Smart Margin Analytics: Why Bolting on a Margin Assurance Capability to an Existing Revenue Assurance System can Deliver Big Savings – a presentation by Efrat Nissimov, cVidya’s Director of Product Management at the “Big Data and Analytics for Telecom & Mobile Carriers” event in Atlanta.

1. OPERATIONAL
RISK MANAGEMENT
& COMPLIANCE
© 2012 – PROPRIETARY AND CONFIDENTIAL INFORMATION OF CVIDYA
Beyond Prevention:
Revenue Assurance
Margin Analysis

2. 2
Agenda
 Market Trends
 Why Margin Analysis
 Margin Analysis on top
of Revenue Assurance

3. 3
Market Trends

4. 4
Trends in the Market – New Challenges?
 New technologies
 New pricing models
 New services
 Additional players in the revenue chain
 Data traffic explosion
Market Trends - New Challenges

5. 5
Global Mobile Data Traffic Drivers
More Mobile Connections Faster Mobile Speeds
More Mobile Users More Mobile Video

6. 6
Data Traffic Explosion

7. 7
The Hunger Games
7
 New technologies (LTE)
 New business models
 Policy-based charging
 Data sharing family plans
Results of the ever-hungry bandwidth consumer:

8. 8
Variety of Pricing Models
UNLIMITED DATA DATA THROTTLING
• 3GB of usage per month for
3G unlimited customers
• 5GB for 4G LTE customers
and then throttling
• 2GB of data per month and
then throttling only on
congested cells
DEVICE PACKAGES

9. 9
Why Margin Analysis?

10. 10
The Need …
Money…
 Operators are under increasing market and competitive pressure
 While OPEX and CAPEX costs must be lowered, shareholder demands for increased values must
be met
Understand the Revenues
Identify the Costs
Optimize the Margins

11. 11
Why is Margin Analysis So Important Now?
 Multiple operators have been licensed to compete, so tweaking services to
achieve maximum profitability has never been more important
 Over-the-top players are not only eating scarce bandwidth, they are offering
profit-killing alternatives to voice and SMS
 Revenue per subscriber is decreasing, and operators needs to remain
profitable, protect their business and exploit opportunities
 Service-bundling has exploded, and triplequad-play operators need to gain a
consolidated view of margins
 Interconnect and content partners have expanded, underscoring the need to
monitor these partners from a service profitability aspect

12. 12
Traditional Approaches for Margin Analysis
 For years people have been performing margin
analysis using Excel spreadsheets
 In the early 90s, margin analysis was also a key
benefit of owning a data warehouse
 Why are these approaches less than optimal?
 Time consuming
 Results are not granular enough
 Excel is suited to producing periodic reports
(monthlyquarterly). Once product categories are
mixed and segmentation is required, the Excel
model becomes clumsy

13. 13
A long term goal of many RA
organizations is to understand
profitability for different segmentations
Determine revenue generated and cost ,
effectively analyzing the margin per
segmentation
The Goal

14. 14
Margin Assurance
 Conceptually: Margin = Revenue - Costs
 Verify that each segmentation, or group of segmentations, has a
positive margin
 Costs include:
– Direct costs, for example, payment to a partner per minute for calls
– Indirect costs, for example, network costs, customer acquisition costs
(indirect costs are more difficult to define)
By using direct costs only, it is still possible to set upper limits on the margins

15. 15
Margin Challenges  Revenue challenges
 Multiple rate plans and bundle complexity
 Consumption- or service-based charging
 Quality of service-based ratings
 Cost challenges
 Partnership arrangements and commissions
 Interconnect partnerships, where wholesale
rates are higher than retail rates
 Content supplier relationship where content
received and paid for is not delivered or
billed

16. 16
Margin Analysis on-top of a
Revenue Assurance Solution

17. 17
Easy to Implement — Based on RA Data
 Margin analysis and Revenue Assurance are
complimentary activities that share similar techniques
and information
 RA paves the way for margin analysis since most of the
source data has already been collected, normalized, and
augmented with additional data (e.g., customers’
demographic, regional, and network information)
 Since platform is based on xDR-level (not just aggregate
numbers), operators can view various dimensions in
highly granular segmentations

18. 18
What Should Be Analyzed?
 Content providers
 International carriers
 Inter-carrier traffic
 MVNOs
Content
Provider
A
Soccer Video
Basketball Results
Golf Updates
Sports Package
Settlement
Settlement
Content
Provider
B
Content
Provider
C
National Geographic
The Wild Life
Discovery
Nature Package
The Runner
Poker
Packman
Games
CSP
Austria 0.25$
Belgium 0.20$
Hungary 0.30$
Zone A (0.25$)
Settlement
Settlement
CSP
Germany 0.55$
Italy 0.45$
France 0.50$
Zone B (0.50$)
UK 0.75$
Spain 0.70$
Romania 0.80$
Zone C (0.75$)
International
A
International
B
National
Carrier
A
Transit Traffic
Terminating Traffic
Orginating Traffic
Carrier A
Settlement
Settlement
National
Carrier
B
National
Carrier
C
CSP
Transit Traffic
Terminating Traffic
Orginating Traffic
Carrier B
Transit Traffic
Terminating Traffic
Orginating Traffic
Carrier C
CSP
MVNO
A
MVNO
B
MVNO
C
Transit Traffic
Orginating Traffic
SMS
Data
Terminating
A
Settlement
Settlement
Transit Traffic
Orginating Traffic
SMS
Data
Terminating
B
Transit Traffic
Orginating Traffic
SMS
Data
Terminating
C

19. 19
Most Important Uses for Margin Analysis
 Service hierarchies
 Margins on hierarchies of services and sub- services
 Pricing plan analysis
 Analyze whether a pricing plan has a high or a
low margin
 Customer usage patterns for a particular plan
 Market segmentation
 Customer profitability in great detail - margins
for subscribers per region, business customers in
a particular industry, etc.

20. 20
Most Important Uses for Margin Analysis
 LTE service monitoring – QoS-based pricing, bandwidth consumption, services
enhanced during an actual session, etc.
 Analyzing service margins and profitability presents a challenge
 Complex plans (e.g. Friends and Family mobile data plans)
 Requires constant vigilance to ensure profitability, since there are many
variables that could make costs spike
 Experimentation, testing and “what if” scenarios
 Uptake of a particular service is getting tougher to forecast - being able to
assess the margins of a service in advance or soon after launch is critical
for making adjustments to the product

21. 21
Financial Dashboards
 Centralized financial dashboard, configurable to
organizational business topology
 Financial impact reporting, tracking and decision
support for C-level, CFO, Risk Management, RA experts,
Management, and others
 Drill down for impact on relevant business entities
(revenue streams, services, platforms, customer types)
 Hierarchical finance trend analysis and deviation
detection
 Forecasting and “what if” scenarios for selected
entities based on common forecasting models

22. 22
Margin Analysis Dashboard Example

23. 23
Margin Analysis – The Full Picture
Margins
Customer
Segment
Service
Subscriber
Invoices
Partner
Settlements
Exact revenue &
costs
Revenue Assurance
Adjusting parameters
– Impact margins?
Destination
Rates
Plan Bundle
Best approach to
maximize margin
Automatic
Recommendations
Service Type
Customer
Segment
You Need
to Know
Service
Type
Region
Margin Analysis
Where are you
underperforming?
Service in
Bundle
Pricing
Plan
“What if” Analysis
Why you are
underperforming?

24. THANK YOU!
www.cvidya.com