Bringing Unique Network Insights Straight to the Executive Desktop

Marc Potteiger, Sprint LTD

Sam Miller, Agilent Technologies

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Bringing Unique Network Insights Straight to the Executive Desktop

Agenda

•Some Typical Approaches to Revenue Assurance

•New Services, M ore Data & The “Irrelevance Gap”

•Building a Revenue Operations Center around Network Centric Data

•Some Real-Life Examples

•Concluding Thoughts

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Some Typical Approaches to Revenue AssuranceThe Classic ‘Leaky Pipe’ M odel

Factors, SS7 records and CABS Billing

mods

Access/Interconnect Billing

Subscriber Fraud

“Losses due to revenue leakages amount to 3 to 8% of total revenues, and sometimes reach as high as 15%” *

*Cap Gemini, 2002

Solution A

Solution B

Solution C

Solution D

How do operators detect it at present?

Basic Error Checks,

DUFAnalysis

SS7/AMA Correlation

Fraud detection engines

Trunk provisioning/ Switch Translations

Active Call Tests, Switch

Tools

Mediation/Rating/Billing

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Impact of New ServicesThe Pipe is Getting Longer & M ore Complex

Service providers are looking to sell content, commerce and communications as an augmented product

• Irrespective of wireless/wireline market –more services are becoming available

• New technologies like IP and 2.5G/3G convergence are powering this

• 3rd party content like ringtones and games -Now you need to worry about Billing On Behalf of Others (BOBO)

• Each new service introduces a new type of leak, and a new type of misuse, a new type of ‘leaky pipe’

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Revenue Assurance Data Explosion

IP Applications, VoIP,Web, Multimedia RA (IPDR apps)

Wireless mobility with revenue leaks caused by SMS abuse/Billing (TDR apps)

ISUP Telephony with revenue leaks caused by Fraud, Mediation and Billing and Routing (CDR apps)

Roaming revenue capture : (Record Exchange)

Time

Future Applications

New

services

Data required

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React slowly = lost revenueThe time between a RA issue arising and deploying a revenue assurance solution to locate/solve is lost revenue:

• You have to realize that there could be a hole

• W ait for a solution to be developed

• And patch it

But what if the hole is significant, but hard to see?

• Classic business decision making problem: too much data, not enough information

• Drowning in a sea of data –not able to find the RA issues

• Bridging the irrelevance gap –drilling down to the nuggets

Info I have Info I have ((xDRsxDRs))

Irrelevance gapIrrelevance gap

RA Relevant InsightsRA Relevant Insights

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Physical NetworkCircuit Switched, W ireless and IP

Signaling Layer (SS7, SIP etc)“The Nervous System of the Network”

xDRs

VoIP-SDRsData W arehouse

•Switching Connectivity•M obility•Advanced Services •Fraud

•Interconnection•M essaging•Location•Roaming

Signaling Records

•Comprehensive•Accurate•Efficient

AMA Recs

Cell CDRs

IPDRs

GPRS TDRs

The Intelligent Source for Network Centric Data

Data M arts

RA Dashboards

Wireless TDRs

SS7 CDRs

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Some Real-Life Examples from

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Detection of Simplistic CLEC Arbitrage

Sprint’s local network noticed that terminating volumes were rapidly increasing from a select group of Competitive Local Exchange Carriers (CLECS)

Agilent’s’acceSS7 system was able to see multi-jurisdictional traffic on a local interconnection trunk group.

Interconnection contract restricted the traffic to be terminatedon these trunks to local and non-equal access intralata traffic.

— Test calls verified the Agilent data— Sprint has investigated four CLECs and have found

similar patterns of arbitrage. These companies were billed in excess of $7 Million US in lost access revenues.

— Sprint is currently investigating other CLECs.

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Auditing for AM A

Perform AM A audits utilizing SS7 data for Switched Access revenue

• Randomly select “newly” installed trunk groups to validate AM A recording.

• In event of no AM A, are able to take SS7 data and back bill carriers.

• Revenue recovery for future opportunity and back billing are significant considering the small base of trunk groups included in this analysis..

Analysis M ethod (comparing Old to New)

• Old M ethod ---Very manual process utilizing switch trunk usage data.

• New M ethod ---Agilent BI tool allows means to automate extraction of new trunk groups and summarize trunk groups that are billable, then compare it to switch AM A files.

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Customer Caller ID Complaints

Investigating Complex Call Scenarios

• POTS North Carolina customer complained that their number was appearing on caller ID all over the country and they weren’t making these calls. Customer was ready to cancel service with Sprint!

• SS7 correlated call records provided discovery information to aid in identifying the cause leading to a quick resolution

Analysis M ethod (comparing Old to New)

• Old M ethod ---Switch engineers could not locate source of problem through traditional translations tools. No exposure to why and where this number was populating inappropriately.

• New M ethod ---Extracted SS7 correlated call records from Agilent BI. Identified problem was not end user switch, but rather a competitor’s switch as indicated by JIP and point code information.

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One W ay Traffic Trunk Groups

Trunk groups that should only be carrying one-way traffic are allowing 2-way bi-directional and no AM A creation

• SS7 summary records targeted to report trunk groups that should only have one-way traffic.

• Significant revenue opportunity determined for the limited number of trunk groups identified.

Analysis M ethod (comparing Old to New)

• Old M ethod ---Limited exposure to summarized data utilizing traditional switch trunk usage reports.

• New M ethod ---Agilent reports provide summary data at a trunk group level with traffic direction indicators.

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Validating Reciprocal Compensation Expenses

Lack AM A recordings to validate reciprocal compensation expense

• Summary Trunk group reports aid the Finance Access Verification organization in reviewing and comparing billing expense from CLEC’s.

Analysis M ethod (comparing Old to New)

• Old M ethod ---No data available to validate expense

• New M ethod ---Agilent reports provide listing of M OU’s by carrier

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Concluding ThoughtsConcluding Thoughts

New technologies enable New technologies enable integrated content, integrated content, commerce and commerce and communications. communications.

Revenue pipe getting Revenue pipe getting longer and more complexlonger and more complex

Providing a dashboard Providing a dashboard on top of the on top of the

warehouse allows RA, warehouse allows RA, Billing, Network Billing, Network

Operations & M arketing Operations & M arketing to share benefits to share benefits

Signaling in circuitSignaling in circuit& packet networks& packet networks

can form the the basis of can form the the basis of a network centric a network centric DatawarehouseDatawarehouse