Transcript 2.Knowledge Management

The Knowledge Management
Infrastructure
Prof.E.Vandijck
“ If we only knew what we know at TI “
Jerry Junkins
Former chairman ,
President and CEO of TI
Knowledge

Knowledge is a broader and more
difficult to define concept than
information.

We obtain knowledge when the
information is also interpreted and
therefore made usable. We get
knowledge by creating associations and
by earning insight.
The Pyramid
Wisdom
Knowledge
Information
Data
Types of Knowledge
We can distinguish between two major types of
knowledge

Tacit Knowledge

Explicit Knowledge
Tacit Knowledge

Tacit knowledge: resides in someone´s head, it
does not exist in explicit form and is not easily
transferred to others.
Undocumented
In people´s heads
A source of explicit knowledge

The highest-value knowledge is that held by
employees
Experience
Insight
expertise
Explicit Knowledge

Explicit knowledge is stored in digitized form so that it
can be viewed, read, used and applied.

Structured
 Books, reports
 Databases
 Drawings
 Methodologies
 Trend analysis

Unstructured
 Illustrations
 Articles
 E-mails, news

More directly usable
Forms of Knowledge Conversion
Tacit knowledge
Explicit knowledge
Tacit
Knowledge
Socialization
Externalization
Explicit
Knowledge
Internalization
Combination
Externalization of Tacit Knowledge

Best for:
Advantage:
Limits:
Examples:
Source: Gartner group
Provide guide to
experts

Capture and Codify
Knowledge
Innovative
Unique solutions
Multiple,
Repeatable solutions
Low KM solution cost
Sharable by many
Demand on availability
of experts
Major conversion and
maintenance
Investment banking
Strategic consulting
Supply chain mngt
SAP install
Benefits of Explicit Knowledge

Payoff:
Asset Management

New Intelligence
Reuse elements
Protect from loss
Discover trends
Anticipate
Improve strategic action
Internal
Sources:
Key employees
Critical databases
Critical business
processes
Employees, product,
service and customer
analysis
E-commerce feedback
External
Sources:
Market analysis
Internet research
New feeds
Internet research
Source: Gartner group
Benefits of Tacit Plus Explicit Knowledge

Solution support
Applying pragmatic experience to replicate decision
making for complex problems

Examples
Complex contracts or decisions
Diagnosis and treatment in healtcare
Building direct-marketing campaigns

Payoff
Improve process and service performance
Best practices databases
Knowledge Management
What is Knowledge Management ?

Knowledge management is not
 The implementation of a technology

Knowledge management is
 a multidisciplinary approach
 that integrates
• Business strategy
• Cultural values
• Work processes

Good technological support is crucial, but is not
enough to create a good knowledge environment.
Gartner group definition
Knowledge management is a discipline that
promotes an integrated approach to
identifying, managing and sharing all of an
enterprise's information assets. These
information assets may include databases,
documents, policies and procedures as well
as previously unarticulated expertise and
experience resident in individual workers.
Knowledge Management
The broad process of identifying, capturing,
organizing, transferring and using knowledge .
Knowledge management promotes collaborative
Process
approach and group work.
Framework:
Enablers
Leadership
Apply
Adapt
Measurement
Share
Create
Organizational
Leadership
Knowledge
Organize
Culture
Identify
Collect
Technology
Source: American Productivity & Quality Center - Carla O’Dell, C.Jackson Grayson
Facts

Enterprise invested in KM-relevant technology
Intranets
Groupware
Data warehouses
Data mining

Enterprises forgot the non-technical work
Aligning knowledge to business goals
Mapping knowledge content
Creating networks of knowledge users
Changing culture and defining KM role
Business Benefits of KM

KM generates economic and business benifits by:
 Providing broad and easy access to enterprise knowledge
 Leveraging knowledge trough improved collaboration
processes and technologies
 Integrating KM into work tasks and processes of employees
 Stimulating innovation and the creation of new knowledge

Gartner group study showed that 60% of knowledge
management programs resulted in success
Aspects of Knowledge Management

Knowledge discovery
 Generating knowledge from data

Knowledge representation
 Human-readable knowledge
 Machine-readable knowledge
 Ontologies (study of being, general properties)


Knowledge filtering
Knowledge searching
 Search engines
 Intelligent agents
 Visualization models
Ontologies
from: Dieter Fensel 3-540-41602-1
An ontology provides an explicit conceptualization
(meta-information) that describes the semantics of the
data.
An ontology has a similar function as a database schema, but:
 A language for defining ontologies is syntactically and semantically
richer than common approaches for databases;
 The information that is described by an ontology consists of semistructured natural language texts and tabular information;
 An ontology must be a shared and consensual terminology because
it is used for information sharing and exchange;
 An ontology provides a domain theory and not the structure of a
data container
Definitions of an Ontology

Gruber 1993
An ontology is a formal, explicit specification of a
shared conceptualization.
• A conceptualization refers to an abstract model of some
phenomenon in the world which identifies the relevant
concepts of that phenomenon.
• Explicit means that the type of concepts used and the
constraints on their use are explicitly defined
• Formal refers to the fact that the ontology should be
machine readable
• Shared means that it is accepted by a group
An ontology provides a vocabulary of terms and
relations with which to model a domain
Ontology types

Domain ontologies
 Capture the knowledge valid for a particular type of domain (e.g.
electronic, medical, mechanic, …)

Metadata ontologies (e.g. Dublin Core)
 Provide a vocabulary for describing the content of on-line
information sources

Generic or common sense ontologies
 Aim at capturing general knowledge about the world

Representational ontologies
 Not committed to a particular domain (e.g. Frame ontology)

Method and task ontologies

Examples:Wordnet, EuroWordnet(www.let.uva.nl/~ewn )
Cyc (www.cyc.com )
Within the Company

Companies try to manage and use this knowledge in a
more systematic way.

Required actions.
 define which knowledge is required in order to define and
execute the strategic business plan;
 organizations must implement a system that assures a
continuous flow from the members of the organization, the
knowledge workers, towards the infrastructure that supports
the knowledge management;
 there has to be an integration of the strategy, the processes,
the cultural and technical aspects of knowledge management .
 Setup of an Enterprise Knowledge Architecture.
KM Success Is Focused on the
Business

Do first
 Determine role of knowledge in achieving company goals
 Select mission-critical business areas for high KM impact
 Knowledge-enable key processes and decision making
 Try to make the link between improved knowledge and
business results
 Start small projects within the business culture

Do then
 Encyclopedia of R&D or operations knowledge
 Know-how of departing experts
 Capture tacit knowledge in explicit form
Business Architecture
Knowledge Architecture
Enterprise
Architecture
Information Architecture
Data Architecture
IT Architecture
The Enterprise Architecture

The IT architecture: basis for the other components.
 Hardware.
 Network and communication environment.
 The system management tools.
 The middleware and the basic software.

Example
The data architecture.
 How data will be collected, stored and distributed.
 Those data are raw data in an updateable form, needed for later
interpretation and usage.
 Important aspects here are reliability, integrity and security.
The Enterprise Architecture

In the information architecture: basis and the guideline
for the ICT-management.
 The ICT-strategy of the enterprise is captured.
 It is the translation of the enterprise business strategy into
high-level information needs.
 A set of applications that are build to fulfil business needs.

The knowledge architecture.
 How and where the organization creates and distributes
knowledge in all the forms.

The business architecture.
 The way the enterprise planned to achieve its business
strategy.
 This strategy includes goals and objectives, seen in the
context of the environment of stakeholders, employees,
competitors and other internal and external factors.

Gathering.
 Document management.
 Office systems.
 Data entry.

Dissemination.





Email, voice mail, …
Web.
Inquiry systems.
Data warehouse, data mart.
Networks.
 Lan, wan,
 Internet, intranet, extranet.

Storage.
Knowledge
Management Infrastructure
•extract
•combine
•transform
•derive
•analyze
•present
 Databases, files, ...
 Meta data, dictionaries, …

Groupware.
 Collaboration tools.
 Conferencing tools.

Analysis.
 Data mining.
 OLAP.
Knowledge
Architecture
Data Layer
Metadata
- Data Structure
- Data Content
- Taxonomy
- Knowledge maps
- Thesaurus
Data Sources
Data Types
Data Formats
• Groupware repository
• Relational databases
• XML
• Document management
• Text files
• HTML
• Intranets
• Audio/video
• ASCII
• File servers
• Web pages
• GIF
• WWW
• E-mails
• MPEG
• …
• …
•
…
Portals
Provide a window into information, systems and
processes of an organization

Portals are essential to support KM
 Enterprise portals
 Personal portals

A portal provides a uniform access to
 Documents (unstructured data)
 Databases (structured data)
 Applications
…

Based on a knowledge map, repositories and indexes

Build-in filtering mechanisme

To be combined with Push Technology
Capabilities of Enterprise Portals








Indexes and search mechanisms
Multiple data repositories
Structured as well as unstructured data
Internal and external data
Taxonomy
Application integration
Security and authorization
Personal
The Knowledge Framework in Practice

The components of a technologic
knowledge architecture
Knowledge repositories and libraries
Knowledge carthography
Communities of knowledge workers
The Knowledge Flow
Knowledgerepositories
and
Libraries
Organizing available
Explicit knowledge
e.g. case based reasoning
Also tacit knowledge
of specific experts
Source:Borghoff 1998
The
Knowledge
Flow
Communities
of
knowledgeworkers
Technological
applications for
exchanging tacit
knowledge
Technology that supports
conversion from tacit to
explicit knowledge and
the other way around
Knowledge
Carthography
Meta-knowledge.
Map of knowledge
domains
Explicit Knowledge in Document Format



Documents is a traditional method for the
codification of knowledge
Better usage of already available documents
On-line document databases
Lessons-learned archives
Best practices databases

Document knowledge bases for knowledge
domains without unique answers
Development of a knowledge repository
Setup of a Knowledge
Repository

What documents are we going to store, and why?
 Manuals to support maintenance
 Client documentation for marketing
…

Avoid overload

Selection based on predefined criteria

Alternatives
 Special task to select documents
 Everybody can add documents
Organizing Documents

Values in an index or meta-knowledge

Attributes of a knowledge document
Activities
Keywords
Type of document
Product or service
Authority (owner, usability, quality, …) of the
knowledge
Time and validity period
The Knowledge Flow



Support the knowledge flow is the basic goal of
knowledge management.
It is the central component in the framework, and the
the link between the three other components.
It stimulates the interaction between:
 The tacit knowledge generated and exchanged between the
community of the knowledge workers;
 The explicit knowledge in the knowledge repositories;
 The explicit meta-knowledge used as the corporate knowledge
map.
The basis for the technological structure.
are the intelligent agents.
Intelligent Agents

Intelligent agents:
 perform tasks on behalf of something else like e.g. a person, a
system or a business process;.
 it is a small computerprogram that can perform tasks on his
own, including take some decisions;
 an agent can react on events;
 it can contain simple rules or it can be based on more complex
techniques like neural networks;
 they run in background, often without being seen by the users.

Useful in two of the components of the framework:
 in knowledge repositories;
 in knowledge carthography.
Intelligent Agents in Knowledge
Repositories

Personal agents
To master information overload;
To switch from pull to push mode;
Personalized content filtering;
User profile, based on a personal thesaurus and
intelligent search algorithms;

Technical agents
Automatic document indexing;
Important in case-based reasoning systems;
Intelligent Agents in Communities
of Knowledge Workers

Personal agents
 Responsible for activity planning (workflow environments);
 Interaction with actor agents that define the role of the worker
in the business process;

A workflow agent
 tries to find a personal agent that can perform a certain task;
 Asks the personal agent whether this task fits in planning of
the specific knowledge worker;

A deliberation agent
 will check the requests against the availability of the personal
agents;
 An instance of the actor, containing the goals and activities of
the task, is added to the personal agents.
Integration of the Components
Using Intelligent Agents
Knowledge repositories
• Technical agent
(e.g.indexing)
•Personal agents
Knowledge Workers
2. Inquiry for explicit knowledge
1. Add explicit knowledge
Explicit  Explicit
• Technical agent
(e.g.workflow agent)
•Personal agents
Tacit  Tacit
4. Input for profiles
of people and
communities
6. Input for profiles
of people,
communities
and processes
Dynamic adaption and creation
3. Inquiry for profiles
of people and
communities
Knowledge carthography
• Agents / Profiles
Definition
•Personal agents
•Communities
•Processes
5. Inquiry for profiles
of people,
communities
and processes
Building the Environment
Decision Framework for Kmproject
Identify Key Values
Define KM strategy
Evaluate Enterprise
Strategy/direction for KM
« Values »
• Business model
• Service goals
• Identify business goals for KM
• Select a knowledge recovery
strategy
• Evaluate potential for Cultural
and business shift
• Evaluate potential benefits
Analyse Benefits/measures
• Set performance measures
• Determine cost and other
resources for KM
• Ensure business unit support
and funding
Source: Gartner Group
Set KM performance goals
•Explicit knowledge apps.
•Tacit knowledge apps.
•Combined apps.
•Set performance goals
Critical Success Factors

KM strategy
 Mission, goals, vision, alternatives, responsibilities, …

Resources
 Budget for staff, development, …

Technology
 Network, user delivery, tools, maintenance, storage

Motivation
 For sharing knowledge

Promotion and Training
Cultural Success Factors

Combine value contributed by individual with value of
contributions by groups.

Face-to-face meetings are still required to bring
contributers together.

Consistent terminology and models are critical.

Communities of practice and experience on processes
and knowledge.
Cultural change is required.
Citation
There is nothing more difficult to plan ,
more doubtful of success,
nor more dangerous to manage
than the creation of a new system.
For the initiator has the enmity of all who
would profit by the preservation of the old
system and merely lukewarm defenders in
those who would gain by the new one.
Machiavelli, 1513
Computer Technologies for KM

Groupware: mail, Lotus Notes, Intranet,Chat
boxes, …

Multimedia, video, …

Documentation systems and XML

Expert systems

Artificial Intelligence systems

Data Warehousing, OLAP, data mining, statistics

Search engins, encyclopedia, in-text search

Agents

Computer based training
Mentioned reasons for KM
In decreasing order of importance:
 Integrate multiple sources of data
 Marketing and sales
 Growth and innovation
 Business process improvement
 People orientation
 Service improvement
 IT orientation
 Information Management orientation
 Cost savings
Source: Gartner group
Think about this !
Knowledge management technology
does not equal
Knowledge management
for the same reason that
an exercise machine
does not equal
exercise