Data-Driven Business Practices: A Travel Industry Case Study
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Using Data to Build Business Practice
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Table of Contents
Introduction......................................................................................................................................3
1. Analysis of the Data and understanding pattern of Travel.......................................................4
2. Findings and Observations.......................................................................................................6
3. Recommendations..................................................................................................................10
Conclusion.....................................................................................................................................12
References......................................................................................................................................13
2
Introduction......................................................................................................................................3
1. Analysis of the Data and understanding pattern of Travel.......................................................4
2. Findings and Observations.......................................................................................................6
3. Recommendations..................................................................................................................10
Conclusion.....................................................................................................................................12
References......................................................................................................................................13
2

Introduction
The assignment is based on the spreadsheet file TravelPac Q3 2017, which requires the analysis
and calculation of relationships between 2 or more variables from the data collected by The
International Passenger (IPS). An employer of a reputed firm is trying to collect data on the
passengers traveling the to-from UK and overseas, so as to prepare a report on a segment with
the most potential to grow and in which company may operate to gain a competitive advantage
over its competitors. The task requires the application of various tools so as to establish a
meaningful relation between the 2 variables in the data and hence enable to arrive at a conclusion
in regards to the various requirements of the marketing department for it to formulate and
implement appropriate marketing and decide a target segment to operate in and expand into in
the future.
3
The assignment is based on the spreadsheet file TravelPac Q3 2017, which requires the analysis
and calculation of relationships between 2 or more variables from the data collected by The
International Passenger (IPS). An employer of a reputed firm is trying to collect data on the
passengers traveling the to-from UK and overseas, so as to prepare a report on a segment with
the most potential to grow and in which company may operate to gain a competitive advantage
over its competitors. The task requires the application of various tools so as to establish a
meaningful relation between the 2 variables in the data and hence enable to arrive at a conclusion
in regards to the various requirements of the marketing department for it to formulate and
implement appropriate marketing and decide a target segment to operate in and expand into in
the future.
3
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1. Analysis of the Data and understanding pattern of Travel
The spreadsheet contains all kinds of data relating to passengers traveling the to-from UK and
overseas such as year, gender, nationality, purpose, package, age, duration, visits, nights and the
spending pattern. It can be seen from the data that most of the information is irrelevant and can
be discarded in the analysis process and while setting up relationships between different
variables. Also, data generated is too detailed and complex which would make the processing
time consuming and ambiguous. Hence sampling technique is adopted where data for 50% or
more data in amount is selected as representatives the population and thus considered valid for
reflecting and retracing the results collected from them, onto the population. Several
relationships have been established to ascertain the dependency of data on each other and if they
conclude the whole data overall. These relationships will be calculated as one of the elements as
independent and other as a dependent (Silverman, 2018).
With the given data it can be seen that out of the total UK resident (4271), 3057 have traveled
through air mode, 470 through tunnels and rest 744 through sea mode. This suggests that the air
mode is the widely used option by UK residents from the July-September period. Although air
mode is more costly than the other 2, people prefer it and opt for this option more in comparison
to other 2 options. The reason could be that the passengers don't want to waste time on the
traveling element of the trip as the individuals get a scarce amount of leisure time and have other
responsibilities to fulfill. Hence, the cost of traveling by air mode is outweighed by its benefit of
less traveling time and more comfort for the passengers.
Another aspect of the data reveals the destination preferences for UK residents in the period of
July-September. 471 passengers have traveled to France, while 34 have traveled to Australia, and
an equal amount has traveled to Germany and the Netherlands (255). Few of them have also
traveled to Austria (52), Barbados (12). A very insignificant number have traveled to Channel
Island i.e. 2. It can be seen that most UK residents are traveling to France, while the least are
traveling to Channel Island (Grbich, C., 2012). There are other destination places, but hold no
significance in the study and hence not analyzed and documented in the report. The difference in
number translates to the taste and preference of the customers along with their willingness to
spend on their lifestyle and leisure.
4
The spreadsheet contains all kinds of data relating to passengers traveling the to-from UK and
overseas such as year, gender, nationality, purpose, package, age, duration, visits, nights and the
spending pattern. It can be seen from the data that most of the information is irrelevant and can
be discarded in the analysis process and while setting up relationships between different
variables. Also, data generated is too detailed and complex which would make the processing
time consuming and ambiguous. Hence sampling technique is adopted where data for 50% or
more data in amount is selected as representatives the population and thus considered valid for
reflecting and retracing the results collected from them, onto the population. Several
relationships have been established to ascertain the dependency of data on each other and if they
conclude the whole data overall. These relationships will be calculated as one of the elements as
independent and other as a dependent (Silverman, 2018).
With the given data it can be seen that out of the total UK resident (4271), 3057 have traveled
through air mode, 470 through tunnels and rest 744 through sea mode. This suggests that the air
mode is the widely used option by UK residents from the July-September period. Although air
mode is more costly than the other 2, people prefer it and opt for this option more in comparison
to other 2 options. The reason could be that the passengers don't want to waste time on the
traveling element of the trip as the individuals get a scarce amount of leisure time and have other
responsibilities to fulfill. Hence, the cost of traveling by air mode is outweighed by its benefit of
less traveling time and more comfort for the passengers.
Another aspect of the data reveals the destination preferences for UK residents in the period of
July-September. 471 passengers have traveled to France, while 34 have traveled to Australia, and
an equal amount has traveled to Germany and the Netherlands (255). Few of them have also
traveled to Austria (52), Barbados (12). A very insignificant number have traveled to Channel
Island i.e. 2. It can be seen that most UK residents are traveling to France, while the least are
traveling to Channel Island (Grbich, C., 2012). There are other destination places, but hold no
significance in the study and hence not analyzed and documented in the report. The difference in
number translates to the taste and preference of the customers along with their willingness to
spend on their lifestyle and leisure.
4
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Another aspect that can be considered while analyzing the data is the purpose of traveling. It can
be seen from the data that the majority of the passengers are traveling for the VRF or study
purposes (1378), while the least are traveling for business purposes (486). 2191 people are
travelling for the leisure time and just to enjoy the holidays with their families and loved ones.
216 UK residents are also travelling for misc. purposes. The reason for least number of business
travels is because they are formal in nature and is only required as and when unlike leisure time
where people travel whenever they get the chance.
It can be seen from the data that the male candidates in the data are significantly higher than that
female candidates. Male candidates being 2325, while female candidates being 1929, suggesting
that the male candidates are frequent travelers as compared to female candidates. Another reason
could just be the gender ratio i.e. men being more than women in general. So there is a
possibility that this study plays no part in the assignment and hence requires no more analysis
and calculations. But it’s important to keep this data in the back of the mind, as it may be useful
in further analysis (Pender, et. al., 2013).
Another important aspect of the study could be related to the age group traveling from the UK to
overseas. There are 299 UK residents in the age group of 16-24, while there are only168 in the
age group of 0-15. Although, it can be seen that the majority of people travel in the age group of
35-44 and 25-34. This overview will enable the company to target a particular age group for
specific products and services as different age groups have different needs and requirements.
The overview of the data can be interpreted on the basis of different variables to suit the needs of
the company. Different variables will depict different aspects of the data and thus will affect the
decision making differently. And thus there is a requirement that an optimum balance is
maintained and a middle ground is achieved keeping in mind, all the aspects and customer
behavior over the period (Bezerra, et. al., 2015).
5
be seen from the data that the majority of the passengers are traveling for the VRF or study
purposes (1378), while the least are traveling for business purposes (486). 2191 people are
travelling for the leisure time and just to enjoy the holidays with their families and loved ones.
216 UK residents are also travelling for misc. purposes. The reason for least number of business
travels is because they are formal in nature and is only required as and when unlike leisure time
where people travel whenever they get the chance.
It can be seen from the data that the male candidates in the data are significantly higher than that
female candidates. Male candidates being 2325, while female candidates being 1929, suggesting
that the male candidates are frequent travelers as compared to female candidates. Another reason
could just be the gender ratio i.e. men being more than women in general. So there is a
possibility that this study plays no part in the assignment and hence requires no more analysis
and calculations. But it’s important to keep this data in the back of the mind, as it may be useful
in further analysis (Pender, et. al., 2013).
Another important aspect of the study could be related to the age group traveling from the UK to
overseas. There are 299 UK residents in the age group of 16-24, while there are only168 in the
age group of 0-15. Although, it can be seen that the majority of people travel in the age group of
35-44 and 25-34. This overview will enable the company to target a particular age group for
specific products and services as different age groups have different needs and requirements.
The overview of the data can be interpreted on the basis of different variables to suit the needs of
the company. Different variables will depict different aspects of the data and thus will affect the
decision making differently. And thus there is a requirement that an optimum balance is
maintained and a middle ground is achieved keeping in mind, all the aspects and customer
behavior over the period (Bezerra, et. al., 2015).
5

2. Findings and Observations
During the analysis of the data, many major findings have been identified and hence important
observations have been recorded in the process, which will enable the department head to make
alert decisions and implement sound marketing policies for the company. Findings have to make
the difference in the decisions of the management to be considered useful and an effort has been
made for the same. Given are the few major and interesting findings in the analysis and study of
the data:
With respect to the mode of transportation
It has been previously concluded that the air mode of transportation is more widely used in
comparison to other 2 i.e. sea and tunnel mode. This information should help the company to
target the passengers opting for air mode as then it will be able to generate more revenue from
the same (McGuinness, et. al., 2016). Also, the company could come up with attractive
incentives and prices in this sector to capture more of the market.
Descriptive statistics of variable
'visits' of first 500 variables
Mean 3560.53
Standard Error 388.71
Median 1615.99
Mode 962.37
Standard Deviation 8691.91
Sample Variance 75549306.18
Kurtosis 99.06
Skewness 9.10
Range 116424.04
Minimum 75.79
Maximum 116499.83
Sum 1780265.25
Count 500.00
6
During the analysis of the data, many major findings have been identified and hence important
observations have been recorded in the process, which will enable the department head to make
alert decisions and implement sound marketing policies for the company. Findings have to make
the difference in the decisions of the management to be considered useful and an effort has been
made for the same. Given are the few major and interesting findings in the analysis and study of
the data:
With respect to the mode of transportation
It has been previously concluded that the air mode of transportation is more widely used in
comparison to other 2 i.e. sea and tunnel mode. This information should help the company to
target the passengers opting for air mode as then it will be able to generate more revenue from
the same (McGuinness, et. al., 2016). Also, the company could come up with attractive
incentives and prices in this sector to capture more of the market.
Descriptive statistics of variable
'visits' of first 500 variables
Mean 3560.53
Standard Error 388.71
Median 1615.99
Mode 962.37
Standard Deviation 8691.91
Sample Variance 75549306.18
Kurtosis 99.06
Skewness 9.10
Range 116424.04
Minimum 75.79
Maximum 116499.83
Sum 1780265.25
Count 500.00
6
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Descriptive statistics of variable
'nights' of first 500 variables
Mean 43613.66
Standard Error 3623.42
Median 19621.62
Mode 8067.99
Standard
Deviation
81022.06
Sample Variance 6564574729.6
0
Kurtosis 52.40
Skewness 6.16
Range 934128.27
Minimum 480.32
Maximum 934608.59
Sum 21806827.92
Count 500.00
Descriptive statistics of variable 'spend' of
first 500 variables
Mean 1868728.02
Standard Error 229914.15
Median 643498.51
Mode 0.00
Standard Deviation 5141036.79
Sample Variance 26430259254012.40
Kurtosis 83.77
Skewness 8.19
Range 67628489.78
Minimum 0.00
Maximum 67628489.78
Sum 934364010.97
Count 500.00
The above three tables indicate the statistical data for the first 500 variables taking base as visit,
nights and the spending pattern of the passengers so as to establish a relationship between the
variables and arrive at a conclusion (Elvbakken and Hansen, 2018). It can be seen that the mean
7
'nights' of first 500 variables
Mean 43613.66
Standard Error 3623.42
Median 19621.62
Mode 8067.99
Standard
Deviation
81022.06
Sample Variance 6564574729.6
0
Kurtosis 52.40
Skewness 6.16
Range 934128.27
Minimum 480.32
Maximum 934608.59
Sum 21806827.92
Count 500.00
Descriptive statistics of variable 'spend' of
first 500 variables
Mean 1868728.02
Standard Error 229914.15
Median 643498.51
Mode 0.00
Standard Deviation 5141036.79
Sample Variance 26430259254012.40
Kurtosis 83.77
Skewness 8.19
Range 67628489.78
Minimum 0.00
Maximum 67628489.78
Sum 934364010.97
Count 500.00
The above three tables indicate the statistical data for the first 500 variables taking base as visit,
nights and the spending pattern of the passengers so as to establish a relationship between the
variables and arrive at a conclusion (Elvbakken and Hansen, 2018). It can be seen that the mean
7
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for the visit comes out to be 3,560, suggesting that on an average these much visits have taken
place, while the mean for the nights is calculated as 43,614 suggesting that the average nights
spent are this much. On an average $1,868,728 is spent by the passengers when on a trip. Other
relationships can also be achieved with the given table such as the most recurring pattern of
spending or just the median of the nights spend for the company to be able to plan prospectus in
such a manner to suit the needs of the customers.
With respect to the purpose of the places to visit
Destination analysis will enable the company to plan and schedule more trips to the most favored
destination and hence will attract more customers and company will be able to make more profit
in the process (Di Ciommo, et. al., 2013). From the data, it can be concluded that the USA seems
to be the most favored place of traveling. But the data needs to be considered as a whole and not
on an individual basis for implementing policies and decision making.
With respect to the purpose of traveling
Purpose analysis will help the company to prepare holiday packages which would suit
customers’ needs and requirements. Requirements for the business trip and a leisure trip differ
and thus need different itinerary which would meet customers’ expectations.
With respect to the proportion of male and female residents
The data suggest that the male candidates are significantly higher in comparison to the female
candidates which may or may not have an impact on the requirements of a holiday package, but
its certain that company will need to include more attractive incentives for the women and thus
attracting more female customers in the market.
With respect to the age group
Holiday packages need to include special sections, specific to the age groups and need to differ
on the basis of such age group as a different age of people enjoy different sections of a trip (El
Faouzi and Klein, 2016).
8
place, while the mean for the nights is calculated as 43,614 suggesting that the average nights
spent are this much. On an average $1,868,728 is spent by the passengers when on a trip. Other
relationships can also be achieved with the given table such as the most recurring pattern of
spending or just the median of the nights spend for the company to be able to plan prospectus in
such a manner to suit the needs of the customers.
With respect to the purpose of the places to visit
Destination analysis will enable the company to plan and schedule more trips to the most favored
destination and hence will attract more customers and company will be able to make more profit
in the process (Di Ciommo, et. al., 2013). From the data, it can be concluded that the USA seems
to be the most favored place of traveling. But the data needs to be considered as a whole and not
on an individual basis for implementing policies and decision making.
With respect to the purpose of traveling
Purpose analysis will help the company to prepare holiday packages which would suit
customers’ needs and requirements. Requirements for the business trip and a leisure trip differ
and thus need different itinerary which would meet customers’ expectations.
With respect to the proportion of male and female residents
The data suggest that the male candidates are significantly higher in comparison to the female
candidates which may or may not have an impact on the requirements of a holiday package, but
its certain that company will need to include more attractive incentives for the women and thus
attracting more female customers in the market.
With respect to the age group
Holiday packages need to include special sections, specific to the age groups and need to differ
on the basis of such age group as a different age of people enjoy different sections of a trip (El
Faouzi and Klein, 2016).
8

The company needs to consider each and every aspect of the findings for it to make an impact on
the company's decision-making process and thus help them generate attract more customer and
earn more profit. Considering only a few and disregarding others may have a negative impact on
the policy of the company and eventually lead to losses instead of profits.
9
the company's decision-making process and thus help them generate attract more customer and
earn more profit. Considering only a few and disregarding others may have a negative impact on
the policy of the company and eventually lead to losses instead of profits.
9
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3. Recommendations
It has been observed that there is a wide variation between UK residents when compared to
different variables. Furthermore, since there are multiple variables, it would lead to a give a clear
picture when a single variable is analyzed and processed further.
In addition to this, the use of Ms-excel has been taken to the fullest level as it will help to
interpret one variable at a point of time in the best possible manner. For the sake of convenience,
only period and duration of quarter covering July- Sept of the year 2017 has been taken and
accordingly the data belonging to this period has been taken for the purpose of analysis and
interpretation.
The main focus or the primitive objective of preparing this report is to analyze the variable ‘UK
residents' in the best possible manner and accordingly all the given variables have been analyzed
in relation to the ‘UK residents' variable. Wherever feel necessary a comparison has been made
between the data pertaining to UK residents and overseas residents. Such a difference will
enhance the overall given data. Apart from that, it will help to further actions that will help to
improve the tourism sector of the UK. It will not only help the local residents or tourists but also
the overseas residents will be benefitted (Kouwenhoven, et. al., 2014).
Different observations have been carried out according to which some suitable and appropriate
recommendations and suggestions have been inserted at appropriate places. Such measures, if
properly implemented will not only help the UK tourism sector but also the UK residents in the
long run.
The first and foremost recommendation is to foster the working of governmental authorities and
private sector in a collaborative manner. Such collaboration will bring out the best result and
everyone will be benefitted. The primary purpose of UK residents is to provide necessary and
amenities in the best possible manner. On the other hand, the private sector works for earning a
higher amount of profits thereby reaching the customer at the large. If both these sector works
together, then it will bring out the best-required output and everyone will be able to access
various facilities and services and that too with the reasonable and at an affordable price
(Schoenduwe, et. al., 2015).
10
It has been observed that there is a wide variation between UK residents when compared to
different variables. Furthermore, since there are multiple variables, it would lead to a give a clear
picture when a single variable is analyzed and processed further.
In addition to this, the use of Ms-excel has been taken to the fullest level as it will help to
interpret one variable at a point of time in the best possible manner. For the sake of convenience,
only period and duration of quarter covering July- Sept of the year 2017 has been taken and
accordingly the data belonging to this period has been taken for the purpose of analysis and
interpretation.
The main focus or the primitive objective of preparing this report is to analyze the variable ‘UK
residents' in the best possible manner and accordingly all the given variables have been analyzed
in relation to the ‘UK residents' variable. Wherever feel necessary a comparison has been made
between the data pertaining to UK residents and overseas residents. Such a difference will
enhance the overall given data. Apart from that, it will help to further actions that will help to
improve the tourism sector of the UK. It will not only help the local residents or tourists but also
the overseas residents will be benefitted (Kouwenhoven, et. al., 2014).
Different observations have been carried out according to which some suitable and appropriate
recommendations and suggestions have been inserted at appropriate places. Such measures, if
properly implemented will not only help the UK tourism sector but also the UK residents in the
long run.
The first and foremost recommendation is to foster the working of governmental authorities and
private sector in a collaborative manner. Such collaboration will bring out the best result and
everyone will be benefitted. The primary purpose of UK residents is to provide necessary and
amenities in the best possible manner. On the other hand, the private sector works for earning a
higher amount of profits thereby reaching the customer at the large. If both these sector works
together, then it will bring out the best-required output and everyone will be able to access
various facilities and services and that too with the reasonable and at an affordable price
(Schoenduwe, et. al., 2015).
10
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Another measure that can be taken is by providing complete knowledge and information
regarding any particular governmental policy that is going to be launched. Without complete
information, a region or area can be developed or flourished. If a UK resident is not aware of
newly launched or even existing policies, such launching of policies will be no use and will be
considered as wastage of time and money.
It is very crucial to take initiative and every person, whether corporate or not, should come
forward to take part in any manner so that overall GDP can be improved in any manner or
approach.
11
regarding any particular governmental policy that is going to be launched. Without complete
information, a region or area can be developed or flourished. If a UK resident is not aware of
newly launched or even existing policies, such launching of policies will be no use and will be
considered as wastage of time and money.
It is very crucial to take initiative and every person, whether corporate or not, should come
forward to take part in any manner so that overall GDP can be improved in any manner or
approach.
11

Conclusion
The purpose of the report was the analysis of the given data with the use of the excel tools and
calculation of linear relationships between the variables, taking one of them as independent and
other as a dependent. Such analysis will allow the company to formulate and implement future
marketing policies of the company. The analysis will enable the company to identify customer
behavior and if there is any pattern or trend in their behavior as such. The study will lead the
company to come up with more attractive itinerary and packages in the future for the customers
according to their preferences and requirements.
12
The purpose of the report was the analysis of the given data with the use of the excel tools and
calculation of linear relationships between the variables, taking one of them as independent and
other as a dependent. Such analysis will allow the company to formulate and implement future
marketing policies of the company. The analysis will enable the company to identify customer
behavior and if there is any pattern or trend in their behavior as such. The study will lead the
company to come up with more attractive itinerary and packages in the future for the customers
according to their preferences and requirements.
12
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