SV O&ICT Final
College 9 – Knowledge Management
Why knowledge management
There is a trend towards knowledge economy
➢ Knowledge economy refers to the production and services based on knowledge-intensive
activities that contribute to an accelerated pace of technical and scientific advance, as well
as rapid obsolescence.
o Greater reliance on intellectual capabilities than on physical inputs or natural
resources.
o Efforts to integrate improvements in every stage of the production process, from the
R&D lab to the factory floor to the interface with customers.
➢ A transition started in the 70s → Growth in patents.
➢ Expansion is tied to computer technology, biotechnology...
➢ Knowledge workers require high education and are better paid.
➢ NL bets strongly on knowledge economy → The top sector policy of Dutch government
contributes to an advanced and innovative knowledge-based economy
Knowledge is an important resource
➢ These are examples of knowledge: Methods to conduct a project, Processes to produce a
product, Insights in market opportunities, Financing new projects, Recruitment of talented
personnel → provide a company with competitive advantage
➢ Why is knowledge different from capital goods?
o Knowledge does not wear out like capital goods: it increases when it is applied!
o Law of diminishing returns does not apply to knowledge generation
o Knowledge itself can be created (sometimes out of nothing) and then sold many
times
What is knowledge management
➢ Knowledge management (KM) refers to the set of business processes developed in an
organisation to acquire, (create), store, disseminate (transfer, share), and apply knowledge.
➢ Knowledge management increases the ability of the organisation to learn from its
environment and to incorporate knowledge into its business processes.
Different types of knowledge
➢ Explicit
o Knowledge expressed into words, numbers, and graphics; ‘Know that’;
Facts; In handbooks; IT essential for storage and transfer
➢ Tacit (a.k.a. implicit)
o Knowledge as experience, insights, intuitions, and hunches; ‘Know how’;
Skills; In the minds of people; IT mainly as support
➢ Structured
o Reports, presentations; Formal rules
➢ Semi-structured
o E-mails, videos, pictures
➢ Unstructured, tacit knowledge
o In the minds of workers; Disperse, imprecise
1
, ➢ Much of the business content is semi-structured or unstructured!
➢ Learn in the book about important dimensions and characteristics of knowledge!
Managing knowledge
➢ There are several value-
adding steps in the
knowledge management
cycle.
➢ The cycle requires the
support of tools called
knowledge management
systems
➢ Focus on humans,
technology is secondary
o Knowing is a
human act, it involves thinking
o Information is not knowledge
➢ KM cannot be separated from technology
o Technological advances shape the field of knowledge management
o 1990s: ERP systems, connectivity / 2000s: Social networks, Big Data technique
➢ Tools must support human knowledge workers
Knowledge management systems
Examples
➢ Business intelligence system
(acquire/create)
o Data mining, warehousing
➢ Communications & networking
(disseminate/ transfer)
o Email, social media, knowledge
network, forum
➢ Enterprise content management systems
(store)
o Repositories, wiki’s, databases
➢ Intelligent systems (apply)
o Business rules & expert systems
➢ Knowledge work systems (acquire /create &
apply)
o Specialised systems
Enterprise content management systems
➢ Enterprise content management systems
need knowledge repositories. (opslagplaats)
➢ Knowledge repositories contain organisational knowledge (corporate memory)
(documents)
➢ Search and retrieval functionality are essential (Keywords, full text search, navigation)
Issues for repositories
2
, ➢ Structuring knowledge
o How to arrange it in a way it is comprehensible? Giving a meaningful structure to
knowledge helps both humans and computers in finding the right knowledge
➢ Adding knowledge
o Who can add what? Everyone (wiki) or just some employees? Specialist knowledge
managers? Experts?
o How easy is it to add knowledge? Mechanisms for tagging and structuring additions?
o What are the incentives to add? Money? Respect?
➢ Retrieving knowledge
o How easy is it to browse and find knowledge? Techniques for smart retrieval and
personalisation? What are the incentives to retrieve?
Structuring knowledge
➢ Giving a meaningful structure to knowledge helps both humans and computers in finding
the right knowledge
➢ Two possible options for structuring knowledge:
o Taxonomies (trees, directories)
o Semantic networks (topic maps)
➢ Taxonomies (rangschikking) are classifications of objects (documents, knowledge
types)
o Trees of concepts
o Usually restricted to is a relations, but others are possible
o Example of taxomony: GRI Standards
o A disadvantage of taxonomies is that they only allow for a single link
between classes instances. If we want more relations between concepts in our
repository, we need to structure it as a (semantic) network (graph instead of tree)
➢ Semantic networks are structures where objects are
part of classes, have attributes and are linked by
meaningful links
o is a relations between classes and individuals
o other relations between classes (or
individuals)
o part of; stakeholder in; implemented by; etc.
o Graphs (instead of trees)
➢ Semantic network is the general term for a network with semantic (“meaningful”) links
➢ Topic Maps are semantic networks defined according to specific standards and technologies
(ISO/IEC 13250:2003)
➢ Buiding a network or a map
o Tagging → Assign keyword to information/document – Keyword can be a class,
property; Hashtags, social bookmarking
o Linking → Explicitly indicating a relationship; Commenting
o Manual tagging and linking is time consuming → Have people do it when they add
knowledge; Automated ontology learning
➢ Expert systems are an intelligent technique for capturing tacit knowledge in a very specific
and limited domain of human expertise.
o Capture the knowledge of skilled employees in the form of a set of rules in a
software system that can be used by others in the organisation.
3
College 9 – Knowledge Management
Why knowledge management
There is a trend towards knowledge economy
➢ Knowledge economy refers to the production and services based on knowledge-intensive
activities that contribute to an accelerated pace of technical and scientific advance, as well
as rapid obsolescence.
o Greater reliance on intellectual capabilities than on physical inputs or natural
resources.
o Efforts to integrate improvements in every stage of the production process, from the
R&D lab to the factory floor to the interface with customers.
➢ A transition started in the 70s → Growth in patents.
➢ Expansion is tied to computer technology, biotechnology...
➢ Knowledge workers require high education and are better paid.
➢ NL bets strongly on knowledge economy → The top sector policy of Dutch government
contributes to an advanced and innovative knowledge-based economy
Knowledge is an important resource
➢ These are examples of knowledge: Methods to conduct a project, Processes to produce a
product, Insights in market opportunities, Financing new projects, Recruitment of talented
personnel → provide a company with competitive advantage
➢ Why is knowledge different from capital goods?
o Knowledge does not wear out like capital goods: it increases when it is applied!
o Law of diminishing returns does not apply to knowledge generation
o Knowledge itself can be created (sometimes out of nothing) and then sold many
times
What is knowledge management
➢ Knowledge management (KM) refers to the set of business processes developed in an
organisation to acquire, (create), store, disseminate (transfer, share), and apply knowledge.
➢ Knowledge management increases the ability of the organisation to learn from its
environment and to incorporate knowledge into its business processes.
Different types of knowledge
➢ Explicit
o Knowledge expressed into words, numbers, and graphics; ‘Know that’;
Facts; In handbooks; IT essential for storage and transfer
➢ Tacit (a.k.a. implicit)
o Knowledge as experience, insights, intuitions, and hunches; ‘Know how’;
Skills; In the minds of people; IT mainly as support
➢ Structured
o Reports, presentations; Formal rules
➢ Semi-structured
o E-mails, videos, pictures
➢ Unstructured, tacit knowledge
o In the minds of workers; Disperse, imprecise
1
, ➢ Much of the business content is semi-structured or unstructured!
➢ Learn in the book about important dimensions and characteristics of knowledge!
Managing knowledge
➢ There are several value-
adding steps in the
knowledge management
cycle.
➢ The cycle requires the
support of tools called
knowledge management
systems
➢ Focus on humans,
technology is secondary
o Knowing is a
human act, it involves thinking
o Information is not knowledge
➢ KM cannot be separated from technology
o Technological advances shape the field of knowledge management
o 1990s: ERP systems, connectivity / 2000s: Social networks, Big Data technique
➢ Tools must support human knowledge workers
Knowledge management systems
Examples
➢ Business intelligence system
(acquire/create)
o Data mining, warehousing
➢ Communications & networking
(disseminate/ transfer)
o Email, social media, knowledge
network, forum
➢ Enterprise content management systems
(store)
o Repositories, wiki’s, databases
➢ Intelligent systems (apply)
o Business rules & expert systems
➢ Knowledge work systems (acquire /create &
apply)
o Specialised systems
Enterprise content management systems
➢ Enterprise content management systems
need knowledge repositories. (opslagplaats)
➢ Knowledge repositories contain organisational knowledge (corporate memory)
(documents)
➢ Search and retrieval functionality are essential (Keywords, full text search, navigation)
Issues for repositories
2
, ➢ Structuring knowledge
o How to arrange it in a way it is comprehensible? Giving a meaningful structure to
knowledge helps both humans and computers in finding the right knowledge
➢ Adding knowledge
o Who can add what? Everyone (wiki) or just some employees? Specialist knowledge
managers? Experts?
o How easy is it to add knowledge? Mechanisms for tagging and structuring additions?
o What are the incentives to add? Money? Respect?
➢ Retrieving knowledge
o How easy is it to browse and find knowledge? Techniques for smart retrieval and
personalisation? What are the incentives to retrieve?
Structuring knowledge
➢ Giving a meaningful structure to knowledge helps both humans and computers in finding
the right knowledge
➢ Two possible options for structuring knowledge:
o Taxonomies (trees, directories)
o Semantic networks (topic maps)
➢ Taxonomies (rangschikking) are classifications of objects (documents, knowledge
types)
o Trees of concepts
o Usually restricted to is a relations, but others are possible
o Example of taxomony: GRI Standards
o A disadvantage of taxonomies is that they only allow for a single link
between classes instances. If we want more relations between concepts in our
repository, we need to structure it as a (semantic) network (graph instead of tree)
➢ Semantic networks are structures where objects are
part of classes, have attributes and are linked by
meaningful links
o is a relations between classes and individuals
o other relations between classes (or
individuals)
o part of; stakeholder in; implemented by; etc.
o Graphs (instead of trees)
➢ Semantic network is the general term for a network with semantic (“meaningful”) links
➢ Topic Maps are semantic networks defined according to specific standards and technologies
(ISO/IEC 13250:2003)
➢ Buiding a network or a map
o Tagging → Assign keyword to information/document – Keyword can be a class,
property; Hashtags, social bookmarking
o Linking → Explicitly indicating a relationship; Commenting
o Manual tagging and linking is time consuming → Have people do it when they add
knowledge; Automated ontology learning
➢ Expert systems are an intelligent technique for capturing tacit knowledge in a very specific
and limited domain of human expertise.
o Capture the knowledge of skilled employees in the form of a set of rules in a
software system that can be used by others in the organisation.
3
