Slide Deck represents simplified Summary of Proof of Concept to take Sales Operations data from Oracle, crunch the numbers using Hadoop/Hive stack, and present specific Metrics using Tableau visualization.

1. From Sales Ops to SaaS Metrics
(A Simplified Business Case)
- Donald F, Nagaraj P and Team
2015

2. SaaS Metrics Defined
MRR The Monthly Recurring Revenue at the end of each month. Computed by taking the MRR
from the previous month and adding Net New MRR.
ARR Annualized Run Rate = MRR x 12ARR is annual run-rate of recurring revenue from the
current installed base.
ACV Annual Contract Value of a subscription agreement. This is very close to ARR above.
Churned MRR/ACV The lost MRR from churning customers in the current month.
Expansion MRR/ACV The increase in MRR from expansion in your installed base in the current month.
Net New MRR/ACV Net New MRR = New MRR + Expansion MRR – Churned MRR
This is the sum of the three different components that will change MRR during each month.
Billings Billings is the amount that you have invoiced that is due for payment shortly.
Revenue Revenue is amount of money that can be recognized according to accounting policy. Even if it
is paid for upfront, usually subscription revenue can only be recognized ratably over time as
the service is delivered. If more money has been paid than can be recognized, the difference
goes into a balance sheet item called Deferred Revenue.
Avg Contract Length Assuming a mix of different contract lengths, this gives you the average duration in months
or years.
Months Up Front Average of months (or years) of payment received in-advance with new bookings. Getting
paid in advance has a big positive impact on cash flow. This metric has been used as a way to
incent sales people to get more paid up front when a new customer is signed.
ARPA – Average monthly
recurring Revenue per
Account
This number is tells you the average monthly revenue per customer. It is useful to look at this
for just the new customers booked in the month. Plot a trend line to show you the average
price point that your new customers have chosen.
Current Scope Next Phase Out of Scope

3. Reporting Matrix
Current Scope Next Phase Out of Scope

5. Presentation Mockups (MRR)

6. Presentation Mockups (ARR)

7. Presentation Mockups (Activity)

8. Architectural Framework

9. Business Assumptions/ Limitations
1 All Amounts to be computed/displayed in USD only
2 Service Duration attribute is maintained at the individual SKU level
3 Renewal Contract does not have the Original Contract Linkage.
4 Service Durations are for whole months only
5
Revenue Waterfall Report is the mutually agreed data source. Additional Metrics
may be possible after extending ETL to other data sources like Bookings, Billings etc.
6
Static GL Account Mapping for Term License and Data Subscription Revenue Groups
is accurate enough to slice the “SaaS” component of the business.
7
Parent-Child SKU relationship within a Bundling arrangement is not currently
available, thereby limiting the Product-level reporting
8
SaaS Metrics are non-GAAP reports, and cannot be reconciled 1:1 with GAAP
Reports

10. POC Conclusions
POC Accomplishments
(actual Q2-2015 Waterfall)
Gap from POC to Production Post-Production
Capability to source data from ERP
Revenue Data (revStream) into
Hadoop AWS stack
Increase the columns made available
for reporting (Ship To Customer,
Product, as present on the source) to
maximize Self-Service capabilities
Perform MRR calculation based on
Day Unit (use 1/365 Day Unit instead
of 1/12 Month Unit)
Self-Service capability in Visualization
to create custom reports
Fine-tune SaaS data selection rule
to exclude Purchase Accounting
Entries
Pull in additional required data
sources (SFDC, Oracle) to get
Contracts + Renewals Data, in order
to compute Churn, Renewals Metrics
Capability to dynamically compute
and display SaaS Metrics
(ARR, MRR)
Fine-tune Product-Account mapping
to exclude non-SaaS transactions
(example GFY)
Pull in additional required data
sources (Excel, Oracle) to get SaaS
Customer Acquisition Cost, etc to
enable perform Break-Even Analysis
Report-level and Role-level security
to segregate data sets based on
business requirement
Provide additional AS-OF-DATE user
parameter, to allow for dynamic
selection of data set
Additional Reports and Metrics:
Monthly Activity, Top 10 Customers,
Customer Lifetime Value, ETC
Acceptable overall Query
Performance to retrieve data
Change the data source type from
File to MV, to eliminate staging
storage area and manual step
Revisit process for Maintenance-to-
Term Conversions, for more accuracy
Publish/Excel Export/Distribution
capabilities
Re-engineer operational process for
Prepayments and Adjustments
Data Reconciliation (upto 98%
accuracy) for Q2-2015