Mobile Phone Market Analysis and Forecasting

The assignment provides an analysis of the mobile phone market in the UK, highlighting key trends and statistics. It explores different forecasting methods, including linear and hybrid models, and concludes that a hybrid model is suitable for this case study. The report also examines the features of smartphones that have made them popular among older customers, such as easy payment and calendar management. Additionally, it evaluates the potential benefits of expanding Eco-phone's business in Kingston, concluding that it would be beneficial due to more pros than cons. The net outcome is positive, indicating a favorable decision for business expansion.

ANALYSING INFORMATION
AND DATA

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
TASK 1............................................................................................................................................1
Brief overview of mobile phone market.....................................................................................1
TASK 2 ...........................................................................................................................................2
Linear forecast not suitable and which forecast model will work in this case............................2
TASK 3............................................................................................................................................3
Features that makes the smartphone so popular with older customers.......................................3
TASK 4............................................................................................................................................4
Should Eco-Fone should expand the business in Kingston pros and cons.................................4
TASK 5............................................................................................................................................5
TASK 6............................................................................................................................................6
Findings presentation..................................................................................................................6
TASK 7............................................................................................................................................7
TASK 8............................................................................................................................................8
TASK 9............................................................................................................................................8
REFERENCES................................................................................................................................8
TASK 10 .........................................................................................................................................9
Findings.......................................................................................................................................9

INTRODUCTION
Data analysis is referred as process for systematically applying statistical and logical
techniques for describing, condensing, recap, illustrating and evaluating data. The present report
is about case study of Eco-Fones smartphone which sells smartphone and accessories through
two shops which are located in Putney and other in Richmond. It has provided brief overview of
UK's mobile phone market and related activities of 2016 to 2017. Furthermore, this report will
provide better understanding of smartphone market to analyse perceived increment in sales of
smartphone through older customer along with summarising its features. In the same series, it
will give pros and cons that Eco-fone should expand their business in Kingston or not.
TASK 1
Brief overview of mobile phone market
The workforce of UK has currently 33.5 million people in which 32 million are in work.
In this aspect, half of respondents were currently employed with use of smartphones for at least
single work related business activity and argued with proportion could be much higher. As of
mid 2017, very common application of smartphones among the workers whereas email of 44%,
calendar management of 23% and voice calls about 34%. There are various workers who are
using email, calendar applications which were directly optimised with context of smart phone
and very easier for use. The applications which are very difficult with application within
smartphone confines like legacy information along with reporting systems which are likely to
have less usage (Consumer and business usage patterns, 2017).
With this perspective, there is presence of unofficial application of smartphone which are
widely used in business like mobile browsers, instant messaging, photo application and
navigation. In the same series, 43% of workers uses Whatsapp at least once a day as all are
optimised for usage of smartphone. On the contrary, there was presence of usage of modest
smartphone with context to other work related application and laid special focus on work flow
instead of communication (Dayour, Park and Kimbu, 2019). Simultaneously, 5% of workers use
their smart phones for submitting a time sheet and 4% use this for submitting expense whereas
6%to access intranet.
Mixed Bar Chart
Activity 2016 2017
Email 41.00% 37.00%
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Making standard calls 33.00% 32.00%
Managing my time/ workload 8.00% 6.00%
Making voice calls using the
Internet (VoIP) 6.00% 4.00%
TASK 2
Linear forecast not suitable and which forecast model will work in this case
2

From the above, it can be analysed that the linear forecast model is not suitable for this
case because its only defines the linear relationship between the variables. It is limited to linear
relationship. Moreover, it looks at the mean of dependent variable (Barak and Sadegh, 2016).
The chart presented is also not suitable as it shows minor fluctuations. However, for this case,
Hybrid forecast model will work.
TASK 3
Features that makes the smartphone so popular with older customers.
The smartphone sales are increasing in UK with older customers which provide various
features that makes the smartphone more popular. As per the article it is identified that the age
group has seen faster adoption rate than any other (Mozersky and et.al., 2017). Moreover, the
smartphone provide the customer with easy access to the friends and relatives through installed
Facebook and other social media sites which connect the people with each other. Also, the
growing number of parking meter is the feature that is provided by smartphone encourage the
payment through mobile -phones which assist in providing convenience to older customers.
It has provided easier access to book taxi through installing the apps in the smartphone
which has made the smartphones more popular in older customers (Smartphone sales boom with
over-55s, 2017). Moreover, smartphones have bigger screen which provide easy view to older
customers and they have louder speaker too which provide clear sound and which has made
3

smartphone more popular for older customers. The smartphones have become easier to use over
the years as the android manufacturer offer streamlined version of their apps that aims at older
people.
Moreover, the smartphone providing handset might attract the older generations. Another
feature of smartphone includes facial recognition which is a popular authentication mechanism
among the elderly people. Older peoples like smartphone as there are no buttons to press which
make easy for them to understand the phones and typing passwords rather smartphones can help
them to use finger for unlocking their phone (Strain, Wijndaele and Brage, 2019). These feature
of smartphone helps the older customer to understand the phones in a better way and helps them
in using the technology in most efficient manner and easy access over other things.
TASK 4
Should Eco-Fone should expand the business in Kingston pros and cons
Should we expand our business to Kingston?
Pros Score/10 Cons Score/10
 Eco- fone by
expanding its
business in
Kingston will be
able to increase
its profitability
and market
share for
smartphone in
Kingston. 9
 But the
company by
expanding its
business in
Kingston will
have to follow
the laws and
legislation of
the Kingston
and the tax
liability of the
company will
be increased. 5
 It will lead to
global
expansion of the
8  Eco- fone have
to face
problems in
4
4

business of Eco-
Fone (Lydia and
et.al., 2016).
expanding its
business as it
will increase its
cost for
offering the
products to
customers
(Vázquez And
et.al., 2016).
 It will attract
new customers
towards the
smartphone of
Eco-Fone which
will be
beneficial for
firm. 9
 The company
will require
more capital for
expanding its
business in
Kingston. 5
 It will increase
the company's
market share
and will be
beneficial for
the growth of
Eco- fone. 9
 The company
have to face
tough
competition
from the
smartphone
companies
already existing
in that market. 6
Total Pros 35 Total Cons 20
Average Pros 8.75 Average Cons 5
5

Net outcome = Total pros -Total Cons
35 – 20 = 15
From the above calculation it is identified that Eco-Fone must expand its business in
Kingston because it will be profitable for the firm. The above calculation has provided that
Kingston will be able to get more benefits in expanding as there are more pons than the cons. For
example, The company by expanding its business in Kingston will be able to expand its business
globally which have more chances than increasing the cost of firm through expanding its
business.
TASK 5
Repayment mortgage 350000
Negotiable 350000
Mortgage rate 7
Asking price 400000
Year 15
Debt payment
Total loan amount / Discounting factor------------ (1)
[((1+0.07)^15)-1]/[0.07*(1+0.07)^15]
1.76/0.19 = 9.11--------------- (2)
By inserting (2) in (1)
350000/9.11
Total loan amount= 38419.32
Monthly repayment amount= 38419.32 / 12
= 3201.6
TASK 6
Findings presentation
First shop
Particulars Amount
Sample 40
Mean 100
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Standard deviation 20
Second shop
Particulars Amount
Sample 40
Mean 90
Standard deviation 40
Setting hypothesis
Null hypothesis: There is no difference in net taking of both shops.
Alternative hypothesis: There is difference in net taking of both shops.
Implementation of Z Score
First shop
Z score= (Mean value of 1 shop – Mean value of second shop) / Standard deviation of one shop
= (100 – 90) / 20
= 0.5
Second shop
Z score= (Mean value of 1 shop – Mean value of second shop) / Standard deviation of second
shop
= (100 – 90) / 40
= 0.25
With context of assessing value of Z score along with alpha value, if p value is greater
than 0.05 then null hypothesis is accepted and vice versa situation. While assessing Z score of
both shops, it has been articulated that both values are more than 0.05 so there is acceptance of
null hypothesis which could be elaborated as there is absence of difference in net taking of shop
one and two.
TASK 7
Particulars
Questio
n 1
Questio
n 2
Questio
n 3 (a)
Questio
n 3 (b)
Questio
n 3 (c)
Questio
n 3 (d)
Questio
n 4
Questio
n 5
Questio
n 6
7

Average 2.95 2.89 1.98 2.5 3.25 2.51 2.51 2.52 3.71
Standard Error
(SE) 0.15 0.09 0.08 0.09 0.12 0.1 0.12 0.09 0.11
Median 3 3 2 2 4 3 2 2 4
Mode 4 3 2 2 4 3 2 2 4
Standard
Deviation (Sd) 1.48 0.95 0.84 0.87 1.25 1.07 1.19 0.92 1.15
Sample Variance 2.18 0.9 0.71 0.76 1.56 1.13 1.41 0.84 1.33
Kurtosis -1.46 -0.72 0.24 -0.65 -0.82 -1.21 -0.17 -0.13 0.24
Skewness -0.03 -0.27 0.75 0.26 -0.89 -0.16 0.84 0.47 -1.1
Range 4 4 3 3 4 3 4 4 4
Min 1 1 1 1 1 1 1 1 1
Max 5 5 4 4 5 4 5 5 5
On basis of above descriptive statistics about the outcome of 103 respondents of 6
criteria. With reference to first question is all about last time purchased about service or product
from Eco-Fone as average respondents had performed between 6 months and 1 year whereas its
useful life of product is in 3 to 5 years. With context of rating of every criteria, average
respondents had ranked customer support or service is fair. In the same series, product or
service's quality is good and with context of sales staff respondents ranked it on good category
and value or price in the similar category. Furthermore, with observation of customer satisfaction
was marked on neutral mode where average respondents and similar for continuing business.
Thus, with reference to recommendation average respondents likely suggested their products and
services to others.
TASK 8
Poisson
random
variable
Mean rate of
success
Poisson
probability
P(X=2)
Cumulative
probability
P(X<2)
Cumulative
probability
P(X>2)
Cumulative
probability
P(X>=2)
2 15 0 0 1 1
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The above table is specifying Poisson distribution for this case as it is appropriate
because of presence of discrete probability as is description about distribution of rare events in
large population. Poisson distribution is considered as discrete probability distribution of number
of events which occur in specified duration and offered average number of times event occur
over this time period (Wang and Hailemariam, 2018.). On basis of above case, accounts
department had delivered 10000 invoices in per month along with average of 2 was returned with
default. Simultaneously, as per procedure quality assurance, minimum 3 invoices should be
returned in a month which has been met through company so it is approved.
TASK 9
REFERENCES
Books and Journals
Barak, S. and Sadegh, S. S., 2016. Forecasting energy consumption using ensemble ARIMA–
ANFIS hybrid algorithm. International Journal of Electrical Power & Energy
Systems. 82. pp.92-104.
Dayour, F., Park, S. and Kimbu, A. N., 2019. Backpackers’ perceived risks towards smartphone
usage and risk reduction strategies: A mixed methods study. Tourism Management.72.
pp.52-68.
Lydia, M. and et.al., 2016. Linear and non-linear autoregressive models for short-term wind
speed forecasting. Energy conversion and management. 112. pp.115-124.
Mozersky, J. and et.al., 2017. Toward an ethically sensitive implementation of noninvasive
prenatal screening in the global context. Hastings Center Report. 47(2). pp.41-49.
Poushter, J., 2016. Smartphone ownership and internet usage continues to climb in emerging
economies. Pew Research Center. 22. pp.1-44.
Strain, T., Wijndaele, K. L. and Brage, S., 2019. Physical activity surveillance through
smartphone applications and wearable trackers: Examining the UK potential for nationally
representative sampling.
9

Vázquez, M. Y. G. And et.al., 2016. Mobile phones and psychosocial therapies with vulnerable
people: A first state of the art. Journal of medical systems. 40(6). p.157.
Wang, F. K. and Hailemariam, S. S., 2018. Sampling plans for the zero-inflated Poisson
distribution in the food industry. Food Control. 85. pp.359-368.
Online
Consumer and business usage patterns. 2017. [Online]. Available through
<https://www.deloitte.co.uk/mobileuk/assets/img/download/global-mobile-consumer-
survey-2017_uk-cut.pdf>
Smartphone sales boom with over-55s. 2017. [Online]. Available through
:<https://www.bbc.com/news/technology-41319684>.
TASK 10
Findings
From the above report it has been find out that mobile phone market in UK is increasing
as the 44% of workers in UK are using E- mails, 23% are calendar management and 34% for
voice calls. Moreover, it has been identified that linear forecast is not suitable for this case study
as it only shows the linear relation between the variables and the charts which are presented are
also not suitable as there are fluctuation in the charts. Also, Hybrid forecast model will work in
this case. Furthermore, this report has provided understanding about the features of smartphones
which has made them popular for older customers that consist features such as easy convenience
in payment through apps, easy access in booking taxi etc.
Moreover, smartphones have bigger screen which provide better view to the older people.
As peer the report, It has analysed that the Eco- fone should expand its business in Kingston as it
will be more beneficial for its growth as there are more pros than the cons. The net outcome
provide is equal to 15 which means it is positive and thus it is beneficial for the company to
expand their business in Kingston. Also, the monthly repayment amount for the mortgage is
3201.6. The findings show that the net taking of the two shops have no difference which is being
identified through use of Z score. From the analysis, it has been found that there were 103
respondents of 6 criteria from which average respondents have recommended the products and
services of Eco- phone. Poisson distribution is appropriate because of presence of discrete
10