Slideshow Transcript

1. Slide 1: Journal of Knowledge Management Vol. 11, No. 1 (2007) A Strategy-Based Ontology of Knowledge Management Technologies André Saito, Katsuhiro Umemoto and Mitsuru Ikeda Japan Advanced Institute of Science and Technology Graduate School of Knowledge Science Ver 1.1 – 2006.01.17
2. Slide 2: Background Knowledge management (KM) is still emerging  The word knowledge has many different meanings  Contributions come from many disciplines  The role of technology in KM needs further  explanation Technology itself is complex and fast-paced  Existing accounts present limitations  A link between KM technologies and strategy  is missing KM itself suffers from lack of strategic alignment  Strategic alignment of IT is a well known issue  Saito, Umemoto and Ikeda 2006 2
3. Slide 3: Objectives and Methodology Objectives  To describe the relations among technology, KM, and  strategy To categorize available KM technologies according to  those relations. Methodology  An ontology development method was used to identify  and formally define concepts and their relationships Two sub-domains were mapped: KM technologies and  KM strategy Saito, Umemoto and Ikeda 2006 3
4. Slide 4: Findings on KM strategy Three meanings associated to the term: An approach to KM  Express a particular perspective on knowledge and how it can be managed A knowledge strategy  Identify and prioritize knowledge to be managed, based on its contribution to business strategy A KM implementation strategy  Describes steps and conditions for the successful implementation of KM initiatives Saito, Umemoto and Ikeda 2006 4
5. Slide 5: KM strategy as… Approach to KM Saito, Umemoto and Ikeda 2006 5
6. Slide 6: KM strategy as… Knowledge strategy Saito, Umemoto and Ikeda 2006 6
7. Slide 7: KM strategy as… KM implementation strategy Saito, Umemoto and Ikeda 2006 7
8. Slide 8: KM strategy conceptual map Saito, Umemoto and Ikeda 2006 8
9. Slide 9: Findings on KM technologies Common sources of misunderstanding: Technologies are usually associated with  knowledge processes, which are numerous and highly context-dependent Technologies are usually integrated into  systems, in many different levels Component technologies ≠ KM systems  KM systems can be either generic or  domain-specific applications Generic KM applications ≠ Business applications  Saito, Umemoto and Ikeda 2006 9
10. Slide 10: An ontology of KM technologies Three basic categories: Component technologies (integrated into other systems)  KM applications (for general knowledge processes)  Business applications with KM functionality (for specific  business processes) Saito, Umemoto and Ikeda 2006 10
11. Slide 11: KM component technologies Storage. Databases, repositories, file-servers, Collaboration. Calendaring, file sharing, meeting data warehouses, data marts, etc. support, application sharing, group decision support, etc. Connectivity. Internet, security, wireless, mobility, authentication, P2P, etc. Community. Community management, web logs, wikis, social network analysis, etc. Communication. E-mail, mailing lists, discussion groups, chat, instant messaging, audio/video Creativity. Cognitive mapping, idea generation, conferencing, VoIP, etc. etc. Authoring. Office suites, desktop publishing, Data mining. Statistical techniques, multi- graphic suites, multimedia, imaging, etc. dimensional analysis, neural networks, etc. Distribution. Web, intranets, extranets, Text mining. Semantic analysis, Bayesian enterprise portals, personalization, syndication, inference, natural language processing, etc. audio/video streaming, etc. Web mining. Collaborative profiling, intelligent Search. Search engines, search agents, indexing, agents, etc. glossaries, thesauri, taxonomies, ontologies, Visualization. 2D and 3D navigation, geographic collaborative filtering, etc. mapping, etc. Analytics. Query, reporting, multi-dimensional Organization. Ontology development, ontology analysis (OLAP), etc. acquisition, taxonomies, glossaries, thesauri, Workflow. Process modeling, process engines, etc. etc. Reasoning. Rule-based expert systems, case- E-learning. Interactive multimedia (CBT), web based reasoning, knowledge-bases, machine seminars, simulations, etc. learning, fuzzy logic, etc. Saito, Umemoto and Ikeda 2006 11
12. Slide 12: KM applications Decision support Document management Integrate a series of tools for decision Automate the control of electronic making. documents through their entire life-cycle. Discovery and data mining Content management Support the identification of patterns and Manage the whole Web publishing in large amounts of data. process. Search and organization Process management Facilitate access to and organize Automate the flow of tasks and unstructured content. information across business processes. Enterprise portals Group support Integrate access to a range of Support work and collaboration of groups information at a single point of entry. and teams. Learning management Project management Support the delivery of online courses in Support the management of project a variety of formats. activities and resources. Expertise management Community support Brokers expertise in large communities. Coordinate interaction in large groups. Saito, Umemoto and Ikeda 2006 12
13. Slide 13: Business apps with KM funcionality Sales Force Automation Solutions Representative Data database warehousing Contact Center Customer Backoffice systems profiling Field Service Customer Information Analytical on demand applications Self-Service Segmentation Profiling Personalization Profitability analysis E-Commerce Needs analysis Focus Sales analysis groups Campaign analysis Campaign Etc. Management Operational CRM Analytical CRM Saito, Umemoto and Ikeda 2006 13
14. Slide 14: Linking KM technologies to strategy A KM program is strategic if it includes:  A knowledge strategy that defines knowledge intents  KM initiatives that support those knowledge intents  KM initiatives are inherently associated with particular  approaches to KM Personalization Codification Knowledge Knowledge Creation creation creation through through personalization codification Four generic modes of KM support for strategy Knowledge Knowledge Transfer transfer transfer through through personalization codification Saito, Umemoto and Ikeda 2006 14
15. Slide 15: KM component technologies Personalization Codification Collaboration Discovery Connectivity Storage Creation Communication Search Authoring Analytics Collaboration Data mining Community Text mining Creativity Web mining Workflow Visualization Dissemination Repository Connectivity Connectivity Transfer Communication Storage Authoring Authoring Distribution Search E-learning Workflow Collaboration Organization Community Reasoning Saito, Umemoto and Ikeda 2006 15
16. Slide 16: KM applications Personalization Codification Collaboration Discovery Creation Group support Decision support Project management Discovery & data mining Community support Search & organization Dissemination Repository Transfer Enterprise portals Document management Learning management Content management Expertise management Process management Saito, Umemoto and Ikeda 2006 16
17. Slide 17: An ontology of KM technologies Saito, Umemoto and Ikeda 2006 17
18. Slide 18: Conclusions A wide range of technologies can support KM  Three basic categories: component technologies,  KM apps and business apps with KM functionality KM applications summarize KM functionality  KM technologies are linked to strategy  through KM initiatives that support specific knowledge intents There are four generic modes of technological  support for strategy in KM Saito, Umemoto and Ikeda 2006 18
19. Slide 19: Some implications For research  KM technologies can be better analyzed in the context  of KM initiatives instead of knowledge processes There seems to be exemplary KM initiatives that  connect specific knowledge intents to typical approaches to KM and KM technologies For practice  Guidance in the design of particular KM strategies  Guidance in the selection of adequate  KM technologies for particular KM initiatives Saito, Umemoto and Ikeda 2006 19