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C11- Managing Knowledge

C11- Managing Knowledge. About Knowledge . Knowledge is a firm asset: . Data: Flow of events or transactions captured by organization’s systems Knowledge: Cognitive event in people's heads; know how; situational Knowledge Management:

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C11- Managing Knowledge

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  1. C11- Managing Knowledge

  2. About Knowledge Knowledge is a firm asset: • Data: Flow of events or transactions captured by organization’s systems • Knowledge: Cognitive event in people's heads; know how; situational • Knowledge Management: • The set of business processes developed in an organization to create, store, transfer, and apply knowledge The Knowledge Management Landscape 15-4

  3. The KM value chain Knowledge acquisition, Knowledge storage, Knowledge dissemination, Knowledge application The Knowledge Management Landscape 15-6

  4. Types of KMSystems There are three major categories of knowledge management systems, and each can be broken down further into more specialized types of knowledge management systems. 15-10 Enterprise-wide Knowledge Management System

  5. Enterprise-wide KMS • Knowledge repository • A collection of internal and external knowledge in a single location for management and utilization by the organization • Structured Knowledge System • Knowledge repository for explicit knowledge –formal, structured text documents and reports or presentations • Needs to be accessible Enterprise-wide Knowledge Management System

  6. Knowledge Systems • Semi-structured Knowledge Systems • Knowledge repository for less-structured documents, such as e-mail, voicemail, chat room exchanges, videos, digital images, brochures, bulletin boards • Also known as digital asset management systems • Organizing Knowledge: Taxonomies and Tagging • Taxonomy: • Scheme of classifying information and knowledge for easy retrieval • Tagging: • Marking of documents according to knowledge taxonomy Enterprise-wide Knowledge Management System

  7. Knowledge Network Systems • Online directory of corporate experts, solutions developed by in-house experts, best practices, FAQs • Document and organize “tacit” knowledge • Also known as expertise location and management systems Enterprise-wide Knowledge Management System

  8. The Problem of Distributed Knowledge Enterprise-wide Knowledge Management System

  9. The Ask-Me Knowledge Network System 15-16 Enterprise-wide Knowledge Management System

  10. Supporting Technologies: Portals, Collaboration Tools, and Learning Management Systems • Learning Management Systems (LMS): • Provides tools for the management, delivery, tracking, and assessment of various types of employee learning and training • Integrates systems from human resources, accounting, sales in order to identify and quantify business impact of employee learning programs Enterprise-wide Knowledge Management System

  11. Knowledge Workers and Knowledge Work • key roles of knowledge workers: • Keeping the organization current in knowledge as it develops in the external world – in technology, science, social thought, and the arts • Serving as internal consultants regarding the areas of their knowledge, the changes taking place, and opportunities Enterprise-wide Knowledge Management System

  12. Requirements of Knowledge Work Systems Knowledge Work Systems

  13. Examples of Knowledge Work Systems • Computer-aided Design • Information system that automates the creation and revision of industrial and manufacturing designs using sophisticated graphics software • Virtual Reality • Interactive graphics software and hardware that create computer-generated simulations that emulate real-world activities or photorealistic simulations Knowledge Work Systems

  14. Knowledge Discovery • Identification of underlying patterns, categories, and behaviors in large data sets, using techniques such as data mining • Intelligent Agents • automating tasks like searching for information for e-commerce, supply chain management Intelligent Techniques

  15. Capturing Knowledge: Expert Systems (ES)‏ • How Expert Systems Work • Two strategies for searching the rule base in an ES • Forward Chaining: • Begins with the information entered by the user and searches the rule base to arrive at a conclusion • Backward Chaining: • Acts like a problem solver by beginning with hypothesis and seeking out more information until the hypothesis is either proved or disproved Intelligent Techniques

  16. Capturing Knowledge: Expert Systems (ES)‏ • Knowledge Engineer: • A specialist who elicits information and expertise from other professionals and translates it into a set of rules for an expert system Intelligent Techniques

  17. Organizational Intelligence • Case-Based Reasoning (CBR) • Knowledge system that represents knowledge as a base of cases and solutions • Searches for stored cases with problem characteristics similar to the new case and applies solutions of the old case to the new case • Rules in an expert system • Coming up Intelligent Techniques

  18. Genetic algorithms are useful for finding the optimal solution for a specific problem by examining a very large number of possible solutions for that problem • Machine learning focuses on algorithms and statistical methods that allow computers to “learn” by extracting rules and patterns from massive data sets and make predictions about the future.

  19. 15-21 Intelligent Techniques

  20. 15-22 Intelligent Techniques

  21. Case-Based Reasoning 15-24 Intelligent Techniques

  22. Intelligent Agents in P&G’s Supply Chain Network Intelligent agents are helping Procter & Gamble shorten the replenishment cycles for products such as a box of Tide. 15-28 Intelligent Techniques

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