BT – Data Analytics

British
Telecommunications Plc

● A British multinational telecommunications company with head offices in
London, United Kingdom and was founded in 1969.
● CEO: Gavin Patterson (since 2013)
● It operates in over 180 countries and is the largest provider of fixed-line,
mobile and broadband services in the UK, and also provides subscription
television and IT services.
● Purpose: to use the power of communications to make a better world
● Revenue: £24.062B
● 106,400 employees
BT Overview

How is it relevant to us?
Source: Accenture

Process of examining data sets in order to draw conclusions about
the information they contain, with the aid of specialized systems and
software, in order to improve products and services, decision-
making and business operations.
What is Data Analytics?

“We can now process the billions of messages that are being alerted
from millions of pieces of our network electronics. Five years ago
that data would not have been processable in near real time, but
today it is.” – Clive Selley, BT CIO

Business Model Canvas
Provide world-class:
telecommunications,
information products &
services, and to develop
& exploit our networks,
at home and overseas
- 106,400 employees
- Offices over 180
countries
- Telecom infrastructure:
- £3B worth + superfast
optic fibre network
- 4G network
- Phone line + TV
network (broadband)
￡520m in R&D
102 patent fields
£14.1bn spent with
suppliers
Online service
(company website &
My BT app)
Call Centres
Account managers
- Retail Telecom Services
- Retail IT Services
- Business Services
Solutions
- Provide Telecom
Infrastructure
- Network maintenance
- Marketing & Sales
Revenue: £24.062 B
(-5.26% drop from
2014/2017)
Communication
Providers (CPs)
Media Companies
and Broadcasters
Businesses (SMEs,
MNCs)
Governments
Public Institutions
General Public
(households)
Contractual based
Call Centres
BT Chat
Shift towards self- service
for BT’s Consumer
business division
- Newness
- Improved
Performance
- Accessibility (e.g:
4G coverage over
80% of UK )
- Convenience/
usability

Multinational
companies
Small and
medium-sized
enterprises
Large
enterprises
and public
sector
- Voice and
data
- Mobility
- IT services
Products and services in:
- Fixed voice
- Broadband
- Mobile
- TV and broadcasting
Services in:
- Fixed voice
- Cloud
- Mobile
- Networking
- IT
Households
Network and
infrastructure
servicesOpenreach – nationwide
Infrastructure:
Copper and
Fibre
connections
Communications
providers and
media companies
Network
products and
services
- Data
transmission
services

Our Competitors
National (direct competitors) Worldwide (indirect comparable
competitors)
Mobile carriers
Vodafone Group plc
O2
GiffGaff
Three
China Telecom
Deutsche Telekom
Telefónica
Verizon Worldwide
IT solutions
Kcom
Vodafone Group plc
Deutsche Telekom AG
Cisco
Softbank
Dell Cloud
Intel
Internet services
Kcom
Eurocoms
O2
Three UK
Vodafone Group plc
Sky UK
Virgin Media
China Telecom
Deutsche Telekom AG
Verizon
SoftBank Group Corp
Cisco
Sprint
Broadband
Sky UK
Virgin Media
Eurocoms
TalkTalk Group
O2
Three UK
Vodafone Group plc
China Telecom
Telefonica Europe
AT&T Inc
Verizon
SoftBank Group Corp
America Movil
Movistar
Sprint
Division
Companies

Understanding the maturity of the Telecom Industry
“Telecommunications Industry at cliff’s edge”
– McKinsey (2016)

Current challenges for BT
● Growth in number of contracts is slowing down (Smartphone Saturation)
● Decline in number of TV & broadband & fixed line subscriptions
● Consumers demand the latest services/technologies at a lower price,
while data consumption is predicted to grow by 53% by 2020 (EY)
● Highly competitive → Price war between operators in tariffs
● High expenditure in infrastructure
○ BT is still expanding its 4G network (15% in the UK yet to be covered)
○ Estimated cost to implement 5G in the EU → €57B by 2020
WILL DATA & ANALYTICS HAVE ANY IMPACT ON THESE?
WHAT KEY APPLICATIONS DO DATA & ANALYTICS HAVE?

Competitors and their use of
Data Analytics
News/Blog database: 1619 stories

News/Blogs Database: News article network with 1109 stories
Quid BT & Big Data Network

Timeline of Predominance of AI potential
and Cloud in media in regards to BT
News/Blogs Database: News article bar chart with 962 stories
BT implemented the Cloud of
Clouds
Announcement on future
launch of CoC

Consultant sources we borrowed information from:
Consultant
Sources
ArticlesReports
KPMG (2)
Deloitte (1)
Gartner (1)
McKinsey (7)
PwC (2)
Bain & Company (2)
BCG (2)
Forbes Insights (2)
MIT Sloan (8)
IBM (1)
KPMG (2)
Deloitte (1)
Gartner (1)
McKinsey (1)
PwC (3)
Bain & Company (2)
Accenture (2)
EY (2)
Forbes Insights (2)
MIT Sloan (1)
IBM (3)

Application Clusters
Network Operations Service
Customer
Management &
Relations
Business Assurance
Optimisation of network
utilization (21)
Network monitoring and
protection (20)
Network capacity planning (9)
Anomaly and detection
troubleshooting (1)
Total : 51
Product development & tariff
optimization (19)
Service personalization (5)
New product rollout visibility
(2)
Subscriber profiling and
segmentation (4)
Total : 30
Campaign management &
precision marketing (42)
Customer loyalty management
(6)
New Customer Experience
(11)
Existing customer information/
data (2)
Churn Prevention (15)
Total : 76
Fraud detection/ management (21)
Suspicious traffic management (14)
Cloud Utilization (13)
Real time reports (6)
Forecasting and planning (2)
Credit scoring system (1)
Cost reduction (4)
Enhance decision-making process
(9)
Total : 70

How are Data & Analytics going to change our...
1. Key Products & Services
1. Key Decisions
1. Key Processes

1. Key Products & Services:
Multinational
companies
Small and
medium-sized
enterprises
Large
enterprises
and public
sector
- Voice and
data
- Mobility
- IT services
- Fixed voice
- Broadband
- Mobile
Services in:
- Fixed voice
- Cloud
- Mobile
- Networking
- IT
Households
Network and
infrastructure
services
Openreach – nationwide
Infrastructure:
Copper and Fibre
connections
Communications
providers and
media companies
Network
products and
services
- Data
transmission
services

a. Households
- Fixed voice
- Broadband
- Mobile
Households

a. Households
Enriching Customer Experience:
2014
MTS Telecom – By using customer analytics they implemented a
system of user gratification based on their loyalty and plan usage
(‘customer delight’) → Doubled their conversion rate, from 3% to 6%
● Prescriptive Analytics (Internal)
Virgin Mobile – Used predictive analytics to improve retention by
targeting at-risk/new subscribers → Increased their data usage by
19% and SMS utilisation by 41%
● Descriptive Analytics (Internal + External)
BT –Reducing faults and predicting churn at EE → Churn reduced
from 2.1% (2014) to 1.1% (2015)
● Predictive Analytics (Internal Data)
2012
T-Mobile – Data-based customer care in order to fight churn →
Reduced net customer losses from 99,000 to 50,000 the quarter
after implementing
● Descriptive Analytics (Internal Data)
TalkTalk – By using an analytics and reporting platform for
improved customer experience, they reduced number of calls to
the customer service centre by 40%, (2011–2012)
BT – By using cross-channel interaction with their customers and
by tracking them in those channels (360º view) → Reduced
complaints by 50% and dissatisfaction contracts reduced from
28% to 12% from 2011 to 2014
● Descriptive Analytics (Internal+External)
2022
BT – Prescriptive Analytics (External +
Internal Data) + AI + Outside Insight to enrich
customer experience, improve customer
relationship and deliver increased value as a
service wrapped around their products
● £30M Investment in Belfast R&D AI,
Analytics and IoT Centre
Verizon – Customer service with Cognitive Intelligence and
personalised marketing → Customer satisfaction went up from 81% to
87% (2016 to 2017)
● Predictive Analytics (Internal + External) + AI
T-Mobile – By leveraging social media data together with historical and
transaction data from the Customer Relationship Management and
billing system, they are able to better predict customer defections and
react on time → In a single quarter (Q4 2016) they cut down the churn
rate by 50%
● Predictive Analytics (External + Internal) + AI
BT – Real-time data analytics and customer behavior analysis in BT
Mobile together with fault reductions → Churn rate reduction 2.8%
(2016) to 1.9% (2017)
2017

Key Characteristics of Applications (.a):
2012 2014 2017 2022
Technology Data Analytics Data Analytics
Data Analytics
+ AI
Data Analytics
+ AI +
Automation
Type(s) of
Analytics
Descriptive
Introduction of
Predictive
Predictive Prescriptive
Data Source(s) Internal Internal
Internal
+ External
Internal +
External + OI
Cluster
Churn
prevention
Precision
marketing &
Churn
prevention
Precision
marketing &
Churn
prevention
Precision
marketing &
Churn
prevention

b. Businesses & Public Institutions
Multinational
companies
Small and
medium-sized
enterprises
Large
enterprises
and public
sector
- Voice and
data
- Mobility
- IT services
Services in:
- Fixed voice
- Cloud
- Mobile
- Networking
- IT
Network and
infrastructure
services

Cloud service improvement:
b. Businesses & Public Institutions
2017
Hewlett-Packard - Design, deploy and implement data analytics consulting
solutions → Leading to an application improvement in response time by
33% for RI-solution
● Prescriptive analytics (internal & external)
Telefonica - It has a simple web services interface (API) that can be used
to store and retrieve any amount of data, at any time, from anywhere on
the web → Resulted in a high return in investment
● Predictive analytics (internal & external)
BT - Becomes the first global network services provider to offer direct
access to the Oracle cloud → Cutting the typical dedicated connection
deployment time from months to days
● Cloud computing (internal & external)
2014
Vodafone x Argyle Data - combat fraud → $4.5m additional funding to help
companies detect and combat fraud through real-time analytics which can be
accessed as soon as data enter the system
● Predictive analytics (internal)
Cloudera - Provide an open source big data analytics framework (Apache
Spark) to support in-memory processing → Perform significantly 10 - 100x
faster than MapReduce
● Prescriptive analytics (internal)
BT - Announces the “Cloud of Clouds”, the first ever integration between
different cloud providers, third party services, analytics solutions, customer
data centres and customer users together with the BT Network.
2012
Dell Cloud - Customization of cloud deployment (build, manage, use, consult) →
They cut deployment time by 80% compared to Cisco; cut operating cost;
respond faster to business demand
Hewlett-Packard - Speeds the deployment of application-based services →
They decreased spam by 70% and increased administrator efficiency up to
33%
● Descriptive analytics (internal & external) + Cloud computing
BT - Expansion of data centre capacity in the Benelux with a new facility in
Rotterdam which supported Microsoft Lync and Cisco’s Hosted Collaboration
Solution (HCS) → Increased IT services capacity in the Benelux region by 50%
2022
BT is currently one of the leaders in Cloud services (“Cloud
of Clouds”). Nevertheless, they don’t have a Data Lake that
could allow them to systematically analyse their customers’
data. Together with external data, and Outside Insights, they
could potentially offer a better service. In the future, they
could also include IoT data analysis.
- The data lakes market size is expected to grow
from USD 2.53 Billion in 2016 to USD 8.81 Billion
by 2021, at a Compound Annual Growth Rate
(CAGR) of 28.3% during the forecast period.

Key Characteristics of Applications (.b):
2012 2014 2017 2022
Technology
Data Analytics
+ Cloud
Computing
Data Analytics
+ Cloud
Computing
Data Analytics
+ Cloud
Computing
Data Analytics
+ Cloud
Computing + AI
Type(s) of
Analytics
Predictive
Predictive &
Prescriptive
Predictive &
Prescriptive
Prescriptive
Internal +
External
Internal +
External + OI
Cluster
Cloud
Utilization
Cloud
Utilization
Cloud
Utilization
Cloud
Utilization +
Real time
analytics

2012 2014 2017 2022
Technology
Data Analytics
+ Cloud
Computing
Data Analytics
+ Cloud
Computing
Data Analytics
+ Cloud
Computing
Data Analytics
+ Cloud
Computing + AI
Type(s) of
Analytics
Predictive
Predictive &
Prescriptive
Predictive &
Prescriptive
Prescriptive
Internal +
External
Internal +
External
Data Variety Structured Structured
Structured +
Unstructured
Structured +
Unstructured
Data Velocity Near Real-time Real-time Real-time Real-time
Cluster
Cloud
Utilization
Cloud
Utilization
Cloud
Utilization
Cloud
Utilization +
Real time
analytics

c. Telecommunication Companies
Openreach – nationwide
Infrastructure:
Copper and Fibre
connections
Communications
providers and
media companies
Network
products and
services
- Data
transmission
services

Sprint – Real-time data analytics to control
the network driving → Increased 90% of its
capacity
● Predictive analytics (Internal) + AI
BT – Real time threat monitoring
● Descriptive analytics
(Internal+external) + AI
c. Telecommunication Companies
Infrastructure Improvement:
!
2014
2012
2020
BT - Will use IoT data analytics
and security technologies to do
5G testing for future
implementation and will develop
the network with Nokia and
Huawei→ It is expected from BT
to provide improved ultrafast
speeds and latency in the range
of one millisecond.
● Prescriptive analytics
(External + Internal data)
Cablelabs-proactive network maintenance (PNM)
● Descriptive analytics (Internal+external)
Amazon – Integrates machine learning to transactional and operational
data centres → To extract meaning and forecasts out of their data now no
longer need third-party machine learning platforms.
● Predictive analytics (Internal) + Machine Learning
BT- Implemented Cloudera-powered enterprise data hub to accelerate
data velocity → Process five times more customer data and achieve a
velocity increase of 15%.
● Descriptive (Internal)
2017
Vodafone – Uses AI to increase network optimisation speed by over 45,000%. Tested in C-SON, the
Initial results confirmed an average 6% improvement in the mobile download speed and lower
interference at the cell sites.
● Prescriptive analytics (Internal) + AI + Machine learning
Cisco – By using Global Mobile Data Traffic Forecast, an ongoing initiative to track global networks
→ Mobile data traffic will grow at a compound annual growth rate (CAGR) of 47 percent, reaching
49.0 exabytes per month by 2021, and with the implementation they will be able to cope with it.
● Predictive analytics (External + Internal data)
BT Openreach – By using data transmission technology and FTTP, BT developed the world’s first
ever live demonstration of 100Gbps ‘hyperfast’ broadband with Huawei → Boost the broadband
signal with enough capacity to stream 4,000 ultra HD quality movies simultaneously
● Predictive analytics (External +Internal data)

Key Characteristics of Applications (.c):
2012 2014 2017 2020
Technology
Data Analytics +
AI
Data Analytics +
Machine
Learning
Data Analytics +
Machine Learning +
AI
Data Analytics +
Machine Learning
+ AI
Type(s) of
Analytics
Descriptive &
Predictive
Descriptive Predictive Prescriptive
Data
Source(s)
Internal Mainly internal
Internal
+ External
Internal + External
Data Velocity Real-time
Real-time &
Near Real-time
Real-time Real-time
Data Variety Structured
Structured +
Unstructured
Structured +
Unstructured
Structured +
Unstructured
Cluster
Suspicious traffic
management
Optimisation of
network
utilization
Optimisation of
network utilization
Optimisation of network
utilization + Network
monitoring and protection

Company - wide
● 2: Shrink an
existing business
● 3 : Grow an
existing business
● 4: Corporate
restructuring
Develop products
● 5: Enter new
industry/ start a
new business
Market and sell
● 6: Negotiating a
major contract
Deliver & Support
● 1: Collaborate
with competitors
● 7: Major
business
investment
● 8: Corporate
financing
Decision architecture
One-off
decisions
Ongoing
decisions
6 5
7
32
41
8

BT Key Decisions
Company-wide: Reconstructing/adapting business model/culture (ongoing)
Develop Products:
- New launches for product/services or reductions for existing ones (ongoing)
- Infrastructure upgrades or maintenance (ongoing)
Market and Sell:
- Advertising (ongoing)
- Maintaining and gaining new customer relationships and segments (ongoing)
Deliver:
- Mergers and acquisitions (once off)
- Development of new or existing investments (ongoing)
- Collaboration - ventures (ongoing)
Support:
- Security/ fraud management (once off)
- Obtaining financing (once off)

2. Key Decisions
2017
2014
2012
Analytics: Predictive and Prescriptive
Database: Internal and External
Technology: AI, machine algorithms, data
analytics.
In addition, Outside Insight may be used to
augment decision-making: AI
Vodafone - Simulate the expected effects of possible new pricing
packages or services, and use the results to decide “when and where is
best to roll them out.”
● Predictive Analytics (Internal data)
Celcom Axiata Bhd. - Used customer experience analytics and
performance indicators data to make decisions surrounding campaign
launches and reduced campaign launch time by 80%
● Diagnostic Analytics (Internal data)
BT – Continues using the cloud-based business intelligence system →
Allowing agile decision making
Telefonica O2 – Used analytics for decision-support. In specific, to
support corporate planning and management decisions. This led to an
18% increase in precision of forecasts and an increase of 200% in
forecast modelling speed.
Aruba – Used analytics and cloud to generate automated reports based
on internal data, ultimately reducing decision-making time
● Descriptive Analytics (Internal Data) + Automation
BT – Used a cloud-based business intelligence system to glean
information and unify reporting from 5000 Salesforce users across 3 BT
divisions to accelerate (saved time = 93%) and improve the accuracy of
their decision-making process.
Verizon – Combining artificial intelligence with human
judgement for key decision-making → “Using AI to illuminate
choices but not to abdicate authority.”
● Prescriptive Analytics (Internal Data) + AI
OTE Cosmote - Uses analytics to analyse growing volumes of
network and customer data in seconds instead of minutes, this
accelerates the decision-making process.
● Prescriptive Analytics (Internal Data) + Big data
BT - They are using Big Data to reveal key business insights,
highlight key trends and needs that will guide the direction and
speed of new product development → Allowing them to make
smarter and faster decisions
● Advanced prescriptive analytics (internal data) → +
Big data - Structured & unstructured data
2020

Characteristics of Applications in Decision-making:
2012 2014 2017 2020
Technology Data Analytics
Data Analytics +
AI
Big Data + AI
Machine
algorithms + AI
+ Big Data
Type(s) of
Analytics
Descriptive
Predictive +
Descriptive +
Diagnostic
Mainly
Prescriptive
Predictive +
Prescriptive
Data Source(s) Internal Mainly Internal Internal
Internal +
External
Actual decision
made by
Human Human
Machine and
Human
Machine and
Human
Main Cluster
- Forecasting and
planning
- Real-time reports
- Cloud Utilization
- Campaign
management &
Precision marketing, -
Existing customer
information/ data
- Cloud Utilization
- Existing customer
information/ data
- Cost reduction
- enhance decision-
making process
-

Source: PwC, 2016
Future Decision Making
“The combination of data analytics and
human intuition adds up to judgment that
is more capable and effective.”
- PWC, 2016

Talk Talk – Natural Language Call Steering (routes calls to the correct
division in Talk Talk). They were able to save £3 million and reduce call
times by 23%
● AI + Automation + Descriptive Analytics (Internal Data)
Vodafone – Uses fraud analytics to detect fraud. Saved 99% time (from 24
hours to 3.5 minutes) spent.
● Prescriptive Analytics (Internal Data)
BT – Debatescape - social monitoring tool - uses AI to search out
customers who might need help but don't know who to approach in BT to get
it. Saved ￡2 million.
● Big data (social media) & Predictive Analytics (Internal Data) + AI
Vodafone – Implemented an IBM Business Intelligence (BI)
platform used by top management for querying and KPI
reporting → Saved £105k the first year after implementation.
O2 (Telefonica) – Automation Blue Prism software applied to
reduce back office operation costs and remove reliance on
offshore activities to improve workload management during
peak hours → reduced offshore costs which for equate to ¼ of
onshore costs.
● Descriptive Analytics (Internal Data) + Automation
BT – Used Business Intelligence (BI) software (Oracle BI), able
to cut down from 8,000 systems to 4,000, consolidating and
homogenising the company’s technology. Allowed a clearer
view of processes leading to an increase of Key Performance
Indicators (KPI).
● Prescriptive Analytics (Internal Data)
Rostelecom - SAS credit scoring software used to automate credit management
process. It reduced international operators’ bad debt reserves by US$3.8 million,
achieved by reducing the amount of funds the company should set aside to cover
risky debts.
● Descriptive, Predictive & Prescriptive Analytics (External + Internal Data) +
Automation
CenturyLink - Implemented Conversica AI powered assistant (Angie), used in sales
automation to help sales reps and save costs of hiring. Around 90,000 sales leads
sent to company every quarter. Angie sends ≈ 30,000 emails a month, analyses
responses, identifies and sends most promising leads to the right reps. Earnt $20 in
new contracts for every dollar invested in the software.
● Descriptive & Predictive Analytics (Internal Data) + AI
BT - Truecall technology blacklists nuisance numbers (unwanted calls). Real time
analysis of data from radio access networks (RAN) used to identify rouge numbers
(large numbers dialled in quick succession).
Aim to block 25 million calls /week.
● Descriptive, Predictive & Prescriptive Analytics (Internal data)
BT – Analysing constant process improvements by using
internal and external data and AI algorithms. More real-time
analytics and virtual assistants are expected to help in areas
such as fraud detection, cost reduction and real-time reports.
● Prescriptive Analytics (External + Internal Data, OI) +
AI & Algorithms
3. Key Processes

Characteristics of Applications in Key Processes:
2012 2014 2017 2022
Technology
Data Analytics
+ BI
Data Analytics
+ AI
+ Automation
Data Analytics
+ Automation
Data Analytics
+ AI
Type(s) of
Analytics
Mainly
Descriptive
Descriptive
Predictive
Prescriptive
Mainly
Descriptive &
Predictive
Prescriptive
Data Source(s) Internal Internal Internal
Internal &
External
Main Cluster
Optimisation of
network
utilization
Optimisation of
network utilization,
Fraud & Anomaly
detection
Product
development &
optimisation of
tariffs
-

Example of a Key Process (Network Capacity Planning):

Yesterday (until 5pm), BT had 11 cases of Broadband Outage across the
UK
WHY?
WHY?
WHY?
WHY?
WHY?
We extensively rely on our internal database, which is why we are
unable to anticipate through Big Data.
We currently don’t make any use of external data (IoT analytics nor
Outside Insight) in our predictive model.
Our predictive model is not as sophisticated as it should to be.
Our estimations are not accurate enough.
Our chase demand does not match the actual demand.

* Full details on value creation will be provided in the
report (along with the impacts on processes,
operations and value propositions for customers)
*
*

BT could eventually regain its
competitive edge whilst:
● Enriching customer service
● Better network utilisation and
service improvement
● Making smart decisions faster
● Potentially reducing operation
costs
An additional Recommendation
Internal + External data
(OI)

BT – Data Analytics

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