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D riving Business Value w ith MDM Jolene Jonas MDM Data Architect/Product Manager Intel Corporation Nimish Mehta Senior Vice President, EIM SAP Labs LLC.

Driving Business Value With MDM

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Driv ing Business Valuew i t h MDM

Jolene Jonas

MDM Data Architect/Product Manager

Intel Corporation

Nimish Mehta

Senior Vice President, EIM

SAP Labs LLC.

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Driv ing Business ValueWi t h Dat a Unif i c a t ion

Nimish MehtaSVP, EIM

SAP LABS LLC.

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Data Unification with SAP NetWeaver

Customer Success Stories

The Data Problem

Data Unification withSAP NetWeaver

Best Practices and Getting Started

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The New In t egrat ion Chal lengeDispara t e t ec hno log ies do no t suppor t p rocess innovat ion

Inflexible, slows process change “Hardwired” process

IT silos can’t meet LOB needs

IT silos prevent delivering

composites

Costly to maintain, ties up budget

Exponential # of integrations

No cohesive master data

Appl ica t ionServer 

PortalBusiness

In te l l igence

Messaging

Secur i ty

Mas ter Data

Mgmt

Enterpr iseIn tegra t ion

CRM

SRM

ERP

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Bad Master Dat a h inders proc ess innovat ions ince every depart m ent has a d i f fe rent vers ion o f i t

Master data isdata about yourcustomers,products,suppliers etc.

M & A’s areworsening theproblem

CallCenter

Jane Smith

4418 N. Str.Chicago, IL

60611Part: 2574

SRM

Part: 8975

VENDOR:ABC123

Logistics

VENDOR:XYZ456

YOUR VALUE CHAIN

ERP

Jane Peters199, 3rd StreetPalo Alto, CA

Part: B7521

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Costs and Com plex i t y inc rease over t im eAs bus iness events c on t inue to impac t t he dat a

57% of marketing contentwork was to mitigate

errors

40 % orders gettingblocked due to masterdata problems

$6 billion Maytag merger

DataQuality

Time

Wit hout Mast er Dat a Management

Doing business is expen sive

DataWarehousing

One-off

cleansing

M & A

Outsourcing

New productlaunch

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ConsolidationEnsure consistent masterdata across systems

HarmonizationCleanse and distributeacross entire landscape

Central ManagementCreate consistent master datafrom the start, centrally

Managing Mast er Dat a Ac t ive lyI s Impera t i ve to ensur ing op t im a l p roc ess innovat ion

DataQuality

Time

New ProductLaunch

Mast er Dat a ManagementImprove da ta qua l i t y in s teps

M&A

Outsourcing

Consolidation

Harmonization

CentralMDM

DataQuality

Time

Without Consol idat ionDoing bus iness is expens ive

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Data Unification with SAP NetWeaver

Customer Success Stories

The Data Problem

Data Unification withSAP NetWeaver

Best Practices and Getting Started

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SAP Net Weaver – A St rat eg ic Plat form for Ent erpr ise SOAMaster Data i s an in tegra ted c apab i li t y o f t he Pla t form

SOA Provis ioni ng

Stable, scalable core

Open, standards-based Service-enabling

processes, information, events

Com posi t ion Env i ronment Fast paced “edge” of the business

Don’t just code – compose!

Lean consumption

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© SAP AG 2006, Data Unification / 10

Master Dat a Managem entw i t h SAP Net Weaver  

Compose cross applicationprocesses in SOA withconsistent master data

Infinitely configurableschema options

Support consolidation,harmonization, centralmgmt

Pre-packaged IT and

business scenarios

500+ customers

Manage Any Master Data

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Benefits: Complex product and

relationship management

Print/web publishing including

layout and production

GEAR

Parts1038-GID

Example: Product information is

consolidated and enriched and

published internally or externally

A124K

Parts

GEAR

Ric h Produc t Cont ent Managem entOne v iew o f p roduc t in fo rmat ion anyt im e anyw here

Publish

GearsBR-2K

SPIDERGEAR

C

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© SAP AG 2006, Data Unification / 12

Jane Smith

4418 N. Str.Chicago, IL60611

Extensive matching framework

Provides web services tocustomer data access

SAP & Non-SAP integration

Cust om er Dat a In t egrat ionOne view o f cus t omer i n fo rmat ion anyt ime anyw here

Analysis

Jane Peters

199, 3rd StreetPalo Alto, CA94304

Jane PetersSmith

4418 North St.Chicago, IL

60610

I d B i I t l l i

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© SAP AG 2006, Data Unification / 13

Understand your most profitableproducts, best customers andcheapest/reliable vendors

Gain insights by integrating

transactional data fromheterogeneous systems withmaster data for analysis

Im proved Business In t e l l igenc eDel iver un ique ins igh ts w i th an in tegra ted p la t fo rm

+

TRANSACTIONAL

DATA

MASTER

DATA

=

BUSINESS INSIGHT

CO SO G S S

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CONSOLIDATING HAS NEVER BEEN EASIERConsol idate, harmonize and cent ra l ly manage mast er data

Instance Consolidation from R/3 and other sources

Direct ODBC System Access, extract flat files, 3rd partyapplication data, XML sources, many more..

Single pass data transformation, Auto-mapping, Validation

Rules, Exception handling

Business Users can define matching rules, complex matchingstrategies, conduct data profiling, enrich data

Data Enrichment Controller to use 3rd party sources likeTrillium, D & B and other partners for address completion,company validation and enriching data

Search and compare records, identify sub-attributes forconsolidation in sub-second response times

Merge Records seamlessly, tracking source systems with built

in key mappings

Leverage out of box data models for consolidated data

CONSOLIDATING HAS NEVER BEEN EASIER

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CONSOLIDATING HAS NEVER BEEN EASIERConsol idate, harmonize and cent ra l ly manage mast er data

Leverage built in workflow to manage compliance process,ensure administrators can validate imported records

Enforce data governance through user roles, security,workflow, audits to prevent future data problem

Syndicate master data in XML or to any SAP or non-SAP

applications

Works with SAP and non-SAP distribution technologies foreasy fit in heterogeneous environments

Centrally manage master data

Leverage validation rules to enforce data integrity

Manage rich content set and relationships associated withmaster data record

Wh C st om ers are c hoosing SAP ?

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IDENTIFY SUPPLIER MANAGE CUSTOMERVERIFY AVAILABILITYTAKE ORDER

Why Cust om ers are c hoosing SAP ?One so lu t ion for ALL mast er da ta in your indust ry spec i f i c p roc ess

SAP NetWeaverOne master data solution for all business processes

Who is mycustomer?

Do I have theright product?

Who is my bestvendor?

Which employeeshould we assign to?

Firs t s t ep t o ent erpr ise SOA

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Firs t s t ep t o ent erpr ise SOAAcc e lera te new business processes w i th acc urat e mas te r dat a

Unify any data

Unify customer, product, employee, supplier and user defined data

with one solution to build robust business processes

Industry insights

Supports 1Sync (UCCnet, Transora), configurable forother industries

Easy deployment

Pre-built data models, mappings and iViews

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Mast er Dat a Managem ent a t In t e l

Jolene JonasSAP MDM Product Manager

SAP Data Architect

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Company Background

Formalizing Data QualityWhat is Master Data?

Data Modeling Approach – Tops Down

Physical ImplementationSummary/Q&A

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Company Background

Formalizing Data QualityWhat is Master Data?

Data Modeling Approach – Tops Down

Physical ImplementationSummary/Q&A

C B k d

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© SAP AG 2006, Data Unification / 21

Intel is the world's largest chip maker, and a leading manufacturer ofcomputer, networking and communications products.

Founded in 1968, first microprocessor shipped 1971

Worldwide Presence

124 Offices in 57 countries

97,000 employees + 39,000 Contingent workers

Over 450 products & services

2005 revenues $39 billion

Information Technology Group –  6,469 Employees + 2,254 Contingent workers

 –  79 IT Sites in 27 countries

 –  26 data centers all running Intel® architecture-based servers

SAP* since 1996, key of our ERP implementation –  Centrally-located infrastructure

 –  Distributed implementation by business functions

 –  Future: Replatforming SAP and moving to SOA*

* SOA – Service Oriented Architecture

Com pany Bac k ground

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Company Background

Formalizing Data QualityWhat is Master Data?

Data Modeling Approach – Tops Down

Physical ImplementationSummary/Q&A

F l i i D t Q l i t

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Form al izing Dat a Qual i t y

Effort began in 2001

Elevated awareness corporate wide

Data is an asset

 –  Systems are temporary but Data lasts forever

Quantified impact of poor data, the pain of poor Master Data

 –  Per Data Quality Experts - assume 10% error rate due to poor quality

 –  High TCO*

- 25+ Customer Apps all doing same work

- No single place where Customer is created

- Lack of an integrated view

Formed an Information Quality Organization Message given tops down

Targeted training classes

 –  Management and detail level

TCO – Total Cost of Ownership

Form al izing Dat a Qual i t y

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Form al izing Dat a Qual i t y

Defined data quality goals: Single terms/definitions - One language

Single Record of Origin for Configuration and Master Data

Increase reuse

Monitors & audits to track improvement

Streamline business processes

Standards & Governance:

Data Architects

 –  Lead Data Architect per subject area- Finance, Location, HR, Customer, Supplier, Item

 –  Owns standards, governance, project deliverables

 –  Defined a Data Model driven approach for development

Business gatekeepers

 –  Focused Change Control Boards

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Company Background

Formalizing Data QualityWhat is Master Data?

Data Modeling Approach – Tops Down

Physical ImplementationSummary/Q&A

Fi rs t What is Mast e r Dat a?

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Fi rs t - What i s Mast e r Da t a?

Includes Master Data & Config

Persistent (lifecycle outside a single business process)

Has a CRUD* process outside of the business processes where consumed

Definition independent of other data –  i.e. Item is Master Data, BOM is not as it is dependent on Item

Highly reused – (Used in more than one business process)

Primarily created for use in other processes

* Create, Read, Update, Delete

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Company Background

Formalizing Data QualityWhat is Master Data?

Data Modeling Approach – Tops Down

Physical ImplementationSummary/Q&A

Tops Dow n Approac h t o Dat a

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Tops Dow n Approac h t o Dat a

First - Define the conceptual layer Sets the foundation, the business framework

Brings Intel to one data dictionary –  Single terms and definitions

Second – Seed the logical layer from the conceptual

Reuses approved conceptual entities

Adds all the facts/attributes, business data rule

Grows as new needs are identified Acts as blueprint for physical design

Services being designed based on the model

Third - Use logical model to “seed” the physical models

Ensures reuse of approved entities and attributes Physical representation of the applications

Why? –  Links application speak to Intel speak

 –  Roadmap for enhancements/integration/reuse

 –  Impact analysis

Pre- Ent erpr ise Com m odit y Dat a Mode l

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Pre Ent erpr ise Com m odit y Dat a Mode l

Reporting

SAP CRS

Material Master (CIM)

Material Group = Commodity

Tax Man

Spends

Analyst

SpendsManager

MaterialPlanner

Summarize by taxable area

Planning Categories

Summarized Grouping

Lowest Detail

One Term, Many Definitions

Ent erpr ise Dr iven Com m odi t y Dat a Model

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Ent erpr ise Dr iven Com m odi t y Dat a Model

Reporting

SAP CRSMaterial Master(CIM)

Material Group= Commodity Detail

New Commodity Hierarchy

Tax Man

SpendsAnalyst

SpendsManager

MaterialPlanner

Summarize by taxable area

Summarized Grouping

Commodity plusHierarchy

Detail CommodityReport

CommodityGatekeeper

Controlled Entry

Single Definition per Term

Ent erprise I t em Conc ept ua l Model

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Ent erprise I t em Conc ept ua l Model

Item

Product

Subassembly

Material

Finished Good

Kit

Service

Direct Material Indirect Material

Manufacturing Indirect Material

BOM

Intangible Product

Subject Area

Product

Subject Area

Material

Subject Area

Item

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Company Background

Formalizing Data QualityWhat is Master Data?

Data Modeling Approach – Tops Down

Physical ImplementationSummary/Q&A

In t e l Mast er Dat a Di rec t ion

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In t e l Mast er Dat a Di rec t ion

Finance data

Currently using SAP R/3 as single Record of Origin

 –  Minimal gaps –  Meets business need

Therefore – move to SAP ECC^

Location data

SAP R/3 works well

 –  But has data gaps- Effective dating, status codes, type codes

Therefore – move to SAP ECC

Build out SAP NetWeaver MDM to close data gaps

 –  Utilize SOA to glue them together

ECC – Enterprise Central ComponentMDM – Master Data Management

Determining Best Fit for Record of Origin

In t e l Mast er Dat a Di rec t ion

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In t e l Mast er Dat a Di rec t ion

Item (Material Master) & Commodity

Currently use R/3 as authorized Record of Origin

Large gaps in data & business rules

Therefore, targeting Record of Origin as SAP NetWeaver MDM

Customer/ Supplier

Currently use R/3 for Direct Customer and Supplier

 –  Indirect Customers in many other apps

Building out mySAP CRM and SRM in 2007

Long term goal is SAP NetWeaver MDM as Record of Origin

Integrated SAP Netweaver BI

Distribution from authorized Record of Origin only

 –  Requires controlled distribution attribute by attribute

Requires strict control of Master Data number ranges

Determining Best Fit for Record of Origin

*ROO – Record of Origin – Single point of create for unique identifier

SAP Net Weaver MDM w i l l run on In t e l®Arch i tec tu re

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Arch i tec tu re

Certified on 64-bit Intel® Xeon® processor

Benefits

Premier performance, scalability, and the highest reliability at a fraction of the

cost of proprietary systems

Integrated, advanced RAS features for highest standards of system availabilityand uptime

Greater range of optimized solutions than proprietary platforms support, at a

lower cost

Optimized SAP solutions to run best Intel architecture via massive Intel and SAPengineering investment

SAP NW MDM Live at In t e l s inc e Nov 2006

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Started with our logical data models

Built our own physical data model due to Intel specific needs

MDM plugged into existing infrastructure

 –  Redundant applications will be phased out over time as in-house expertise isgained with new application

 –  Allows us to identify gaps and work with SAP for closure

1.8m Materials, 180K Suppliers = ~$10-15Bn spend, 6m Customers

2007/2008 will see further rollout of MDM to business applications

Collaborating with SAP on a Master Data Service/xApp

Get Supplier, Search Supplier

Leverages MDM Web Services delivered in latest release –  6 week effort

OOB – Out Of Box

Lessons Learned

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Being an early adopter has benefits

Strong influence on SAP strategy for central maintenance

 –  Customer champion on the Influence Council

Many product enhancements at Intel request

Alignment with SAP SOA team on a Master Data Service

Very strong support from SAP enabling our success

Go with SAP data model

More complete integration back to core SAP

Extend what is delivered

Sum m ary: ROI sav ings est im at ed at $10-18m

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y g $

Benefits of a Data Model Driven Approach Grounds Intel on common language

Ensures fully integrated, reusable design

Provides consistent blueprint to development community

Reduces Total Cost of Ownership (TCO) through Record of Origin

 –  Cost Avoidance - reduction in applications (infrastructure and headcount)

Delivers better data quality

Must have management buy-in to succeed

SAP NetWeaver MDM has a key role in Master Data Management

Both as an Record of Origin and Record of Reference