The Knowledge Management Infrastructure

1. The Knowledge ManagementInfrastructure Prof.E.Vandijck

2. “ If we only knew what we know at TI “ Jerry Junkins Former chairman , President and CEO of TI

3. Knowledge • Knowledge is a broader and more difficult to define concept than information. • We obtain knowledge when the information is also interpreted and therefore made usable. We get knowledge by creating associations and by earning insight.

4. The Pyramid Wisdom Knowledge Information Data

5. Types of Knowledge We can distinguish between two major types of knowledge • Tacit Knowledge • Explicit Knowledge

6. Tacit Knowledge • Tacit knowledge: resides in someone´s head, it does not exist in explicit form and is not easily transferred to others. • Undocumented • In people´s heads • A source of explicit knowledge • The highest-value knowledge is that held by employees • Experience • Insight • expertise

7. Explicit Knowledge • Explicit knowledge is stored in digitized form so that it can be viewed, read, used and applied. • Structured • Books, reports • Databases • Drawings • Methodologies • Trend analysis • Unstructured • Illustrations • Articles • E-mails, news • More directly usable

8. Forms of Knowledge Conversion Tacit knowledge Explicit knowledge Tacit Knowledge Explicit Knowledge Socialization Externalization Internalization Combination

9. Best for: Advantage: Limits: Examples: Capture and Codify Knowledge Multiple, Repeatable solutions Sharable by many Major conversion and maintenance Supply chain mngt SAP install Externalization of Tacit Knowledge • Provide guide to experts Innovative Unique solutions Low KM solution cost Demand on availability of experts Investment banking Strategic consulting Source: Gartner group

10. Payoff: Internal Sources: External Sources: New Intelligence Discover trends Anticipate Improve strategic action Employees, product, service and customer analysis E-commerce feedback New feeds Internet research Benefits of Explicit Knowledge • Asset Management Reuse elements Protect from loss Key employees Critical databases Critical business processes Market analysis Internet research Source: Gartner group

11. Benefits of Tacit Plus Explicit Knowledge • Solution support • Applying pragmatic experience to replicate decision making for complex problems • Examples • Complex contracts or decisions • Diagnosis and treatment in healtcare • Building direct-marketing campaigns • Payoff • Improve process and service performance • Best practices databases

12. Knowledge Management

13. What is Knowledge Management ? • Knowledge management is not • The implementation of a technology • Knowledge management is • a multidisciplinary approach • that integrates • Business strategy • Cultural values • Work processes • Good technological support is crucial, but is not enough to create a good knowledge environment.

14. Gartner group definition Knowledge management is a discipline that promotes an integrated approach toidentifying, managing and sharing all of an enterprise's information assets. These information assets may include databases, documents, policies and procedures as well as previously unarticulated expertise and experience resident in individual workers.

15. Knowledge Management The broad process of identifying, capturing, organizing, transferring and using knowledge . Knowledge management promotes collaborative approach and group work. Framework: Process Enablers Leadership Leadership Apply Create Adapt Organizational Knowledge Measurement Culture Share Identify Organize Collect Technology Source: American Productivity & Quality Center - Carla O’Dell, C.Jackson Grayson

16. Facts • Enterprise invested in KM-relevant technology • Intranets • Groupware • Data warehouses • Data mining • Enterprises forgot the non-technical work • Aligning knowledge to business goals • Mapping knowledge content • Creating networks of knowledge users • Changing culture and defining KM role

17. Business Benefits of KM • KM generates economic and business benifits by: • Providing broad and easy access to enterprise knowledge • Leveraging knowledge trough improved collaboration processes and technologies • Integrating KM into work tasks and processes of employees • Stimulating innovation and the creation of new knowledge • Gartner group study showed that 60% of knowledge management programs resulted in success

18. Aspects of Knowledge Management • Knowledge discovery • Generating knowledge from data • Knowledge representation • Human-readable knowledge • Machine-readable knowledge • Ontologies (study of being, general properties) • Knowledge filtering • Knowledge searching • Search engines • Intelligent agents • Visualization models

19. Ontologies from: Dieter Fensel 3-540-41602-1 An ontology provides an explicit conceptualization (meta-information) that describes the semantics of the data. An ontology has a similar function as a database schema, but: • A language for defining ontologies is syntactically and semantically richer than common approaches for databases; • The information that is described by an ontology consists of semi-structured natural language texts and tabular information; • An ontology must be a shared and consensual terminology because it is used for information sharing and exchange; • An ontology provides a domain theory and not the structure of a data container

20. Definitions of an Ontology • Gruber 1993 • An ontology is a formal, explicit specification of a shared conceptualization. • A conceptualization refers to an abstract model of some phenomenon in the world which identifies the relevant concepts of that phenomenon. • Explicit means that the type of concepts used and the constraints on their use are explicitly defined • Formal refers to the fact that the ontology should be machine readable • Shared means that it is accepted by a group • An ontology provides a vocabulary of terms and relations with which to model a domain

21. Ontology types • Domain ontologies • Capture the knowledge valid for a particular type of domain (e.g. electronic, medical, mechanic, …) • Metadata ontologies (e.g. Dublin Core) • Provide a vocabulary for describing the content of on-line information sources • Generic or common sense ontologies • Aim at capturing general knowledge about the world • Representational ontologies • Not committed to a particular domain (e.g. Frame ontology) • Method and task ontologies • Examples:Wordnet, EuroWordnet(www.let.uva.nl/~ewn ) Cyc (www.cyc.com )

22. Within the Company • Companies try to manage and use this knowledge in a more systematic way. • Required actions. • define which knowledge is required in order to define and execute the strategic business plan; • organizations must implement a system that assures a continuous flow from the members of the organization, the knowledge workers, towards the infrastructure that supports the knowledge management; • there has to be an integration of the strategy, the processes, the cultural and technical aspects of knowledge management. • Setup of an Enterprise Knowledge Architecture.  .

26. KM Success Is Focused on the Business • Do first • Determine role of knowledge in achieving company goals • Select mission-critical business areas for high KM impact • Knowledge-enable key processes and decision making • Try to make the link between improved knowledge and business results • Start small projects within the business culture • Do then • Encyclopedia of R&D or operations knowledge • Know-how of departing experts • Capture tacit knowledge in explicit form

27. Business Architecture Knowledge Architecture Enterprise Architecture Information Architecture Data Architecture IT Architecture

28. The Enterprise Architecture • The IT architecture: basis for the other components. • Hardware. • Network and communication environment. • The system management tools. • The middleware and the basic software. • The data architecture. • How data will be collected, stored and distributed. • Those data are raw data in an updateable form, needed for later interpretation and usage. • Important aspects here are reliability, integrity and security. Example

29. The Enterprise Architecture • In the information architecture: basis and the guideline for the ICT-management. • The ICT-strategy of the enterprise is captured. • It is the translation of the enterprise business strategy into high-level information needs. • A set of applications that are build to fulfil business needs. • The knowledge architecture. • How and where the organization creates and distributes knowledge in all the forms. • The business architecture. • The way the enterprise planned to achieve its business strategy. • This strategy includes goals and objectives, seen in the context of the environment of stakeholders, employees, competitors and other internal and external factors.

30. Knowledge Management Infrastructure • Gathering. • Document management. • Office systems. • Data entry. • Dissemination. • Email, voice mail, … • Web. • Inquiry systems. • Data warehouse, data mart. • Networks. • Lan, wan, • Internet, intranet, extranet. • Storage. • Databases, files, ... • Meta data, dictionaries, … • Groupware. • Collaboration tools. • Conferencing tools. • Analysis. • Data mining. • OLAP. • Visualization. • extract • combine • transform • derive • analyze • present Knowledge Architecture

31. Data Layer • Metadata • - Data Structure - Taxonomy • Data Content - Knowledge maps • Thesaurus • Data Sources • Groupware repository • Document management • Intranets • File servers • WWW • … • Data Types • Relational databases • Text files • Audio/video • Web pages • E-mails • … • Data Formats • XML • HTML • ASCII • GIF • MPEG • …

32. Portals Provide a window into information, systems and processes of an organization • Portals are essential to support KM • Enterprise portals • Personal portals • A portal provides a uniform access to • Documents (unstructured data) • Databases (structured data) • Applications • … • Based on a knowledge map, repositories and indexes • Build-in filtering mechanisme • To be combined with  Push Technology

33. Capabilities of Enterprise Portals • Indexes and search mechanisms • Multiple data repositories • Structured as well as unstructured data • Internal and external data • Taxonomy • Application integration • Security and authorization • Personal

34. The Knowledge Framework in Practice • The components of a technologic knowledge architecture • Knowledge repositories and libraries • Knowledge carthography • Communities of knowledge workers

35. The Knowledge Flow Technological applications for exchanging tacit knowledge Knowledge- repositories and Libraries Communities of knowledge- workers The Knowledge Flow Organizing available Explicit knowledge e.g. case based reasoning Also tacit knowledge of specific experts Technology that supports conversion from tacit to explicit knowledge and the other way around Knowledge Carthography Meta-knowledge. Map of knowledge domains Source:Borghoff 1998

36. Explicit Knowledge in Document Format • Documents is a traditional method for the codification of knowledge • Better usage of already available documents • On-line document databases • Lessons-learned archives • Best practices databases • Document knowledge bases for knowledge domains without unique answers Development of a knowledge repository

37. Setup of a Knowledge Repository • What documents are we going to store, and why? • Manuals to support maintenance • Client documentation for marketing • … • Avoid overload • Selection based on predefined criteria • Alternatives • Special task to select documents • Everybody can add documents

38. Organizing Documents • Values in an index or meta-knowledge • Attributes of a knowledge document • Activities • Keywords • Type of document • Product or service • Authority (owner, usability, quality, …) of the knowledge • Time and validity period

39. The Knowledge Flow • Support the knowledge flow is the basic goal of knowledge management. • It is the central component in the framework, and the the link between the three other components. • It stimulates the interaction between: • The tacit knowledge generated and exchanged between the community of the knowledge workers; • The explicit knowledge in the knowledge repositories; • The explicit meta-knowledge used as the corporate knowledge map. The basis for the technological structure. are the intelligent agents.

40. Intelligent Agents • Intelligent agents: • perform tasks on behalf of something else like e.g. a person, a system or a business process;. • it is a small computerprogram that can perform tasks on his own, including take some decisions; • an agent can react on events; • it can contain simple rules or it can be based on more complex techniques like neural networks; • they run in background, often without being seen by the users. • Useful in two of the components of the framework: • in knowledge repositories; • in knowledge carthography.

41. Intelligent Agents in Knowledge Repositories • Personal agents • To master information overload; • To switch from pull to push mode; • Personalized content filtering; • User profile, based on a personal thesaurus and intelligent search algorithms; • Technical agents • Automatic document indexing; • Important in case-based reasoning systems;

42. Intelligent Agents in Communities of Knowledge Workers • Personal agents • Responsible for activity planning (workflow environments); • Interaction with actor agents that define the role of the worker in the business process; • A workflow agent • tries to find a personal agent that can perform a certain task; • Asks the personal agent whether this task fits in planning of the specific knowledge worker; • A deliberation agent • will check the requests against the availability of the personal agents; • An instance of the actor, containing the goals and activities of the task, is added to the personal agents.

43. Integration of the Components Using Intelligent Agents • Knowledge repositories • Technical agent • (e.g.indexing) • Personal agents • Explicit  Explicit • Knowledge Workers • Technical agent • (e.g.workflow agent) • Personal agents • Tacit  Tacit 2. Inquiry for explicit knowledge 1. Add explicit knowledge 4. Input for profiles of people and communities 6. Input for profiles of people, communities and processes Dynamic adaption and creation 5. Inquiry for profiles of people, communities and processes • Knowledge carthography • Agents / Profiles • Definition • Personal agents • Communities • Processes 3. Inquiry for profiles of people and communities

44. Building the Environment

45. Decision Framework for Km-project Identify Key Values Define KM strategy • Evaluate Enterprise • Strategy/direction for KM • « Values » • Business model • Service goals • Identify business goals for KM • Select a knowledge recovery • strategy • Evaluate potential for Cultural • and business shift • Evaluate potential benefits Analyse Benefits/measures Set KM performance goals • Set performance measures • Determine cost and other • resources for KM • Ensure business unit support • and funding • Explicit knowledge apps. • Tacit knowledge apps. • Combined apps. • Set performance goals Source: Gartner Group

46. Critical Success Factors • KM strategy • Mission, goals, vision, alternatives, responsibilities, … • Resources • Budget for staff, development, … • Technology • Network, user delivery, tools, maintenance, storage • Motivation • For sharing knowledge • Promotion and Training

47. Cultural Success Factors • Combine value contributed by individual with value of contributions by groups. • Face-to-face meetings are still required to bring contributers together. • Consistent terminology and models are critical. • Communities of practice and experience on processes and knowledge. Cultural change is required.

48. Citation There is nothing more difficult to plan , more doubtful of success, nor more dangerous to manage than the creation of a new system. For the initiator has the enmity of all who would profit by the preservation of the old system and merely lukewarm defenders in those who would gain by the new one. Machiavelli, 1513

49. Computer Technologies for KM • Groupware: mail, Lotus Notes, Intranet,Chat boxes, … • Multimedia, video, … • Documentation systems and XML • Expert systems • Artificial Intelligence systems • Data Warehousing, OLAP, data mining, statistics • Search engins, encyclopedia, in-text search • Agents • Computer based training

50. Mentioned reasons for KM In decreasing order of importance: • Integrate multiple sources of data • Marketing and sales • Growth and innovation • Business process improvement • People orientation • Service improvement • IT orientation • Information Management orientation • Cost savings Source: Gartner group