Knowledge Management Webinar

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accadisHochschuleBad Homburg

Self Guided Lecture #3

Knowledge Management

Cristin Howell-Vischer, MIM

MANAGEMENT II – MAN 2600

accadisHochschuleBad Homburg 2

Knowledge Management


Knowledge Management: The Challenge


History of Knowledge Management

The trend towards Knowledge Management (KM) was fueled by the development of IT systems which made it simple to store, display and archive classified, indexed information

In the 1980’s KM began to be viewed as a competitive asset

KM has many connections to:

Change management

Benchmarking

Risk Management

Best Practices


Why is KM Important?

Organizations now face the following challenges:

The increasing value of the intellectual capital which is embedded in end products and services

The increasing convergence of technologies that enable organizations to globalize at the press of the button

The rapid growth of Internet

"Economies are increasingly based on knowledge….What is new is that a growing chunk of production in the modern economy is in the form of intangibles, based on the exploitation of ideas rather than material things…"

Economist Newspaper. September, 23, 2000


The Value of KM

It is important to manage knowledge assets because – Organizations compete increasingly on the base of

knowledge (the only sustainable competitive advantage, according to some)

Most of our work is information based (and often immersed in a computing environment)

Our products, services, and environment are more complex than ever before

Workforces are increasingly unstable leading to escalating demands for knowledge replacement/acquisition


KM – A Cross-Disciplinary Approach

Knowledge management draws from a wide range of disciplines and technologies:

Cognitive science: How do we learn?

Expert systems & “Artificial Intelligence”: Using computers to understand human intelligence

Technical writing

Document management

Decision support systems

Relational and object databases

Simulation

Organizational science


What is Knowledge Management?

1. Treating the knowledge component of business activities as an explicit concern of business reflected in strategy, policy and practice at all levels of the organization

2. Making a direct connection between an organization’s intellectual assets and positive business results


Aren’t we Already Managing Knowledge?

Well, no…..

In fact, most of the time we’re making a really ugly mess of managing information

The terms information and knowledge are often used interchangeably


Data vs. Knowledge

Data is unorganized words, numbers and images Data alone has no meaning or context. Example:

The name Bob Jones in a database is merely data

Bob Jones is a regular customer of our products. This is information Information is - organized or categorized data. It has meaning or

value Knowledge is the use of information An organization using information that Bob Jones is a regular

customer of our products and take initiative to establish a special relationship with Bob Jones is using the information and thus creating customer knowledge

If the information we gained is not used, then the knowledge remains passive. It cannot be considered as an active intangible asset

Similarly if employees have skills but he/she does not use them, then such skills remain passive and of no benefit to the organization


2 Key Thrusts

Sharing existing knowledge“I know what you know”

Developing knowledge for Innovation“Creating and Converting”


Two “Tracks” of KM – According to Sveiby

Data

Information

Knowledge

Intelligence

Two: Management of InformationCodifiableExplicitEasily transferable

One: Management of People•Human•Judgmental•Contextual•Tacit•The transfer requires learning


Knowledge Assets

There are two types of knowledge assets

Explicit or formal assets

copyrights, patents, templates, publications, reports, archives, etc.

Tacit or informal assets

Which are rooted in human experience and include personal belief, perspective, and values


Knowledge Agenda ... in Practice

Knowledge Teams - multi-disciplinary, cross-functional

Knowledge (Data)bases - experts, best practice

Knowledge Centres - hubs of knowledge

Learning Organization - personal/team/org development

Communities of Practice - peers in execution of work

Technology Infrastructure - Intranets, doc mgt


Seven Levers

Customer Knowledge - the most vital knowledge

Knowledge in Products - ‘smarts’ add value

Knowledge in People - but people ‘walk’

Knowledge in Processes - know-how when needed

Organizational Memory - do we know what we know?

Knowledge in Relationships - richness and depth

Knowledge Assets - intellectual capital


Knowledge-Management-

System*(Strategy)

InformalOrganisation(Values and

Culture)

Formal Organisation(Roles andStructure)

ProcessesProcesses

IT- Technology

&Infrastructure

IT- Technology

&Infrastructure

Competence(People)

Competence(People)

Balanced Approach To Successful KM

Source: SBS Consulting


Knowledge Discovery

Knowledge discovery may be defined as the development of new tacit or explicit knowledge from data and information or from the synthesis of prior knowledge


Knowledge Management Processes

Discovery•Combination•Socialization

Capture•Externalization•Internalization

Sharing•Socialization•Exchange

Application•Direction•Routines


Discovery

Combination: When multiple bodies of explicit knowledge (information + data) are

synthesized to create new, more complex sets of explicit knowledge

This happens: through communication via integration and systemization of multiple streams of explicit

knowledge when existing explicit knowledge, information, and data are

reconfigured, recategorized, and recontextualized

Example: Data mining techniques may be used to uncover new relationships among explicit data, to produce predictive or categorization models that create new knowledge






Discovery

Mechanisms that facilitate combination

collaborative problem solving joint decision making collaborative creation of documents






Discovery

Socialization: Synthesis of tacit knowledge across individuals

This happens: through joint activities instead of written or verbal instructions

Examples:

By transferring ideas and images, apprenticeships or internships help newcomers to see how other think.

Conversations at the water cooler helped knowledge sharing among groups at IBM






Discovery

Mechanisms that facilitate socialization

apprenticeships employee rotation across areas conferences brainstorming retreats cooperative projects across departments initiation process for new employees






Knowledge Capture

Knowledge capture is defined as the process of retrieving either explicit or tacit knowledge that resides within people, artifacts or organizational entities

Examples:

Knowledge may reside within an individual’s mind, without that individual having the ability to recognize it and share it with others (tacit knowledge)

Knowledge might reside in an explicit form in a manual, but few people might be aware of it (explicit knowledge)

Knowledge capture might reside outside the organizational boundaries including consultants, competitors, customers, suppliers and prior employers of the organization’s new employees


Capture

Externalization: Involves converting tacit knowledge into explicit forms such as words concepts visuals figurative language (metaphors, analogies, narratives, etc.)

Examples:

Use of metaphor: understanding and experiencing one kind of thing in terms of another

A consultant team writing a document that describes the lessons the team has learned by observing a client organization, executives and approaches






Capture

Mechanisms that facilitate externalization

An Example from the consulting company Viant:

Before every project, consultants are required to complete a “quicksheet” describing:

the knowledge they need what aspects of knowledge can be leveraged from prior projects what they need to create the lessons they hope to learn that they can share with others later






Capture

Internalization: The conversion of explicit knowledge into tacit knowledge Internalization represents the traditional notion of “learning” Explicit knowledge may be embodied in action and practice Or, individuals can acquire tacit knowledge in virtual situations

Vicariously through reading manuals or other’s stories Experientially through simulations or experiments

Example:

A new software consultant reads a book on innovative software development and learns from it.






Capture

Mechanisms that facilitate internalization learning by doing on-the-job training learning by observation face-to-face meetings

Example:

A firm’s Product Division sends their new-product development people to the firm’s telephone call center to chat with the telephone operators, thereby `re-experiencing’ their experiences






Knowledge Sharing

Knowledge sharing systems support the process through which explicit or implicit knowledge is communicated to other individuals


Sharing

Socialization: Promotes sharing of tacit knowledge and exchange or sharing of explicit

knowledge

Technologies which help facilitate Socialization include: Instant messaging Social chat groups VoIP (Voice over Internet Protocol) Video-conferencing Electronic support for communities of practice (COPs)






Sharing

Mechanisms and Technologies that facilitate socialization:

May play an equally important role for knowledge sharing as in knowledge discovery

Example:

Topically focused discussion groups (or technology-enabled chat groups) facilitate knowledge sharing by enabling individuals to explain their knowledge to the rest of the group.






Sharing

Exchange: Mechanisms facilitating exchange: memos & letters manuals progress reports presentations

Technologies facilitating exchange: Groupware & other team collaboration mechanisms web-based access to data and databases repositories of information including best practice databases, lessons learned

systems and expertise locator systems






Knowledge Application

Knowledge Applications systems support the process through which some individuals utilize knowledge possessed by other individuals without actually acquiring, or learning that knowledge

Mechanisms and technologies support knowledge application systems by facilitating routines and direction


Example: Merck Yellow Pages

Yellow pages aim at personal skills of Merck staff

Basic information (no details) comes from HR data bases

Staff may enhance personal information on education and professional experience


Merck’Blue Pages

Collects and structures information and experience with third party companies

Supported by incentive system


Application

Mechanisms that facilitate direction include: traditional hierarchical relationships in organizations help desks support centers

Technologies that support direction include: Experts’ knowledge embedded in expert systems and decision support

systems Troubleshooting systems based on the use of technologies like case based

reasoning






Application

Mechanisms that facilitate routines include: organizational policies work practices standards

Technologies that support routines include: expert systems enterprise resource planning systems traditional management information systems





Knowledge Management Webinar

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