Business Decision Making Report: Restaurant Location Analysis

This report provides a comprehensive analysis of business decision-making processes, specifically focusing on the feasibility of opening a new restaurant location. It begins with an introduction outlining the importance of decision-making in business and then proceeds to detail the sources used for data collection, including primary and secondary data. The report describes the methodology for conducting a questionnaire survey, including the sampling frame and the questionnaire itself. The analysis section covers various data analysis techniques, such as measures of dispersion, quartiles, percentiles, and correlation coefficients, along with the interpretation of results. The report further demonstrates how to produce information in appropriate formats using graphs and trend lines within spreadsheets. The inclusion of a business presentation and a formal business report exemplifies the effective communication of findings. Finally, the report explores the use of software-generated information for making decisions at operational, tactical, and strategic levels, incorporating financial tools like payback period, internal rate of return, and net present value to assess investment projects. The conclusion summarizes key findings and recommendations, while the references and illustrations support the analysis.

BUSINESS DECISION MAKING
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TABLE OF CONTENTS
INTRODUCTION................................................................................................................................5
TASK 1 SOURCES FOR THE COLLECTION OF DATA.................................................................5
1.1 Collection of primary and secondary data............................................................................5
1.2 Survey methodology and sampling frame............................................................................5
1.3 Questionnaire for a survey....................................................................................................6
TASK 2 RANGE OF TECHNIQUES TO ANALYSE DATA .............................................................7
2.1 Information for decision making...........................................................................................7
2.2 Analyse the results to draw valid conclusions.......................................................................8
2.3 Analyse data using measures of dispersion...........................................................................9
2.4 Analysis of quartiles, percentiles and the correlation coefficient.........................................9
TASK 3 PRODUCE INFORMATION IN APPROPRIATE FORMATS...........................................10
3.1 Graphs using spreadsheets and draw valid conclusions......................................................10
3.2 Trend lines in spreadsheet graphs to assist in forecasting sales revenue............................11
3.3 Business presentation..........................................................................................................12
3.4 Formal business report........................................................................................................12
TASK 4 SOFTWARE GENERATED INFORMATION TO MAKE DECISIONS...........................13
4.1 Information processing tools for operational, tactical and strategic level decisions...........13
4.2 Plan for the activity.............................................................................................................14
4.3 Financial tools for decision making....................................................................................16
CONCLUSION..................................................................................................................................17
REFERENCES...................................................................................................................................19
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ILLUSTRATION INDEX
Illustration 1: Histogram for revenue and profit.................................................................................10
Illustration 2: Line chart for revenue and profit.................................................................................11
Illustration 3: Trend line.....................................................................................................................12
Illustration 4: Gantt Chart...................................................................................................................15
Illustration 5: Network Diagram........................................................................................................15
Illustration 6: Gantt Chart...................................................................................................................16
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INDEX OF TABLES
Table 1: 10 Year financial data.............................................................................................................7
Table 2: Revenue Statistics...................................................................................................................7
Table 3: Profit Statistics........................................................................................................................8
Table 4: Quartile...................................................................................................................................9
Table 5: Percentile................................................................................................................................9
Table 6: Correlation Coefficient.........................................................................................................10
Table 7: Plan for the activity...............................................................................................................14
Table 8: Financial Information...........................................................................................................16
Table 9: Pay Back Period....................................................................................................................16
Table 10: Internal rate of return..........................................................................................................17
Table 11: Net Present Value................................................................................................................17
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INTRODUCTION
Decision making plays a crucial role in every business as it assist in prudent judgement with
the support of feasibility and profitability. It thus requires a through research in the internal and
external environment of the business environment so that each area is examined properly. In respect
with this, the following report is prepared on decision making for a new restaurant location. The
report covers market and financial feasibility analysis to design strategies to achieve the targets.
Previous financial performance of the existing chain is also examined to forecast the future
performance. Along with this, different investment projects are also analysed in terms of feasibility
to carry out the activities.
TASK 1 SOURCES FOR THE COLLECTION OF DATA
1.1 Collection of primary and secondary data
The purpose of market research is to collect and analyse consumer perception for the
existing restaurant. It thus helps in determining the strengths and weaknesses to take necessary
actions. Different sources are identified for collection of information to examine the internal and
external environment of the business (Bai, Nunez and Kalagnanam, 2012). Primacy - A structured questionnaire survey is used to collect first hand information from
the customers who regularly visit restaurants for dining out. This helps in analysing the
preferences and choice of customer in terms of food variety, quality, prices, decor, and many
more (Desai, 2008). Although questionnaire consumed time and cost, but provide valuable
information from the customer's side.
 Secondary - Information already collected by another person for some other purpose comes
under secondary data. For the present market research, data from online websites, books,
journals and case studies are obtained to analyse various other variables such as trends in the
industry, upcoming events, presence of competitors and market share (Hoaglin, 2003).
Both these sources contributes effectively to get insight into the current and future trends of
the restaurant industry.
1.2 Survey methodology and sampling frame
Survey methodology assist in developing a systematic plan to carry out collection of data
through questionnaire survey. To investigate into the consumer behaviour for the existing branch of
restaurant, questions related with menu choices, quality and price are taken into consideration. The
questionnaire survey is completed in a day's activity (Morato, 2013). Specific locations that attracts
huge number of crowd are selected, so that valid opinions are collected. The sample population for
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the questionnaire survey is limited to 15 respondents. Although more than 40 questionnaire were
distributed, but only 20 received back. Among the total received, there were only 15 which were
fully completed. According to the plan, incomplete questionnaires were not taken into consideration
for the analysis.
1.3 Questionnaire for a survey
Demographic profile
1. Age
 20-30
 30-40
 40-50
 Above 50
2. Gender
 Male
 Female
 LGBT
3. Occupation:
4. Monthly household Income:
5. Size of the household:
6. Marital status:
7. Presence of children:
8. How frequently do you visit restaurant on monthly basis?
 Less than one
 Weekly
 Bi weekly
 Bi monthly
9. what time do you prefer for dining out?
 Breakfast
 Lunch
 Afternoon
 Dinner
10. How do you like menu choices at Moonlight
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 Ok
 Good
 Very Good
 Excellent
11. How do you find prices of food at Moonlight?
 Ok
 Good
 Very Good
 Excellent
12. How do you find food quality at Moonlight?
 Ok
 Good
 Very Good
 Excellent
TASK 2 RANGE OF TECHNIQUES TO ANALYSE DATA
2.1 Information for decision making
Table 1: 10 Year financial data
Year Revenue Profit
2005 528 160
2006 590 180
2007 450 120
2008 335 100
2009 280 60
2010 300 67
2011 450 125
2012 490 149
2013 525 155
2014 585 183
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Table 2: Revenue Statistics
Revenue
Mean 453.3
Standard Error 35.8469121559
Median 470
Mode 450
Standard Deviation 113.3578894965
Sample Variance
12850.011111111
1
Kurtosis -1.2205102304
Skewness -0.4566573894
Range 310
Minimum 280
Maximum 590
Sum 4533
Count 10
Table 3: Profit Statistics
Profit
Mean 129.9
Standard Error 13.7795742556
Median 137
Mode #N/A
Standard Deviation 43.5748398352
Sample Variance 1898.7666666667
Kurtosis -0.9530479149
Skewness -0.4913144776
Range 123
Minimum 60
Maximum 183
Sum 1299
Count 10
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2.2 Analyse the results to draw valid conclusions Primary Data Analysis - It has been analyse through the questionnaire survey that majority
of customers who regularly visit belong to age group of 25 to 45 years. All genders are
equally interest in dining out on regular basis. Income of respondents who visit restaurants
are between £5000 to £20000. This means that there are customers available for every kind
of food varieties ranging from low to high price (Ofir, Simonson and Yoon, 2009). Majority
of customer visit on weekly basis at the dinner time. this indicates that customer enjoy their
weekend at some restaurants and have quality of time with friends and family. The food
quality and prices are rates excellent in favour of Moonlight. The only thing customer do not
like is variety of food choices.
 Secondary Data - Previous 10 years financial data is taken into consideration to analyse the
performance of the existing location. The average sales and profit earned by the restaurant
are £453 and £129. this reflects consistency of the brand to achieve income and manage its
expenses.
The median revenue for the restaurant is £470 and profit is £137. Both the values are higher
than the mean which indicates overall increasing profits for the business (Tracy, 2009). The mode
value for revenue is £450 which means there is repetition the figure more than once in ten years.
There is no mode value for the profit.
The Skewness value for both revenue and profit is negative which indicates data is skewed
to the left. Similarly Kurtosis value for both the variables are also negative which shows data is less
clustered around the mean.
2.3 Analyse data using measures of dispersion
 Range - This is the simplest measure of dispersion which measure the spread between the
highest and smallest value. The measure is not widely used as it ignores other values in the
population (Witzel, 2004).
Revenue - 310
Profit - 123 Standard Deviation - It is square root of variance and quantified variability. It is expressed
in same units as data is presented. The higher the value, the more spread is the data from the
mean. Standard deviation for revenue and profit is 113.35 and 43.57 respectively.
 Variance - It measures the spread in data points in the observation. Variance for revenue and
profit is 12850.01 and 1898.76 respectively (Newbold and et. al. 2009).
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2.4 Analysis of quartiles, percentiles and the correlation coefficient
 Quartile - The table below shows calculation of quartiles that divides the observations into
four equal parts. First quartile represents lowest 25% of the data, while third quartile
presents highest 25% of the data. In below table, 363.75 is the first quartile and 527.25 is the
third quartile.
Table 4: Quartile
Revenue Profit
Quartile 1 363.75 105
Quartile 2 470 137
Quartile 3 527.25 158.75
Quartile 4 590 183
 Percentile - This measure is similar to quartile with the only difference that divided the
observations into 100 equal parts. 10 percentile stands at 298 which is the lowest while 90
percentile stands at 585 which is the highest (Walliman, 2011).
Table 5: Percentile
Revenue Profit
Percentile 10 % 298 66.3
Percentile 60% 504 151.4
Percentile 80% 539.4 164
Percentile 90% 585.5 180.3
 Correlation Coefficient - This measure represents the linear relationship between two
variables - revenue and profit. the values indicates change in one variable from the change in
another. It is important that the two variables are continuous and quantitative. In below
table, there is perfect positive correlation between revenue and profit indicating change in
revenue directly impacts the profit margin (Platt and Huettel, 2008).
Table 6: Correlation Coefficient
Revenue Profit
Column 1 1
Column 2 0.9882430426 1
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TASK 3 PRODUCE INFORMATION IN APPROPRIATE FORMATS
3.1 Graphs using spreadsheets and draw valid conclusions
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
0
100
200
300
400
500
600
700
Revenue
Profit
Illustration 1: Histogram for revenue and profit
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
0
100
200
300
400
500
600
700
Revenue
Profit
Illustration 2: Line chart for revenue and profit
Interpretation
Analysing the revenue and profit of the last 10 years of the existing restaurant, it can be
concludes that business decisions taken in the past were successful in achieving the desired benefits.
The chart shows revenue for the year 2005 was £528 which increased to £590 in 2006. Sales was
positive in 2007 at 450 but low from the previous levels. It further declined to in 2008 (£335) and in
2009 (£280). The reason for decline is attributed to the economic recession as consumer cut
spending on various things. During these years, profit margin was also declined, but managed to
remain positive. Margins rose from 2010 and continued to move upwards till 2014. The upside and
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decline of revenue and profit margins shows that despite the spending cuts from the consumer side,
the restaurant was able to cover its expenses and earn hefty income for shareholders and employees
(Degu and Yigzaw, 2006). This also indicates decision making by the management and devising
strategies to attract consumers and earn sales. Percentage of profit margin to revenue was 30.30 in
2005 which increase to 31.28 in 2014. This can be interpreted as allocation of financial funds to
areas that generates higher sales. The business is eyeing for higher sales as compared with profit so
as to retain the existing customers.
3.2 Trend lines in spreadsheet graphs to assist in forecasting sales revenue
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
0
100
200
300
400
500
600
700 f(x) = 3.77575757575758 x + 432.533333333333
R² = 0.0101698873139623
f(x) = 1.56969696969697 x + 121.266666666667
R² = 0.0118951926441
Revenue
Linear (Revenue)
Profit
Linear (Profit)
Illustration 3: Trend line
Forecasting
The above chart shows trend lines of revenue and profit for the existing restaurant location.
above chart is drawn assuming the linear trends for both variables. It can be seen from the above
chart that R square value stands at 0.01 for both the variables. This indicates extreme fluctuations in
the values in the last 10 years. This fluctuation can be understood in the sense that business was
able to earn increasing revenue and profit in the first two years, then margins declined in the next
six years. With the improvements in the economic conditions, the business was able to earn margins
compared with the first year basis. An important thing identified in the financial performance is that
margins did not fell into negative state in any of the years (Bai, Nunez and Kalagnanam, 2012).
Somehow the restaurant managed to earn profits after meeting all expenses. Keeping in mind these
performance levels, it can be said that restaurant has the capability to earn higher margins in the
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coming years. From the financial data, the sales and profit improved in 2010 and continued to
increase since then. This is again a positive aspect of the business which shows its ability to remain
stable even in weak economic scenario. The reason for this performance is ability of the
management to take wise decisions which help it to compete effectively.
3.3 Business presentation
POWER POINT PRESENTATION
3.4 Formal business report
FORMAL BUSINESS REPORT
Opening of new restaurant
To: Board of directors
From:
Status: Confidential
Date: 7 September 2015
Introduction and terms of reference
The report is aimed at analysing the consumer and market behaviour to assist in decision making
for opening of new restaurant. The process begins with market research and previous financial
analysis, so that future trends and performance can be predicted.
Method
Following methods were used to collect and analyse data -
Primary - Data is collected through questionnaire survey to take into consideration consumer
attitude and behaviour towards dining out. In addition to this, customer response for the current
location is also examined.
Secondary - financial information of business of last 10 years are analysed to judge profitability
and forecasting future performance.
Findings
The questionnaire survey reveals that existing restaurant is able to deliver value to customers in
terms of quality and prices. The only thing customer do not like is menu choices.
Annual financial reports shows that business has been able to earn sufficient margins even during
the downtimes. There were declining sales, but in none of the years the figures move towards
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negative.
Conclusion
It can be concluded from the analysis that existing location is performing well in terms of
customer satisfaction and shareholder value. It can be said that it is the decision making ability of
the management that maintains the stability and profitability of the restaurant. It moreover
provides the opportunity to expand into new locations and provide service to more new customers.
TASK 4 SOFTWARE GENERATED INFORMATION TO MAKE DECISIONS
4.1 Information processing tools for operational, tactical and strategic level decisions
Information processing tools are combination of planned methods which are structured in
well designed format to assist in collection, recording and analysis of information for use by
managers at different events in the business Transaction Processing System (TPS) - This system collects data related with routine
business transactions that took place in the course of business such as purchase, sales,
orders, etc. at the current business location, data is recorded through computer systems
which are only accessible to authorised users (Desai, 2008). Management Information System (MIS) - This is the decision support system for use by
the middle level management to analyse issues in the business. Managers directly interact
with the data and use statistical tools to analyse it and draw conclusions (Tracy, 2009).
Conclusions are drawn to cut unnecessary expenses and allocate money to profitable areas. Decision Support System (DSS) - These are computer based systems that assist decision
makers to deal with complex issues. Specialists and experts in the organization use this type
of information. It provides access to TPS to collect information summary.
4.2 Plan for the activity
Table 7: Plan for the activity
Task List of Activities Estimated time (weeks) Preceding activity
A Market Research 3
B Legal Formalities 3 A
C Location 4 B
D Identifying resource requirement 2 A
E Supply Sources 1 D
F Floor Designing 1 D
G Kitchen Equipment Delivery 1 E
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H Furniture Delivery 1 F
I Employee Recruitment, Training, Development 1 D
J Interior Decor 1 H
K Marketing & Advertising 3 I, J
Illustration 4: Gantt Chart
Illustration 5: Network Diagram
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Illustration 6: Gantt Chart
Activity Early Start Early Finish Late Start Late Finish
A 0 3 0 3
B 3 6 4 7
C 6 10 7 11
D 3 5 3 5
E 5 6 9 10
F 5 6 5 6
G 6 7 10 11
H 6 7 6 7
I 5 6 7 8
J 7 8 7 8
K 8 11 8 11
Project 11
Critical Path: The above tables and charts shows the list of activities to be carried out to establish
the space for new restaurant location. Gantt chart indicates critical activities which are important to
be carried out with utmost care. The entire planned development is estimated to be completed
within 11 weeks if all activities are completed within the set duration.
4.3 Financial tools for decision making
Table 8: Financial Information
Year Project A Project B
Cost 600000 600000
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Net Cash flow (￡’000) Net Cash flow (￡’000)
1 100 50
2 200 150
3 400 300
4 440 500
5 500 400
 Pay Back Period - This measure is used to estimate the time duration each investment
project need to generating cash flows after covering initial cost (Witzel, 2004). In the below
table, Project A is more profitable compared with project B as it will start earning profits
after 2.75 years. Project B will take 3.2 years to contribute to profit margins.
Table 9: Pay Back Period
Year Project A (￡’000) Cumulative Project B (￡’000) Cumulative
Cost -600 -600
1 100 -500 50 -550
2 200 -300 150 -400
3 400 100 300 -100
4 440 540 500 400
5 500 1040 400 800
Payback period 2.75 years 3.2 years
 Internal Rate Of Return - This measure calculates the rate of return at which the net present
value of investment project becomes zero (Morato, 2013). From the table below, Project A
provides higher rate of return at 34.31% compared with Project B at 26.51% (Internal rate
of return. 2011).
Table 10: Internal rate of return
Year Project A (￡’000) Project B (￡’000)
Cost -600 -600
1 100 50
2 200 150
3 400 300
4 440 500
5 500 400
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IRR 34.31% 26.51%
 Net Present Value - This is the most commonly used method of capital budgeting as it
calculates future cash inflows in present value. Present value factor at the rate of 10% is
assumed to calculate cash inflows. After deducting initial cost, Project A (£567.52) provides
higher earnings compared with Project B (£384.55).
Table 11: Net Present Value
Year Project A (￡’000) Project B (￡’000) PV factor @10% Project A Project B
1 100 50 0.909 90.9 45.45
2 200 150 0.826 165.2 123.9
3 400 300 0.751 300.4 225.3
4 440 500 0.683 300.52 341.5
5 500 400 0.621 310.5 248.4
Total present value (￡’000) 1167.52 984.55
Cost 600 600
Net present value (￡’000) 567.52 384.55
It can be concluded from the above calculations that project A is feasible and profitable
compared with project B. Although calculation shows positive earnings for both the projects, but
upon comparison project A leads project B, So higher earnings from project A can be used for
further investment or savings.
CONCLUSION
From the above report, it can be concludes that business decision making must be backed by
sufficient information from the current and past to ensure feasibility. Various data sources must be
targeted to collect relevant and valuable information to maintain accuracy and reliability. The
present reports helps in understanding the statistical tools and methods used in evaluating business
performance from various aspects. It also helps in analysing the use of capital budgeting techniques
to assist in the selection of project on the basis of the profitability and feasibility.
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REFERENCES
Journals and Books
Bai, X., Nunez, M. and Kalagnanam, R. J., 2012. Managing Data Quality Risk in Accounting
Information Systems. Information Systems Research. 23(2). pp. 453-473.
Desai, P., 2008. Ethnography for Marketers. Qualitative Market Research: An International
Journal. 11(4). pp.443 - 445.
Hoaglin, C. D., 2003. John W. Tukey and Data Analysis. Statistical Science. 18(3). pp. 311-318.
Morato, A. E., 2013. Business Decision Making. eBookIt.com.
Newbold, P. and et. al. 2009. Statistics for Business and Economics. Pearson Education
Ofir, C., Simonson, I. and Yoon, S., 2009. The Robustness of the Effects of Consumers'
Participation in Market Research: The Case of Service Quality Evaluations. Journal of
Marketing. 73(6). pp. 105-114.
Platt, M. L. and Huettel, S. A. 2008. Risky business: the neuroeconomics of decision making under
uncertainty. Nature neuroscience. 11(4).pp. 398-403.
Tracy, A. J, 2009. How to Read a Financial Report: Wringing Vital Signs Out of the Numbers. John
Wiley and Sons.
Walliman, N. S., 2011. Research Methods: The Basics: The Basics. Taylor & Francis.
Witzel, M., 2004. Management: the basics. Psychology Press.
Online
Degu, G. and Yigzaw, T., 2006. Research Methedology. [Pdf]. Available through:
<http://www.cartercenter.org/resources/pdfs/health/ephti/library/lecture_notes/
health_science_students/ln_research_method_final.pdf>. [Accessed on 7 September 2015].
Internal rate of return. 2011. [Online]. Available through:
<http://www.princeton.edu/~achaney/tmve/wiki100k/docs/Internal_rate_of_return.html>
[Accessed on 7 September 2015].
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