Lorsch, J. (1983), Decision Making at the Top, Basic Books, New
York, NY,
10. Gomes,R.,Knowels,AP.,(2006) Non profit marketing ,sage publication
11. Gygi,C.,(2006) six sigma for dummies wiley publication India
12. Hammond, J.S., Keeney, R.L., Raiffa, H. (1999), Smart Choices: A Practical Guide
to Making Better Decisions, Harvard Business School Press, Boston, MA,
13. Kopeikina, L. (2005), The Right Decision Every Time: How to Reach Perfect Clarity
on Tough Decisions, Prentice-Hall, Upper Saddle River, NJ,
14. Lake,C,C.,Harper,C,P., Alliance,M.,(1987) Public opinion pooling ,Island press
15. Malina, M.A., Selto, F.H. (2001), "Selto communicating and controlling strategy: an
empirical study of the effectiveness of the balanced scorecard", Journal of
Management Accounting Research, Vol. 13 pp.47-90.
16. Merchand, K.A., Simons, R. (1986), "Research and control in complex organizations:
an overview", Journal of Accounting Literature, Vol. 5 pp.183-203.
17. Pinson,L., (2002) anatomy of business plan (5th
edition) Dearborn trade publication
69
18. Schwager,J,D.,(1984) A complete guide to the future markets : fundamental analysis
,dchenal wiley publication
19. Seemann, P., Hüppi, R. (2001), "Social capital: securing competitive advantage in the
new economy", Financial Times, London,
20. Simons, R. (2005), Levers of Organization Design: How Managers Use
Accountability Systems for Greater Performance and Commitment, Harvard Business
School Press, Boston, MA, .
21. Simons, R. (1995), Levers of Control: How Managers Use Innovative Control
Systems to Drive Strategic Renewal, Harvard Business School Press, Boston, MA, .
22. Schwager,J,D.,(1984) A complete guide to the future markets : fundamental analysis
,dchenal wiley publication
23. Tylor,S.,(2007) The managers good study guide,(3rd
edition) open university
24. Wiiams(2008) Essenstial of statistics for business & economics (5th
edition) cengage
learning
25. Ulrich, D., Smallwood, N. (2003), Why the Bottom Line Isn't: How to Build Value
through People and Organization, Wiley, New York, NY,
70
Journal
1. Abernethy, M.A., Brownell, P. (1999), "The role of budgets in organizations facing
strategic change: an exploratory study", Accounting, Organization and Society, Vol.
24 No.3, pp.189-205.
2. Abernethy, M.A., Bouwens, J., van Lent, L. (2004), "Determinants of control system
design in divisionalized firms", The Accounting Review, Vol. 79 No.3, pp.545-70
3. Beer, M., Eisenstat, R.A. (2004), "How to have an honest conversation about your
business strategy", Harvard Business Review, Vol. 82 No.2, .
4. Bisbe, J., Otley, D. (2004), "The effects of the interactive use of management control
systems on product innovation", Accounting, Organization and Society, Vol. 29 No.8,
pp.709-37
5. Cannella, A.A., Monroe, M.J. (1997), "Contrasting perspectives on strategic leaders:
towards a more realistic view of top managers", Journal of Management, Vol. 23
pp.213-37.
6. Charan, R. (2001), "Conquering a culture of indecision", Harvard Business Review,
Vol. 79 No.4, pp.74-82.
7. Child, J. (1972), "Organizational structure, environment and performance: the role of
strategic choice", Sociology, Vol. 6 pp.1-22.
8. Koene, B.A.S., Vogelaar, A.L.W., Soeters, J.L. (2002), "Leadership effects on
organizational climate and financial performance: local leadership effect in chain
organizations", Leadership Quarterly, Vol. 13 No.3, pp.193-215
9. Waldmann, D.A., Ramirez, G.G., House, R.J., Puranam, P. (2001), "Does leadership
matter? CEO leadership attributes and profitability under conditions of perceived
environmental uncertainty", Academy of Management Journal, Vol. 44 No.1, pp.134-
43.
10. Simons, R. (1990), "The role of management control systems in creating competitive
advantage: new perspectives", Accounting, Organization and Society, Vol. 15 No.1/2,
pp.127-43.
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Appendix 1 : The Respondent Profile
Response rates have been broken down according to the profile categories included in the
survey. It should be noted that these response rates have not been corrected according to the
student population. The questionnairs were distributed by hand.
According to the questionnaire overall, communication of information was rated as very
important and satisfactory by the student population [B]. The only deviation from this was
within the way timetable is spread over the day and week; students thought this was
important rather than very important [b], and the complaints procedure which students
rated as only ok and important [c]. Students‟ overall level of satisfaction with the
communication of information on programme organisation and assessment was graded as
[B].
The personal tutor system received grade [B] for three of the four questions, with the question
on the ease of discussing personal problems with your personal tutor rated by students as
slightly less important, but just as satisfied [b]. Students overall satisfaction with the personal
tutor system was again graded as [B], satisfactory and very important.
Both the availability of information about assignment deadlines and clarity of information
about assessment dates were awarded [A] grades by students. However the usefulness of
tutor‟s / lecturer‟s feedback, the amount of feedback and the promptness of feedback on
assignments were graded lower by students as only [C], indicating only levels of average
satisfaction for issues which were regarded as very important. This reduced students‟ overall
satisfaction with their level of workload and assessment to [B].
Finally, in Your Evaluation – Overall satisfaction section, students were asked to rate various
aspects of their college experience from 0%, meaning that they were totally dissatisfied to
100% indicating total satisfaction. The college as a whole mean level of satisfaction was
76%. The average department percent was 75% the students‟ union was slightly lower at 67%
and students individual academic programme was rated at 74% and the potential career
prospects at 76% Finally, 93% of students would recommend the college to a friend or a
relative.
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Appendix 2: Project planning
Step 1: Project plan
A project is successful when the needs of the stakeholders have been met. A stakeholder is
anybody directly or indirectly impacted by the project.
As a first step, it is important to identify the stakeholders in St.patrick‟s graduation ceremony.
They are,
The project sponsor.
Students who receives the deliverables.
The users of the project outputs.
The project manager and project team.
By understanding who the stakeholders are, the next step is to find out their needs. The best
way to do this is by conducting stakeholder interviews. Take time during the interviews to
draw out the true needs that create real benefits. Often stakeholders will talk about needs that
aren't relevant and don't deliver benefits. These set the goals and objectives for the project.
The goal of the event is to arrange a graduate ceremony .The objectives of the project are to
form twenty six team members to start the project on 6th
June 2011, complete within 85
weeks, under the allocated budget cost of £40,000 and invite external educational bodies, to
explain the significance of education at St.patrick‟s college. The quality of the conference is
measured from feedback.
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Step 2: Project deliverables
Using the goals have defined in step 1, there are a list of things that the project needs to
deliver in order to meet those goals. They are,
- corroborate the guests
- Carry out a search on event halls.
-choose a venue
- discover and enquire the catering providers
- Confirm venue and Catering services
-arrange the programme for each days of the event.
More accurate delivery date will be established during the scheduling phase, which is next.
Step 3: Project Schedule
At this point in the planning, author could choose to use a software package such as
Microsoft project professional to create project schedule. Moreover the following facilities
are required to manage the project more effectively and efficiently.
• Computers, printers, and software for the project management team.
• These resources can be shared with team members at later stage.
• Utilize the Students database to access for the graduation event.
• External meetings – such as Venues, Meeting rooms‟ facilities.
• Document handing and central storage system electronically and security restrictions.
A common problem discovered at this point, is when a project has an imposed delivery
deadline from the sponsor that is not realistic based on estimation. If author discovers that
this is the case, author must contact the sponsor immediately. The options author has in this
situation are renegotiate the deadline (project delay),employ additional resources (increased
cost),reduce the scope of the project (less delivered),Finally author needs to use the project
schedule to justify pursuing one of these options.
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Step 4: Supporting Plans
This section deals with plans that author attempted to create as part of the planning process.
These can be included directly in the plan.
Human Resource Plan
Communications Plan
Risk Management Plan
Here are some examples of common project risks:
Time and cost estimates too optimistic.
Customer review and feedback cycle too slow.
Unexpected budget cuts.
Unclear roles and responsibilities.
Stakeholder input is not sought, or their needs are not properly understood.
Stakeholders changing requirements after the project has started.
Stakeholders adding new requirements after the project have started.
Poor communication resulting in misunderstandings, quality problems and rework.
Lack of resource commitment.
Risks can be tracked using a simple risk log. And author suggests by reviewing risk log on a
regular basis, adding new risks as they occur during the life of the project.
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Appendix 3: Power point presentation for Q4
A Statistical analysis
of Customer
satisfaction at
Egham wines Ltd
Egham wines Ltd
First Quench Retailing is the UK’s leading independent specialist drinks retailer which brings in Threshers, The Locals, Wine Rack and Haddows. Together First Quench Retailing operates over 1500 outlets and employs over 12,000 people across the country. It’s the UKs 13th largest private retailer and it serves over 150 million customers a year across the different brands all over.
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Measures of Central Tendency
While distributions provide an overall picture of some data set, it is sometimes desirable to represent some property of the entire data set using a single statistic
There are different measures of central tendency,
The mode
The median
The mean
1- 2 times5%
3- 4 times28%
5- 7 times 37%
7 + times 30%
Figure 1
The Mode
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Figure 1 shows the customers shopping frequency at the Threshers where 37% of them shop so frequently to full fill there needs , 30% of them shop on a daily basis which indicates that the organisation has build up a very strong customer base and effective product portfolio, further through this analyse its evident that the customers satisfaction is high.
And the shopping frequency at the discussed branch where the highest frequency density is 11 which is the mode of shopping in a week at the branch is 3- 4 .
The Mean and The Median
The two most common measures of central tendency are the median and the mean, which can be illustrated with an example. Suppose Threshers draw a sample of five customers and measure their purchasing behaviour. They buy products for 100 pounds, 100 pounds, 130 pounds, 140 pounds, and 150 pounds.
To find the median, better to arrange the observations in order from smallest to largest value. If there is an odd number of observations, the median is the middle value. If there is an even number of observations, the median is the average of the two middle values. Thus, in the sample of five customers, the median value would be 130 pounds; since 130 pounds is the middle price.
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The mean of a sample or a population is computed by adding all of the observations and dividing by the number of observations. Returning to the example of the five customers, the mean of their purchasing behaviour would equal (100 + 100 + 130 + 140 + 150)/5 = 620/5 = 124 pounds. In the general case, the mean can be calculated, using one of the following equations: Population mean = μ = ΣX / N OR Sample mean = x = Σx / n
where ΣX is the sum of all the population observations, N is the number of population observations, Σx is the sum of all the sample observations, and n is the number of sample observations.
Measures of dispersionSchwager (1986) illustrates that the important characteristic
of a data set is how it is distributed, or how far each element is from some measure of central tendency (average). There are several ways to measure the variability of the data. Although the most common and most important is the standard deviation, which provides an average distance for each element from the mean, several others are also important.
The mainly used measures of dispersion are as follows.
Range
Standard deviation
Interquartile range
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The information was generated from this basic question.
‘ What’s the features that does not have on customers purchased wine ’ ,Opinion of customers ,
Taste Aroma Body Flavours Blend Other
Table 2 customers preferred opinion on the wine features
0%
5%
10%
15%
20%
25%
30%
35%
40%
Taste Aroma Body Flavours Blend Other
Figure 3, Characters of the wine
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Range
Gegi (2006) the simplest measure of the spread of your data is its range , the range of a distribution is defined as the difference between the largest and the smallest observed data values. One of the simplest measures of variability to calculate, depends only on extreme values and provides no information about how the remaining data is distributed.
From the finding from the customers,the range is as below.
The lowest and highest data values respectively is 2 and 15
15 –2 = 13 is the range in the table 1 this range falls in between the features 3 and 4 which are body of the wine and flavors of the wine which are the features the customers feel lacking in the present range of available wines which need to be taken in to considered in the new product development of wines which will satisfy the customers needs effectively.
Standard deviation
Greg(2002 ) defines standard deviation as the average difference between any values and the mean of all the values, further he explains this statistics is a measure of the variation in a distribution value.
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Values = 4+4+15+10+5+2 = 40 / 6 = 6.6 As per the above calculation the standard deviation value is 6.6 which represent the features of Aroma and Body of the wine which the customers think need to be improved.
Inter quartile Range
Williams(2008) defines inter quartile as a measure of variability that overcomes the dependency on extreme values is the interquratile range .further he states these measure of variability is the difference between the third quartile Q3 and the first quartile Q1.
Lower quartile
Williams (2008) defines interquartile as the value of the boundary at the 25th, 50th, or 75th percentiles of a frequency distribution divided into four parts, each containing a quarter of the population. The 25th being the lower quartile 50th being the median and the 75th being the upper quartile .
explains the lower and the upper quartile values for selected area.
Formula Q1 = n + ¼
Q1 = 40 + ¼
Q1 = 10.25
In table 1 the lower quartile value is represented by the feature is the aroma and the body of the wine, which is one of the main and most sorted after feature by the customers.
Upper quartile
formula Q3 = 3(1+ 1/4)
Q3 = 40 (1+ ¼)
Q3 = 30.75
The above upper quartile value represent the feature body and flavor of the wine , where the opinion reflects that the present features are that very well accepted by the customers where they emphasize the fact that new wines with the selected features which they are interested need to be developed by the organization to retain the present customer base.
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Quartiles
One of the three numbers (values) that divide a rangeof data into four equal parts. The first quartile (lower quartile) is the number below, which lays the 25 percent of the bottom data. The second quartile (median) divides the range in the middle and has 50 percent of the data below it. The third quartile (upper quartile) has 75 percent of the data below it and the top 25 percent of the data above it.
The formulas for the quartiles are as follows.
Q1 = n + ¼ 25th percentile
Q2 = n + 1/2 50th percentile
Q3 = 3(n+1/4) 75th percentile
Percentile
Number (value) that represents a percentage position in a list (range) of data. For example, if the performance of an entity is at 43rd percentile, then it performs better than 43 percent of all entities within its group.
The correlation coefficient is another measure of linear association between two variables that takes on values between -1 and +1. Values near +1 indicate a strong positive linear relationship, values near -1 indicate a strong negative linear relationship, and values near 0 indicate the lack of a linear relationship.
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The above theoretical formulas are practically adopted for the following findings for the customers requirement of feature.
With the above use of measures of dispersion it’s
evident that the need of increasing customer
satisfaction for the organization is a must to
compete in the market and to have a competitive
advantage over the others.
However The need of measures of dispersion is so important if a business is to be viable as identifying the short fall either from the customer nor from its market share can is easy, but to identify the exact factor can be done only through precise data identification and measuring those effectively using the available methods and overcoming the issues is very much important. Further through measures of dispersion the decision making in a business scenario is much effective to the strategic level decision makers.
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Time Series Forecasting
Set of evenly spaced numerical data
Obtained by observing response variable at regular time periods
Forecast based only on past values
Assumes that factors influencing past and present will continue influence in future
Components of Demand at the company
Figure 4 : Components of demand
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The present profit margins
on sales of products
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Wine Spirits Beer Others
Figure 6: Profit margins
The figure 6 states the present profit margins of products at the above organisation which shows 45% is gained from the sales of wine with 60% of sales and by achieving the marketing strategy by 2011 would give the organisation the much needed assistance with the economical constrains which is predicted by world over for next couple of years.
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