Understanding Knowledge Lecture One. Introducing Knowledge Management Lecture One.

Understanding Knowledge

Lecture One

Introducing Knowledge Management

Lecture One Lecture One

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Chapter 1: Understanding Knowledge

Objectives What is Knowledge Management (KM)?

What are the driving forces?

Role of KM in today’s organization

What is Knowledge Management System (KMS)?

Classification of Knowledge Management Systems

Effective Knowledge Management

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Knowledge Management - Motivation

“The 20th anniversary of the landing of an American on the surface of the Moon occasioned many bittersweet reflections. Sweet was the celebration of the historic event itself... Bitter, for those same enthusiasts, was the knowledge that during the twenty intervening years much of the national consensus that launched this country on its first lunar adventure had evaporated...” [Fries,S. 1992].

Copyright NASA, Apollo 11 mission

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Knowledge as Key Resource “Knowledge has become the key

resource, for a nation’s military strength as well as for its economic strength… is fundamentally different from the traditional key resources of the economist – land, labor, and even capital…we need systematic work on the quality of knowledge and the productivity of knowledge … the performance capacity, if not the survival, of any organization in the knowledge society will come increasingly to depend on those two factors” [Drucker,1994]

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What is Knowledge Management? Knowledge management (KM)

may be defined simply as doing what is needed to get the most out of knowledge resources.

KM focuses on organizing and making available important knowledge, wherever and whenever it is needed.

KM is also related to the concept of intellectual capital.

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Forces Driving Knowledge Management

Increasing Domain Complexity: Intricacy of internal and external processes, the rapid advancement of technology.

Accelerating Market Volatility: The pace of change, or volatility, within each market domain has increased rapidly in the past decade.

Intensified Speed of Responsiveness: The time required to take action based upon subtle changes within and across domains is decreasing.

Diminishing Individual Experience: High employee turnover rates have resulted in individuals with decision-making authority having less tenure within their organizations than ever before.

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Role of KM in Today’s Organization

KM is important for organizations that continually face downsizing or a high turnover percentage due to the nature of the industry.

Facilitate today’s younger manager to make the tough decisions daily needed

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Chapter 1: Understanding KnowledgeWhat is Knowledge Management “Systems” ?Social/Structural mechanismsmechanisms (e.g., mentoring and retreats, etc.) for promoting knowledge sharing. Leading-edge information technologiesinformation technologies (e.g., Web-based conferencing) to support KM mechanisms.Knowledge management systems (KMS): the synergysynergy between social/structural mechanisms and latest technologies.

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Knowledge Discovery Systems

Knowledge Capture Systems

Knowledge Sharing Systems

Knowledge Application Systems

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Effective Knowledge Management (1)

80% - Organizational processes and human factors

20% - Technology

PEOPLE

TECHNOLOGY

ORGANIZATIONALPROCESSESOVERLAPPING

FACTORS

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Knowledge is first created in the people’s minds.

KM practices must first identify ways to encourage and stimulate the ability of employees to develop new knowledge.

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KM methodologies and technologies must enable effective ways to elicit, represent, organize, re-use, and renew this knowledge.

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Effective Knowledge Management (4) KM should not

distance itself from the knowledge owners, but instead celebrate and recognize their position as experts in the organization.

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Review of Last Lecture What is Knowledge Management (KM)?

What are the driving forces?

Role of KM in today’s organization

What is Knowledge Management System (KMS)?


Effective Knowledge Management

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In this Lecture Basic Knowledge-related

Definitions Data, Information and

Knowledge From Data Processing to

Knowledge-based Systems Types of Knowledge Knowledge – An Attribute of

Expertise

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Basic Knowledge-Related DefinitionsCommon Sense

Fact

Heuristic

Knowledge

Intelligence

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Innate ability to sense, judge, or perceive situations; grows stronger over time

Fact

Heuristic

Knowledge

Intelligence

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Fact A statement that relates a certain element of truth about a subject matter or a domain

Heuristic

Knowledge

Intelligence

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Heuristic A rule of thumb based on years of experience

Knowledge

Intelligence

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Knowledge Understanding gained through experience; familiarity with the way to perform a task; an accumulation of facts, procedural rules, or heuristics

Intelligence

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Knowledge Understanding gained through experience; familiarity with the way to perform a task; an accumulation of facts, procedural rules, or heuristics

Intelligence The capacity to acquire and apply knowledge

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Data, Information, and Knowledge Data: Unorganized and

unprocessed facts; static; a set of discrete facts about events

Information: Aggregation of data that makes decision making easier

Knowledge is derived from information in the same way information is derived from data; it is a person’s range of information

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Relationship between data, information and Knowledge

InformationData

Zero Low Medium High Very High

Value

Knowledge

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An illustration

Zero Low Medium High Very High

Value

InformationData

H T H T TH H H T H

…T T T H T

pH = 0.40pT = 0.60RH = +$10RT = -$8

nH = 40nT = 60

EV = -$0.80

Knowledge

CountingpH = nH/(nH+nT)pT = nT/(nH+nT)

EV=pH RH+ pT RT

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Relating Data, Information, and Knowledge to Events

KnowledgeKnowledge

InformationDataInformation

System

Decision

Events

Use ofinformation

Kn

ow

led

ge

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KNOWLEDGE

INFORMATION

WISDOM

Nonalgorithmic(Heuristic)

Nonprogrammable

From Data Processing to Knowledge-based SystemsFrom Data Processing to Knowledge-based Systems

DATAAlgorithmic Programmable

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Types (Categorization) of KnowledgeShallow (readily recalled) and deep

(acquired through years of experience)

Explicit (already codified) and tacit (embedded in the mind)

Procedural (repetitive, stepwise) versus Episodical (grouped by episodes)

Knowledge exist in chunkschunks

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Explicit and Tacit Knowledge

Explicit (knowing-that) knowledge: knowledge codified and digitized in books, documents, reports, memos, etc.

Tacit (knowing-how) knowledge: knowledge embedded in the human mind through experience and jobs

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Illustrations of the Different Types of Knowledge

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Knowledge As An Attribute of Expertise An expert in a specialized area

masters the requisite knowledge The unique performance of a

knowledgeable expert is clearly noticeable in decision-making quality

Knowledgeable experts are more selective in the information they acquire

Experts are beneficiaries of the knowledge that comes from experience

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Expert’s Reasoning Methods

Reasoning by analogy: relating one concept to another Formal reasoning: using deductive or inductive methods Case-based reasoning: reasoning from relevant past cases

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Deductive and inductive reasoning Deductive reasoning:

exact reasoning. It deals with exact facts exact facts and exact and exact conclusionsconclusions

Inductive reasoning: reasoning from a set of facts or individual cases to a general general conclusionconclusion

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Human’s Learning ModelsLearning by experience: a

function of time and talent

Learning by example: more efficient than learning by experience

Learning by discovery: undirected approach in which humans explore a problem area with no advance knowledge of what their objective is.

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End of Lecture One

Understanding Knowledge Lecture One. Introducing Knowledge Management Lecture One.

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