SAP NetWeaver BW Powered by SAP HANA Customer Success

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SAP NetWeaver BW: Powered by SAP HANA

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UNO Bakes to Perfection with SAP Business

Planning and Consolidation, Powered by SAP HANA

(2013/01) Company

UNO (Unmas Unlu Mamuller) Headquarters

Istanbul, Turkey Industry

Consumer Products Products and Services Baked Goods, Packaged Bread Revenue € Employees 1,500 Web Site http://www.uno.com.tr/ Partner IBM Metric Technology Business challenges

 Managing and analyzing huge data volumes required for daily operations, while supporting company growth

 Enhance data-monitoring capabilities to improve production-to-consumption process for 370 trucks covering 95% of the country

 Provide management team with the means for faster, more accurate data analysis and reporting

Technical implementation

 Implemented the SAP NetWeaver®_{Business Warehouse solution}

powered by SAP HANA®

 Deployed the SAP Business Planning and Consolidation, version for SAP NetWeaver®_{powered by SAP HANA}® _{for automated and}

accelerated business planning and reporting cycles Key benefits

 Compressed big data into a manageable series of reports, enabling faster decision-making and market response times based on more accurate information

 Streamlined planning data from more than 10,000 retail stores, maximizing product shelf life and reducing food wastage

 Improved data compression by a factor of 9.5, reducing IT demands

“UNO has a history of embracing technology that supports our innovation. We are proud to be the first users of BPC on HANA in our country, and in our industry. We can now manage our

growing business more efficiently with visibility into strategic data that we never had before.”

Kaan Aktoluğ, Assistant General Manager, UNO

10x

Reduction in database size for lower cost of ownership

400%

Faster reporting speed for accelerated analysis and planning cycles, time to action

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SAP NetWeaver BW on SAP HANA

Marathon Oil

Business Challenge

Marathon Oil Corporation, based in Houston, Texas, is an independent international energy company engaged in exploration and production, oil sands mining and integrated gas. Marathon Oil faced new challenges stemming from increased investor expectations for faster and more granular information about their business. The reporting challenge was magnified by investor reporting demands due to significant ramp up of drilling activity in North America, and the pressing need for accurate and timely information in their international operations.

Performance and benefits

 Reduced SAP BW support costs

 10x Faster Data Loading - Batch load for over 6 million records now

takes only 9 minutes with SAP BW running on HANA . This used to take over 8 hours with SAP BW running on the traditional database

 Near-real time reporting capability

 100x Faster Reporting - Legacy BEx queries now run much faster  5x Data compression savings

 Simplified BW design and modeling - better use of DSOs

 Reporting requests and changes completed much more quickly

with far fewer BEx queries to modify

 More granular information with the ability to aggregate and

disaggregate with transparency.

 Implementation of new GL substantially improved detailed financial

reporting below the segment level. This level of detail was

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SAP NetWeaver BW on SAP HANA

Home Trust

Project scope and business scenario

Home Trust successfully migrated SAP BW to SAP HANA in early 2012 moving significant data volumes from Oracle DB to HANA. This led to drastic improvements in query run-times and data loading in BW as well as in reporting performance in SAP BusinessObjects BI . The result: improved customer service responsiveness and loan processing times while providing a long term scalable platform for future growth.

 Loan processing: From 3 hours to 45 minutes

 Improved accuracy of data for regulatory reporting

 Financial close process: From 10 days to 5 days

 DSO/Cube loading speeds up about 1.3x faster

 DSO activation 19x

 BW query average 8-12x

Customer quotes

“We are very impressed with the proof-of-concept results running BW on SAP HANA. As a result, we are re-architecting our Reporting

environment to leverage BW on HANA. Our plan is to replatform reporting over the course of summer 2012.”

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NongFu Spring

CPG Industry (Bottled water and beverages) – Sales Reporting

We are so satisfied with the operation and speed of the entire BW on HANA implementation. According to end users' feedback, the speed of their standard BW reports is very fast and has been improved greatly. In addition, the running of the whole production system is stable with fast speed of the data extract, ETL, and incremental updates.

CIO NongFu Springs

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Business Challenges



Poor decision making due to slow speed and lack of accurate data



Slower response time to competition, growing business needs

Technical Challenges



Big data: takes more than a day to organize huge amounts of

point-of-sale (POS) data



Lack of coordination between sales, marketing, production, and

logistics

Benefit



Real-time decisions regarding the company’s long-term

development, improving efficiency and lowering costs

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SAP NetWeaver BW on SAP HANA

Shanghai Volkswagen

Migrated original BW system to SAP HANA in late 2011 for significant improvements in streamline data modeling and reporting and query performance in SAP BusinessObjects 4.0

 Cube loading speeds up increased 1.39x

 DSO activation increased 15x

 BW query response times increased 8.5x

 SAP BusinessObjects BI reporting execution 11.6x, compared to BW on Oracle

(Ex. With the same data volume(40 millions) in Cube, SAP NetWeaver BW on SAP HANA: 45 seconds, BW on Oracle: result set returned finally after a 20 minutes wait)

Customer quotes

“Real-time insights combining our customer demand, marketing promotion, with supply chain visibility on a rock-solid enterprise-class data platform is a must in our industry.

With SAP HANA, there is tremendous opportunity to dramatically improve our enterprise data warehouse solution with BW on HANA, drastically reducing data latency and improving speed at which we can return query results with BW on HANA vs. waiting up to 30 minutes for empty results from BW on Oracle.”

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Usha International Ltd.

Consumer Durables – Domestic Appliances

 Due to report-generation time-lag, actual sales and supply-chain performance

could not be tracked

 Poor decision making due to lack of fast analysis

 Slow response to the large data analysis query

 Exponentially increasing data volumes affecting supply chain efficiency

Benefit

 Sales up-lift enabled by faster analysis of secondary sales data  Real-time decision-making for better inventory management

 Enter new markets by analyzing secondary sales data and market research reports

Business users are very thrilled with the results. They are able to run reports faster, and more importantly, productively utilize their time for analysis and better decision making. Our IT department is also very happy as this project has achieved 3 things in one go: achieve a smaller DB footprint for the same size of a BW deployment; faster data loads making more current data available to business; faster reporting and analysis making business users happy. We are now planning to migrate to BPC – HANA. Customer is also planning to upgrade to SAP BusinessObjects BI 4.0.

Subodh Dubey, Group CIO, USHA

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30-80x

faster query performance improvement for large data queries

9:1

data compression factor

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Lenovo

Computer Hardware – Improved reporting performance for the BI Reporting landscape

Business Challenge



Drive operational excellence in reporting Global Shipment Process

data

Technical Challenge



Needed faster sales pipeline reporting from CRM

Benefits



Real-time accurate reporting makes operations more efficient and

productive

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Become SAP’s Hardware partner and sell servers to SAP HANA

customers

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Improve speed and hence utilization of BW reporting tools

In an industry where products become obsolete quickly, we need both a deep and instant knowledge of customer behavior and products being sold globally. That's why Lenovo chose SAP Customer Relationship Management and supercharged it with SAP HANA. Using these solutions side by side will allow us to analyze orders by customer, region or product. This will improve our forecasting abilities and we'll be able to introduce new products and services faster. Reporting on stale data is dead – we now explore the data on the fly and run the business based on the most recent events, customer relationships and product plans.

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and business scenario

Australia-based systems integrator and SAP partner, Innogence set up an SAP HANA instance at its premises, running under SAP NetWeaver BW to run various test scenarios using large volumes of test data loaded into SAP HANA and BW

Customer Feedback

The validation of BW on SAP HANA is particularly promising, as this solution will drive a lot of SAP HANA adoption within SAP’s installed base. What is more is that partners developing on the SAP HANA platform will enable new business scenarios and reach customers and industries that SAP may have otherwise never been able to access

SAP NetWeaver BW on SAP HANA

Innogence

BWB (SQL database) BWH (SAP HANA database) Performance gains

Query against cube

with 20 million rows 110 seconds 0.5 seconds 220x Data transfer process

runtime of loading 1 million records into DSO

294 seconds 87 seconds 3.4x

DSO activation runtime

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SAP NetWeaver BW on SAP HANA

Asian Paints

Asian Paints, the biggest paint manufacturing company in India with very strong brand equity is seen as the early adopter of cutting edge IT

solutions, and is widely regarded in the SAP customer community as very prolific user of SAP BI. In late 2011, Asian Paints decided to implement HANA for their growing analytical needs for the large volume ERP and BW implementations, and with the help of SAP Consulting implemented SAP HANA running under SAP BW in only 3 weeks.

 Data volume compression savings of 6:1 moving from BW/Oracle to BW/HANA

 Significant improvement in the query performance: average query performance improvement was15 x with maximum improvement 266x times.

 Certain queries, for analyzing orders and billing that could not run in the past on BW-Oracle, are returning the results with an impressive query response time of 15-20 secs with BW-HANA.

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Southern California Edison

Energy consumption forecasting with Smart Meter Analytics

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Better understand consumption behavior, optimize campaign

effectiveness, and improve customer energy efficiency

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Poor decision making on service outage, power procurement and

requirement forecasting

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Needed real-time access and insight into huge volume of continually

changing electric usage data (~2 TB)

Benefit



Better match supply to demand



Provide the most reliable service possible to customers



Better power procurement

6.3x

faster data

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“

Real-time insights combining our customer

demand, marketing promotion, with supply

chain visibility on a rock-solid enterprise-class

data platform is a must in our industry...

With SAP HANA, we see a tremendous

opportunity to dramatically improve our

enterprise data warehouse solutions,

drastically reducing data latency and improving

speed when

we can return query results in

45 seconds from BW on HANA vs. waiting

up to 20 minutes for empty results from BW

on Oracle

.

”

Weijun Zhang

IT Manager

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“Enabling HANA to run under our

SAP BW system is a very

important

milestone. We can now create key

reports on shipping more timely

and

accurately across all of our

plants. This is the kind of capability

we need to

drive operational

excellence

and become #1!”

XiaoYu Liu

Vice President

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“Business users are very thrilled with the

results. They are able to run reports faster,

and more importantly, productively utilize their

time for analysis and better decision making.

Our IT department is also very happy as this

project has achieved

faster data loads

making more current data available to

business; faster reporting and analysis

making business users happy.

”

“Our IT department is also very happy as this

project has achieved

a smaller DB footprint

for the same size of a BW deployment.

”

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