Business Decision Making Report: Data Analysis for XYZ Hotel London

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This report provides a detailed analysis of business decision-making for the hypothetical XYZ hotel chain, which is considering setting up a hotel in London. The report begins with an introduction highlighting the importance of data-driven decisions and then moves into Task 1, which covers data collection methods, including primary and secondary data sources, and survey methodology. The report includes a questionnaire designed to gather relevant market information. Data collected, including sales and expenditure figures, is then summarized using representative values and analyzed through various statistical tools, such as mean, median, mode, standard deviation, measures of dispersion, quartiles, percentiles, and correlation. Task 2 focuses on graphical representations and capital budgeting techniques, including trend lines and a business report summarizing the findings. The report concludes that opening a hotel in London is a feasible option based on the positive results obtained through the data analysis and statistical tools. The report also uses information processing tools and provides a project plan for an activity, alongside the use of financial tools to aid in decision-making.
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Business decision making
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TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
TASK 1 DATA COLLECTION......................................................................................................1
1.1 Collection of primary and secondary data.............................................................................1
1.2 Survey methodology..............................................................................................................2
1.3 Questionnaire for given business problem............................................................................2
2.1 Collect data and summarize the collected data using representative values..........................4
2.2 Analyze the collected data.....................................................................................................4
2.3 Measures of dispersion..........................................................................................................5
2.4 Your calculations must include quartile, percentiles and the correlation..............................5
TASK 2 GRAPHS AND CAPITAL BUDGETING TECHNIQUES.............................................6
3.1 Graph conclusion...................................................................................................................6
3.2 Trend line...............................................................................................................................7
3.3 Business presentation.............................................................................................................7
3.4 Business report.......................................................................................................................7
4.1 Information processing tools.................................................................................................8
4.2 Project plan for an activity.....................................................................................................9
4.3 Use financial tools for decision making..............................................................................10
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14
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TABLE OF FIGURES
Figure 1: Graph of sales and expenses data.....................................................................................6
Figure 2: trend line for sales and expenses of XYZ........................................................................7
Figure 3: Gantt chart........................................................................................................................9
Figure 4: Critical path....................................................................................................................10
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INTRODUCTION
Decision making quality of the organization is significantly influenced by the quality of
information underlying the decisions. There are various sources through which an entity can
gather useful data that serves its purpose of arriving at timely and relevant information. It is
therefore crucial for every organization to take reasonable initiatives to come up with reasonable
conclusions about the source through which it can get the desired information and identify the
techniques through which the gathered data can be analyzed to derive the useful results. In the
assigned unit, we are taking hypothetical example XYZ hotel chain which is intending to set up
its hotel in London and keen to know whether its action would be viable or not. Therefore, the
discussion undertaken in aforesaid paragraphs will assist it in deciding as to whether it shall
resort to such a move or not.
TASK 1 DATA COLLECTION
1.1 Collection of primary and secondary data
Data can be collected through primary as well as secondary means. While primary means
are concerned with capturing data directly from the target population, secondary means place
reliance on external sources which gives an insight of trends prevailing in the market and people
´s attitude towards the specific industry (Sapsford and Jupp, 2006). Given below are some of the
techniques through which primary and secondary data can be gathered by the organization.
Primary data can be collected through: Interview – It involves personal interaction with the concerned audience in order to gain
in depth understanding of their preferences and their perceptions about the particular
industry. Questionnaires – In this technique, questionnaire is prepared covering relevant aspects
and circulated among the target audience to get an overview about the situations
prevailing in the market.
 Observations – It deals with observing the trend to gather general understanding about
people’s attitude towards the concerned industry.
Secondary data can be collected through external sources such as newspapers, magazines,
journals, internet etc. which gives general information about trends prevailing in market and
performance of the concerned industry (Lusthaus, 2000). However, information collected
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through secondary sources is useful only to limited extent as compared to the information
collected through primary means because secondary data usually offers a broader perspective
which cannot be relied upon as a strong basis for formulating strategic as well as long term
decisions. Accordingly, it is advisable for XYZ to collect information about the prevailing
market trends in London through primary sources as against secondary sources in order to
facilitate effective decision making.
1.2 Survey methodology
Survey methodology refers to selection and study of samples from the target population
and identifying the techniques through which collected data can be analyzed in order to arrive at
reasonable inferences. The sample is selected in such a way that it is representative of the entire
population being targeted and is not just confined to any particular section of the society.
Sampling can be either probabilistic sampling or non probabilistic sampling (Ryan and Ryan,
2002). A brief description of these sampling techniques has been given as follows:
ï‚· Under probabilistic sampling, samples are selected from the target population in such a
manner that they represent the whole population. The level of confidence is high and
probability of error occurrence is comparatively low as compared to the non probabilistic
sampling.
 Non probabilistic sampling – Under this sampling techniques, samples are selected
haphazardly without giving consideration as to whether they are apt for the purpose to be
achieved.
As far as XYZ is concerned, it is advisable for it to go for probabilistic sampling since it
can be observed as more convenient means of yielding relevant outcomes as compared to non
probabilistic sampling.
1.3 Questionnaire for given business problem
1. Name:
2. Age:
3. Gender:
ï‚  Male
ï‚  Female
4. Marital status:
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ï‚  Single
ï‚  Married
5. Income range.
ï‚  Below 30000
ï‚  Between 30000-80000
ï‚  Above 80000
6. Frequency of visiting hotels.
ï‚  Once in a week
ï‚  Twice in a week
ï‚  Monthly
ï‚  Frequently
7. What kind of food they prefer?
ï‚  Continental
ï‚  Fast food
ï‚  Snacks
8. Do they prefer home services for the chosen option?
ï‚  Yes
ï‚  No
9. What aspects do they prefer while visiting hotels?
ï‚  Price
ï‚  Quality
ï‚  Location
ï‚  Ambience
10. What amount are they willing to pay?
 Below £ 2
 Between £ 2- £5
 Above£ 5
11. Do they welcome new entrants?
ï‚  Yes
ï‚  No
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2.1Collect data and summarize the collected data using representative values
Table 1: Sales data for XYZ
2006 2007 2008 2009 2010 2011 2012 2013
Sales (in £) 10000 15000 18000 19000 18500 18000 20000 25000
Expenditure on services (in £) 3000 3800 4000 5000 4500 5000 8000 10000
2.2 Analyze the collected data
Table 2: Analysis of sales data of XYZ
Sales
Mean 17937.5
Standard Error 1507.24
Median 18250
Mode 18000
Standard Deviation 4263.11
Sample Variance 1.8E+07
Kurtosis 1.90043
Skewness -0.4008
Range 15000
Minimum 10000
Maximum 25000
Sum 143500
Count 8
Confidence Level(95.0%) 3564.05
ï‚· Mean: It refers to the average of all the values and is measured by dividing all the
numbers by number of elements in a given set.
Mean = Sum of all the elements / number of elements
In the present scenario mean for sales is 17937.5ï‚· Median: It is regarded as the middle value given in set of element which contains odd
number of values. Median for the present data is 18250ï‚· Mode: It is the number that is present in given set of data most frequently. In the present
case no number is repeating so it is not possible to calculate mode.
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ï‚· Standard deviation: It provides idea how close is the entire set of data to the average.
Furthermore, it provides information in relation with how spread out information is.
Standard deviation for sales is 4263.11.
After applying all the statistical tools it can be easily said that option linked with opening
up of new restaurant in London is feasible as every tool is representing positive result and
business can grab large amount of opportunities by implementing the plan.
2.3Measures of dispersion.
Table 3: Measures of dispersion
Sales
Variance 5618393
Standard deviation 2370.31
Range 7000
Measure of dispersion helps in determining how squeezed a particular distribution is and
takes into consideration variance, standard deviations and inter-quartile range. In many cases it is
possible that two set of elements are interlinked in terms of their mean but they totally differs
from one another.
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Exp on services
Mean 5412.5
Standard Error 838.033
Median 4750
Mode 5000
Standard Deviation 2370.31
Sample Variance 5618393
Kurtosis 0.89015
Skewness 1.31466
Range 7000
Minimum 3000
Maximum 10000
Sum 43300
Count 8
Confidence Level(95.0%) 1981.63
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ï‚· Variance: It refers to the average of squared differences from mean and to calculate
variance it is necessary to determine mean first. It also helps in identifying the exact
range at which set of elements are spread out. In the present scenario variance for sales is
5618393.ï‚· Standard deviation: It helps in knowing about amount of variation from range and is the
square root of variance. Standard deviation for sales is 2370.31
ï‚· Range: It is calculated by deducting lowest value from highest one. Range for sales is
7000.
So the measures of dispersion calculated are also showing positive results and it is
feasible for management to open its second restaurant chain in London where different
opportunities are present and they can be grabbed easily.
2.4 Your calculations must include quartile, percentiles and the correlation.
Table 4: Quartile and percentiles
Sales Expenses
Quartile1/25th percentile 17250 3950
Quartile2/50th percentile 18250 4750
Quartile3/75th percentile 19250 5750
Quartile4/100th percentile 25000 10000
Table 5: computation of correlation
Row 1 Row 2
Row 1 1
Row 2 0.85611 1
TASK 2 GRAPHS AND CAPITAL BUDGETING TECHNIQUES
3.1 Graph conclusion
GraphsDecisions making quality of the organization is significantly influenced by the
quality of information underlying the decisions. There are various sources through which an
entity can gather useful data that serves its purpose of arriving at timely and relevant information
(Mills, 2000). It is therefore crucial for every organization to take reasonable initiatives to come
up with reasonable conclusions about the source through which it can get the desired information
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and identify the techniques through which the gathered data can be analyzed to derive the useful
results.
Figure 1: Graph of sales and expenses data
3.2 Trend line
Figure 2: trend line for sales and expenses of XYZ
We can depict from the above trend line that both sales and expenses are showing an
upward trend. It can therefore be comprehended that growth prospects of the company are going
to be bright in the forthcoming years if XYZ continues to emphasize on the provision of quality
services and economy do not show major fluctuations.
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3.3 Business presentation
Attached ppt
3.4 Business report
Based on the analysis of above statistical data, we can observe that deviation of sales
from the mean is of significant amount insofar as the volume of sales is considered. The
deviation of expenditure from the mean is observed to be high having regard to its quantum
(Simanek, 2014). Hence, it can be said that XYZ has not been able to observe any trend over the
years as regard to the sales pattern and the quantum of expenditure incurred over the years.
Further, the graphical representation of sales reveals that XYZ has not been able to generate
consistently increasing sales over the some of its past years (Engle, 2002). However, reason of
such lower sales has been spotted to be fluctuations in the economy which had an adverse impact
on the growth potential of XYZ in those years. It could further be seen that correlation
coefficient between sales and expenditure on services is coming to be positive which is
indicative of the fact that quantum of sales bears direct connection with the expenditure incurred
on services. Further, the correlation value of 085611 denotes that every 1 rupee of expenditure
has a potential of generating .85611 rupee of sales. Median of 18250 in case of sales reveals that
XYZ has been able to generate 50% of its sales below 18250 and 50% of its sales above 18250
(Wohland, Rigler and Vogel, 2001). Likewise, the median of 4750 as regards expenses reveals
that 50% of its expenses lie above and 50% of its expenses lie below the said amount. Quartiles
represent the range within which certain percentage of the value lie. For example, Quartile 1 of
17250 of sales highlights that 25% of the sales lies within the range of 0- 17250. Likewise,
quartile 2 of 18250 shows that 25% of the values lies between17250 – 18250. The same
interpretation can be used for the quartiles computed in respect of expenditure incurred for
services (Manikandan, 2011). And last but not the least, the trend line of both the sales and
expenses are showing an upward trend which can be used as abasis of making the sales and
expenses forecast for the upcoming years.
4.1 Information processing tools
Information processing tools refers to the computerized tools and techniques which
appreciates the decision making process of an organization. These tools are capable of
automatically processing the data captured from the basic business transactions and manipulate
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them in a manner that is useful for the organization in arriving at the relevant decision. Some of
the basic information processing tools are discussed below: MIS – It stands for management information system. It operates at every managerial
levels of an entity and serves the information needs of every manager within the
organization (Deering, 2011). It can aid XYZ in remaining updated with its operational
performance and formulate relevant timely decision. EIS – It refers to executive information system and serves the information needs of top
level of the organization and aids in strategic decision making by the management. Expert systems – These systems make use of expert knowledge and provide users with
the solution which they usually expect from the experts.
 Transaction processing system – It captures data from the business transactions and
moulds it into the information that facilitates further performance of operations within an
organization (Hodge and Austin, 2004). For example, in case of XYZ, these systems may
be used in automatic generation of invoices, automatic payments, automatic generation of
cheques etc.
4.2 Project plan for an activity
Activity Description Immediate
predecessors
Expected
time
Number of staff
required
A Planning Nil 5 3
B Preliminary design Nil 3 2
C Market survey A 2 2
D Data analysis A 5 5
E Identifying locations A 3 3
F Costing C 2 2
G Selection of marketing
techniques
D 4 5
H Selection of suppliers B,E 6 4
I Pricing estimates H 2 1
J Final report F,G,I 6 2
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Figure 3: Gantt chart
Figure 4: Critical path
From the above diagram, we can see that the project takes 42 days to get completed i.e.
starting from 4th January and ending on 15th February(Morris, 2004). If Xyz wants to complete its
project within shorter duration, then it may on reducing the duration on critical through use of
additional resources keeping in mind that other path does not become critical in which case it
curtail the durations on consequential critical paths simultaneously.
4.3 Use financial tools for decision making
Capital budgeting techniques finds its importance while evaluating the proposals
requiring heavy capital outlays. There are multiple techniques available for the said purpose of
which the most commonly used techniques is identified to be NPV method, IRR method, and
Payback period method (Ng, 2013). These techniques are explained with the help of a
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hypothetical example wherein then initial capital outlay of XYZ is taken to be £200000 and the
cash inflows for the period of 5 years from two alternative proposals are given below:
Table 6: Cash flow data
Year ProjectA ProjectB
(Cash inflows) (Cash inflows)
1 40000 70000
2 60000 50000
3 50000 60000
4 65000 85000
5 75000 55000
Before staring the analysis of said data, the capital budgeting techniques mentioned above are
briefly explained as follows:ï‚· NPV method- It stands for net present value. This method is the most preferable method
over other methods because of the time value of money it considers. Under this
technique, a discounting rate is considered which is generally taken to be the cost of
capital in order to arrive at the present values of cash inflows. It facilitates evaluating
every aspect from the present point of view thereby augmenting the decision making
process (Ingait, 2007). Internal rate of return – It refers to the discounting rate at which present values of cash
inflows equates the present values of cash outflows (Ingait, 2007). The project with
higher internal rate of return is more preferable over the projects with lower IRR.
 Payback period – It refers to the period within which the initial investments will be
recovered. The projects with lower payback periods are the one which are capable of
recovering the initial capital investment within the shorter span of time (Gorshkov and et
al, 2014). It can therefore be said that firm will be more inclined towards the project
which are having shorter payback periods as compared to the projects with longer
duration of recovery.
a) Net present value
Table 7: Net present value
Year Project A Project B
Discounting
factor
Present value
of A (in £)
Present value
of B (in £)
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(Cash
inflows)
(Cash
inflows)
1 40000 70000 0.909 36360 63630
2 60000 50000 0.826 49560 41300
3 50000 60000 0.751 37550 45060
4 65000 85000 0.683 44395 58055
5 75000 55000 0.621 46575 34155
a) 214440 242200
Less: Initial investment b) 200000 200000
Net present value a)- b) 14440 42200
b) Payback period method
Table 8: Payback period method
Year ProjectA
Cumulative cash
flows for A ProjectB
Cumulative cash
flows for B
(Cash flows
in£)
(Cash flows
in£)
0 -200000 -200000 -200000 -200000
1 40000 -160000 70000 -130000
2 60000 -100000 50000 -80000
3 50000 -50000 60000 -20000
4 65000 15000 85000 65000
5 75000 90000 55000 120000
Payback period 3.769231 3.235294
c) Internal rate of return
Table 9: Internal rate of return
Year Project A Project B
(Cash flows in£) (Cash flows in£)
0 -200000 -200000
1 40000 70000
2 60000 50000
3 50000 60000
4 65000 85000
5 75000 55000
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Irr 13% 18%
In the given case, cost of capital is taken to be 10%. From the analysis of data computed
in the aforesaid table, we can ascertain that Project B is giving higher net present value as
compared to project A. Further, internal rate of return is also evidenced to be high in project B
when compared to project A. And last but not the least, payback period of project B is coming to
be lower than that of project A. Evaluation of all these aspects lead to the conclusion that it is
beneficial for XYZ to invest in project B since all the techniques has given its consent to the said
project. If any of the techniques lead to contradictory selection, then it is advisable for the
organization to base its decision on the outcome yielded by net present value technique.
However, no such situation has observed in the proposals enumerated in example, every
technique has resorted to one outcome. Therefore, XYZ can smoothly arrive at the decision of
selecting project B.
CONCLUSION
From the above discussion, we can infer that the importance of information in decision
making process. The assigned unit gives an insight of various sources through which information
can be collected and how the inferences drawn from such information can be used in the best
interests of the organization to arrive at logical decisions. Further, a light has been thrown on
various information processing tools that are available to an organization to derive the optimum
results out of the available information. Graphical representations of sales and expenses have
been shown in respect of hypothetical organization to give an insight of how decisions can be
formulated on the basis of observing the performances over the years. And, finally the unit is
concluded which shows the use of capital budgeting techniques in selecting the most feasible
proposal out of various alternative proposals that is in best interests of the organization. It is
expected that this unit serves the basic purpose of bringing within the knowledge of learners the
aspects covered in the above discussed paragraphs.
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REFERENCES
Books and journals
Engle, R., 2002. Dynamic conditional correlation: A simple class of multivariate generalized
autoregressive conditional heteroskedasticity models. Journal of Business & Economic
Statistics. 20(3).pp.. 339-350.
Gorshkov, A. S. and et al., 2014. Method of calculating the payback period of investment for
renovation of building facades. Construction of Unique Buildings and Structures. 2(17).
pp.82-106.
Hodge, V. J. and Austin, J., 2004. A survey of outlier detection methodologies. Artificial
Intelligence Review. 22(2).pp.. 85-126.
Manikandan, S., 2011. Measures of dispersion. Journal of pharmacology &
pharmacotherapeutics. 2(4).pp.. 315.
Mills, G. E., 2000. Action Research: A Guide for the Teacher Researcher. Prentice-Hall
Morris, M., 2004. Network epidemiology: a handbook for survey design and data collection.
Oxford University Press.
Ng, J. J., 2013. A systematic approach to finding internal rate of return using the interpolation
method, based on'big vs. small'concept. International Journal of Education Economics
and Developme. 4(3).pp.. 278-284.
Ryan, P. A. and Ryan, G. P., 2002. Capital budgeting practices of the Fortune 1000: how have
things changed. Journal of Business and Management. 8(4). Pp. 355-364.
Sapsford, R. and Jupp, V., 2006. Data collection and analysis. Sage.
Wohland, T., Rigler, R. and Vogel, H., 2001. The standard deviation in fluorescence correlation
spectroscopy. Biophysical journal. 80(6).pp.. 2987-2999.
Online references
Deering, D., 2011. Automation software that puts hours back in your day. [Online]. Available
through: <www.automationanywhere.com/products/automation-software?
r=google&w=automationsoftware&kw=Automation
%20Software&match=b&network=g&place=&gclid=CInOhsuS98ICFUosjgodoVMAJw
>. [Accessed on 8th January 2015].
Ingait, P.C., 2007. Measures of dispersion. [Online]. Available through
<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3198538/> [Accessed on 8th January
2015].
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Lusthaus, 2000. Identify Sources of Data and Data Collection Methods. [Online]. Available
through: <http://www.unep.org/ieacp/iea/training/manual/module8/1165.aspx>.
[Accessed on 8th January 2015].
Simanek, D.E., 2014. EFFICIENT CALCULATION OF THE STANDARD DEVIATION.
[Online]. Available through:<www.lhup.edu/~dsimanek/scenario/errorman/distrib.html>.
[Accessed on 9th January 2015].
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