in-memory for industries_boeckle

In-Memory for IndustriesHow to position HANA in the Industry Context

Klaus BoeckleVice President

SAP, EMEA Consumer Industries

HANA Partner Enablement

Walldorf, April 19+20, 2011

© 2011 SAP AG. All rights reserved. 2Confidential

2009: Recession

CRISIS

Operating Margins

Costs, Customers, Revenue


Position for upturn

while managing for the downturn

2010: Recovery

HOPE

The World In 2011


To be successful in 2011,

Industry Leaders need to…..B

usin

ess S

trate

gie

s

“Work” the

Business Network

Co-creation:

Power of People

BETTER

BETTER

BETTER

Instant or “Real”

Real-time

Business Value

Functional

Efficiencies

Personal

Productivity

Days or

Weeks

Co

mp

lexit

y

leaders


Agenda

1

2

3

Why Industries need In-MemoryCompelling reasons how In-Memory computing

changes everything

HANA can provide value now! First results from use cases

What comes next?Sneak Peak into the Future


Soaring Data Volume – Daunting Task for many companiesPoses Challenge to Both IT and Business Alike

IT: How Can I Run Leaner and Yet Help

Business Grow■ Higher costs for IT to support soaring data volume

and end user demands

■ New and unstructured consumer data sources

present challenges and cost

■ Flexibility to redefine business models and to

evaluate and New go to market strategies

End users require greater speed and flexibility

IT Faces Rising Costs

Business: How Can I Run Faster and

Decide Better■ Able to analyze soaring volume of data and have

instantaneous access to consumer insight

■ Blend operations with analytics - become more agile in reacting to events that impact operations

■ Improve responsiveness to meet changing consumer and market conditions

■ Effectively plan and execute at the level of detail required to gain insight and decision making

Business Faces Information Latency


Initial learnings from customer engagementSell the tranformational value of In-Memory Computing to position SAP HANA

Dont„s

•Make this a technical conversation

•Don„t focus on just speed

•Don„t leave it as „faster reports“

•Risk of reducing the power of In-memory to

saving time of IT analysts

•Example:

• Executing a dunning process in seconds instead of hours

• Proves the concept, demonstrate the technical value

• But: No significant business value, nobody runs dunning

several times a day, no business gain

Dos

•Position the transformation value

•Link to key customer business processes

•Work out the strategic benefits of

• Real time access

• Faster analyis

• Deeper insight

• Elimination of latency

• Simplification and flexibility

•Example: Consumer Products company

• Fast analyis of complex data to drive profitable trade

promotions

• Deeper insight into consumer data for better innovation,

better offerings

• Elimination of latency to drive faster response to

changes in demand and supply


HANA in Industries Transformational value along multiple dimensions

Run existing processes better

• Examples:

• Analysis of POS data in Retail and CP

• Prediction of user behaviour and network load in

Telecommunications

Enable new process and business innovation

• Examples:

• Smart grids and smart meter innovation in Utilities

• Precision Retailing with targeted personalized offers

Deliver strategic competitive advantage by

linking to key business processes

• Example HiTech:

• Innovation: Instantly predict market trends and identify

customer needs

• Sales: Quickly adapt to how customers want to buy, use, and

pay

• Operations: Instantly evaluate granular changes in supply

and demand


In-Memory comes alive in the industry contextTransformational value in 24 industries


HANA in action: HILTI

“Absolutely Great!...It is not about

accelerating reporting, it will change the

way we work with information. We will work

completely differently in the future. Instead

of waiting three months for a complex

analysis it will be accessible to each

employee directly. It is not a continuous

improvement, it is a transformational

innovation…a breakthrough innovation.”

Dr. Martin Petry, CIO of HILTI


Agenda

3


changes everything



2

1


Ca

pa

bil

itie

sB

en

efi

ts

In-Memory Analytics

HANA 1.0 Real-time operational analytics with HANA 1.0

Complete BI Suite with BI 4.0 (Aurora) runs on HANA

Flexible real time analysis of operations at non-aggregated level

HANA 1.0

Real-Time operational planning and simulation capabilities: link to execution

Primary persistence and optimized for SAP BW

Next generation applications

SAP BW fully running on HANA

HANA 1.5 platform for IM Apps

Business Suite runs on HANA

Further optimization of BI 4.1 Suite for HANA

Industry and LOB Business Analytics Solutions “BAS”

“Innovation“

Mid-term

One Store for Data and

Analytics

HANA only persistence layer for SAP Business Suite

SAP Business Suite optimized for In-Memory

Reduced landscape complexity

Value chain transformation

“Transformation”

Longer Term

SAP In-Memory StrategyProduct Strategy



CO-PA (Profitability Analysis)

Past: 15-60 min to generate a summary profitability

report

Now: 2.9 sec for 600 Million records

Drill down to detail

Actively evaluate all data to offer near real-time

profitability measures and validated business

scenarios;

Improved revenue growth and profitability

Data Intensive Point of Sale Analysis

460 bn records

120 TB traditional system = 40 TB HANA

20x Faster Analysis

200x price performance improvement

Eliminate Out-of-Stock during promotions,

Im improved shelf turnaround

Banking Scenario

19 mio records

19 TB traditional system = 1,8 TB HANA

Traditional system 30 min – HANA 8 sec.

Analyze risk faster, make credit approvals at the

speed of thought, make stock buying decisions

on real time data

Sportmart PoS (Point of Sale)

3.2 bn data records

Analyses customer bahaviour in real time

with very large, complex, and fast changing

data volume

Optimize shopping basked by client,

increase revenue by client


CPG Customer Snapshot: Point of Sale Analysis

Business Pain Points

Fortune 200 Global CPG firm needed to analyze

460 Billion records (40 TB) for global POS analysis

to predict demand

Challenges

Unable to analyze data using current database

platform

Need to stock shelves with 48 hour turnaround

120 TB environment with 6 BW Systems and

Teradata

Proof of Concept Results

120 TB Total System/40TB Raw compressed to 4TB

Improved shelf turnaround from 5 days to 2

Out of stocks eliminated during promotions


Industry Scenarios: Real Real-Time Business Analytics

Financial Services

Hedge fund trading analysis .

Real-time systematic risk management and reporting

based on market trading exposure

Consumer Products

Supplier Risk Management

Inventory Recall Reconciliation Product track and

trace

Product Lifecycle and Cost management

EPA standards compliance

On-Shelf Availability Analysis

Real-time Warranty and defect analysis

Retail

Store Operations

Point-of-Sales Retail Sales Analytics

Load Balance Optimization

Real-time completive multi-channel pricing

Product damage, returns and spoilage

Manufacturing

O&G Operational Performance Management

Manufacturing Production and Maintenance Analytics

Real-time Asset Utilization Analytics

Capital Markets Prime Brokerage Analytics

Real-time Analysis Example: Hedge Fund Analysis

edge fund account managers can manage exposure to currencies,

equities, derivatives and other instruments for hedge fund clients ...


Agenda


changes everything



1

3

2


SAP HANA for UtilitiesValue Proposition

Quickly analyze Smart Grid meter/profile data to

maximize energy delivery

Correctly predict market trends and improve the

balance of energy demand and supply

Optimize your asset investments by correlating

Smart Grid operations data

Support decision-making of existing asset

maintenance priorities and capital planning for

network expansion

High visibility into Grid operations data to

optimize capital planning and reduce costs

Ensure Revenue Assurance from Meter to Cash

–Ensure that all customers are correctly billed and

payments received on schedule


SAP HANA for BankingValue Proposition

Quickly analyze customer data to gain customer insight

and improve customer service

Manage customer communication through several different

business process channels (Online Banking, ATM, Branch,

Mail)

Think it, get it: Real-time access to the 360° view on

customer data

Enable real time finance & risk management processes

Quickly understand financial positions so that management can address both business problems and opportunities

Understand risk exposures and make more informed risk decisions

Any volume of transactional data available for real time decision support

Improve service and performance to customers

Find trends in information with the data mining capabilities of HANA, and analyze large volumes of data e. g. for predictive analysis, fraud detection


How HANA Helps Consumer Product companies Opportunities for your Business

Finance

Enable system wide visibility of customer and product profitability

Understanding of cost dynamics and margin drivers in real time

Enable timely and accurate reporting of financial and operational performance

Expedite the “Dunning” process

Flexible financial analysis to enable proactive margin management

Sales

Integrated view of A/R, customer demand and inventory provides real time visibility into market dynamics

Promotional sales analysis to drive profitable trade spend.

Sales order analysis –evaluate consumption vssell in rates

Visibility of new production introduction consumption –can adjust capacity and spend to maximize profits

Supply Chain

Real time supply chain planning and execution improving fill rates and working capital

Out of stock analysis and prevention at retail

Immediately respond to changes iwith real-time, detailed visibility to planned & actual demand across product, channel and geography dimensions

Understanding of demand

dynamics at any level

balancing capacity and

supply

IT

Integrate disparate customer, product and operational data sources into single version of the truth – in seconds

Enable reporting at the most granular hierarchy level with sub second response times

Reduce overall cost of information

Rapidly model data to meet changing go to market and organization strategies


HANA for Consumer Products Use casesFinance

Opportunity for your business In-memory enabled Innovations

Capability

enabled by

Financial and cost analysisEnable real time analysis of G/L and invoice data to

indentify cost leakage, reduce audit costs and invoice delays and improve Days sales outstanding

Customer and product ProfitabilityUnderstand who you profitable customers are and

what the cost levers are to impact margins by deep understanding off changes in cost dynamics and price optimization opportunities

Expedited “Dunning” ProcessExpedite the “Dunning” process to send out

communications to customers regarding outstanding Accounts Receivable

Financial and Cost Analysis Enables real time analysis and monitoring at the

granular level to rapidly indentify root cause issue of cost variances

Invoice analysis in real time to identify non conformance and increase perfect order performance

Profitability and Cost Analysis Analyze large data sets of cost elements, pricing

conditions, and customer data to eliminate unprofitable sales transactions

Enable real-time visibility to key KPIs Evaluate product mix to meet margin targets

Expedited “Dunning” Process Access large amount of customer and financial

data to perform “dunning” analysis Identify in real time customers to send out

communications to regarding outstanding account receivable items

Hana 1.0

Hana 1.0

Hana 1.0


HANA for Consumer Products Use cases Sales


Capability

enabled by

Real time Sales analysisTimely and accurate evaluation of sales orders to

evaluate actual vs planned on base and promotional items at a granular level – identifying trends and forecast errors

360 Degree view of the customer Integrated view of A/R, customer demand,

promotional sales, market take away and inventory provides real time visibility into market dynamics

Real-time sales analysis Access and analyze vast amounts of data of

customer/SKU / Location combinations Quickly compare sell in data to forecast for

promotions and new products rapidly indentifying by location if promotional volumes are sold in

Identify micro market changes – where sell in volume varies greatly from forecast so trade funds or supply can be redirected to meet opportunities

360 Degree view of the customer Access large data sets of customer, transactional,

and inventory information

Combine different kinds of information into one

consolidated view of the customer Historical pricing & Customer purchases

Inventory availability

Financial history

Hana 1.0

Hana 1.0


HANA for Consumer Products Use cases Sales


Capability

enabled by

Trade Promotion Management and Optimization

Real time planning and visibility to promotional plans comparing actual volume to planned uplift at the micro market and outlet level Identify promotion non compliance and rapidly

communicate to field resources when uplift is under performing

Shopper Sentiment analysis

Shopper Sentiment analysisevaluate internal , 3rd party data and social media to understand and evaluate shopper

All category volume planning

In Real time evaluate POS data, with shipment data and syndicated data to have an all volume view of demand at the retailer location/ skupromotion level to have true insight into consumer insight and preference Leverage all category view to improve category

management and rapid evaluation of sales promotion and design at a micro market level

Trade Promotion Management & optimization

Application built to take advantage in memory speed and data capacity to plan and execute promotions in real time to micro markets

Identify micro market changes – where sell in volume varies greatly from forecast so trade funds or supply can be redirected to meet opportunities

Optimize promotional plans based on actual results and market demand – simulate promotion designs and forecast anticipated demand

Shopper Sentiment analysis

Evaluate structured and unstructured shopper data to evaluate trends and develop insights

All Category Volume planning

Access and combine operational shipment information

with

Combine different kinds of information into one

consolidated view of shopper behavior and demand

Leverage ACV to dramatically improve product mix and

category management alternatives and options

Future

Future

Future


HANA for Consumer Products Use casesSupply Chain


Capability

enabled by

Line Performance analysisEvaluate in real time manufacturing yield,

resource capacity and perform root cause analysis

Supply Chain VisibilityReal-time, detailed visibility to planned & actual

demand across product, channel and geography dimensions Improve Supply Chain effectiveness and

efficiency

Sales and Operations PlanningProvide a single real time data and planning

environment for strategic and tactical planning across all commercial, brand, trade and financial planning areas

Demand Signal RepositoryEnable single repository of shipment POS and

syndicated data from which to analyze and improve supply chain management, category management and customer service

Line Performance analysisBecause in memory can handle vast amounts of data

in real time it is possible to measure and manage yield and production performance at lower levels to provide yield improvements.

Supply Chain Visibility Access Real-time supply chain data to get, visibility

into planned & actual demand information across

product, channel and geography dimensions at the

most granular level

Sales and Operations planning

• Access Real-time supply chain data to get, visibility into planned & actual demand information across product, channel and geography dimensions at the most granular level

Demand Signal Repository• In memory provides the capability to store massive

amounts of POS and syndicated data with unique modeling capability to plan and manage demand, category performance and customer service

Hana 1.0

Hana 1.0

Future

Future


HANA for Consumer Products Use casesSupply Chain / Procurement


Capability

enabled by

Procurement Spend analysisEvaluate in real time procurement spend across

all categories of materials identifying areas of non conformance, pricing exceptions and procurement savings opportunities

Efficient Supply chain Management

Visibility to understand in real time root cause issues and flexible Reponses to cost efficiently meet changing customer demand

Procurement Spend analysisProcess , access and analyze vast amounts of

purchasing data to quickly perform the necessary spend analysis. Identify procurement savings opportunities

Efficient Supply chain management• Drill-down on Industry Supply Chain Metrics

• Root-Cause Analysis of Supply Chain Issues

• Accelerated KPI and Business Metric reporting in

Supply Chain Performance Management

• True Global Available-to-Promise Check

• Transportation and route Analytics

Hana 1.0

Future


SAP In-Memory Computing Ground-Breaking Technology Specifically-Tuned for Industries

Only SAP combines transactional and analytical

applications enabled by in-memory computing

Only SAP can conduct analysis, performance

management, and operational execution in a

single system with real-time links between insight,

foresight, and action

Only SAP can enhance existing investments with

in-memory capabilities without disruptions or

changes to IT roadmaps

Only SAP collaborates with industry leading

partners to deliver in-memory computing solutions

tailored to your business


Make the business value of this disruptive technology

transparent to CEOs and LOB buyers in all industries

and show transformational value, enabling them to

run and manage their business in new ways.

CALL TO ACTION:

LET‟S COLLABORATE


Let’s Win Together!

Have a Great 2010!

No Limits

In-Memory Computing

Thank You!

Klaus Boeckle

Klaus Boeckle, Head of Consumer Industries, EMEA | April 19th 2011

in-memory for industries_boeckle

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