1. Telecom Revenue Assurance Reporting
Training
Ikwe Gideon
Revenue Assurance Consultant
gideon.ikwe@datahouseconsulting.com
This document contains information confidential and proprietary to Datahouse. No part of it may
be used, circulated, quoted or reproduced with out Datahouse’s consent.
2. Training agenda
1 Overview of the Revenue Assurance(RA) Incident Reporting
2 Overview of RA Monthly Management Report
3 Quantification of Revenue Leakages
29 July 2015 (c) 2014 Datahouse Consulting
3. Overview of the Revenue Assurance(RA) Incident
Reporting
39 July 2015 (c) 2014 Datahouse Consulting
Sources of data used or evidence of finding
Findings/observation
Recommendations and conclusion
Background of the investigation
Revenue and Business impact
4. 49 July 2015 (c) 2014 Datahouse Consulting
Sources of data used or evidence
of finding
Findings/observation
Recommendations and conclusion
Background of the investigation
Revenue and Business impact
Content
• Brief introduction of your investigation
• Why you are conducting it
• Any reference to prior investigation/assignment e.g
management request etc
Example
• As part of our weekly/monthly RA review of prepaid
traffic, we noticed that some GRPS traffics are not
being charged. And these traffic does not belong to
bundled GRPS service, there are normal per usage
billing traffic type. This prompt our further investigation
to know why this is happening
5. 59 July 2015 (c) 2014 Datahouse Consulting
Sources of data used or evidence
of finding
Findings/observation
Recommendations and conclusion
Background of the investigation
Revenue and Business impact
Content
• All the various data uses and their sources
• Other non data sources as evidence of findings
Example
• OCS,
• Billing and rating
• Invoices
• GPRS
• Confirmation from other department
• etc
6. 69 July 2015 (c) 2014 Datahouse Consulting
Sources of data used or evidence
of finding
Findings/observation
Recommendations and conclusion
Background of the investigation
Revenue and Business impact
Content
• What you observed
• All reasonable deduction noticed
Example
• Missing CDR’s
• Under and over Billing
• Missing data
• Misapplication of business rules
• etc
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Sources of data used or evidence
of finding
Findings/observation
Recommendations and conclusion
Background of the investigation
Revenue and Business impact
Content
• The Revenue loss, per day, month and year
• The potential revenue loss, if the risk exist but not
precipitate yet
• The effect of this observation on customers, short and
long term
• The effect on the image of the company long and short
term
Example
• Adverse effect on customer perception about MCI
• Effect on customer perception about billing system and
professionalism
• The total revenue loss compare to total revenue from
that revenue stream
• Customer churning the network
• etc
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Sources of data used or evidence
of finding
Findings/observation
Recommendations and conclusion
Background of the investigation
Revenue and Business impact
Content
• Possible action to be taken to correct effect
• Follow up action to ensure effect is ratify
Example
• The under billing should be fixed immediately because
we are losing money daily.
• The new data source should be incorporated in the
billing system immediately.
• Marketing should recall the product and improve on the
features because we are losing money
• Customer should be informed at a massive level
campaign on the feature of the service to stimulated
demand.
• etc
9. Training agenda
1 Overview of the Revenue Assurance(RA) Incident Reporting
2 Overview of RA Monthly Management Report
3 Quantification of Revenue Leakages
99 July 2015 (c) 2014 Datahouse Consulting
10. 109 July 2015 (c) 2014 Datahouse Consulting
Quantification of the impact on revenues due to issues during the month
KPIs for the reporting month and previous two months along with the year to date
status
Other ad-hoc details and analysis requested by the Group on a periodic basis
A listing of major issues faced during the month
Details of Major Revenue Stream including deferred revenues as per IN system
Overview of RA Monthly Report
11. 119 July 2015 (c) 2014 Datahouse Consulting
Quantification of the impact on revenues
due to issues during the month
KPIs for the reporting month and previous
two months along with the year to date
status
Other ad-hoc details and analysis requested
by the Group on a periodic basis
A listing of major issues faced during the
month
Details of Major Revenue Stream including
deferred revenues as per IN system
• Prepaid (IN, SDP, Charging, Tariff Table, Service
Class, Voucher Errors, Activation)
• Post paid (CDR Rating, Tariff Table, Package Plan,
Activations, Disconnections)
• Switch (MSC & HLR Service Provisioning,
Subscriber mismatch between switch)
• VAS (SMS, Roaming, MVoucher, jiring, WLL
Network, GPRS, SMS Info,)
Risk
Issue
Revenue
Leakage
Risk
Description
Date
ident
ified
Priority
Level
Estimated
Revenue
Loss/saving
Action
Taken
Current
Status
12. 129 July 2015 (c) 2014 Datahouse Consulting
Quantification of the impact on revenues
due to issues during the month
KPIs for the reporting month and previous
two months along with the year to date
status
Other ad-hoc details and analysis requested
by the Group on a periodic basis
A listing of major issues faced during the
month
Details of Major Revenue Stream including
deferred revenues as per IN system
Finding for the Month of Prepaid Post-paid Network VAS
Interconnec
t/Roaming
Revenue Losses (1)
Fraud Losses (2)
Reporting Errors (3)
Revenue Foregone (4)
Revenue Exposure (5)
Total Risk Exposure
(1+2+3+4+5)
Monthly Gross Revenue
% of identified Total risk
exposure to gross revenue
Revenue Savings from Loss
Prevention
% of total savings to Total Risk
exposure
13. 139 July 2015 (c) 2014 Datahouse Consulting
Quantification of the impact on revenues
due to issues during the month
KPIs for the reporting month and previous
two months along with the year to date
status
Other ad-hoc details and analysis requested
by the Group on a periodic basis
A listing of major issues faced during the
month
Details of Major Revenue Stream including
deferred revenues as per IN system
No. KPI Formula Oct,2012 Nov,2012 YTD
1
Provisioning
Failures –
Prepaid
(Total unsuccessful prepaid
provisioning )/Total prepaid subscriber
sent for provisioning via the platform)
2% 1% 3%
2
Provisioning
Failures –
Postpaid
(Total unsuccessful postpaid
Provisioning)/ Total postpaid subscriber
sent for provisioning via the platform)
9% 10% 12%
3
HLR vs. Prepaid
billing system
Prepaid MSISDNs present only in HLR
and not in prepaid billing
system(IN))/Total Prepaid MSISDNs
present in HLR
0.1% 0.2% 0.4%
4
HLR vs.
Postpaid billing
system
(MSISDNs present only in HLR and not
in postpaid billing system)/Total
Postpaid MSISDNs present in HLR
0.02% 0.03% 0.05%
14. 149 July 2015 (c) 2014 Datahouse Consulting
Quantification of the impact on revenues
due to issues during the month
KPIs for the reporting month and previous
two months along with the year to date
status
Other ad-hoc details and analysis requested
by management on a periodic basis
A listing of major issues faced during the
month
Details of Major Revenue Stream including
deferred revenues as per IN system
Retail
Revenue
Reporting
Voice(rials) SMS(rials) GPRS/Data(rials) MMS(rials) VAS(rials) Monthly
Recurring
charges
Credit
Transfer
Post-paid
Prepaid
Total(rials)
Wholesale Revenue/Cost Reporting Voice(rials) SMS(rials) GPRS/Data(rials) MMS(rials) VAS(rials) Total(rials)
Roaming TAPIN
Roaming TAPOUT
Mark-up Revenue(TAPIN)
Interconnect Outgoing all Partners
Interconnect Incoming all Partners
National roaming(kish)
WLL interconnect cost all Partners
TIC international cost
VAS
Total(rials)
Prepaid Post-paid
Revenue and Volume traffic per destination Voice(rials)/Minutes SMS(rials)/count Voice(rials)/Minutes SMS(rials)/Count
On-net
Off-net
International
Total
Freebies Reporting Voice(Minutes) SMS(count) GPRS/Data(MB) MMS(MB) VAS(count)-SMS
Tot
al
Post-paid
Prepaid
Total
Precentage of Freebies value to Total revenue
15. Training agenda
1 Overview of the Revenue Assurance(RA) Incident Reporting
2 Overview of RA Monthly Management Report
3 Quantification of Revenue Leakages
159 July 2015 (c) 2014 Datahouse Consulting
16. 169 July 2015 (c) 2014 Datahouse Consulting
Revenue Exposure
Revenue Forgone
Reporting Error
Revenue Loss
Revenue Savings and Recovered(Actual and Exposure)
Quantification of Revenue Leakages-Definition and
methods
17. 179 July 2015 (c) 2014 Datahouse Consulting
Revenue Exposure
Revenue Forgone
Reporting Error
Revenue Loss
Revenue Savings and Recovered(Actual and
Exposure)
• Definition
Actual Revenue Loss resulting from the non-
collection (or incomplete/inaccurate
computation) of revenues for services
provided to customers and/or partners i.e.
service was provided but revenues not
collected or inaccurately charged to
customer's account. E.g. incorrect rating of
calls, free calls due to configuration errors,
subscription fraud etc.
• Method of Calculation
Will be determined as follows –
count/volume/duration of unbilled ‘free’
network event (or differential of incorrectly
billed) x blended tariff plan for the affected
network event.
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Revenue Exposure
Revenue Forgone
Reporting Error
Revenue Loss
Revenue Savings and Recovered(Actual and
Exposure)
• Definition
Potential Exposures arising from process or
systems gaps which could easily be converted
to revenue losses either by internal omission
or commission errors or deliberate exploitation
of the process/system gaps by fraudulent
parties. E.g. weak RCV activation process;
weak access control etc.
• Method of Calculation
Will be determined as follows – total potential
loss exposure as at a point in time i.e.
money/revenues at risk as a result of the
exposure..
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Revenue Exposure
Revenue Forgone
Reporting Error
Revenue Loss
Revenue Savings and Recovered(Actual and
Exposure)
• Definition
This is lost revenue generation opportunity as
a result of service unavailability and typically
results in loss of market share for the duration
of the incident. E.g. core network node
downtime resulting in customers' inability to
call for the duration of downtime
• Method of Calculation
Will be calculated as a projection based on
day-of-week average for last 3 weeks from
day of incident/service failure. Example: If on
a Wednesday there is a drop in normal traffic
trends for a particular node due to some
challenges on the node forgone revenue will
be computed as the difference between
average revenue on that node for immediate
past 3 Wednesdays less revenue reported for
Wednesday with the incident.
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Revenue Exposure
Revenue Forgone
Reporting Error
Revenue Loss
Revenue Savings –Actual
• Definition
This represents revenue saved i.e. losses
adverted as a result of: Revenue/fraud
leakage situation corrected i.e. revenues that
would have been lost if the particular leakage
was not identified and plugged. Prevention of
revenue foregone e.g. RA activities resulting
in prevention or reduction network down time.
A positive addition to revenues gained as a
direct result of an RA intervention
(determined as a positive deviation from
normal revenue or cost trend) e.g.
supplementary invoices/bills issued to
partners/customers as a result of traffic
hitherto unbilled, error in call routing resulting
in free calls, activation of wrong rates on the
charging platform etc.
• Method of Calculation(Cont’)
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Revenue Exposure
Revenue Forgone
Reporting Error
Revenue Loss
Revenue Savings –Actual
• Method of Calculation
When a revenue leakage has been effectively
plugged, the revenue savings from such mitigations
shall be recognized using either of the following
approaches below depending on feasibility:
Approach A:
• Compute actual revenue loss as determined in (A) for
past 6 months or less if duration of leakage < 6
months
• Based on above, compute average monthly loss
• Project average monthly loss for next 12 months to
determine what would have been lost if leakage was
not plugged.
Approach B:
• Determine revenue trend and projections for affected
revenue stream before the leakage was plugged and
compare against new trend and projections
• After the fix over a period of one month. The
difference is then projected for 6 months and reported
as savings gained from fixing the leakage.
• Revenue saving projections will be done by RA
Manager while each operating unit will report only
quantifiable revenue savings (i.e. no projections)
where applicable.
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Revenue Exposure
Revenue Forgone
Revenue Recovered/Reporting Error
Revenue Loss
Revenue Savings –Exposure
• Definition
This represents revenue exposures prevented
as a result of RA mitigation efforts to plug
potential leakage situation i.e. revenues that
could have been lost if the particular exposure
was not identified and plugged
• Method of Calculation
When a revenue exposure has been
effectively plugged, the revenue exposure
savings from such mitigations efforts shall be
recognized as – Total Revenue Exposure
(revenues at risk) divided by X. Where X is
number of days between date exposures was
identified and date exposure was closed.
23. 239 July 2015 (c) 2014 Datahouse Consulting
Revenue Exposure
Revenue Forgone
Revenue Recovered/Reporting Error
Revenue Loss
Revenue Savings –Exposure
• Definition
Revenue Recovered
This is revenue recouped from an actual revenue
loss situation e.g. supplementary invoicing of
partners following traffic reconciliations, arrears
billing for postpaid and increase in revenues due
to reduction in revenues foregone.
Reporting Errors
This relates to under/over statement of revenues
due to error of omission /commission identified by
RA e.g. understatement of minutes of use due to
delayed / unprocessed / damaged TT-files
impacting interconnect traffic.
• Method of Calculation
Revenue Recovered:
Actual amount initial lost and not accounted for in
the daily revenue report but subsequently collected
and captured in the books of accounts.
Reporting Error:
Actual value by with the affected revenue stream
was impacted.
24. 249 July 2015 (c) 2014 Datahouse Consulting
Thank you!