2/6/08 Managing Master Data for Supply Chain Excellence Greg Valdez Director, Master Data Engineering Intel Corporation.

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Presentation transcript:

2/6/08 Managing Master Data for Supply Chain Excellence Greg Valdez Director, Master Data Engineering Intel Corporation

2 Managing Master Data for Supply Chain Excellence  Why focus on Master Data?  Intel’s Experience –Applying Quality Methods to Information –Strategies for Best Results  Q&A

3 Why Focus on Master Data? Every Supply Chain Activity is Dependent on High Quality Master Data AgilityAgilityVisibilityVisibility ExecutionExecutionPlanningPlanning

4 Location Financial Item BOM The Master Data Foundation Product Master Data & Organization EmployeeSupplierCustomer Transaction Systems (ERP,MES) Planning, Analytics Systems Supports the universe of Transactions & Decisions Supports ALL business processes Consistent Master Data Enables Faster & Better Decisions Across the Enterprise

5 Formalizing Information Quality at Intel  Corporate wide information quality initiative began in 2001  Formed a dedicated Information Quality Organization  Included targeted training & objectives tied to bonuses  Elevated Awareness Across the Enterprise  Data is an asset - “It outlives the systems”  Quantified the impact of poor data quality  Redundancy, Excessive process TPT, scrap & rework Mindset change to manage master data as a business capability, not IT infrastructure

6 Quality Methods for Information P1 Assess Data Definition & Informatio n Architectur e Quality P1 Assess Data Definition & Informatio n Architectur e Quality P2 Assess Informa tion Quality P2 Assess Informa tion Quality P3 Measure Nonquality Informatio n Costs P3 Measure Nonquality Informatio n Costs P4 Reengineer And Cleanse Data P4 Reengineer And Cleanse Data P5 Improve Informatio n Process Quality P5 Improve Informatio n Process Quality P6 Establish the Information Quality Environment P6 Establish the Information Quality Environment Information Value/Costs Information Value/Costs Cleansed Data Information Quality Improvement Information Quality Improvement Define it Measure it Impact ? Fix the Data Fix the Root Issues Paradigm Shift ? ? Quality ® TiQM is a register trademark of InfoImpact Inc. TIQM ® 1.Define it 2.Measure it 3.Cost of Non Quality 4.Improve the Data 5.Improve the Process 6.Establish IQ Environment Blueprint Product Specification Product Specification Data Definitions Data Definitions Data (re)-Building Manufactured Product Manufactured Product Information Product Information Product Quality Methods Drive the Right Sustainable Result Quality Methods Drive the Right Sustainable Result

7 Strategies for Best Results  Right Timing  Leverage & Drafting  One Size Does Not Fit All  ‘Mainstream’ Roles  Competency Development  Strategic Partnerships  Right Timing  Leverage & Drafting  One Size Does Not Fit All  ‘Mainstream’ Roles  Competency Development  Strategic Partnerships

8 An Orchestration of Strategies Governing To The Design Standards The Design: Business Data Application Technology The Design: Business Data Application Technology The Blueprint/ Design Spec The Blueprint/ Design Spec Inspect for Compliance to the Design/Standards Inspect for Compliance to the Design/Standards The Architect The Customer The Customer The General (deliver the solution) The General (deliver the solution) The Solution The Solution Business Process Engineering Business Process Engineering Software Engineers Software Engineers Hardwa r e Engine e r s Hardwa r e Engine e r s The Blueprint The Missing Link! I am missing the BOM Corporate mandate to re-implement Standard SAP ImprovedMasterDataImprovedMasterData Master Data Management ROO/ROR For each attribute Distribution Consolidation Administratio n UI Workflow DSS App Business Owned Create/Maint/Steward Profile & Dashboard Industr y Referen ces Trans, DSS Apps Dispar ate Source s SAP SQL Server, Terada ta, Oracle, MD Use Cases SAP SQL Server, Teradata, Oracle, Trans Apps Business Rules Mapping Standardize Merge Cleansing Leverage Business ‘Pull’ Governance & Asset/Product Mgt Roles MDM Capabilities

9 Data Management Capability Reference Model Distribution DSS App Profile & Dashboard MD Use Cases ERP non-ERP, EDW, Other DB’s Trans Apps Consolidation Industry References Trans, DSS Apps Disparate Sources ERP non-ERP, EDW, Other DB’s Business Rules Mapping Standardize Merge Cleansing Develop & sustain MDM competencies Business Owned Create/Maint/Steward Master Data Management ROO/ROR For each attribute Administration UI Workflow

10 Supplier Master Data Capability Roadmap Q1 Q2 Q3 Q Data Governance Compliant ROO/ROR Business Process Information Blueprint v. 1.0 Information Blueprint v. 2.0 Add Spec to SGB Training / Education Information Blueprint Continuous Improvement Conversion Strategy For Illustrative Purposes Conversion Execution (Stage 1) Supplier Interim Next Gen ROO SAP BI ROR Teradata ROR Portal w. workflow (Rev. 2) Search & Select (Basic) Lifecycle (Rev. 2) Enable EOL CVM Portal w. workflow (Rev. 1) Create / Change Spends Hierarchy Role-based Security Conversion Execution (Stage 2) If required Change Notification (Manual) Goal State ROO DUNS Data Quality CIP Supplier Add / Change TPT Reduction ROO / ROR Reduction Lifecycle (Rev. 1) Regulation Biz Process (Manual) Privacy Compliance D&B Data (DUNs, Family Tree, Diversity, etc) Preferred Supplier Next Gen ROO EOL PSG & PSMT EOL SDB External UI Integrated Services: Search & Select, Change Notification, Regulation DQ Monitors Master Data Product Manager Drives Stakeholder Alignment

11 Summary Managing Master Data for Supply Chain Excellence  Focus on Building a Strong Master Data Foundation  Practice the use of Information Quality Methods  Orchestrate Strategies for Best Results

2/6/08 Q & A

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