Driving Business Value with MDM

Transcription

1 Driving Business Value with MDM Jolene Jonas MDM Data Architect/Product Manager Intel Corporation Nimish Mehta Senior Vice President, EIM SAP Labs LLC.

2 Driving Business Value With Data Unification Nimish Mehta SVP, EIM SAP LABS LLC.

3 Data Unification with SAP NetWeaver The Data Problem Data Unification with SAP NetWeaver Customer Success Stories Best Practices and Getting Started

4 The New Integration Challenge Disparate technologies do not support process innovation CRM Enterprise Integration Inflexible, slows process change Hardwired process Master Data Mgmt Security Portal ERP Application Server Business Intelligence SRM Messaging 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 SAP AG 2006, Data Unification / 4

5 Bad Master Data hinders process innovation since every department has a different version of it YOUR VALUE CHAIN SRM Part: 8975 VENDOR: ABC123 Master data is data about your customers, products, suppliers etc. ERP Logistics VENDOR: XYZ456 M & A s are worsening the problem Jane Peters 199, 3 rd Street Palo Alto, CA Part: B7521 Call Center Jane Smith 4418 N. Str. Chicago, IL Part: 2574 SAP AG 2006, Data Unification / 5

6 Costs and Complexity increase over time As business events continue to impact the data Data Quality Without Master Data Management Doing business is expensive 57% of marketing content work was to mitigate errors New product launch Data Warehousing M & A One-off cleansing Outsourcing Time 40 % orders getting blocked due to master data problems $6 billion Maytag merger SAP AG 2006, Data Unification / 6

7 Managing Master Data Actively Is Imperative to ensuring optimal process innovation Data Quality Master Data Management Improve data quality in steps Outsourcing Data Quality Without Consolidation Doing business is expensive New Product Launch M&A Harmonization Central MDM Consolidation Time Time Consolidation Ensure consistent master data across systems Harmonization Cleanse and distribute across entire landscape Central Management Create consistent master data from the start, centrally SAP AG 2006, Data Unification / 7

8 Data Unification with SAP NetWeaver The Data Problem Data Unification with SAP NetWeaver Customer Success Stories Best Practices and Getting Started

9 SAP NetWeaver A Strategic Platform for Enterprise SOA Master Data is an integrated capability of the Platform Composition Environment Fast paced edge of the business Don t just code compose! Lean consumption SOA Provisioning Stable, scalable core Open, standards-based Service-enabling processes, information, events SAP AG 2006, Data Unification / 9

10 Master Data Management with SAP NetWeaver Manage Any Master Data Compose cross application processes in SOA with consistent master data Infinitely configurable schema options Support consolidation, harmonization, central mgmt Pre-packaged IT and business scenarios 500+ customers SAP AG 2006, Data Unification / 10

11 Rich Product Content Management One view of product information anytime anywhere 1038-GID Parts Publish GEAR A124K Parts GEAR BR-2K Gears SPIDER GEAR Benefits: Complex product and relationship management Print/web publishing including layout and production Example: Product information is consolidated and enriched and published internally or externally SAP AG 2006, Data Unification / 11

12 Customer Data Integration One view of customer information anytime anywhere Jane Peters Smith Analysis 4418 North St. Chicago, IL Jane Smith 4418 N. Str. Chicago, IL Jane Peters 199, 3 rd Street Palo Alto, CA Extensive matching framework Provides web services to customer data access SAP & Non-SAP integration SAP AG 2006, Data Unification / 12

13 Improved Business Intelligence Deliver unique insights with an integrated platform BUSINESS INSIGHT MASTER TRANSACTIONAL = DATA DATA + Understand your most profitable products, best customers and cheapest/reliable vendors Gain insights by integrating transactional data from heterogeneous systems with master data for analysis SAP AG 2006, Data Unification / 13

14 CONSOLIDATING HAS NEVER BEEN EASIER Consolidate, harmonize and centrally manage master data Instance Consolidation from R/3 and other sources Direct ODBC System Access, extract flat files, 3 rd party application data, XML sources, many more.. Single pass data transformation, Auto-mapping, Validation Rules, Exception handling Business Users can define matching rules, complex matching strategies, conduct data profiling, enrich data Data Enrichment Controller to use 3 rd party sources like Trillium, D & B and other partners for address completion, company validation and enriching data Search and compare records, identify sub-attributes for consolidation in sub-second response times Merge Records seamlessly, tracking source systems with built in key mappings SAP AG 2006, Data Unification / 14 Leverage out of box data models for consolidated data

15 CONSOLIDATING HAS NEVER BEEN EASIER Consolidate, harmonize and centrally manage master data Centrally manage master data Leverage validation rules to enforce data integrity Manage rich content set and relationships associated with master data record Syndicate master data in XML or to any SAP or non-sap applications Works with SAP and non-sap distribution technologies for easy fit in heterogeneous environments 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 SAP AG 2006, Data Unification / 15

16 Why Customers are choosing SAP? One solution for ALL master data in your industry specific process SAP NetWeaver One master data solution for all business processes TAKE ORDER VERIFY AVAILABILITY IDENTIFY SUPPLIER MANAGE CUSTOMER Which employee should we assign to? Do I have the right product? Who is my best vendor? Who is my customer? SAP AG 2006, Data Unification / 16

17 First step to enterprise SOA Accelerate new business processes with accurate master data 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 for other industries Easy deployment Pre-built data models, mappings and iviews SAP AG 2006, Data Unification / 17

18 Master Data Management at Intel Jolene Jonas SAP MDM Product Manager SAP Data Architect

19 Company Background Formalizing Data Quality What is Master Data? Data Modeling Approach Tops Down Physical Implementation Summary/Q&A

20 Company Background Formalizing Data Quality What is Master Data? Data Modeling Approach Tops Down Physical Implementation Summary/Q&A

21 Company Background Intel is the world's largest chip maker, and a leading manufacturer of computer, 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 SAP AG 2006, Data Unification / 21

22 Company Background Formalizing Data Quality What is Master Data? Data Modeling Approach Tops Down Physical Implementation Summary/Q&A

23 Formalizing Data Quality 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* 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 SAP AG 2006, Data Unification / 23

24 Formalizing Data Quality 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 SAP AG 2006, Data Unification / 24

25 Company Background Formalizing Data Quality What is Master Data? Data Modeling Approach Tops Down Physical Implementation Summary/Q&A

26 First - What is Master Data? 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 SAP AG 2006, Data Unification / 26

27 Company Background Formalizing Data Quality What is Master Data? Data Modeling Approach Tops Down Physical Implementation Summary/Q&A

28 Tops Down Approach to Data 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 SAP AG 2006, Data Unification / 28

29 Pre- Enterprise Commodity Data Model One Term, Many Definitions Material Planner Summarize by taxable area Tax Man Planning Categories SAP CRS Material Master (CIM) Reporting Material Group = Commodity Lowest Detail Spends Manager Summarized Grouping Spends Analyst SAP AG 2006, Data Unification / 29

30 Enterprise Driven Commodity Data Model Single Definition per Term Commodity Gatekeeper Material Planner Controlled Entry Tax Man SAP CRS Material Master (CIM) Material Group = Commodity Detail New Commodity Hierarchy Commodity plus Hierarchy Summarize by taxable area Reporting Summarized Grouping Detail Commodity Report Spends Manager Spends Analyst SAP AG 2006, Data Unification / 30

31 Enterprise Item Conceptual Model Item BOM Subject Area Item Product Material Subassembly Subject Area Product Subject Area Material Kit Direct Material Indirect Material Service Manufacturing Indirect Material Finished Good Intangible Product SAP AG 2006, Data Unification / 31

32 Company Background Formalizing Data Quality What is Master Data? Data Modeling Approach Tops Down Physical Implementation Summary/Q&A

33 Intel Master Data Direction Determining Best Fit for Record of Origin 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 Component MDM Master Data Management SAP AG 2006, Data Unification / 33

34 Intel Master Data Direction Determining Best Fit for Record of Origin 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 *ROO Record of Origin Single point of create for unique identifier SAP AG 2006, Data Unification / 34

35 SAP NetWeaver MDM will run on Intel Architecture 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 availability and 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 SAP engineering investment SAP AG 2006, Data Unification / 35

36 SAP NW MDM Live at Intel since Nov 2006 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 is gained 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 SAP AG 2006, Data Unification / 36

37 Lessons Learned 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 SAP AG 2006, Data Unification / 37

38 Summary: ROI savings estimated at $10-18m 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 SAP AG 2006, Data Unification / 38