CON8747 Oracle Fusion Product Hub: The Foundation for Your Enterprise Product Information

2. CON8747Oracle Fusion Product Hub: The Foundation for Your Enterprise Product Information Sachin PatelDirector, PIM/PLM Product Strategy, Oracle Shyam Lakshman Director, Product Mgmt, Oracle Brian Mericle Director of Information Technology, O ‘ Reilly Media

3. Safe Harbor The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

4. Program Agenda • Business Challenges • Solution Overview • Roadmap • Product Demonstration • Customer Case Study : O ‘ Reilly Media

5. Business Challenges

6. What Happens When Data Inconsistent Across Your Enterprise? “Why are the product specifications different at the store than on the Web?” “When I go online, I can’t easily find what I need. It’s too complicated to find what’s best for me.” Web Catalog/ Direct Mall Store “The call agent had no idea of who I was or what was in my shopping cart!” “How come the products and prices are different in the catalog and store?” E-Mail Call Center “Wouldn’t it be nice if they gave me some product promotions for the friends I have referred?” “I got invoiced for the wrong products?” Social

7. Repercussions of Inconsistent product data Inconsistent information can cause confusion and lead to lost sales Inconsistent Inconsistent

8. How much do you Trust your Data? Source: Drive Business Performance with Product Information Management Aberdeen Group, Sep 2013

9. Solution Overview

10. Centralized Interface to On-Board Product Data Review, Remediate and Import from a Centralized Location • Load item data received in supplier specific file formats • Create a one-time mapping of CSV, XML and other common file formats • Use direct mappings or expressions to transform supplier fields to master fields • Associate Import Maps to one or more suppliers • Upload File from Different Sources • Create Mapping for Different File Types including CSV, XML • Preview Supplier Data Mapped to Product Hub Fields Prior to Import • Drag and Drop to Map Supplier Data to One or More Master Data Fields

11. Embedded Data Quality 1 2 Real-Time Embedded Data Quality with EDQP Auto-Classifies, Standardizes, Parses Attribute Values and Checks for Duplicates Item creation in FPH could potentially begin with non-standard description and no classification 3 Unique Item created in FPH with standard description, appropriate classification and auto-populated attribute values

12. Centralize Management of Enterprise Product Data Extensible and Scalable Enterprise Product Data Model Categorizations in eCommerce, Print, UNSPC, Merchandising, Financial Reporting and other alternate hierarchies Associations to internal stores, suppliers, target markets and channels Sales bundles and configurations Unlimited number of product attributes Business user defined attributes to model marketing attributes, product features, design specifications, etc Cross-sell, up-sell, warranty, and other seeded and user defined product relationships Seeded attributes for the operational needs of the enterprise (Sales and Order Management, Planning, Inventory…) Foundation for Enterprise Product Record People who can view and edit product data Digital assets including images, videos, user manuals and other unstructured data

13. Data Governance Enforcement and Analytics • Key Features • Orchestrate collaborative product definition through a flexible workflow that meets your organizational structure and business needs • Implement changes through a streamlined review and approval process • Enforce business and governance policies via rules and perform what-if analysis • Schedule product changes for a future date through granular version control • Control view and edit privileges through role based and data level security • Monitor key product and governance related information with embedded product data analytics

14. Empower Business Users to Drive Product Data PublicationControl Which Product Data Entities are Published to Which Consuming Systems Consuming System: Web Channel Business Entities to Publish: Products and Catalogs Product Data Entities to Publish: Attributes, Relationships & Digital Assets Product Selection Criteria: ONLY Server Products Catalog Publication Criteria: ONLY eCommerce Catalogs

15. Fusion Product Hub: Deployment Flexibility On-Premise Private Cloud Public Cloud Hybrid

16. Roadmap

17. Oracle Applications: Current Release and Roadmap Oracle Fusion Product Hub • Data Consolidation • Data On boarding for Native Formats using Import Maps • Data Management and Enrichment • Rich Text Format Long Descriptions • Inline Mass Updates through user interface • Inline Images in Compare/Search • Data Governance and Quality • Real-Time/Embedded Data Cleansing, Classification and Standardization • Dynamic Rule-Based Policy Enforcement and What-If Analysis • Cross Entity Business Rules • Role based and Data Level Security • Data Publication • User Defined Criteria for product and catalog publication • Validation Rules for Product Publication • Partner based Print Catalog Integration • Cloud Enablement • File based Import and Export through Secure FTP • Data Consolidation • Self Service Data On-boarding via Product Portal (Vendors/3rd Party) • GDSN infrastructure for on-boarding supplier data via GS1 data pools • Bulk upload and association of digital assets • Visual batch summary • Dedicated batch error management UI • Data Management and Enrichment • Matching by Manufacturer Part Numbers • Matching by GTINs • Audit Trail and Reporting • Item/Web Preview • Carousel View and Thumbnail Visualization for Multiple Images • Data Governance and Quality • Matching by Manufacturer Part Numbers, GTIN • Data Publication • Target System Publication Preview • Integration to Oracle Commerce and RMS • Cloud Enablement • Rich and Secure Cloud based Web Services • Data Consolidation • Vendor Data Upload/Quality Scoring and Metrics • Vendor Collaboration and Social Interaction • Data Management and Enrichment • Digital Asset Meta data Search and Embedded Workflow • Advanced Catalog Management • Extensible Business Context for Product Data • Product Data Relationship Viewer • Data Governance and Quality • Individual Object History/Audit Report • Change Definition Steps/ • Mobile based Change/NIR Review and Approval • Embedded Completeness & Conformity Metrics • Enhanced BI Reports • Data Publication • Desktop Publishing Templates and Style Tags • Cloud Enablement • Enhanced Cloud Based Services Release 7Aug 2013 What’s Next 0-12 month planning cycle Future DirectionsPost 12 month planning cycle

18. Product Hub Portal* – Self Service UI for Vendors/Partners 1 Download Category Specific Templates Review Validation Errors Grouped by Error Types 3 2 4 Remediate Data Errors and Re-Upload Files Upload Product Data and Digital Assets in Various File Formats

19. Demand side GDSN Framework • GDSN Subscription UI • GDSN Item Batches • GDSN standard response messages triggered directly from Item Batches • Message exchange history • Partner based interfaces to GS1 data pools Import Workbench (UI & Staging Tables) Subscriptions Process Orchestration GDSN Integration Connector CIC, CIS, RFCIN GS1 Data Pool (1Sync ) Confirmation Supplier Data Fusion Product Hub Fusion Product Hub Integration Framework CIN, CIC-R, CIS-R, RFCIN-R Status

20. Product Demonstration

21. Fusion Product Hub Demonstration • Karen Curtis (Product Data Steward), Kevin Schott (Brand Product Manager • Efficiently consolidate product data from suppliers • Govern product data and analyze impact of new policies • Discover and enrich product data seamlessly • Scenario

22. Customer Case: O ' Reilly Media Inc

23. O’Reilly Media, Inc. Oracle’s Fusion Product Hub Cloud Service: The Foundation of O’Reilly’s Enterprise Product Information Brian Mericle Director of Information Technology @ O’Reilly Media, Inc. 23

24. Agenda • About O’Reilly • Business Challenges • Technical Challenges • Desired Product Management Solution • Current Systems Architecture • Future Systems Architecture • Vendor Selection Process • Vendor Recommendation • Implementation • Lessons Learned • Questions 24

25. O’Reilly - “spreading the knowledge of innovators” • About the Company • Founded in 1978 by Tim O’Reilly • Offices in US, UK, Germany, Japan, and China • Privately held • ~400 employees • Publishing/Distribution • Books (print and digital) • Videos • Conferences • OSCON, Velocity, Fluent, Strata, Cultivate • Online • oreilly.com, shop.oreilly.com, radar.oreilly.com, programming.oreilly.com • O’Reilly School of Technology • Safari Books Online 25

26. Business Challenges • Our business is changing • Print distribution is being overshadowed by digital • Content is being consumed in an ever increasing variety of ways • Content time to market is a key differentiator • Transitioning from standard publishing model to content model • Increased distribution of 3rd party content • Need to support exponential volume growth on oreilly.com • Current product management solution concerns • Data model not easily extensible • Data attributes editable in multiple places • Hidden business rules expressed in multiple places • Inconsistent workflows • Limited data management (developer access only) • Very limited data quality and validation 26

27. Technical Challenges • Existing systems and processes are expensive to maintain • Multiple sources of truth (Relational DB, XML DB, RDF Triplestores) • ~5% of tickets focus on business enhancements, the rest are supporting lack of data quality • Process relies on 24 different systems with 31 different integration points • Developer ramp up time is 2-3 months • Data changes take ~2 ½ hours to reach production (best case scenario) • Every change to the system requires developer interaction • Difficulty creating separate test environments due to the number of integrations 27

28. Desired Product Management Solution • Minimize developer interaction • Maximize business interaction and control • Definable workflow, business rules, and attribution • User management, notification management • Ability to achieve clean, consistent and accurate data • Allows definition of multiple product hierarchies • Easily model new product types • Aligns security model against product hierarchy • Bulk import/export capabilities • Integration with our existing BI application • Supports internationalization out of the box • Utilize existing SSO capability • Programmatic (service enabled) access to product data 28

29. Current Systems Architecture 29

30. Future Systems Architecture 30

31. Vendor Selection Process • Hired 3rd party company to aid with research • Articulated our business goals and requirements • Documented and ranked required features • Evaluated four different solutions through numerous demonstrations and meetings • Sent RFP to two vendors, and evaluated ourselves as a 3rd vendor • Ranked responses based on 34 weighted categories that rolled up to Technical Requirements, Functional Requirements, and Vendor/Application Profile • Process spanned ~6 months 31

32. Vendor Recommendation • Oracle Fusion Product Hub Cloud Service • Advantages • Infrastructure management • Upgrade and patch management • Pricing (lowest cost of ownership) • Supports future IT cloud strategy • Early Adopter Program • Enhanced Oracle support • Experienced Oracle implementation partner • Key Features • Decreased IT responsibility • Increased business ownership and responsibility • Flexible product taxonomy definitions • Flexible product attribute definitions that can be securely managed • Easily create new product types • Definable product rules 32

33. Phased ImplementationFocus on Video Products Only (~500 products) • Phase 1 (Jan 2013 - April 2013) • Complete Product Hub Setups • Standard Product Hub setups (UAT) • Business Definition of supporting data • Creation of supporting data in Product Hub (UAT) • Define Video Product Taxonomy • Business Definition of Video Product Model • Product Model Creation in Product Hub (UAT) • Mock Conversion (export/transform/import) (UAT) • Clone UAT to Create Production • Standup Service Bus Infrastructure 33

34. Phased Implementation (cont’d) Focus on Video Products Only (~500 products) • Phase 1.1 (May 2013 – July 2013) • Build service to handle product hub data export • Final video product conversion to Product Hub (production) • Create user training documentation and train the users • Video products are “source of truth” in Product Hub in mid July (production) • User acceptance testing • Minor enhancements • Phase 2 (TBD 2014) • Business definition of all other product models • Product model creation in Product Hub • Final product conversion to Product Hub • Programmatic access to Product Data (via Product Hub Web Services) • Decommission existing product metadata stores 34

35. Lessons Learned • Experienced implementation partner was important for us • Don’t underestimate current state to future state planning • Consider data governance from the beginning and assign a data steward, preferably a business user • Don’t underestimate knowledge transfer from implementation partner to internal resources • We thought we could use the manual file-based import/export approach, but soon realized that the our backend integration was taking longer than expected and wouldn’t scale to our needs. Web Service approach to be used in Phase 2. • Although standard attributes were available in the BI application (OTBI), our required custom defined attributes were not exposed. 35

36. Thank You! Questions? Contact: Brian Mericle bmericle@oreilly.com 36

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