Day 2 1425 Pietro Martone Track 5

7/28/2019 Day 2 1425 Pietro Martone Track 5

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Copyright © 2013 Accenture All rights reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture.

100% NetworkedNetwork Analytics for LTE profitability

Accenture





Copyright © 2013 Accenture All rights reserved. 4

Accenture Network Analytics

Networkcapacity,

planning anddeployment

Use accurate andgranular traffic

forecasts to helpimprove asset

utilization by up to5%.

Network serviceassuranceUse deeper insight andresponsiveness toservice outages,increasing serviceuptime by up to 10%.

Network control andoptimization

Analyze customer behavior to

potentially improve ROI by up to 15%.

With data spread across different networks it’s hard to see the whole

picture. This blur of information can be brought into focus with newgeneration of network analytics




Deployment

Network Planning and Optimization Closed Loop

Strategy

Marketing

Budgeting

Planning

Operation

Network Usage

Special Projects

Customer Service

Inventory

• Technology Selection• Infrastructure

Requirements• Deployment Strategies

Network

Provisioning

WorkforceManagement

Network

Inventory

Network

Configuration

ERP

Network Design addresses strategic and operational needs thereby

improving service quality and revenues




TeleCom Processes: Holistic view

Decision support model integrates commercial and technical information

Widgets

EntertainmentMRC

3 Month Avg. Bill $

Demographics

Zip Code

State

Region

Customer

Location

Credit Limit

Open to Buy

Credit Limit Hit

Late Payments

Credit

Tenure

Acct. Holder Age

Acct. Holder Sex

Lifestage Segment

HH Ownership

# of HH Residents

Max. Education

Income Level

Residency Tenure

Ethnicity

Voice

Data

Ownership

Video

Widgets

VAS

Bundles

Under Contract

Contract

RemainingMonths

STBOwnership

STBCapabilities

Devices

BHROwnership

Account

Acquisition / Churn

Voice

Product

Data

Video

Widgets

VAS

Ent. Features

Days SinceContact

Customer Support

Contacts LastWk.

Contacts YTD

ComplaintsLast Wk

Spec. Act. LastWk

ComplaintsYTD

Interaction

Last Bill Amount

Linear Plan

Pay-Per-View

VoD

Widgets

Value

EntertainmentNRC

OCC

Linear Viewership

UsageBehavior

PPV Viewership

VoD Viewership

Widget Usage

By ChannelGroup

by Genre, Day,Time

by Category,Genre

by Category,Genre

Type

Status

Classification

Devices

Dwelling Type

Customer Analytical Record (CAR *)

Network

Traffic XDR

Service Level

QoS

QoE calculation

Voice

NW counters

Network Analytics Extensions

…

…

…

…

…

2-3-4G Access

Core

Transport

Application Probes

NWtopology

User plane

Link usage

Facebook

(*) CAR is Accenture’s patented methodology filed under US Patent # US 7,047,251 B2

Devices

Capabilities

Data

Radioconfig

Youtube

Backup

routes

…

Signaling

Screensize

…

Whatsapp

Backhauling

Availability

Congestion

Data Dimensions




Network Analytics Presents a Better Approach

Network Analytics ApproachLegacy Approach

TrafficForecasting

NetworkDimensioning

Operational andCapital ExpenseManagement

NetworkUtilization Value

Return onInvestment

Optimization

• Singular Forecasting based on MoU /

Data volume (Erlang theory)• Threshold-based planning

• Independent service • Voice: Erlang/Peak based

• Data resources dimensioned on best

effort assumption

• Broad based expenditure estimates - Average load per cell- Average MOU- Manual effort

• Macro Two Dimensional Revenues - Per minute- Per byte

• Budget allocation based on available

capacity for congested cells

• Analyze Current Network usage fromBusiness Perspective

• Per cell forecasting statistical model

• Per cell dimensioning • Continuous dimensioning • Managing QoE targets for each IP

multimedia service

• Integrated analysis (voice, data, cost,

etc.)• QoE Centric: service, value and

budget estimation per cell

• Clustering and prioritizing capacity

and quality upgrades to improve ROI

• Detailed and Multi-Dimensional: Per

minute/ Event/ Byte/ Service / Per location/ Customer Segment/ etc.

• Multiapproach: Inducted Revenues,Connection Service Quality , OTTQuality Of Experience


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Traffic Forecasting: Network Usage – Business PoV

Business Perspective• Market segment

geographic distributionand drill down

• Service used bycustomer type

• Device presence in thenetwork (type, models,etc.)

• Device Vendors MarketShare

• Speed of moving

• …

Geographical ARPUanalysis

Device presence in the network



Video Browsing

Traffic Forecasting: Network Usage – Technical PoV

Technical impacts• Assess bandwidth user

demand per service.

• Identify busy hours

• Monitor network

performance status per service

• Identify trends, seasonalityand event impacts.

• Evaluate data traffic andsignaling needs per cell.

• Etc.

Network Performance Status

Network usage per service



Traffic Forecasting – Congestion Prediction

Advanced forecasting approach anticipates cell congestion and focuses

on clients’ quality of experience.

Sample cell congestion forecast

+9 month forecast

+6 month forecast

+ 3 month forecast

Congestion probability

Mbps



Continuous Dimensioning

Based on an accurate congestion, forecasting cells can be dimensioned

closer to cell traffic peak, thereby increasing network investmentsefficiency.

Inefficiency AreaCell CapacityOver Peak Dimensioning

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

0 5 10 15 20



Operational and Capital Expense Management

OpEx and Capexinvestment estimationis based on realpricelists applied atthe cell level.

Cell CA02 Sample Upgrade

Component Quantity

Baseband Unit 0

Radio Frequency Unit 1

Power Unit 1

Cost 2.356,54 €

Component Quantity

Baseband Unit 1

Radio Frequency Unit 4

Power Unit 2

Cost 12.729,76 €

Cell AZK1 Sample UpgradeNetwork expansion

requirements determined atthe lowest grain (e.g., cell).This feeds into the bill of materials required tomanage anticipatedforecasted traffic for eachcell.



Network Usage Service Based Value

The value of traffic for cell upgrades can now be determined according

the TelCo strategy balancing tree dimensions

Upgrade of a cell attracts additional traffic

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

0 5 10 15 20

Inducted Traffic

InductedRevenues

ConnectionServiceQuality

OTTQuality of

Experience

Inducted traffic value dimension



Network Usage Service Based Value

Specific location capacity expansion value should be based on

Inducted

Revenues

Increment customer ARPU

and network usage

• ToP Spenders location• Premium Services (ex

video, music,bandwidth boost)location

• Regions where islocated under usedequipment

• …

Connection Service

Quality

Contain costs of customer

operations

• Lower Troughtputlocations

• Dropped Sessionlocations

• In house networkcoverage location

• Locations whereclaims came from

• …

OTT Quality Of

Experience

Increase appeal in the

market and loyalty

• Location with lowbandwidth for popular services: videostreaming, social

networking, etc.• Areas where popular

website register longest pagedownload time

• …



Return on Investment Optimization

0

200

400

600

800

1000

1200

0% 20% 40% 60% 80% 100%

U p g r a d e C o s

t

Congestion

Cell G100K €

Cell C100K €

Cell B30K €

Cell I10K €

Cell F10K €

Cell L25K €

Cell A50K €

Cell E35K €

Cell D25K €

Cell H10K €

Potential cell revenue per year

Network Analyticscan identify which

cell upgradesgenerate the bestROI, while stayingin line with budgetconstraints




Summary

• There is a critical need to adopt an analytics-

based approach to optimize network Capexand OPEX.• Granularity of analysis and speed of

intelligence across network optimization arecritical to enhance end-customer experienceand value.

• Telecos need a flexible and scalable networkanalytics framework to handle data of ever-increasing volume, velocity and variety.

• Accenture has technical and domainknowledge to help operationalize networkanalytics insights:

– the comprehensive understanding of data andnetwork architectures

– KPIs to tell you where to extract meaningful data

– and tools and methodologies to analyze large

quantities of data

– all backed by 20,000 analytics skilled

professionals worldwide

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Day 2 1425 Pietro Martone Track 5