What is Knowledge Management? Becerra-Fernandez & Sabherwal:

Becerra-Fernandez &
Sabherwal:
Chapter 1
Introducing Knowledge Management
What is Knowledge
Management?
 Knowledge management (KM) may simply be
defined as doing
g what is needed to g
get the most
out of knowledge resources.
 In general, 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.
Forces Driving Knowledge
Management
Increasing Domain Complexity: • Intricacy of internal and external processes, increased competition, and the rapid advancement of technology all contribute to increasing domain complexity. Accelerating Market Volatility: • The pace of change, or volatility, within each market Th f h g l tilit ithi h k t 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. 1
Knowledge Management Systems
 Information technology facilitates sharing as well as
accelerated growth of knowledge.
 Information technology allows the movement of
information at increasing speeds and efficiencies.
 “Today, knowledge is accumulating at an ever
increasing rate. It is estimated that knowledge is
currently doubling every 18 months and, of course, the
pace is increasing... Technology facilitates the speed
at which knowledge and ideas proliferate.”
Bradley [1996]
Knowledge Management Systems
Knowledge management mechanisms are organizational
or structural means used to promote knowledge
management.
The use of information technologies to support KM
mechanisms enables dramatic improvement in KM.
Knowledge Management Systems
 KM systems classification based on observations on
the KM systems implementations:




Knowledge Application Systems (Chapter 6)
Knowledge Capture Systems (Chapter 7)
Knowledge Sharing Systems (Chapter 8)
Knowledge Discovery Systems (Chapter 9)
2
Knowledge Management
Systems
 Artificial intelligence and machine learning
technologies
g
((Chapters
p
7-12)) important
p
role in the
KM processes, enabling the development of KMS
 Experience management basically experience
develops over time, to coalesce into more general
experience, which then combines into general
knowledge
Issues in Knowledge
Management
 “Effective KM is not about making a choice between
“software vs. wetware, classroom vs. hands-on, formal
vs informal,
vs.
informal technical vs.
vs social…uses
social uses all the options
available to motivated employees to put knowledge to
work …[and] depends on recognizing that all of these
options basically need each other” [Stewart, 2002].
 One of the primary differences between traditional
information systems and KM systems is the active role
that users of KM systems play on building the content of
such systems.
Effective Knowledge
Management
 80% - Organizational culture and
human factors
 20% - Technology
3
Essence of KM
 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.
 KM methodologies and technologies must enable
effective ways to elicit, represent, organize, re-use,
and renew this knowledge.
 KM should not distance itself from the knowledge
owners, but instead celebrate and recognize their
position as experts in the organization.
Text Overview
 13 chapters divided into 3 parts
 Part
a t I - Principles
c p es o
of Knowledge
o edge Management
a age e t
 Part II: Knowledge Management Technologies and
Systems.
 Part III: Management and the Future of Knowledge
Management.
Becerra-Fernandez:
Chapter 2
The Nature of Knowledge
4
What is Data?
 Data comprises facts, observations, or perceptions
 Data represents raw numbers or assertions
What is Information?
 Information is processed data
 Information is a subset of data, only including those
data that possess context, relevance and purpose
 Information involves manipulation of raw data
What is Knowledge?
 A justified true belief (Nonaka and Takeuchi)
 It is different from data & information
 Knowledge is at the highest level in a hierarchy
with information at the middle level, and data to be
at the lowest level
 It is the richest, deepest & most valuable of the
three
 Information with direction
5
Data, Information, and Knowledge
Knowledge
Value
Zero
Low
Medium
Data
High
Very High
Information
Data, Information, Knowledge and Events
Knowledge
Information
System
Information
Use of
information
Knowledge
K
Data
Decision
Events
Procedural and Declarative
Knowledge
 Declarative knowledge (substantive knowledge)
focuses on beliefs about relationships
p among
g
variables
 Procedural knowledge focuses on beliefs relating
sequences of steps or actions to desired (or
undesired) outcomes
6
Tacit and Explicit Knowledge
 Tacit knowledge includes insights, intuitions, and
hunches
 Explicit knowledge refers to knowledge that has
been expressed into words and numbers
 We can convert explicit knowledge to tacit
knowledge
General and Specific
Knowledge
 General knowledge is possessed by a large
number of individuals and can be transferred easilyy
across individuals
 Specific knowledge, or “idiosyncratic knowledge,”
is possessed by a very limited number of
individuals, and is expensive to transfer
Technically and Contextually
Specific Knowledge
 Technically specific knowledge is deep knowledge
about a specific
p
area
 Contextually specific knowledge knowledge refers
to the knowledge of particular circumstances of
time and place in which work is to be performed
7
Different Types of Knowledge
Reservoirs of Knowledge
Knowledge Reservoirs
Artifacts
People
Organizational
Entities
Organizational Units
Individuals
Practices
Technologies Repositories
Groups
Organizations
Inter-organizational
Networks
Different views of knowledge
 Subjective View of knowledge
 Knowledge as State of Mind
 Knowledge as Practice
 Objective View of knowledge
 Knowledge as Objects
 Knowledge as Access to Information
8
Knowledge in Ancient Greece
 Episteme
 Knowledge
o edge (as co
content)
e )
 Epistemology (theory of knowledge)
 Techné
 Technique / Know-how (knowing as action)
 Technology (theory of technique)
 Phronesis
 Practical/social wisdom
Shift in the meaning
of the concept knowledge
Knowledge
Beliefs
Beliefs
ACTION
Truth
Truth
Knowledge
ACTION
9
Continuum
Know-how
Kogut & Zander
(1992)
Know-how
Nonaka (1994)
Tacit
Blackler (1995)
Embodied
Spender (1998)
Individual/Social
Implicit
Brown & Duguid
(1998)
Know-how
Davenport &
D
Prusak (1998)
Experience
Cook & Brown
(1999)
Knowing (tacit)
Pfeffer (1999)
Knowing-Doing
Hassard &
Kelemen (2002)
Newell (2002)
Orlikowski (2002)
Know-that
Information
Explicit
Embrained
Encultured
Embedded
Encoded
Individual/Social
Explicit
Social Knowledge
Know-that
Insight
Processual –
knowing the world
Values
Data
Information
Knowledge
(explicit)
Discourse
Knowledge
Cultural Practices
Being-in-the-World
Processual
perspective
Structurual
perspective
Knowing
Knowledge
Jashapara: Knowledge Management © Pearson Education (2004)
Knowledge Management genres
 Organizational Learning
 Moving from not-knowing to knowing
 Senge – 5th Discipline
 Knowledge Logistics
 Getting the right knowledge to the right place at the right
time.
 Davenport and Prusak – Working Knowledge
 Intellectual Capital
 Measuring the value of knowledge
 Stewart – Intellectual Capital
10
Becerra-Fernandez:
Chapter 3 & 4
Knowledge Management
Foundations and Knowledge
Management Solutions
Knowledge Management
Solutions and Systems
 Knowledge Management Solutions
 Ways in which KM can be facilitated
 4 Levels of KM solutions:




KM processes
KM systems
KM mechanisms and technologies
KM infrastructure
 Knowledge Management Systems
 Integration of technologies and mechanisms that are
developed to support KM processes
An Overview of Knowledge
Management Solutions
KM Processes
KM Systems
KM Mechanisms and Technologies
KM Infrastructure
11
Knowledge Management
Processes
Discovery
• Combination
• Socialization
Sharing
• Socialization
• Exchange
Application
• Direction
• Routines
Capture
• Externalization
• Internalization
Knowledge
Discovery
Knowledge
Capture
Knowledge
Sharing
Knowledge
Application
KM Processes
Combination Socialization
KM Systems
Knowledge
Capture
Systems
Knowledge
Discovery
Systems
KM Mechanisms
KM Infrastructure
Internalization Externalization
Analogies and metaphors
Brainstorming retreats
On-the-job training
Face-to-face meetings
Apprenticeships
Employee rotation
Learning by observation
….
Organization
Culture
Organization
Structure
Exchange
Direction
Knowledge
Sharing
Systems
Knowledge
Application
Systems
Decision support systems
Web-based discussion groups
Repositories of best practices
Artificial intelligence systems
Case-based reasoning
Groupware
Web pages
…
IT
Infrastructure
Common
Knowledge
Routines
KM Technologies
Physical
Environment
Processes, Mechanisms, and Technologies
12
Knowledge
Discovery
Knowledge
Capture
Knowledge
Sharing
Knowledge
Application
KM Processes
Combination Socialization
Internalization Externalization
Knowledge
Discovery
Systems
KM Systems
KM Mechanisms
KM Infrastructure
Knowledge
Capture
Systems
Organization
Structure
Direction
Knowledge
Sharing
Systems
IT
Infrastructure
Common
Knowledge
Routines
Knowledge
Application
Systems
Decision support systems
Web-based discussion groups
Repositories of best practices
Artificial intelligence systems
Case-based reasoning
Groupware
Web pages
…
Analogies and metaphors
Brainstorming retreats
On-the-job training
Face-to-face meetings
Apprenticeships
Employee rotation
Learning by observation
….
Organization
Culture
Exchange
KM Technologies
Physical
Environment
KM Infrastructure
Knowledge
Discovery
Knowledge
Capture
Knowledge
Sharing
Knowledge
Application
KM Processes
Combination Socialization
KM Systems
y
Knowledge
Discovery
Systems
KM Mechanisms
KM Infrastructure
Internalization Externalization
Knowledge
Capture
Systems
Analogies and metaphors
Brainstorming retreats
On-the-job training
Face-to-face meetings
Apprenticeships
Employee rotation
Learning by observation
….
Organization
Culture
Organization
Structure
Exchange
Direction
Knowledge
Sharing
Systems
Knowledge
Application
Systems
Decision support systems
Web-based discussion groups
Repositories of best practices
Artificial intelligence systems
Case-based reasoning
Groupware
Web pages
…
IT
Infrastructure
Common
Knowledge
Routines
KM Technologies
Physical
Environment
13
Becerra-Fernandez:
Chapter 11
Factors Influencing Knowledge
Management
Universal vs Contingency
Universal view of KM
Contingency view of KM
 There is a single best approach of 
managing knowledge, which should be adopted by all organizations in all circumstances 
 Knowledge sharing is recommended as useful to all organizations, although we believe that direction may sometimes represent an equally effective but more efficient alternative. Contingency view suggests that no one approach is best under all circumstances
Contingency perspective considers the path to success to include multiple alternative paths, with success achieved only when the appropriate path is selected Contingency Factors & KMS
Contingency
Factors
3
2
KM Solutions
KM Infrastructure
•
•
•
•
•
Organization Culture
Communities Of Practice
Organization Structure
IT Infrastructure
Organizing Knowledge
1
KM Systems
KM Mechanisms
4 KM Technologies
5
•
•
•
•
Knowledge
Knowledge
Knowledge
Knowledge
Discovery Systems
Capture Systems
Sharing Systems
Application Systems
KM Processes
6
•
•
•
•
Knowledge
Knowledge
Knowledge
Knowledge
Discovery
Capture
Sharing
Application
7
14
Categories of Contingency
Factors
Environmental Characteristics
Organizational Characteristics
Task Characteristics
Knowledge Management
Knowledge Characteristics
Task Characteristics
 KM processes that are appropriate for an
organizational
g
subunit depend
p
on the nature of its
tasks
 Task Uncertainty
 Task Interdependence
Task Uncertainty
 Task uncertainty is argued to reduce the
organization’s ability to develop routines, and
h
hence
kknowledge
l d application
li ti would
ld d
depend
d on
direction
 When task uncertainty is high, externalization and
internalization would be more costly due to
changing problems and tasks
 When task uncertainty is low routines can be
developed for the knowledge supporting them
15
Effects of Task Characteristics on KM Processes
Internalization
Externalization
Direction
Routines
High
Task In
nterdependence
Exchange
Combination
Socialization
Direction
Routines
Exchange
Combination
Routines
I t
Internalization
li ti
Externalization
Routines
Direction
Socialization
Direction
Low
Low
Task Uncertainty
Routines
Internalization
Externalization
Exchange
Combination
High
Direction
Socialization
Task Interdependence
 Indicates the extent to which the subunit’s
achievement of its g
goals depends
p
on the efforts of
other subunits
 Performance of interdependent tasks relies mainly
on dynamic interaction in which individual units of
knowledge are combined and transformed through
communication and coordination across different
functional groups
Knowledge Characteristics
 Explicit vs. tacit
 Procedural vs. declarative
 General vs. specific
16
Effects of Knowledge Characteristics
on KM Processes
Procedural or Declarative
Procedural
Discovery
• Explicit: Combination
• Tacit: Socialization
Sharing
• Tacit: Socialization
• Explicit: Exchange
Application
• Tacit/Explicit: Direction
• Tacit/Explicit: Routines
Capture
• Tacit: Externalization
• Explicit: Internalization
Procedural and Declarative
Knowledge
 Procedural knowledge focuses on the processes or
means that should be used to p
perform the required
q
tasks, such as how to perform the processes
needed to achieve the specific product design
 Declarative knowledge focuses on beliefs about
relationships among variables
Effects on KM Processes
17
Identification of Appropriate
KM Solutions
 Assess the contingency factors.
 Identify the KM processes based on each contingency
factor.
 Prioritize the needed KM processes.
 Identify the existing KM processes.
 Identify the additional needed KM processes.
 Assess the KM infrastructure.
 Develop additional needed KM systems, mechanisms,
and technologies.
Appropriate Circumstances for Various KM
Processes
Prioritizing KM Processes for Doubtfire
Computer Corporation
18