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A Practical Approach to data cleaning David Stroud CEO 12th May 2010

A Practical Approach to data cleaning David Stroud CEO 12th May 2010. Agenda. sparesFinder introduction Key Issues Master data harmonisation Cleansing process Item Management & Governance Governance Issues and Process Key components of data quality / governance / MDM. Company profile.

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A Practical Approach to data cleaning David Stroud CEO 12th May 2010

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  1. A Practical Approach to data cleaning • David Stroud • CEO • 12th May 2010

  2. Agenda • sparesFinder introduction • Key Issues • Master data harmonisation • Cleansing process • Item Management & Governance • Governance Issues and Process • Key components of data quality / governance / MDM

  3. Company profile

  4. Customers 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

  5. “Beyond data cleaning”

  6. Key issues for our customers

  7. Data governance Unconsolidated data or systems Data Complexity Direct Cost of Data Group Benefits and Availability

  8. Content quality is fundamental Accurate, available master data 2. Govern Highly functional systems Basic systems Clean Poor content quality

  9. Before you start..

  10. Legacy Data Batches of Noun/ Modifiers Data life cycle process Quality Control & Approval Query Resolution Text Scanning and Keyword Identification Gap Assessment & Prioritization Data Improvement Cycle Classify, Normalize & Enrich Data Standards Cycle Cleansed Data Acceptance Noun- Modifier & Attribute Review Dictionary Acceptance Ongoing Data Quality Maintenance Gatekeeper Configuration & Integration Classification Mapping as required OEM / Vendor Relationship Settings Clean data to client systems

  11. Control vs. Efficiency

  12. Control decisions

  13. Cost vs. speed, quality and scope

  14. Scoping decisions

  15. Do you need a data quality tool? Research from 2007 by Ventana (http://www.ventanaresearch.com/

  16. Software tool demands

  17. Software and content • Masterpiece • Clean • Content • sparesFinder Dictionary or • Customer’s own taxonomy • OEM Catalogues • Gatekeeper • Govern • Insight • Report • Base Module • User Admin, Dictionary, Catalogue, Interfaces • VPI • Search

  18. Supporting services • Masterpiece • Clean • Professional Services • Data cleansing • Project Management • Data Extract and Load Content • Gatekeeper • Govern • Insight • Report • Base Module • User Admin, Dictionary, Catalogue, Interfaces • Professional Services • Dictionary Creation • Systems integration • Training (for all modules) • Professional Services • Data Governance process design • Ongoing specialist product advice and support Professional Services Consultancy to drive inventory reduction, supplier rationalisation and strategic sourcing programmes . • VPI • Search • Professional Services • Change management • Virtual store creation with key vendors • Transaction support

  19. Foundations

  20. Detailed taxonomy

  21. Classification mapping

  22. Multi Language

  23. Detail, help and classification

  24. Leveraging catalogues

  25. Parent Company Other Brands Part Number FunctionalEquivalent Competitor Brand Part Number Manufacturer Name / Part Number Old part number and other aliases, drawing number, supersessions OEM Part Number OEM Part Number Part Manufacturer (Brand ) Part Number Suppliers Distributor Part Number Distributor Part Number Alternate (e.g. wrong colour) Alternate Brand Part Number Alternate Supplier Primary Supplier

  26. Equipments / BOMs Equipment / Catalogue Specific Higher Assembly System Specific SAP Client 1: Material No XX • Client 1: Material No XY • Client 2: Material No ZZ Part Number Geography Specific 3 of Equipment Locations TAG 1-1-3 • TAG 2-6-9 Catalogue Master Maximo • DB 1: Item No AAC 8 of Component

  27. Single source of data

  28. Creating data quality Masterpiece Core Legacy Data Clean Data

  29. Data Cleansing

  30. Spares MDM Masterpiece Core Multi ERP Syndication New Item Clean Data Data Governance Organisation ERP Data Models

  31. ERP Attribute Management

  32. Corporate ERP Structures

  33. Adding a new item

  34. Checking functional matches

  35. Prioritising and tracking requests

  36. More than software Organization, policies and procedures, authorizations and controls in place to manage data on a long-term basis • Policy changes around item master creation, updates, deletions and approvals • Service levels and turnaround time agreement • Defined communication channels for requests Operating model enhancements to drive better data quality while retaining business intimacy Processes to maintain item master and keep classification codes and standards evergreen • Centralized vs. Centrally Managed vs. De-centralized vs. Outsourced • Reporting relationships • Roles and Responsibilities • Request and Approval processes – item add, change, delete • Notification to other data maintenance owners (BOM, Sales Pricing, etc.) for further item use or processing. • Item availability notification process Metrics to measure and monitor the efficiency and effectiveness of key business processes • Item creation/update cycle time • Percentage of shipments on hold • % of item master maintenance errors

  37. Thank You “Without sparesFinder’s tools we could never have achieved the savings that we have on a global scale. They combine ease of use with a high degree of sophistication, and reflect the deep level of MRO knowledge within the company. Our data cleansing project has resulted in far more efficient buying processes, higher levels of internal stock transfer, and significantly reduced duplication” John Vezey, BAT Global Spares Team.

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