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Master Data Management

Master Data Management

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Master Data Management

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  1. Master Data Management Why Should a DBA Care?

  2. Agenda • Master Data Management and the Data Base Professional • Master Data Management Issues • An approach to solving Master Data Management

  3. Making Sense Of It All

  4. Surrounding the DBA

  5. So, what’s of interest to the Data Base Professional • Companies are looking for • Cost reduction initiatives • Revenue generation initiatives • Cross-sell opportunities • ROI in 12 months or less • The Data Base Professional has a unique view into • Data Structures • Data Quality • Metadata • Enterprise data assets, especially those spanning multiple departments • The Data Base Professional has the unique position of interfacing between • The Physical • The Logical • The Enterprise

  6. Agenda • Master Data Management and the Data Base Professional • Master Data Management Issues • An approach to solving Master Data Management

  7. Master Data Management System New Applications What is Master Data Management? MasterData Existing Applications • Decouples master information from individual applications • Becomes a central, application independent resource • Simplifies ongoing integration tasks and new app development • Ensure consistent master information across transactional and analytical systems • Addresses key issues such as data quality and consistency proactively rather than “after the fact” in the data warehouse Existing Applications MasterData Existing Applications Historical /AnalyticalSystems MasterData

  8. … to serve customers What Who … by delivering products and services to them Product (SKU, Bundle, Part, Service, Assets) Party (Individual and Org Customer, Employee, Supplier, Partner, Citizen) … via effective understanding of their relationship with them Account (Financial account, loyalty points, agreement, contract) How Master Data Management 101:Strategic View • Enterprises exist … Location • Primary Domains • Product • Party • Account • Supporting Domains • Location

  9. Business Business Object in the Context of Other Objects Business Object with Interface Exposed as Services: Behavior Product Customer Specific Pricing • checkCredit() • fetchAddressHistory() • mergeAccounts() Value Proposition Standalone Business Object RDBMS, XML Repositories, Unstructured Content Rep. Customer Customer Customer Infrastructure MDM Builds on Infrastructure and Provides Context

  10. Web Site Contact Center Enterprise Systems Data Warehouse Business Processes Business Processes Business Processes Business Processes Operational Functions Operational Functions Operational Functions Operational Functions Root Cause Collaboration Collaboration Collaboration Collaboration Analytics Analytics Analytics Analytics Customer Customer Customer Customer / Shipping Customer / Shipping Product Product Product Product Location Location Location Location Symptom Supplier Supplier Account Order Order Order Order Analytic / Insight Analytic / Insight Analytic / Insight Analytic / Insight The key word in Master Data Management isn’t “Data” … it’s ”Management” • Many organizations attempted to address only the symptoms and have used: • Data cleansing tools • Data integration tools • Data-centric MDM • The result? They didn’t solve the problem, data is still out-of-synch, and they have one more siloed repository • In order to solve the problem completely, address the root cause – the functionality that manages the data • Collaboration – Data definition, creation, and synchronization with all consumers of data • Operations – SOA data management functionality • Analytics – Generate insight on master data Don’t confuse the symptoms with the root cause Other MDM vendors focus on the symptom (the data) and deliver data-centric tools. IBM is the only vendor who delivers Multiform MDM addressing the Management of master data for all uses and all domains.

  11. Symptom - Islands of key business data = no master dataSlow time to market for products,poor customer satisfaction,missed revenue opportunities • Today most companies have multiple repositories for key business data like customers, products, suppliers, locations, and accounts • This results in: • Inability to understand the value of the customer • Inconsistency in product data across systems • Missed revenue opportunity due to slow product introduction process • Inconsistent customer service across channels Web Site Contact Center Enterprise Systems Data Warehouse Customer Customer Customer Customer / Shipping Customer / Shipping Product Product Product Product Location Location Location Location Supplier Supplier Account Order Order Order Order

  12. A Customer … Name: Jane Smith Address: 123 Oak Account #: 44444 Transaction: purchased a gas grill A Product … Name: Gas Grill SKU: 1111111 Current Price: $550 A Location … Store #: 555 Symptom - A Distortion of realitySiloed data does not accurately represent key business facts Key Business Information Current Representation of Key Business Facts Web Site Contact Center Enterprise Systems Data Warehouse Jane Smith J. Smith Jane Smith-Brown 123 Oak Street Ship to: 123 Oak Gas Grill $550 Gas Grill $700 Prop. Grill $550 Propane Grill Store 555 Oakmill Store Store 555 Store 555 Grills Inc. Big Grill Corp. Account Purchased Gas Grill Purchased Tongs Purchased Gas Purchased Gas Grill Applications force you to manage data in silos and are not capable of accurately representing the key facts you need to run your business. Master Data Management is designed to manage a complete and accurate profile of all key data and provide each application with the appropriate profile.

  13. “77% of 144 CIOs surveyed identified single view of customer as the single most important benefit of MDM” Symptom - A deeper look at the customer data problemReduce customer satisfaction, decrease revenue, hinder relationships • Is a high value web customer Web Site Contact Center Data Warehouse • Companies quantify impact of bad customer data: • 66% indicate profitability of company as a whole was negatively affected by poor information quality • 75% indicate bad customer data quality is harming customer service, quality and loyalty • 52% identified integration of diverse systems as a major source of inaccurate information • Industry Drivers: Privacy Management, Basel II, “Do not Call” compliance, Patriot Act, Sarbanes Oxley, HIPAA Name: Jane F. Smith • Yet… to the call center she is completely unknown • Poor customer service • High cost of service due to “multi call resolution” Name: Jane Smith Name: Name: Jane F. Smith Address: Address: 123 Main St Address: 437 Easy St Cross-sell/Upsell Items: 5432, 4355 Preferences: Preferences: Sales History: Products 5748, 6574 Sales History: Products 1234, 5748 • Inability to act on customer insight leads to missed sales opportunities Account: Customer Value: HIGH Customer Value: Customer Value: HIGH

  14. Product SKU 11111 Product short description: Outdoor gas grill Symptom - A deeper look at the product data problemInconsistent Shopping Experience due to inconsistent data across channels. Web Site Contact Center Store • Gaining control over product information results: • Errors in data – 30% of data in retailers systems is wrong • Lost productivity – 25 minutes manual cleansing per SKU, per year • Slow time to market – 4 weeks to introduce new products • Invoice deductions – 43% of invoices result in deductions • Failed scans – up to 70,000 per week (1 large US Retailer) • Lost sales – up to 3.5% per year • Source: A.T. Kearney, GMA, AMR • Industry Drivers: RFID, Waste Electrical and Electronic Equipment Recycling, Product Information Exchange Standards, Return of Hazardous Substances, Global Data Synchronization, Sarbanes Oxley, etc. (Yankee Group, 2005) Outdoor Gas Grill Name: Jane F. Smith Name: Jane F. Smith Product: Outdoor grill Product: Gas Grill Product: Price: $550 *Special Price: Price: $550 *Special* Product: Gas Grill • Features: auto-shut off, rubber wheels, rotisserie, sound system • Price: Regular $700 • Price: Sale $550 Expiry Sep. 30 • Warranty 1 year • Return Policy 30 days Cross-sell/Upsell Items: 5432, 4355 Cross-sell/Upsell Items: Price: $700 Warranty: 1-year Warranty: Warranty: 1-year Features: Features: Auto shut-off, Rubber wheels, rotisserie Features: Sound system, Rotisserie Warranty: 1-year Stock: Features: sound system, rotisserie Return Policy: 30 days Return Policy: 30 days Return Policy: Return Policy: 30 days Return Policy: 30 days “79% of Retailers and 61% of CPG manufacturers rank “item management” as their top priority”

  15. Business Processes Business Processes Business Processes Business Processes Operational Functions Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Collaboration Analytics Analytics Analytics Analytics “Through 2010, fewer than 20 percent of large organizations will satisfy their single view of the customer requirement solely by using the data model and database beneath a vendors application suite.” Root Cause – Current systems are a barrier The “Master” Data Challenge Web Site Contact Center Enterprise Systems Data Warehouse • Which one is (or could be) the master for all key business data items? • Unfortunately, none of them can • They are all consumers (users) of data … they are not managers of that data • Different definitions of data • Different usage requirements for data • Only care about data from the narrow POV of their application business process Customer Customer Customer Customer / Shipping Customer / Shipping Product Product Product Product Location Location Location Location Supplier Supplier Account Order Order Order Order Analytic / Insight Analytic / Insight Analytic / Insight Analytic / Insight

  16. Root Cause – Current Applications have caused the master data problem Fragmented and incomplete data management functionality is the root cause of the master data problem Web Site Contact Center Enterprise Systems Business Processes Business Processes Business Processes • Each system has discrete and often contradictory functionality to manage data • Business processes – any process related to data management and is reusable across applications • Operational – functions for providing data to operational processes • Collaboration – functions to define, collaborate, and manage master data definition & creation • Analytics – functions to generate insight into data • Lack of consistency across the enterprise for master data functions is the root cause of the master data problem Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Analytics Analytics Analytics Customer Customer Customer Customer / Shipping Customer / Shipping Product Product Product Location Location Location Supplier Supplier Account Order Order Order

  17. Data is used by many applications, each for different reasons • That means that each application • Requires a unique set of data • Requires a unique set of functions to create and use that data • Requires different analysis of that data • The data lifecycle recognizes key facts • Data is dynamic • Data needs to be created, used, and analyzed in a variety of ways by data consumers • Data management requires its own lifecycle management – creation, usage, analysis, event detection, refresh schedule, subscription management – are all data-centric processes Root Cause - Understanding the data lifecycleApplication business processes arethe trigger for data creation, usage,and analysis – but their “siloed”functionality doesn’t address each others requirements

  18. Business Processes Business Processes Operational Functions Operational Functions Collaboration Collaboration Analytics Analytics Root Cause – Understanding the data lifecycle Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements Web Site Contact Center Enterprise Systems Business Processes • Product A is defined in the Enterprise system Operational Functions Collaboration Analytics Product Supplier

  19. Business Processes Operational Functions Collaboration Analytics Root Cause – Understanding the data lifecycle Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements Web Site Contact Center Enterprise Systems Business Processes Business Processes • Product A is defined in the Enterprise system • Enterprise product data is synchronized to the web store • Different definitions of data results in errors Operational Functions Operational Functions Collaboration Collaboration Analytics Analytics X Product Product Supplier Supplier

  20. Business Processes Operational Functions Collaboration Analytics Root Cause – Understanding the data lifecycle Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements Web Site Contact Center Enterprise Systems Business Processes Business Processes • Product A is defined in the Enterprise system • Enterprise product data is synchronized to the web store • Different definitions of data results in errors • A customer orders that product on the web store • Doesn’t identify the customer as a prior client • Web store captures a portion of the customer profile – first and last name, address, email address • Enterprise system processes to order and captures the client data only as a “ship to” address Operational Functions Operational Functions Collaboration Collaboration Analytics Analytics ? Customer Customer / Shipping Customer / Shipping Product Product Location Supplier Supplier Account Order Order

  21. Root Cause – Understanding the data lifecycle Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements Web Site Contact Center Enterprise Systems Business Processes Business Processes Business Processes • Product A is defined in the Enterprise system • Enterprise product data is synchronized to the web store • Different definitions of data results in errors • A customer orders that product on the web store • Doesn’t identify the customer as a prior client • Web store captures a portion of the customer profile – first and last name, address, email address • Enterprise system processes to order and captures the client data only as a “ship to” address • Product B is discounted in the Enterprise system • Change is not reflected in the contact center because the Enterprise system doesn’t understand who subscribes to that change Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Analytics Analytics Analytics Customer Customer / Shipping Customer / Shipping $ $ $ Product Product Product Location Location Supplier Supplier Account Order Order

  22. Root Cause – Understanding the data lifecycle Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements Web Site Contact Center Enterprise Systems Business Processes Business Processes Business Processes • Product A is defined in the Enterprise system • Enterprise product data is synchronized to the web store • Different definitions of data results in errors • A customer orders that product on the web store • Doesn’t identify the customer as a prior client • Web store captures a portion of the customer profile – first and last name, address, email address • Enterprise system processes to order and captures the client data only as a “ship to” address • Product B is discounted in the Enterprise system • Change is not reflected in the contact center because the Enterprise system doesn’t understand who subscribes to that change • Customer orders product B via the call center • Doesn’t get the correct discount • Call center captures a different customer profile – name, phone number, address Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Analytics Analytics Analytics Customer Customer Customer / Shipping Customer / Shipping Customer / Shipping $ Product Product Product Location Location Location Supplier Supplier Account Order Order Order

  23. Business Processes Business Processes Business Processes Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Analytics Analytics Analytics Root Cause – The end result, the majority of data is incorrect These are the key facts aboutyour business that directlyimpact your success Web Site Contact Center Enterprise Systems • Very quickly, data will become • Out-of-synch • Incomplete • Inaccurate • The root cause is separate application functionality for data-centric functionality • How many transactions does your organization process each day? • If the root cause is the application function itself, how can you keep up with the pace of enterprise data corruption Customer Customer Customer / Shipping Customer / Shipping Product Product Product Location Location Location Supplier Supplier Account Order Order Order

  24. Business Processes Business Processes Business Processes Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Analytics Analytics Analytics • Master data is treated as a data model and low-level data access functionality • “A common data model will solve your data problems” • Key master data management functionalityremains in the consuming applications(their application suite) • End result = data problems will continue and you will have “one more incorrect database” Web Site Contact Center Enterprise Systems Application Centric ViewApplication may notseparate master data functionfrom application function Master Data Management in Application Suite Limited Data Integration Capabilities Conclusion: ”Data Consumers don’t make good data managers”

  25. Business Processes Business Processes Business Processes Operational Functions Operational Functions Operational Functions Collaboration Collaboration Collaboration Analytics Analytics Analytics Niche Solution – Master Data Management from single-faceted perspectiveNiche solution often address onlyone usage pattern or domain, • Niche solution typically focus on only one domain and one usage scenario • But your requirements are for multi-dimensional usage of data across multiple domains • You end up starting with the vendor’s domain, then realize you can’t build upon what you have • Most of these vendors offer very limited integration functions – they attempt to integrate data but are not robust enough to perform Web Site Contact Center Enterprise Systems Analytical Product Operational Location Collaborative Customer Product Customer Customer Limited Data Integration Limited Data Integration Limited Data Integration Conclusion: ”You can’t get there from here with niche solution, it may not have the breadth of MDM functionality”

  26. As most data sources are also consumers the integration of data and applications is challenging. Keeping Data Integration in the picture Your infrastructure looks like this … …but data integration complexity is downplayed Integration is about more than having a set of staging tables or a message queue adapter

  27. Agenda • Master Data Management and the Data Base Professional • Master Data Management Issues • An approach to solving Master Data Management

  28. Customer Customer / Shipping Business Processes Business Processes Business Processes Business Processes Operational Functions Operational Functions Operational Functions Operational Functions Location Collaboration Collaboration Collaboration Collaboration IBM Master Data Management Customer Customer Customer Industry SOA Business Processes Analytics Analytics Analytics Analytics Customer / Shipping Customer / Shipping Product Product Product Product Location Location Location Collaborative MDM Operational MDM Analytical MDM Supplier Supplier Account Order Order Order Order Analytic / Insight Analytic / Insight Analytic / Insight Analytic / Insight Supplier Product Account Location Event Management Data Quality Management Data Lifecycle Mgmt Web Site Contact Center Enterprise Systems Data Warehouse • Separation of common data functionality into an enterprise application • Integration of data function via business services to serve all data consumers • Master data management is complementary to application processes • It provides applications with accurate and complete data about all key business entities A Harmonized Solution approachSeparation of applicationfunction from data functionto create common dataprocessing capabilities

  29. Understanding Data Managers v. Data ConsumersBuilding a system of checks and balances betweendata processes and application processes Data consumers are not designed for data management – their data management functionality is defined narrowly within the confines of the individual application.

  30. Multiform MDM Multiple Styles Collaborative MDM – Definition, creation, synchronization Operational MDM – SOA management of master data Analytical MDM – Analysis and insight Multiple Domains Support for multiple master data subject areas Enterprise business processes - SOA industry models Integrate master data with data consumers (business applications) Customer Customer / Shipping Master Data Management Industry SOA Business Processes Collaborative MDM Operational MDM Analytical MDM Supplier Product Account Location Event Management Data Quality Management Data Lifecycle Mgmt A Harmonized Approach to Master Data ManagementKey Characteristics Web Site Contact Center Enterprise Systems Data Warehouse

  31. Multi-Style Collaborative MDM Authoring, workflow, check in/out services to support collaboration on master data creation, management and quality control Operational MDM Business services to ingest master data from range of sources, manage it and fulfill all consumer uses of master data Over 500 Business Services Act as “System of Record” Analytic MDM Identity resolution & relationship discovery Master data simplifies input to analytical environments (DWs) and improves quality (MDM is source) Enterprise reporting and analytics Industry-specific data warehouses Multi-Domain Support for Customer, Product, Account, Location, Supplier …. Master Data ManagementCore Capabilities • Data Quality Management • Duplicate record processing • Data validation, cleansing & standardization • Event Management • Event detection & management • Notification to business processes and systems • Data Lifecycle Management • Data Governance • Data access management • Auditing, enterprise rules and policies

  32. Master Data Management ApproachKey Technology Aspects • Service Oriented Architecture • Standards-based, Open • Application and Process Neutrality • Domain-centrity/Multi-domain capable • Multi-styles capable • Highest Performance and Scalability • Extensibility, while safeguarding upgradeability • Flexibility and Modular • Reactive and proactive

  33. Customer Customer / Shipping Industry SOA Business Processes Collaborative MDM Operational MDM Analytical MDM Supplier Product Account Location Event Management Data Quality Management Data Lifecycle Mgmt Master Data ManagementCollaborative MDM • Flexible, scalable repository managing and linking product, location, trading partner, organization, and terms of trade information • Tools for modeling, managing, capturing and creating this information with high user productivity and high information quality • Integrating and synchronizing this information internally with legacy systems, enterprise applications, repositories and masters • Workflow and solutions for supporting multi-department and multi-enterprise business processes • Exchanging and synchronizing this information externally with business partners • Leveraging this information via many internal and external electronic and human touch points • MDM Process Services • Initiate NPI Workflow • Check-out Item • Publish Catalog

  34. Customer Customer / Shipping Industry SOA Business Processes Collaborative MDM Operational MDM Analytical MDM Supplier Product Account Location Event Management Data Quality Management Data Lifecycle Mgmt Master Data ManagementOperational MDM • Build from the ground up as an SOA solution • Extensive range of business services (500+) • Designed for integration with operational applications • Contains both large and fine grain services • Add customer (large grain) • Update account • Get product • Flexibility • Easily extend or build new services from existing services • Fit product to meet the process, not vice-verse • Business services are “intelligent” containing packaged and configurable interfaces to business logic components • MDM Business Services • Add Customer • Open Account • View hierarchy • profile

  35. Analytical MDM addresses the need to augment MDM operational services with “inline” decision support analytics for purposes of reducing risk of increased costs, regulatory or reputation damage such as through: Compliance Adherence Thread and Fraud Detection Conflict Management Note -- MDM integrates with traditional Analytics (Data Warehouses) as source of quality data to the DW and as consumer of DW information (e.g. lifetime value information) Customer Customer / Shipping Industry SOA Business Processes Collaborative MDM Operational MDM Analytical MDM Supplier Product Account Location Event Management Data Quality Management Data Lifecycle Mgmt Master Data ManagementAnalytical MDM • MDM “Inline” Analytics • Identify Thread/Fraud • Conflict of Interest • AML Alerts

  36. X-Sell / Up-Sell Items: 5432, 4355 Master Data ManagementThe complete master data profile • The master data profile provides the current, accurate and complete business entity data to all systems and channels • Maintains detailed data on all key business entities • Customers & parties • Product • Account • Hierarchies • Location • Relationships Master Data Services Customer: Jane Smith Supplier: Big Grill Co. Product: Gas Grill Account Cust. Ship-to Location Demographics: Income - $100,000 Interests - Running Age - 41 Relationships Household Daughter – Jenny Husband – John Employer – IBM Address: Home - 123 Main St Billing – 437 Easy St Privacy Preferences: Solicitation - No Life Events: Daughters Birthday Wedding Anniversary Agreements & Contracts Service Contract Warranty Sales History: Product 1234, 5748, 6574 Interaction History: Service Issue 4/23/06 Web Order 2/2/06 Store Order 1/5/06 Identifier IDs Customer Value: High ….. ….. …..

  37. MDM and Data Warehousing • Master Data Management (MDM) and Data Warehousing (DW) complement each other; they have significant synergies • MDM and DW provide quality data to the business but MDM is valuable beyond the DW for 2 reasons • Latency • Feedback Analytic Services (DW Models, Identity Services & Predictive Analytics ) Data Services Metadata • MDM and DW have different use cases • MDM provides a “golden” source of truth that is used collaboratively for authoring, operationally in the transactional / operational environment and supports the delivery of "quality" Master Data to a DW system • DW systems are a multidimensional collection of historical transactional data that may be include than Master Data used to determine trends and create forecasts • Introducing MDM enhances the value of existing DWs by improving data integrity and closing the loop with transaction systems

  38. Access Transport and Collaboration Delivery Web Browser Portals Web Services Devices Analysis &Discovery EmbeddedAnalytics Query, Search & Reporting Mining Metrics Visualization Identity Analytics Information Services Master Data & InformationIntegration Information Integrity Lifecycle Management Hierarchy & Relationship Mgmt Authoring Master Data Event Management ETL EAI EII Semantic Reconciliation Balance and Controls Data Services Metadata Services Content Services Data Repositories Unstructured Analytical Operational Master Data Metadata Security and Privacy Systems andInfrastructure Systems Management & Administration Network & Middleware Hardware & Software Data Sources Content Mgmt Applications Others.. MDM and Your Enterprise Architecture Master Data Management is a critical layer in an Information Architecture • Key differentiator – trust – IBM will be there, we’ve done it before – we have services, support, training to make this work! • Key message – MDM isn’t a standalone packaged application, it’s integrated with everything – you want to work with a vendor that understands integration infrastructure Legend: Master Data Management Services Master Data Integration Services Supports developing Information Intensive Solutions