White Paper SAP Co-Innovation Lab

REVENUE AND SPEND INSIGHTS: ANALYZING

GROSS-TO-NET PROFITABILITY USING SAP® HANA

A CO-INNOVATION STORY WITH VISTEX AND IBM

Editors

Varma Datla, Vistex

Matthew Hays, Vistex

Catherine Moran, SAP

Kevin Liu, SAP

March 2012

Version 1.0

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 2

Acknowledgements

This document is the work of a virtual project team at SAP Co-innovation Lab, whose members have

included:

Christopher Y Chung (IBM), David Cruickshank (SAP), Varma Datla (Vistex), Matthew Hays (Vistex),

Kevin Liu (SAP), Magnus Meier (SAP), Siva Gopal Modadugula (SAP), Catherine Moran (SAP), Rebecca

Newell (SAP), Hans-Joachim Odlozinski (SAP), Juergen Schmerder (SAP), Sanjay Shah (Vistex), Goran

Stoiljkovski (SAP), Wilson Ramos (SAP), Tag Robertson (IBM), and many colleagues from IBM, SAP, and

Vistex who helped with the project

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 3

Content 1 Executive Summary ....................................................................................................................................... 4

2 Challenges of Traditional Approaches to Analytics .................................................................................. 4 2.1 Infrastructure and Technological Constraints ...................................................................................................4 2.2 Increasing Complexity of the Gross-to-Net Equation .......................................................................................5 2.3 Increasing Demand for Insights ........................................................................................................................5

3 Revolutionary Solution for Today’s Business Analytics ........................................................................... 5 3.1 Why in-memory is relevant for Analytics ...........................................................................................................6 3.2 Revenue and Spend Insights ............................................................................................................................6

4 Co-innovate at SAP Co-Innovation Lab ....................................................................................................... 7 4.1 Key components of the COIL test landscape ...................................................................................................7 4.2 Architecture of the COIL test landscape ...........................................................................................................7 4.3 Hardware ...........................................................................................................................................................8

5 Reporting Example ........................................................................................................................................ 9 5.1 Scenario ............................................................................................................................................................9 5.2 Requirements ....................................................................................................................................................9 5.3 Outcomes ....................................................................................................................................................... 10

6 Conclusion.................................................................................................................................................... 14

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 4

1 Executive Summary

SAP Incentive Administration and SAP Paybacks and Chargebacks by Vistex are applications that extend

SAP® ERP and SAP CRM software functionality. These applications provide companies with an embedded,

fully-integrated solution for handling discount pricing, marketing fund claims, sales commissions & broker

fees, in- & outbound royalty payments, and volume- & growth-based sales or purchasing rebates.

With visibility into costs, pricing and incentives, SAP Incentive Administration and SAP Paybacks and

Chargebacks can analyze the gross-to-net profitability of sales in complex channels involving any number of

intermediary channel partners. The solutions define the eligible products, channels, customers, pricing and

incentives in each sales agreement. In many cases, multiple agreements may be involved in selling a product

to the end-customer since there is typically an agreement between each intermediary partner in the supply

chain.

These applications are able to consolidate a view of the multiple agreements, incentives and transactions,

providing insight into revenue and spend. Operationally, the system needs to process the large influx of daily

transactions, and analytical reporting consumes a significant portion of system resources.

SAP® HANA™ technology takes these solutions to the next level by enabling real-time insight into revenue

and spend. First, the solution lowers data demands on the operational database used for transaction

processing. Second, the solution virtually eliminates the data latency that is inherent in replicated data marts

using traditional database technologies. Third, the solution accelerates analytical processing to provide

insight on larger data sets (including Big Data) at faster speeds than traditional analytical tools.

SAP Co-innovation Lab (COIL) global network is designed for driving open innovation projects and

initiatives to extend SAP’s solution coverage and enhance our solution infrastructure efficiency with partners.

Vistex partnered with SAP and IBM in the SAP Co-Innovation Lab to develop a solution to provide real-time

profitability analytics while reducing the overall impact on transactional processing and other business

operations. As part of the project, an operational system was created with millions of lines of transactional

data reflecting a large size (multi-billion dollar revenue) company, and reports analyzing revenue and spend

were defined. This environment was used to evaluate the speed at which the analytical data set could be

updated with new and changed data, as well as the time necessary to analyze and report revenue and spend

data using multiple transaction types.

SAP HANA was used to reduce typical analytical report generation from several minutes to less than one

second, while maintaining an up-to-date analytics data source that is updated within milliseconds of data

changes in the operational system.

2 Challenges of Traditional Approaches to Analytics

Analyzing gross-to-net profitability—and business analytics in general—can pose challenges technically and

operationally. The root-cause of these challenges can be found in several areas.

2.1 Infrastructure and Technological Constraints

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 5

Companies have long relied on operational data that has been replicated to data marts for reporting purposes.

Reporting is system resource-intensive, and transaction processing cannot be subject to delays. Immediately,

it becomes apparent from this model that the transaction processing system is not the ideal system to use for

analytical reporting. Replicating operational data into a data mart is not real time, and frequent refreshing of

this data is necessary to provide a current view of operational data.

2.2 Increasing Complexity of the Gross-to-Net Equation

Due to the growing number of business partners a particular customer can have, the number of agreements,

variance in models, and the volume of transaction data, the complexity of gross-to-net analyses increases. As

a result, analyses performed on revenue and spend data require new levels of sophistication.

2.3 Increasing Demand for Insights

As the pace of change in the business climate accelerates due to economic and social factors, the time to

analyze business conditions and react to evolving situations shrinks. Information analysts are asked to

perform increasingly sophisticated analyses at ever faster speeds to provide the revenue and spend insights

that enable their businesses to compete and win.

Figure 1: SAP Incentive Administration and SAP Paybacks and Chargebacks with traditional BW system

3 Revolutionary Solution for Today’s Business Analytics

Today’s solution to analytical reporting needs to be a fundamental leap ahead of traditional approaches.

CHALLENGES

Standard Reporting

• Reports draw from operational system

• Analytics impact business

Optional Reporting

• Typically once-a-day update of data

• Data may be aggregated to improve analytic speed

Limited Insight

• Aged data yields equally aged analysis

• Analysis may be limited by data aggregation

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 6

SAP HANA technology provides a secondary data source for business analytics that can be updated in real-

time without significantly impacting the primary data source, used for business operations. SAP Landscape

Transformation replication software is used to replicate new and changed data almost instantaneously,

keeping the analytical data source current. HANA’s in-memory structure eliminates input/output contention

to physical storage and accelerates the analysis of large data sets.

3.1 Why in-memory is relevant for Analytics

HANA provides the capacity and speed to sift through detailed data without aggregation, so the analytical

results can be drilled into for deeper insight. It has the ability to query and analyze very large data sets to

perform intensive tasks such as consolidated, multi-year line-item and lifetime analysis of revenue by product

or customer. HANA enables instant access to relevant decision information in a user-initiated or automated

fashion.

Figure 2: SAP Incentive Administration and SAP Paybacks and Chargebacks with HANA as secondary database

3.2 Revenue and Spend Insights

Gross-to-net analyses are especially difficult to perform using traditional analytical technologies because it

involves a significant amount of data investigation, calculation and summarization. This extensive analysis

requires all of the financial transactions related to the sale of products. These transactions are spread

throughout the sales channel, involving any number of channel partners, the end customer, and all

agreements to which the transaction is governed. The relevant transactions must be found, linked, computed

and summarized for presentation.

Furthermore, valuable information can be found by drilling into data to search for specific customers or

products, make comparisons, and find patterns or discrepancies. The reporting mechanism must maintain the

ability to drill into high-level reports through a number of data dimensions. This requires the ability to query

BENEFITS

Improve Reporting

• Business user-driven data analysis

• Instant response times

Eliminate Boundaries

• No pre-defined data aggregation levels

• Complete lifetime, line-item analysis

Gain Deeper Insight

• Big Data and ad hoc queries

• No limitations on reporting dimensions

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 7

and manipulate very large data sets quickly, since these actions are performed in real-time by the business

analyst.

With its advanced analytical capabilities and extreme speed, HANA performs the complex queries,

calculations and analysis in a single user request, delivering results quickly while maintaining the ability to

drill into the summarized data to see rich detail with equal speed.

Performing gross-to-net analyses on real-time transaction data allows businesses to determine profitability

instantly and react to changes in manufacturing cost, trade spend, and other expenses quickly. Faster

detection of changes in profitability allows businesses to adjust pricing as soon as possible to limit the impact

of cost changes on profitability.

4 Co-innovate at SAP Co-Innovation Lab

SAP Co-innovation Lab (COIL) is a global lab network that is designed to bring value to our customers by

driving open innovation projects and initiatives to extend SAP’s solution coverage and enhance our solution

infrastructure efficiency. Both Vistex and IBM are members of the SAP Co-innovaiton Lab and leveraged the

lab‘s project enablement platform to conduct a HANA Proof-of-Concept (PoC) to determine the feasibility

and potential performance improvement of in-memory processing using HANA technology in data-intensive

applications commonly encountered by Vistex solutions. In particularly, the PoC checked the feasibility of

putting transactional data (obtained from IP Docs) in-memory to support near-real-time operational reporting.

4.1 Key components of the COIL test landscape

The following SAP and partner components were deployed at COIL to support this PoC:

- ECC 6 IDES with ehp5 with IBM DB2 and SLES

o Vistex Solution Extension for ECC

- BI Platform 4.0 on Windows 2008 64 bit and SQL server, with Advanced Analysis OLAP and MS

Office

- HANA 1.0 with SLT 4.2 Architecture of the COIL test landscape

SAP HANA provides a secondary data source dedicated to analytical reporting. This data source is updated

in real-time by SAP’s Landscape Transformation replication software. The implementation of SAP HANA

does not disturb the original architecture of SAP ECC and Vistex.

The architectural diagram for the SAP Co-Innovation Lab set-up is shown below.

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 8

4.3 Hardware

SAP HANA software requires specialized hardware to provide the memory storage and memory access

bandwidth. IBM provided the hardware necessary to install SAP HANA software in the SAP Co-Innovation

Lab. The specifications for the hardware are listed below.

IBM System x3850 X5

Machine Type: 7145

Number of processor: 4, Intel Xeon Nahalem EX, 8C

Memory: 512GB / Hard drives: 8 X 300GB

High IOPS SSD: 1 X 320GB

More details for IBM System x3850 X5

4 socket @ Intel Xeon 8C Processor Model X7560

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 9

512 GB Memory, eight memory cards, each with eight DIMM sockets (64 DIMM @ 8GB/DIMM).

2.4 TB SAS per chassis (using eight 300 GB 2.5" SAS HDDs).

320 GB High IOPS SLC DUO Adapter for IBM System x

5 Reporting Example

The following setup was used in the SAP Co-Innovation Lab environment to simulate the transactions that

would be used in a typical revenue and spend analysis report. This volume of data represents the annual

transaction data for a small enterprise or the monthly transaction data for a medium-to-large enterprise.

5.1 Scenario

• 5 Million Billing line items • 5 Million Sales rebates items • 5 Million Sales Incentive items • 5 Million Chargeback items

5.2 Requirements

To test the ability to perform typical analyses, the following capabilities needed to be performed to ensure

robust utility.

• Report on product- or customer-related profitability • Drill down to customer rebates • Sales incentives • Chargebacks for a single company

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 10

5.3 Outcomes

The timing of the report generation using SAP HANA and the traditional approach are shown in the table

below.

SAP HANA Less than 1 second (Runtime is measured for this specific scenario, no general

statement is made for all analytical scenarios.)

SAP Business Warehouse Several minutes (A tradition Data Warehouse would take several manual

steps to achieve the same results as SAP HANA and would

typically take several minutes.)

• Directly on line item level, no pre-calculated data aggregation levels required

• No limit on drill-downs and details • Data immediately available for reporting, no waiting on data load processes to data

warehouse

• Pre-calculated data aggregation levels • Processing time for next navigation step depends on whether aggregate exists

• Parallel drill-down to multiple dimensions may not be possible anymore

The gross-to-net analysis report was generated in a fraction of a second using SAP HANA. This is

significantly faster than the minutes required to produce the same report using traditional technologies.

Figure 3: The Gross-to-Net Analysis for a Company (all customers, all materials)

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 11

In addition to the superior speed of analytics, the detailed data is still retained and is available to drill deeper

into the analysis. Drilling into the report is equally as fast as the initial report generation, so there is no need

to sacrifice details for speed or vice versa.

Figure 4: The same Gross-to-Net Analysis demonstrating the ability to drill into details (one customer, each material)

The same analytical capabilities demonstrated for Gross-to-Net analysis can also be applied to particular

components of the profitability analysis. The following reports demonstrate drilling into the profit

components for Sales Incentives and Sales Rebates.

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 12

Figure 5: Drilling into the Sales Incentives component of the Gross-to-Net Report

Figure 6: Drilling into the Sales Rebates component of the Gross-to-Net Report

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 13

The demonstrated speed of analysis and delivery of the report enables the use of mobile devices for

requesting and reviewing revenue and spend data.

Figure 7: Gross-to-Net Analysis delivered to a mobile device (Apple iPad shown)

Analyses can be filtered on several dimensions and components of the analyses can be drilled into as shown

below.

An SAP HANA CO-INNOVATION STORY WITH VISTEX AND IBM 14

Figure 8: The Sales Incentive component of the Gross-to-Net report is filtered on fiscal period (Apple iPad shown)

6 Conclusion

Although each company’s transaction data will vary and its approach to revenue and spend analyses will

differ, the scenario demonstrated by Vistex in the SAP Co-Innovation Lab proved that significant

improvements in analytical capabilities can be achieved without sacrificing delivery speed or data latency.

SAP HANA enables Vistex to provide revenue and spend insights faster than traditional technologies. The

data used in the analyses performed by SAP HANA can be obtained in real-time without impacting other

business processing operations. The business analyst can drill into the delivered results with equal speed to

find insights that are masked by summarization. The full data record from the original source can be

available in SAP HANA and displayed in the report without impacting performance.

The benefits of this speed and capability are obvious to the business user requesting and viewing the analysis.

The benefits to the business itself are realized by the faster detection of challenges to be overcome, such as

increased expenses in cost to manufacture or trade spend affecting profitability; and quicker discovery of

opportunities to pursue, such as underperforming channels or below-forecast sales to certain customers or of

particular products.

Copyright/Trademark

2

Copyright

© Copyright 2012 SAP AG. All rights reserved SAP Library document classification: PUBLIC No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP AG. The information contained herein may be changed without prior notice. Some software products marketed by SAP AG and its distributors contain proprietary software components of other software vendors. Microsoft, Windows, Excel, Outlook, PowerPoint, Silverlight, and Visual Studio are registered trademarks of Microsoft Corporation. IBM, DB2, DB2 Universal Database, System i, System i5, System p, System p5, System x, System z, System z10, z10, z/VM, z/OS, OS/390, zEnterprise, PowerVM, Power Architecture, Power Systems, POWER7, POWER6+, POWER6, POWER, PowerHA, pureScale, PowerPC, BladeCenter, System Storage, Storwize, XIV, GPFS, HACMP, RETAIN, DB2 Connect, RACF, Redbooks, OS/2, AIX, Intelligent Miner, WebSphere, Tivoli, Informix, and Smarter Planet are trademarks or registered trademarks of IBM Corporation. Linux is the registered trademark of Linus Torvalds in the United States and other countries. Adobe, the Adobe logo, Acrobat, PostScript, and Reader are trademarks or registered trademarks of Adobe Systems Incorporated in the United States and other countries. Oracle and Java are registered trademarks of Oracle and its affiliates. UNIX, X/Open, OSF/1, and Motif are registered trademarks of the Open Group. Citrix, ICA, Program Neighborhood, MetaFrame, WinFrame, VideoFrame, and MultiWin are trademarks or registered trademarks of Citrix Systems Inc. HTML, XML, XHTML, and W3C are trademarks or registered trademarks of W3C®, World Wide Web Consortium, Massachusetts Institute of Technology. Apple, App Store, iBooks, iPad, iPhone, iPhoto, iPod, iTunes, Multi-Touch, Objective-C, Retina, Safari, Siri, and Xcode are trademarks or registered trademarks of Apple Inc. IOS is a registered trademark of Cisco Systems Inc. RIM, BlackBerry, BBM, BlackBerry Curve, BlackBerry Bold, BlackBerry Pearl, BlackBerry Torch, BlackBerry Storm, BlackBerry Storm2, BlackBerry PlayBook, and BlackBerry App World are trademarks or registered trademarks of Research in Motion Limited. Google App Engine, Google Apps, Google Checkout, Google Data API, Google Maps, Google Mobile Ads, Google Mobile Updater, Google Mobile, Google Store, Google Sync, Google Updater, Google Voice, Google Mail, Gmail, YouTube, Dalvik and Android are trademarks or registered trademarks of Google Inc. INTERMEC is a registered trademark of Intermec Technologies Corporation. Wi-Fi is a registered trademark of Wi-Fi Alliance. Bluetooth is a registered trademark of Bluetooth SIG Inc. Motorola is a registered trademark of Motorola Trademark Holdings LLC. Computop is a registered trademark of Computop Wirtschaftsinformatik GmbH. SAP, R/3, SAP NetWeaver, Duet, PartnerEdge, ByDesign, SAP BusinessObjects Explorer, StreamWork, SAP HANA, and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and other countries. Business Objects and the Business Objects logo, BusinessObjects, Crystal Reports, Crystal Decisions, Web Intelligence, Xcelsius, and other Business Objects products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of Business Objects Software Ltd. Business Objects is an SAP company. Sybase and Adaptive Server, iAnywhere, Sybase 365, SQL Anywhere, and other Sybase products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of Sybase Inc. Sybase is an SAP company. Crossgate, m@gic EDDY, B2B 360°, and B2B 360° Services are registered trademarks of Crossgate AG in Germany and other countries. Crossgate is an SAP company. All other product and service names mentioned are the trademarks of their respective companies. Data contained in this document serves informational purposes only. National product specifications may vary. These materials are subject to change without notice. These materials are provided by SAP AG and its affiliated companies ("SAP Group") for informational purposes only, without representation or warranty of any kind, and SAP Group shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP Group products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty.