c11- managing knowledge

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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: - PowerPoint PPT Presentation

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C11- Managing Knowledge

About Knowledge

• 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

Intangible asset

Requires organizational

resources

Can be source of competitive

advantage

Knowledge is a firm asset:

15-6

The KM value chain

The Knowledge Management Landscape

Knowledge acquisition, Knowledge storage, Knowledge dissemination, Knowledge application

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

Types of KMSystems

Enterprise-wide Knowledge Management System

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

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

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

The Problem of Distributed Knowledge

Enterprise-wide Knowledge Management System

15-16

The Ask-Me Knowledge Network System

Enterprise-wide Knowledge Management System

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

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

Requirements of Knowledge Work Systems

Knowledge Work Systems

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

• 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

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

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

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

• 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.

15-21Intelligent Techniques

15-22Intelligent Techniques

15-24

Case-Based Reasoning

Intelligent Techniques

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.

15-28Intelligent Techniques

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