Sim Ch 11 Managing Knowledge

KELOMPOK 8Stephanie d.a.g 12030112130138Yohana ambarita 12030112130199Indika sandra agita 12030112130277Astri dias maharani 12030112140173Arini nur khulil j. 12030112140212

MANAGING KNOWLEDGE

The Knowledge Management Landscape

Important Dimension of Knowledge1. Knowledge is an intangible asset2. Knowledge has different forms3. Knowledge has a location4. Knowledge is situational


Organizational LearningProcess in which organization learn :- Gain experience through collection of data, measurement, trial and error, and feedback- Adjust behavior to reflect experience


Knowledge ManagementSet of business processes developed in an organization to create, store, transfer, and apply knowledge


Knowledge Management Value Chain1. Knowledge acquisition - Documenting tacit and explicit knowledge - Creating knowledge - Tracking data from TPS and external source


Knowledge Management Value Chain2. Knowledge Storage - Databases - Document management systems - Role of management


Knowledge Management Value Chain3. Knowledge Dissemination Training programs, informal networks, and shared management experience communi- cated through a supportive culture help managers focus their attention on the important knowledge and information


Knowledge Management Value Chain4. Knowledge Application Knowledge that is not shared and applied to the practical problems facing firms does not add business value


Types of Knowledge Management Systems1. Enterprise-wide knowledge management systems2. Knowledge work systems3. Intelligent technique

Enterprise-Wide Knowledge Management Systems

Three major types of knowledge in enterprise1. Structured documents Reports, presentations Formal rules

2. Semi structured documents E-mails, videos

3. Unstructured, tacit knowledge

80% of an organization’s business content is semistructured or unstructured

Enterprise content management systemsHelp capture, store, retrieve, distribute,

preserve Documents, reports, best practices Semistructured knowledge (e-mails)

Bring in external sources News feeds, research

Tools for communication and collaboration


AN ENTERPRISE CONTENT MANAGEMENT SYSTEM

Enterprise content management systems

Key problem – Developing taxonomy Knowledge objects must be tagged with categories

for retrieval Digital asset management systems

Specialized content management systems for classifying, storing, managing unstructured digital data

Photographs, graphics, video, audio


Knowledge network systems Provide online directory of corporate experts in well-defined

knowledge domains Use communication technologies to make it easy for employees to

find appropriate expert in a company May systematize solutions developed by experts and store them in

knowledge database Best-practices Frequently asked questions (FAQ) repository



.

A knowledge network maintains a database of firm experts, as well as accepted solutions to known problems, and then facilitates the communication between employees looking for knowledge and experts who have that knowledge. Solutions created in this communication are then added to a database of solutions in the form of FAQs, best practices, or other documents


Portal and collaboration technologies Enterprise knowledge portals: Access to external and internal

information News feeds, research Capabilities for e-mail, chat, videoconferencing, discussion

Use of consumer Web technologies Blogs Wikis Social bookmarking


Learning management systems Provide tools for management, delivery, tracking, and assessment

of various types of employee learning and training Support multiple modes of learning

CD-ROM, Web-based classes, online forums, live instruction, etc. Automates selection and administration of courses Assembles and delivers learning content Measures learning effectiveness


Knowladge worker perfom three key roles that are critical to the organization and to the managers who work within organozation :

keeping the organization current in knowladge as it develops in the external world-in technology ,science, soscial thought and the arts

Serving as internal consultants regarding the areas of their knowladge, the changes taking place, and opportunities

Acting as change agents, evaluating, intuiting, and promoting change projects

Knowledge Work Systems

Requirement of Knowladge Work Systems

Knowledge Work Systems

Examples of knowledge work systemsCAD

VIRTUAL REALITY SYSTEMS

AUGMENTED REALITY

VIRTUAL REALITY MODELING LANGUAGE(VRML)

Intelligent Technique

Intelligent techniques: Used to capture individual and collective knowledge and to extend knowledge base To capture tacit knowledge: Expert systems, case-based

reasoning, fuzzy logic Knowledge discovery: Neural networks and data mining Generating solutions to complex problems: Genetic

algorithms Automating tasks: Intelligent agents

Artificial intelligence (AI) technology: Computer-based systems that emulate human behavior


Expert systems: Capture tacit knowledge in very specific and limited

domain of human expertise Capture knowledge of skilled employees as set of

rules in software system that can be used by others in organization

Typically perform limited tasks that may take a few minutes or hours, e.g.: Diagnosing malfunctioning machine Determining whether to grant credit for loan

Rules In A Expert System


How expert systems work Knowledge base: Set of hundreds or thousands of

rules Inference engine: Strategy used to search

knowledge base Forward chaining: Inference engine begins with

information entered by user and searches knowledge base to arrive at conclusion

Backward chaining: Begins with hypothesis and asks user questions until hypothesis is confirmed or disproved


Interference Engines In Expert System


Case-based reasoning (CBR) Descriptions of past experiences of human specialists (cases),

stored in knowledge base System searches for cases with problem characteristics similar to

new one, finds closest fit, and applies solutions of old case to new case

Successful and unsuccessful applications are grouped with case Stores organizational intelligence: Knowledge base is

continuously expanded and refined by users CBR found in

Medical diagnostic systems Customer support


How Case-based Reasoning Works



Fuzzy logic systems Rule-based technology that represents

imprecision used in linguistic categories (e.g., “cold,” “cool”) that represent range of values

Describe a particular phenomenon or process linguistically and then represent that description in a small number of flexible rules

Provides solutions to problems requiring expertise that is difficult to represent with IF-THEN rules Autofocus in cameras

How A Neural Network Works


GENETIC ALGORITHMSUseful for finding the optimal solution for a specific problem by examining a very large

number of possible solution for that problem


HYBRID AI SYSTEMSGenetic algorithms, fuzzy logic, neural

networks and expert systems can be integrated into a single application to take

advantage of the best features of these technologies


Intelligent Agents in P&G’s Supply Chain Network


Case Study

1. The conditions preceding the flash crash involved fearful and uncertain investors is stock market that was “already down and trending even lower”.

2. The benefits of electronic trading are “speed, reduced cost, and more liquid markets” and the use of algorithms that learn what will work in the market and “adjust their stock trading strategies” based on what the market is doing.

3. The features of electronic trading and automated trading programs that contributed to the crash were the “computer selling algorithm that dumped 75,000 contracts” within twenty minutes triggering other HFTs that used algorithms to begin selling as well.

4. The only way that the flash crash could have been prevented would be if computer were never allowed to have control over buying and selling. When you give computers this type of control, no matter what the limitations are, there is always the potential for something to go very wrong. Unless humans are given back the power.

Sim Ch 11 Managing Knowledge

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