Business Intelligence and Analytics Implementation Report for Three UK

This report focuses on the implementation of a business intelligence (BI) and analytics system for Hutchison 3G UK Limited, also known as Three UK, to address issues with call quality and service reliability. The report outlines the project management and planning skills required, including initiati...Read More

BUSINESS INTELLIGENCE

TABLE OF CONTENTS
Backgorund, context and outline of the report................................................................................1
Appraisal of porject management and planning skills required for implementation of BI and
analytics solution.............................................................................................................................1
Skills required by data analyst to make efficient use of BI.............................................................2
CONCLUSION AND RECOMENDATION..................................................................................4
REFERENCES................................................................................................................................4

Backgorund, context and outline of the report
Hutchison 3G UK Limited is one of the known company in the UK and it is known by
name Three UK. Mentioned company usually provide internet services and telecommunication
related services to customers. Currently, firm is providing both 3G and 4G services and serving
around 98% of peopulation. Even though business is growing there are some of issues that are
faced by the firm. One of these problems is that call quality was poor and services suddenly get
lost during calling that is made by one person to another. Voicemails and text messages services
were also not good which tarnish firm image among customers. In the current report, in respect
to these problems implementation of analytics and business intelligence system is proposed.
Different aspects related to business intelligence and analytic system will be discussed latter on
in the report.
Appraisal of porject management and planning skills required for
implementation of BI and analytics solution Initiation phase: Main aim of the project is to improve mobile network services across
UK and this regard company intend to increase strength of its mobile tower signals by
implementation of effective business intelligence system. In this stage use of Tableau
software will be done and in this regard KPI will be developed (Turban, Sharda and
Delen, 2011). In KPI different locations will be plotted on single chart in dashboard and
charts will reflect strength of signal in different locations across UK. On basis of KPI
results targe will be set for the limit up to which signals strength must be increased in
each geographic area. Thus, it can be said that at this stage main focus will be on
determination of goals so that according activities can be determined that need to be
performed in order to achieve objectives in business.
 Scope of business analyst: In order to make this project successful business analyst will
be appointed. First of all new machines will be installed on towers or modifications will
be done on towers. Thereafter by using IOT equipments or any other thing strength of
signal will be measured. By doing so data will be automatically transferred to online
database and same will be used by buisness analyst for analysis purpose (Chaudhuri,
Dayal and Narasayya, 2011). On daily basis business analyst will use Tableau software
and through preparing dashboards will measure strength of signal from towers in
different locations. Moreover, in dashboard comparison will be made between signals
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and same will be reported to relevant manager by business analyst. In this way business
analyst will play crucial role in manging entire project.
 Scheduling: MS Project software will be used and in same different activities will be
entered along with days within which same will be completed. CPM method will be used
to identify activities that can not be delayed at any cost in order to control cost of the
project. Different activities are determine like development of project charter, work plan
will be developed along with project control plan (Vercellis, 2011). Finally, entire system
of data collection and testing will be developed and duration of all these activities will be
fixed. According to, critical path method chart actiuvities will be performed and delayed
as well as performed on time. By doing so on time work that need to be done on towers
and business will be completed.
 Budgeting: Budgets will be prepared for each activitiy of the project. In this regard there
are multiple approaches that can be used by the firms like zero based budgeting and
incremental budgeting. In case of zero based budgeting department managers have to
prepare budget and same get approved by top managers. Finally, budget of all
departments are combined to prepared budget for entire firm. Apart from this,
incremental budget can also be prepared and under this values that are in past years
budget can be increased. By doing so, budgets can be prepared in proper manner.
 Project team and communication plan: In this project different teams will work
altogether like technicians and business analyst team. There will be multiple technicians
that will handle towers individually. These experts will send entire data to the team of
business analysts which will do detail discussion on received data and will prepare varied
sort of charts. On basis of charts dashboards will be prepared. On basis of dashboard
reports will be prepared and same will be used by technicians in order to identify that in
which area they need to work extensively to improve performance (Yeoh and Koronios,
2010). As part of communication plan on common software communication will be done
between technicians and business analysts team. If there is different requriements of
technicians in respect to improving mobile services then in that case according to need
pictorial presentation will be done and assistance will be provided to technicians in
respect to making decisions in respect to improving mobile services.
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Skills required by data analyst to make efficient use of BI Programing: Data analyst need to have good programing background in R, SAS, SQL,
python, IBM SPSS Modeler. All these softwares can be used according to requirments by
the data analyst. One must have good knowledge of all these programing languages
because all firms does not use only SAS or R. SQL usage is common to extract relevant
data from huge database. IBM SPSS Modeler can also be used as an alternative to R and
SAS if dataset size is not so huge. Hence, it can be said that data analyst must be expert
in programing language. Statistics: Data analyst must be proficient in statistics and must be aware about concept
of normal distribution etc which are used to make predictons and make useful estimtions
(Anandarajan, Anandarajan and Srinivasan, 2012). By using same varied facts can be
identified about signal strength from towers installed by Three mobile communications. Data processing: Data that is received by data analyst is not arranged in systematic
manner and same can not used directly for analysis purpose. Thus, data analyst must have
data cleansing related knowledge on R or SAS software. Data transformation is another
area about which data analyst must be aware. Thus, it is another area about which data
analyst must have good knowledge for efficient use of BI and analytic system. Data mining: Data analyst must also have strong knowledge of data mining methods like
regression analysis, cluster analysis, decision tree diagram and other techniques. By using
these tools different facts can be identified. For example linear regression model can be
developed and by considering independent variables it can be identified at specific cutoff
point whether signals will increase or decrease from towers. It can be said that by using
logistic regression tool mangers can identify those towers on which specific attention
need to be paid. By using Tableau software close eye can be maintained on signals and
accordingly decisions can be made by managers. Story telling: Data analyst must have story telling skills because data is readily available
to the individual but from same one need to identify hidden trends (Williams. and
Williams, 2010). If analyst have story telling skills then in that case it can identify lots of
things and can make strong decisions in respect to improving firm performance. Dashboard: Data analyst must have knowledge of preparing dashboard and in this regard
one must have knowledge of functions like LOD and inner as well as outer joins that are
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in Tableau. By simply looking at chart one can easily identify direction in whicg there is
need to do work for benefit of 3 mobile firm. Business accumen: Data analyst must have business accumen and it must have capability
to handle business related data. One must be able to understand business and its
requirements as well as growth drivers and factors that affect their performance (Tableau,
2018). If one have strong business accumen then in that case on can easily comprehend
data and can identify lots of hidden facts use of which can accelerate business growth
rate.
CONCLUSION AND RECOMENDATION
On basis of above discussion it is concluded that there is significent importance of
business intelligence or analytic system because by using same time to time signal strength can
be measured and targets can be set in respect to improving performance of towers. It is also
concluded that data analyst appointed by the firms must have strong knowledge of programing,
statistical tools and many other things so that they can do well on their job. On basis of disussion
it is recommended that some of tools like logistic regression must be used by the firm to identify
selected towers where close eye need to be maintained. It is also recommended that advanced
options that are available on software like Tableau must be used to analyze data with more
granularity. By doing so better decisions can be made by the managers and analysts.
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REFERENCES
Books and Journals
Anandarajan, M., Anandarajan, A. and Srinivasan, C.A. eds., 2012. Business intelligence
techniques: a perspective from accounting and finance. Springer Science & Business
Media.
Chaudhuri, S., Dayal, U. and Narasayya, V., 2011. An overview of business intelligence
technology. Communications of the ACM. 54(8). pp.88-98.
Turban, E., Sharda, R. and Delen, D., 2011. Decision support and business intelligence systems.
Pearson Education India.
Vercellis, C., 2011. Business intelligence: data mining and optimization for decision making.
John Wiley & Sons.
Williams, S. and Williams, N., 2010. The profit impact of business intelligence. Morgan
Kaufmann.
Yeoh, W. and Koronios, A., 2010. Critical success factors for business intelligence
systems. Journal of computer information systems. 50(3). pp.23-32.
Online
Tableau, 2018. [Online]. Available through:< https://www.tableau.com/>.
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