OTE Group in Greece Value Based Rollout

October 2016

Contents

2

1. OTE Group overview

2. Customer Network Experience Landscape in OTE

3. SAS VA Access to Hadoop Setup

4. Problem Definition - Targets

5. Enabling Sound Decisions based on Value Insights – Drill down

OTE is the leading integrated telecommunications operator in southeast Europe,

providing Fixed and Mobile services (Telephony and Broadband) and TV

Romania

Greece

Greece

Mobile

7,4

TV

0,5

Broadband

1,4

Fixed

2,7

Customers (mil.)

Νο 1 in Fixed

Νο 1 in Mobile

Albania

Mobile

1,7

Customers (mil.)

Νο 2 in Mobile

Romania

Broadband Mobile

6,0

TV

1,5 1,2

Fixed

2,2

Customers (mil.)

Νο 1 in Fixed

Νο 3 in Mobile

All data: 31/12/2015

Revenues Distribution

Romania

25%

Albania

2% Greece

73%

ΟΤΕ Group: Leader in South East Europe…

3

4

SAS

Access to Hadoop

Ded

icate

d

SA

S S

ch

em

a

RAW data Agg. data

SAS Analytics interworking with Big Data

HADOOP - Cloudera

Slave nodes

Active-Active HA solution

SAN

Data preparation & processing takes place on Hadoop and then loaded in memory for Analytics & Visualization

• Distributed environment

• Parallel processing

• Memory analytics

5

Centralised Collection & Mediation

Aggregation &

Metrics calculation

TDR Filter traffic

by VLAN tagging

Time

Aggregation Layer

GTP stream

DPI Layer

CONTROL Plane USER Plane

2G/3G LTE

Distributed collection Layer

Partitioning & Storage

Customer Data Sessions

SAS VA

SAS

Access to Hadoop Real Time Broker (RTB)

Processing engine

2G & 3G

Enriched CDRs

Distributed collection Layer

Primary storage

Encryption Layer

Enrichment Layer

IP Data stream

Voice/SMS stream

SAS Schema

RAW data Agg. data

KPIs calculation

Data Ingestion Layer

SAS Analytics positioning in the Mobile CEM Landscape

In memory

Analytics

HADOOP - Cloudera

Visualization

SAS Access to Hadoop Use Cases

6

1. Rollout Prioritization

2. LTE Devices Capability

3. Device Analytics

4. Location Analytics

Problem Definition – Rollout Prioritization 7

Traditionally the Rollout Activities are based on a number of inputs:

High Traffic demand (Voice and Data) in geographical areas

Coverage targets

Commercial priorities and hot spots

Strategic locations (airports, ports, etc)

Nowadays operators have to deal with new challenges, which makes the Rollout

Planning activities even more complex:

Flat Rates (Voice and Data)

New Technologies/Services

Smartphones penetration

Micro-spots

Budget restrictions

Value Based Rollout provides an alternative way to prioritize Network Rollout

based on two key elements:

Faster Return On Investment

Targeted Rollout based on Devices capabilities

Methodology - Revenue Distribution Rules 8

Calculate Value (€) per SITE based on :

o ARPU per Customer

o Distribution of Customer Traffic in the Network Cells

Customer ARPU & usage

ARPU (€) Customer

usage (MB)

Revenues

per MB

Customer A 10 € 200 0.05 €

Customer B 20 € 500 0.04 €

…

Customer X 12 € 75 0.16 €

Customer traffic distribution

Site 1 Site 2 … Site Y

Customer A 50% 20% 30%

Customer B 10% 10% 80%

…

Customer X 30% 40% 30%

Customer revenue distribution per siteSite 1 Site 2 … Site Y

Customer A 5 € 2 € 3 €

Customer B 2 € 2 € 16 €

…

Customer X 4 € 5 € 4 €

Revenues per

Site11 € 9 € 23 €

Traffic per site (MB)

Site 1 Site 2 … Site Y

Customer A 100 40 60

Customer B 50 50 400

…

Customer X 23 30 23

Traffic per

site MB173 120 483

Revenues per

MB0.06 € 0.07 € 0.05 €

Illustrative example

The ARPU of each individual customer is distributed amongst the sites

Key for the distribution “algorithm” is the traffic of each individual customer per site

As each customer pays a different price per Mbyte (e.g flatrate but different usage), each site has a different value per MByte

Comment

Regional Analytics - Overview 9

SAS Access to Hadoop Use Cases

10

1. Rollout Prioritization

2. LTE Devices Capability

3. Device Analytics

4. Location Analytics

Prioritize Rollout/Commercial actions based on Value & LTE Share 11

LTE Devices capability share per SITE

NO LTE Traffic

Prioritize LTE Sites Rollout based on existing LTE Devices Share and Value

SAS Access to Hadoop Use Cases

12

1. Rollout Prioritization

2. LTE Devices Capability

3. Device Analytics

4. Location Analytics

Devices analytics/monitoring (II) 13

Penetration of devices

Geo-map

Devices footprint monitoring

SAS Access to Hadoop Use Cases

14

1. Rollout Prioritization

2. LTE Devices Capability

3. Device Analytics

4. Location Analytics

Location analytics 15

Classify services/subscribers based on Mobility

Optimize network to support enhanced mobility patterns

Combine with ARPU to define QoS if necessary

Thank You !

16