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Taxonomy Development An Infrastructure Model Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services

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Presentation on theme: "Taxonomy Development An Infrastructure Model Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services"— Presentation transcript:

1 Taxonomy Development An Infrastructure Model Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services

2 2 Agenda Introduction The Enterprise Context – Making the Business Case Infrastructure Model of Taxonomy Development – Taxonomy in 4 Contexts Content, People, Processes, Technology Infrastructure Solutions – the Elements Conclusion

3 3 Business Case for Taxonomies: The Right Context Traditional Metrics – Time Savings – 22 minutes per user per day = $1Mil a Year – Apply to your organization – customer service, content creation, knowledge industry – Cost of not-finding = re-creating content Research – Advantages of Browsing – Marti Hearst, Chen and Dumais – Nielsen – Poor classification costs a 10,000 user organization $10M each year – about $1,000 per employee. Stories – Pain points, success and failure – in your corporate language

4 4 Business Case for Taxonomies: IDC White Paper Information Tasks – Email – 14.5 hours a week – Create documents – 13.3 hours a week – Search – 9.5 hours a week – Gather information for documents – 8.3 hours a week – Find and organize documents – 6.8 hours a week Gartner: Business spend an estimated $750 Billion annually seeking information necessary to do their job. 30-40% of a knowledge workers time is spent managing documents.

5 5 Business Case for Taxonomies: IDC White Paper Time Wasted – Reformat information - $5.7 million per 1,000 per year – Not finding information - $5.3 million per 1,000 – Recreating content - $4.5 Million per 1,000 Small Percent Gain = large savings – 1% - $10 million – 5% - $50 million – 10% - $100 million

6 6 Business Case for Taxonomies: The Right Context Justification – Search Engine - $500K-$2Mil – Content Management - $500K-$2Mil – Portal - $500-$2Mil – Plus maintenance and employee costs Taxonomy – Small comparative cost – Needed to get full value from all the above ROI – asking the wrong question – What is ROI for having an HR department? – What is ROI for organizing your company?

7 7 Infrastructure Model of Taxonomy Development Taxonomy in Basic 4 Contexts Ideas – Content Structure – Language and Mind of your organization – Applications - exchange meaning, not data People – Company Structure – Communities, Users, Central Team Activities – Business processes and procedures – Central team - establish standards, facilitate Technology / Things – CMS, Search, portals, taxonomy tools – Applications – BI, CI, Text Mining

8 8 Taxonomy in Context Structuring Content All kinds of content and Content Structures – Structured and unstructured, Internet and desktop Metadata standards – Dublin core+ – Keywords - poor performance – Need controlled vocabulary, taxonomies, semantic network Other Metadata – Document Type Form, policy, how-to, etc. – Audience Role, function, expertise, information behaviors – Best bets metadata Facets – entities and ideas –

9 9 Taxonomy in Context: Structuring People Individual People – Tacit knowledge, information behaviors – Advanced personalization – category priority Sales – forms ---- New Account Form Accountant ---- New Accounts ---- Forms Communities – Variety of types – map of formal and informal – Variety of subject matter – vaccines, research, scuba – Variety of communication channels and information behaviors – Community-specific vocabularies, need for inter-community communication (Cortical organization model)

10 10 Taxonomy in Context: Structuring Processes and Technology Technology: infrastructure and applications – Enterprise platforms: from creation to retrieval to application – Taxonomy as the computer network Applications – integrated meaning, not just data Creation – content management, innovation, communities of practice (CoPs) – When, who, how, and how much structure to add – Workflow with meaning, distributed subject matter experts (SMEs) and centralized teams Retrieval – standalone and embedded in applications and business processes – Portals, collaboration, text mining, business intelligence, CRM

11 11 Taxonomy in Context: The Integrating Infrastructure Starting point: knowledge architecture audit, K-Map – Social network analysis, information behaviors People – knowledge architecture team – Infrastructure activities – taxonomies, analytics, best bets – Facilitation – knowledge transfer, partner with SMEs Taxonomies of content, people, and activities – Dynamic Dimension – complexity not chaos – Analytics based on concepts, information behaviors Taxonomy as part of a foundation, not a project – In an Infrastructure Context

12 12 Taxonomy in Context: The Integrating Infrastructure Integrated Enterprise requires both an infrastructure team and distributed expertise. – Software and SMEs is not the answer - keywords Taxonomies not stand alone – Metadata, controlled vocabularies, synonyms, etc. – Variety of taxonomies, plus categorization, classification, etc. Important to know the differences, when to use which Multiple Applications – Search, browse, content management, portals, BI & CI, etc. Infrastructure as Operating System – Word vs. Word Perfect – Instead of sharing clipboard, share information and knowledge.

13 13 Infrastructure Solutions: The start and foundation Knowledge Architecture Audit Knowledge Map - Understand what you have, what you are, what you want – The foundation of the foundation Contextual interviews, content analysis, surveys, focus groups, ethnographic studies Category modeling – Intertwingledness -learning new categories influenced by other, related categories Natural level categories mapped to communities, activities Novice prefer higher levels Balance of informative and distinctiveness Living, breathing, evolving foundation is the goal

14 14 Infrastructure Solutions: Resources People and Processes: Roles and Functions Knowledge Architect and learning object designers Knowledge engineers and cognitive anthropologists Knowledge facilitators and trainers and librarians Part Time – Librarians and information architects – Corporate communication editors and writers Partners – IT, web developers, applications programmers – Business analysts and project managers

15 15 Infrastructure Solutions: Resources People and Processes: Central Team Central Team supported by software and offering services – Creating, acquiring, evaluating taxonomies, metadata standards, vocabularies – Input into technology decisions and design – content management, portals, search – Socializing the benefits of metadata, creating a content culture – Evaluating metadata quality, facilitating author metadata – Analyzing the results of using metadata, how communities are using – Research metadata theory, user centric metadata – Design content value structure – more nuanced than good / poor content.

16 16 Infrastructure Solutions: Resources People and Processes: Facilitating Knowledge Transfer Need for Facilitators – Amazon hiring humans to refine recommendations – Google – humans answering queries Facilitate projects, KM project teams – Facilitate knowledge capture in meetings, best practices Answering online questions, facilitating online discussions, networking within a community Design and run KM forums, education and innovation fairs Work with content experts to develop training, incorporate intelligence into applications Support innovation, knowledge creation in communities

17 17 Infrastructure Solutions: Resources People and Processes: Location of Team KM/KA Dept. – Cross Organizational, Interdisciplinary Balance of dedicated and virtual, partners – Library, Training, IT, HR, Corporate Communication Balance of central and distributed Industry variation – Pharmaceutical – dedicated department, major place in the organization – Insurance – Small central group with partners – Beans – a librarian and part time functions Which design – knowledge architecture audit

18 18 Infrastructure Solutions: Resources Technology Taxonomy Management – Text and Visualization Entity and Fact Extraction Text Mining Search for professionals – Different needs, different interfaces Integration Platform technology – Enterprise Content Management

19 19 Conclusion Taxonomy development is not just a project – It has no beginning and no end Taxonomy development is not an end in itself – It enables the accomplishment of many ends Taxonomy development is not just about search or browse – It is about language, cognition, and applied intelligence Strategic Vision (articulated by K Map) is important – Even for your under the radar vocabulary project Paying attention to theory is practical – So is adapting your language to business speak

20 20 Conclusion Taxonomies are part of your intellectual infrastructure – Roads, transportation systems not cars or types of cars Taxonomies are part of creating smart organizations – Self aware, capable of learning and evolving Think Big, Start Small, Scale Fast If we really are in a knowledge economy We need to pay attention to – Knowledge!

21 Questions? Tom Reamy KAPS Group Knowledge Architecture Professional Services

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