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Beyond Ten Blue Links: Why Search-Driven Applications Matter to the Enterprise

Beyond Ten Blue Links: Why Search-Driven Applications Matter to the Enterprise. Mike Shine Sales Director, Central U.S. BA Insight. 5+ years experience with SharePoint Degree in Computer Engineering from Valparaiso University

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Beyond Ten Blue Links: Why Search-Driven Applications Matter to the Enterprise

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  1. Beyond Ten Blue Links: Why Search-Driven Applications Matter to the Enterprise Mike Shine Sales Director, Central U.S. BA Insight

  2. 5+ years experience with SharePoint Degree in Computer Engineering from Valparaiso University Helped lead large-scale search deployments at ADP, Pfizer, Exxon, CBS and others About Mike Experience Employed at BA Insight • ISV focused on Unified Information Access since 2004 • Technical Team Led by Jeff Fried, former Senior Product Manager for Microsoft Enterprise Search • 2.5M corporate users worldwide • Blog: http://www.bainsight.com/Pages/sharepoint-fast-search-blog.aspx

  3. Beyond Ten Blue Links

  4. Q&A

  5. 5-Step Enterprise Search Maturity Model Cloud Readiness Role-BasedApplications Information Management • Compliance • Info. Governance • Retention policies • Search as a Service • Information re-use Unified View • Personas • Composites • Expertise • 360° views • Information “Mash-Ups” • Vertical Solutions Siloed Search • Entity Extraction • Content Classification • Linguistics • Navigation • Aggregation • Multiple Data Sources • Data Access Layer • Diverse Content Types • Multiple Security Models • Information Mapping Goal: Access Device and Location Independence • 10 Blue Links • Optimized for HTML • Single Content Type • Same as Web • Point Solution Goal: User and application independence Goal: Enrich content to unleash the information in unstructured data Goal: Breakdown information silos Goal: Provide basic access to data

  6. Case Study: Pharma R&D R&D researched where it was spending its time, and discovered 56% of R&D time (human capital and budget) was spent: Duplicating existing research It blew them away, until they reviewed why…

  7. Case Study: Pharma R&D • Research done in separate groups • Seemingly unrelated research projects • Later in lifecycle (mfg, reg/test) Top 3 reasons for 56% effort duplication: • Data not accessible • Isolated content source • Restricted / limited access • Source not searchable • Special knowledge required • Data not linked • Various names/changes leave data disconnected • People not connected to data (experts) • Data managed in many unconnected systems

  8. Case Study: Pharma R&D Multiple Sources One Search Documentum Image SharePoint Doc Regulatory Record MEDLINE article Search: amgen 655 Relationships Discovered: Antibodies: mAb Receptors: DR5, IGF-1R Labs: Oncology 1 People: David Chang

  9. Search: Find and Explore Microwave ovens Viagra LSD Corn Flakes Uranus Safety glass Inkjet printers Infrared radiation Chocolate chip cookies Penicillin

  10. Information and application silos abound Marketing Sales Consulting Procurement Production Research Support HR / Legal Siloed UI Applications ContentSilos Search bridges silos; Search-Driven Applications serve specific populations

  11. Introducing "Paul" from SupportCustomer support – the hard way Time CRM DB CMS Agreements Wikis and blogs Intranet Issue DB 82 minutes 7 minutes 10 minutes 5 minutes 15 minutes 20 minutes 15 minutes 10 minutes

  12. Introducing "Paul" from SupportCustomer support – the hard way Time 82 minutes 7 minutes 10 minutes 5 minutes 15 minutes 20 minutes 15 minutes 10 minutes • Challenges; • Time to resolution = Cost • Quality on solution and cost of reworking information • Customer satisfaction • Frustration

  13. Where is “Paul” looking for information? A B Line Of Business Applications Other content sources Fileshares Product catalogues Public web stites Extranet Content Unstructured data Structured data

  14. The “spaghetti” infrastructure Sales Commerce Extranet .com Intranet Fileshares Product catalogues Public web stites Extranet Content Unstructured data Structured data

  15. The concept Support Sales Commerce Extranet .com Intranet Solutions and services Interaction Enterprise Search Platform Platform Data Capture and Enrichment CRM Finance Intranet Fileshares Product catalogues Public web stites Content Sources Technical information People Extranet Content Sales and marketing Unstructured data Structured data

  16. Introducing "Paul" from SupportCustomer support – the hard way Time CRM DB CMS Agreements Wikis and blogs Intranet Issue DB 82 minutes 7 minutes 10 minutes 5 minutes 15 minutes 20 minutes 15 minutes 10 minutes

  17. What if?Customer support – the new way Time 1 minute 2 minutes 3 minutes Search platform CRM DB CMS Agreements Wikis and blogs Intranet Issue DB

  18. FAST and SharePoint Support Search-Driven Applications Search-Driven Applications are found in every industry and every function Traditionally, search vendors describe these as possibilities using their platforms; but implementation costs have been >$1M Packaged apps are now possible, leveraging the SharePoint ecosystem

  19. Anatomy of a search-based application: Matter-centric dashboard (Legal Vertical) Invoice Graph Source: Aderant Attorney Billing Source: Aderant Graphical Navigation Emails Source: Exchange Documents Source: Hummingbird

  20. Anatomy of a search-based application: Matter-centric dashboard (Legal Vertical) 1 2 3 4 Setup in days Documents Emails Invoices

  21. Legal Research example Attorneys spend too much time looking for information and assessing the relevancy of search results • Must download entire document and conduct manual review to determine relevancy • No way to internally search documents & items • Excessive burden to network resources for geo-distributed offices • No way to quickly review, annotate , compile, and reuse relevant information

  22. Legal Research Search-Driven Application Demo Information from multiple source systems in one index Metadata enrichment during indexing Document Preview and Assembly

  23. One index, multiple search-driven applications Best Practicecs • Involve the end users • Do business case app by app • Do each app in iterations • Use components

  24. Data Growth and Transformation 2006 2010 2015 Source: IDC (1 Exabyte = 1 Million Terabytes) 30% Unstructured Data State of the Enterprise 60% Unstructured Data 90% Unstructured Data 161 Exabytes 10+ Data Silos 988 Exabytes 80+ Data Silos 8,000 Exabytes 500+ Data Silos • “Orphaned” (uncategorized) data inhibits implementation of robust information strategy • Widespread duplication of effort across business units, subsidiaries • Data proliferating exponentially • 60% Year over Year Growth (Gartner) • Business unable to get a holistic view of data across numerous content repositories

  25. Unstructured Content needs Gardeners

  26. Metadata is also used for relevancy tuning, multi-level sorting and advanced search Metadata is at the heart of great Search Apps • Use Search Prototype to understand what metadata you have • Create Metadata by Machine • Entity extraction • Hierarchical classifiers File Formats , Precise hit counts in deep refiners are computed across the whole result set. Companies Products Concepts And many more… Enables deep refinement Enables precision relevancy

  27. Creating Metadata by Machine:Entity Extraction vs. AutoClassification • Entity Extraction (OOB in FAST) • Open Vocabulary: people, places, organization • Closed Vocabulary: projects • OOB, Custom, and 3rd Party (for FAST and for SharePoint Search) • Each Entity is detected each time (can provide counts) • Hierarchical Classifiers (not OOB, add-on) • Works on hierarchies • Europe->France->Paris vs. • North_America->USA->Maine->Paris • Tags once for whole document “Process in Place” vs. “Process during Indexing”

  28. Customizing Search IP Portfolio mgmt Intel/Surveillance Drug Discovery …. Intranet Search People Search Site Search Research Portal Case Management Save Results to Excel file …..

  29. FAST Search for SharePointDesigned for Customization … Format Conversion Lemmatization EntityExtraction Language Detection Mapper User Context Metadata Creation Content Processing Pipeline Content OpenSearch Query Processor Indexer Content Processor Crawler Federation People Search Search Center User Profiles Index Partition User Experience Federation Relevance Control Indexing Connectivity

  30. iManage Elite PM data bios SharePoint Server People Search (+mysites, etc) Profile store Example add-on:Expertise Search Custom Web Parts + Pages BA-Insight Connectors FAST Search for SharePoint Content Processing Indexing Relevence Ranking Grouping • Connect to: • HR systems • Billing systems • Content Repositories • Group content by people • Find experts based on best content match • Push to Profile Store • Consolidated profile • Improved people search & mysites Search Center Other Content Sources (newsgator, etc) Content Acquisition End User Experience Search Platform (w/configuration)

  31. Tips for successful SDA projects built on FAST • Start early with OOB experience • Stand up FAST, show it to users • Keep an active staging system • Full scale, with production content • Search exposes/’audits’ security issues! • Grow incrementally & continually • Additional content sources • Design and feature changes and additions • Content grooming / gardening • Use regular rhythm to debug/tune • Don’t be afraid to customize • Buy what you can, build what you can’t • Establish success early, build on • Many search apps will emerge

  32. One index, multiple search-driven applications Best Practicecs • Involve the end users • Do business case app by app • Do each app in iterations • Use components

  33. Search-Oriented Architecture Marketing Sales Consulting Procurement Legal Research Compliance HR Knowledge Center Inventory Reuse Research Portal Expertise Finding Competitive Intelligence Early Case Assessment Compliance Dashboard Customer 360 View Dynamic Visualization Structured Data Preview Document Preview Metadata Navigation Self-Learning Relevancy Data & Text Analytics Entity Extraction Relationship Extraction Auto-Classification Metadata Mapping Security Mapping Usage Analytics Connector Framework Structured Data Connectors Unstructured Data Connectors Metadata Auto-Discovery Search Engine Federator Search Platform Indexing Pipeline Query Pipeline Pipeline Unified Data Store (Index) Crawling CRM ERP ECM, Search, Collaboration Unstructured data (file shares) Structured data (databases) Public web sites Data Silos

  34. Component approach to SDAs • Similar Patterns across Industries • Component-based Example Mockup

  35. How FAST and SharePoint “change the equation”RelativeCost of a ‘typical’ Search-Driven Application

  36. SharePoint 2010 Search Comparison

  37. Takeaways

  38. Thank You Mike Shine Sales Director, Central U.S. 312.878.4030 Mike.Shine@bainsight.com www.BAinsight.com

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