Statistical Analysis of Vinpearl's Business Objectives and Strategies

This assignment, completed by Tran Tuan Minh, provides a comprehensive statistical analysis of Vinpearl's business objectives, specifically focusing on the expansion plan of constructing new Vin Wonders. The assignment begins with an introduction to Vinpearl's goals and the importance of re-evaluating current services. It recommends the use of statistics for data-driven decision-making, detailing how to collect and analyze data from both primary and secondary sources. The analysis includes a discussion of structured versus unstructured data, the use of graphs for data illustration, and a breakdown of statistical methods like descriptive, inferential, and measures of association. The student recommends Da Nang as a potential location for a new Vin Wonders based on tourism statistics and spending habits. Furthermore, the assignment covers approaches to calculate the budget and timeline for the project, considering the company's financial performance and the impact of past investments. The analysis utilizes both inductive and deductive research methods, exploring exploratory and confirmatory data analysis to assess the viability of the expansion plan, especially in light of the 2019 financial results and the ongoing COVID-19 pandemic. The student concludes that the timing of the expansion should be reconsidered, given the current financial situation. The student's work demonstrates the practical application of statistical methods in business strategy and financial planning.

STATISTICS FOR MANAGEMENT
Assignment 1 – Part 1
Name: Tran Tuan Minh ; Class: F12E
Student ID: F13-294
Gmail: [e-mail]
Word count: 2563 words

1. A brief introduction to Vin Pearl’s main business objective in 2020: To expand the scale
of the organization by constructing a brand new Vin Wonders before the end of 2021.
As the leading organization in the hospitality sector in Viet Nam, it is really important for us to
re-evaluate our current services and quality in our resorts all across the country and make
innovations out of that. The prioritized objective at the moment of ours is to expand the scale of
the organization by constructing a brand new Vin Wonders before the end of 2021. However,
there are a lot of variances that needed to be taken into consideration in order for our company to
evaluate whether this will be profitable or not. For instance, those factors can be the average
spending of visitors to different tourist attractions or how long they would stay,…
2. Recommendation on the use of statistics in achieving Vin Pearl’s business objective and
how to collect them:
Personally I would recommend the use of statistics in this situation to achieve the company’s
current business objective. Statistics can bring multiple data, information and explore certain
point of views for the company which significantly influence the actions of the organization. For
this particular objective of Vin Pearl, what statistics can offer here is plenty. Firstly, you can
know about the amount of money a visitor is willing to spend and determine which would be the
area that is most likely to gain the most profit for Vin Pearl based on the spending of tourists and
the time they stay in Viet Nam.
Da Nang Nha Trang Phu Quoc Phan Thiet
0
20
40
60
80
100
120
140
160
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5150
135 128
45
3.9
3.6
3.2
2.1
A verag es sp en d i n g an d stayin g time of
tou ri sts i n famou s attracti on s in Viet Nam
Dollars
Days
(LAND. M, 2020)

For example, to determine where would be the most profitable place to open a new Vin Wonder
among the finest tourism locations in Viet Nam, I have gathered the statistics about the average
spending of tourist and how long they stay in those attractions. In terms of the origin of it, this is
a set of data that comes from the secondary sources. It means that the one who is analyzing the
data is not actually the person who initiated the research themselves. Available sources of
secondary data can be books, journals, articles,… Alternatively in cases that there are not
sufficient sources of data available for companies so choose from, primary sources should be
used. Primary sources are the research that were conducted directly by the data analyzer
(Vinpearl in this case), companies can dictate the variables that needs to be collected based on
the initial purposes of the research without any limitation. Additionally, when dealing with a set
of data, the data analyzer must take notice of whether the data is structured or unstructured. It
would be easier for Vinpearl to use structured data because it can provide a better overview on
the situation whereas unstructured data is more complex and take considerable amount of time to
fully analyze. There are some actions we can do to convert unstructured to structured data,
sorting them into categories and then encode it is the most common, efficient way to do. After
successfully converting our data into structured, we should also use graphs a better illustrations
of those information. In the above research about the average expense on holidays of tourists in
some places in Viet Nam and the amount of time they spend travelling, I’ve decided to illustrate
those data into a combination of bar chart and line graph. The main reason for my choice is in
this way, I can compare the figures between the four places and also easily see how the number
of days interrelate with the amount of money tourists would spend. Therefore, most objective
conclusions can be made with all the variables taken into consideration.
3. Statistical methods in choosing the most profitable market and practical future strategies
to develop the company business of the new Vin Wonders:
Initially, Vinpearl wanted to indicate the potential locations that will most likely to generate
more profits than others. Because of that, various observations were made in order to find the
most valuable statistics to help conducting a conclusion for this problem. After intensive days of
observation and data gathering, I was managed to find out an useful set of statistics which is the
chart above. Overall, a standard statistics analyzing process should consist of descriptive,
inferential and measure of association methods to be fully expressed. Looking at a data set, the
first thing you want to do should be summarize all those data and describe it as briefly as
possible to select out key information that can actually contribute to the research. In order to do
so, descriptive statistic is required because it is the most optimal way to illustrate those key data
in a more systematic fashion so the researcher can interpret those data set more easily.
Descriptive statistic consists of common factors like the mean, mode, range, standard deviation,
skewness, kurtosis,… Overall, the mean shows the average of the data set, the mode indicates the
most duplicated figure and the range means the difference between your highest figure and the
lowest one. The more important figures that are standard deviation, skewness and kurtosis will
indicate how the data is distributed in the set as well as how spread they are. Therefore from a
business perspective, the we would want our spread of data kept relatively small because it is an
indication of a correct research and the results are relevant and can be used to gain competitive
advantages. But in this particular example of the average money & time spent in Vietnamese

tourists attraction above, descriptive statistics would not be necessary due to the fact that this set
of data is a relatively small one and we can easily summarize key points from that chart without
the need of making complicate calculations in descriptive statistical method. Moreover, to be
specific, it is clear that in average tourists spend the most money and days in Da Nang with Nha
Trang, Phu Quoc and Phan Thiet follow respectively. In general, the use of descriptive statistical
method is recommended in instances that researchers are having to deal with a large set of data
and is not required in this particular situation where all the data are presented clearly and easy to
summarize.
After summarizing key points and describe the trends occurred in the data set, there are more
statistical methods to be applied because the data (even after being summarized) can’t work on
itself and that is where inferential statistical method come into practice. So basically inferential
statistic allows you to make predictions out the summarized data, moreover you can use the data
collected from a sample and then make generalizations about a total population (). For instance,
in the chart above, we can make an assumption that generally tourists love staying in Da Nang
the most and spend the most money as a consequence. As a result. I would recommend the
company to select Da Nang as the next location to open a Vin Wonders because Da Nang is the
city that will most likely to generate the most benefits just purely based on the statistics above.
But with such a massive business objective scale like we’re having, taking further researches are
highly recommended to prove the statistics are consistent and reliable in order to make the final
decision. (Inferential Statistics: Definition, Uses - Statistics How To, 2020).
Another statistic method that can be taken into consideration is the measure of association, the
main use of this method is to illustrate the relationship between two or more variables in a set of
data. As shown in the example above, using measure of association will tell us that the longer
tourists stay the more money they would spend on their holiday in those four attractions. With
that information kept in mind, we should come out with more strategies to extend the duration of
visitors’ vacation in our area of business. For instance, a significant reduction of room expense
will be given to visitors if they decide to stay longer than 1 week. Another practical strategy can
be preparing a more spread-out visiting schedule thus extending the amount of days taken by a
relatively large margin.
In conclusion, the most optimal way to deal with the above set of data is to make a combination
of descriptive statistic with inferential and measure of association. But to save more time with
such small data set like this instance, we can just easily summarize the key points without the
need of using descriptive statistical method which can be really tricky and require a lot of
calculation and can grow a lot of problems within the process. On the other hand, inferential and
measure of association are extremely useful in this case as the statistics are pretty clear. By using
inferential statistical method, we were able to determine the most potentially profitable market to
open a new Vin Wonders which is Da Nang. And as for measure of association, by seeing the
important relationship between the amount of time and money spent of tourists, possible future
strategies were immediately made to increase the revenue of Vinpearl in the future after the
establishment of the new Vin Wonders.

4. Approaches to calculate the appropriate budget and time to initiate the project:
According to our annual report at the end of 2019, with the mass opening of many new
infrastructures like the Vinpearl Luxury chain, Vinpearl Golf & Resort in southern Hoi An,
Vinpearl Imperia Hai Phong, Vinpearl discovery Phu Quoc, Vinpearl Condotel Nha Trang,
VinOasis Phu Quoc, Vinpearl Golf Phu Quoc, VinWonders Nha Trang and VinSafari Phu Quoc.
With that many investments made in 2019, it is estimated that Vinpearl will need at least 18
months to fully recover and start generating revenue from those newly opened infrastructure.
Therefore, Iit is not suitable for our company to invest heavily on such massive project like
VinWondes Da Nang before gaining back profits from 2019 investments because we have
simply lost a lot of money in 2019 and the time for the initiation of Da Nang VinWonders should
be postponed to 2020. After making my hypothesis about the current state of business in
Vinpearl, I will now looking to prove whether my statement was correct or incorrect.
Looking at the annual report of our company at the end of 2019 again, I have collected indexes
regarded to the loss/profit made by Vinpearl in the recent years and compare them together and
illustrate those statistics in the graph below.
1 2 3 4 5
-5000
-4000
-3000
-2000
-1000
0
1000
2000
233
681 1059
515
-4708
Loss/Profi t from Vinpearl's business from
2015-2019
Years ( 2015-2019 )
Billion VND
((VPL: CTCP Vinpearl - VINPEARL JSC - Tải tài liệu | VietstockFinance, 2020))
This set of statistics is conducted from Vinpearl’s own annual reports from 2015 to 2019,
therefore this type of information came from the primary sources as our company directly made
this research. Looking at the line graph, we can definitely see a relatively stable fluctuation in the
first four years of the period where Vinpearl gain profits consistently throughout the years. But in
2019, there was a sudden dive in which the amount money being lost is approximately 4,708
billion VND. Thus proving my assumption about the ability of Vinpearl to open another
VinWonders in Da Nang despite the potential profitability. After developing my own theory

about the compatibility between the fundings of Vinpearl and our business objective at the
moment, I was able to collect sufficient data to test my hypothesis. As a result, those data
collected from Vinpearl was proven supportive to my original theory and indicated that we
should not recklessly construct a new VinWonders in the current situation especially within the
Covid-19 Pandemic.
The approach that I’ve chosen to execute the research was a combination between both inductive
and deductive research with both the data analysis of exploratory and confirmatory. The reason
for that is because I assume that I would be better to use the elements of both approaches and
apply them into my study. Starting with a simple observation that Vinpearl has been opening
new infrastructures during the year and then I came out with my new theory about our new
business situation. After that, I looked to prove this hypothesis by collecting data from
Vinpearl’s annual reports of the recent 5 years. In general, my work includes both creating a new
theory and proving the theory itself.
For deductive approach, it can simply be understood as collecting data to verify an already
existed theory/hypothesis. In particular, it starts with an existing theory and then develop it into
an actual assumption for the practices of your own business. After that, you would want to look
for data that can verify whether the statistics support your hypothesis or not. This research
approach corresponds with confirmatory analysis as the nature of this approach is to prove if an
existed theory is correct or not. Alternatively, researchers can also go with the opposite way
which is inductive research. Here, you would start with an ordinary observation and then form a
pattern out of that and at the end coming out with a whole new hypothesis. This kind of approach
more or less is similar to the exploratory analysis as the main goal you are looking for is to
develop a whole new theory based on practical observations. (Inferential Statistics: Definition,
Uses - Statistics How To, 2020).
For business intelligence, the more research conducted, the more proven theory they would have
for their knowledge. For instance of our own company Vinpearl, our future decision making
process should be easier with the existence of my new developed hypothesis about our financial
situation. Therefore, these kind of researches are extremely important in terms of expanding the
data base to gain competitive advantages and significantly shorten their decision making process.
Moreover, less mistakes would be taken as a result of inexperience because those problems were
solved by reading the previous researches of the company. Lastly, corporations should
proactively make observations from the reality and develop & prove their own hypothesis in
order to widen their knowledge and everyone knows that knowledge is actually power and the
most important thing to have if you want to make a successful business.
5. Conclusion
In conclusion, statistics play a vital role in fulfilling our business objective in 2020 which is to
open a new VinWonders. With the appropriate use of statistical methods, a potential high-
profitability location was selected and also future strategies to increase our revenue were also
taken into account. However, research approaches were also masterfully applied into our case to
point out the limitations in terms of monetary of our current business and avoid making reckless,

fatal mistakes. Moreover, it also enrich our data base of past business experience & research and
thus substantially make the future decision making process a lot more simple than it has been.
6. References
LAND, M., 2020. MŨI NÉ SUMMERLAND - Điểm Đến Giải Trí Của Phan Thiết. [online] MŨI NÉ
SUMMER LAND. Available at: <http://muinesummerland.vn/tin-tuc/don-bay-tu-du-lich-giai-tri-voi-bat-
dong-san-nghi-duong-phan-thiet> [Accessed 15 October 2020].
Statistics How To. 2020. Inferential Statistics: Definition, Uses - Statistics How To. [online] Available at:
<https://www.statisticshowto.com/inferential-statistics/#:~:text=Descriptive%20statistics%20describes
%20data%20(for,make%20generalizations%20about%20a%20population.> [Accessed 15 October 2020].
Static2.vietstock.vn. 2020. [online] Available at:
<http://static2.vietstock.vn/data/HOSE/2019/BCTN/VN/VPL_Baocaothuongnien_2019.pdf> [Accessed 15
October 2020].
VietstockFinance. 2020. VPL: CTCP Vinpearl - VINPEARL JSC - Tải Tài Liệu | Vietstockfinance. [online]
Available at: <https://finance.vietstock.vn/VPL/tai-tai-lieu.htm?doctype=1> [Accessed 15 October 2020].
Base, K. and reasoning, I., 2020. Inductive Vs. Deductive Research Approach (With Examples). [online]
Scribbr. Available at: <https://www.scribbr.com/methodology/inductive-deductive-reasoning/#:~:text=The
%20main%20difference%20between%20inductive,reasoning%20the%20other%20way%20around.>
[Accessed 15 October 2020].