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© 2004 Superfactory™. All Rights Reserved.
Knowledge Management
and
Learning Organizations
Superfactory Excellence Program™
www.superfactory.com
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© 2004 Superfactory™. All Rights Reserved.
Outline
1. Why the Interest?
2. Knowledge Management
1. Trends in Knowledge Management
2. Forms of Knowledge
3. Intellectual Capital
4. Challenges & Critical Success Factors
3. Learning Organizations
1. Team Learning & Personal Mastery
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© 2004 Superfactory™. All Rights Reserved.
“The basic economic resource is no longer
capital, nor natural resources, nor labor. It
is and will be knowledge.”
Peter Drucker
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Why the Interest?
 Opinion leaders
 Perceived growth in knowledge
 Bandwagon effect
 Become part of everyday parlance
 Skills shortage
 Recognition of growing difference between tangible and
intangible assets
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Opinion Leaders
 When the rate of change outside the firm is greater than
the rate of change inside the firm, the end is in sight.
Jack Welch - CEO General Electric
 The rate at which individuals and organizations learn may
be the only source of sustainable competitive advantage.
Ray Stata - CEO Analog Devices
 Any organization can change, but change without the
benefit of learning is risky and inefficient.
Sal Belardo
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Exponential Growth in Knowledge
 By the year 2020 knowledge will double every 73 days or
less
 World Wide Web is doubling every 90 days
 Internet is doubling every 250 days
 Moore s Law The power of silicon technology doubles every
18 months
 Metcalfe s Law The value to those connected to a network
increases by n square
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Bandwagon Effect
 General Electric, ABB, Siemens, BMW, Toyota, Monsanto,
Teltech, Roche, Microsoft, Andersen Consulting, McKinsey &
Company, A.D. Little, 3M, Otican, Pfizer, Skandia,
Steelcase, US West, British petroleum, etc.
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Part of Everyday Parlance
 Go to Amazon.com, and look at the number of books
devoted to the subject
 Search the journal databases
 Look at the number of Ph.D. thesis titles
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Skills Shortage
 The less translation that occurs within someone’s head, the
better. There is a 17% turnover in our business every year.
That means that every five years we lose most of our
knowledge. A knowledge management system must
capture this personal knowledge and translate it into
institutional knowledge.
- Roger Siboni KPMG Peat Marwick
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Tangible vs Intangible Benefits
 The difference between market value and net assets in
growing. Think of this difference as intangible assets or
various types of intellectual capital customer capital,
investor capital, structural capital, human capital.
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“Knowledge management is leveraging
relevant intellectual assets to enhance
organizational performance.”
What is knowledge management?
Stankosky, 2002
Knowledge Management
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The systematic process of creating, maintaining
and nurturing an organization to make the best
use of knowledge to create business value and
generate competitive advantage.
Knowledge Management
another useful definition
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“Management” of Knowledge
 Knowledge management is an integrated systematic approach to
identifying, managing and sharing all of an enterprise’s
information assets, including databases, documents, policies, and
procedures, as well as previously unarticulated expertise and
experience held by individual workers. Fundamentally it is about
making the collective information and experience of an enterprise
available to individual worker.
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Knowledge Management
Some Definitions
 Policies, procedures and technologies employed for
operating a continuously updated linked pair of networked
databases. (Anthes)
 Bringing tacit knowledge to the surface, consolidating it in
forms by which it is more widely accessible, and promoting
its continuing creation. (Birket)
 Process of capturing, distributing and effectively using
knowledge. (Davenport)
 Knowledge management is the process of capturing a
company s collective expertise wherever it resides-in
databases, on paper, or in people s head-and distributing it
to wherever it can help produce the biggest payoff.
Knowledge management is getting the right knowledge to
the right person at the right time .(Info Week 10/20/97)
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The creative process through which additional economic
value is extracted from the stock of knowledge (OECD,
2001)
Redefining Business Innovation
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Why Knowledge Management?
 Organizing existing corporate knowledge
 New ways to share tacit knowledge
 Support for research and knowledge generation
 New ways to share explicit knowledge
 Smart tools to aid decision making
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 The cutting edge of organizational
success (Nonaka, 1991)
 The engine transforming global
economies (Bell, 1973, 1978)
 Leading us toward a new type of
work with new types of workers
(Blackler, Reed and Whitaker, 1993)
 The element that will lead to the
demise of private enterprise
capitalism (Heilbruner, 1976)
 The sum total of value-added in an
enterprise (Peters, 1993)
 The “mobile and heterogeneous
[resource that will end the]
hegemony of financial capital [and
allow employees to] seize power”
(Sveiby & Lloyd, 1987)
Why Knowledge Management?
Knowledge is fast becoming a
primary factor of production (e.g.,
Handy, 1989, 1994; Peter, 1993; Drucker, 1992)
Knowledge is: Knowledge results in:
Conclusion
 The “learning organization” (Mayo
& Lank, 1995)
 The “brain-based organization”
(Harari, 1994)
 Intellectual capital” (Stewart, 1994)
 “Learning partnerships” (Lorange,
1995)
 Obsolete capitalists economies
and radically different societies
(Drucker, 1993)
Source: Theseus International
Management Institute, February 2000
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Knowledge Management Trends
 Survey of 200 Large Firms found:
 82% have KM underway in their organization
 50% have KM staff & budget
 27% have a Chief Knowledge Officer
(Conference Board)
 Survey of nations leading CEOs:
 Second top priority “Improving KM” (88%)
(Foundation for Malcolm Baldrige Award)
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Knowledge Management Trends
 By 2001, enterprises that lack ongoing KM infrastructure will lag
KM-enabled competitors by 30-40% in speed of deployment for
new competitive programs and products
(Gartner Group)
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Dow Chemical: $100m
Silicon Graphics: $2.8m
Texas Instruments: $500m (cost avoidance)
Computer Sciences Corp: $5.8b
Chevron: $150m
Cemex: (average delivery time 20 minutes)
Ford: 3 month reduction in cycle time
Cisco: One hour virtual financial close
KM Pays Off
True KM Implementation and Results
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Knowledge is the human capacity
(potential & actual ability) to take
effective action in varied and uncertain
situations.
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Wisdom is a state of the human mind
characterized by profound understanding
and deep insight. It is often, but not
necessarily, accompanied by extensive
formal knowledge.
Meeker, Joseph, “What is Wisdom”, LANDSCAPE, Vol. 25, No. 1, Jan 1981.
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Use of Knowledge
 Knowledge Identification: Where is the knowledge? Who
has it? What type of knowledge is it?
 Knowledge Elicitation: How can we acquire it? What tools
can we use?
 Knowledge Dissemination: In order for it to be
disseminated, it must be represented so that it can be
stored and processed.
 Knowledge Utilization: We must be able to evaluate the
benefits of its use.
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Paradoxes of Knowledge
 Using knowledge does not consume it but it does get
obsolete.
 Transferring knowledge does not lose it but market
mechanisms allow ownership.
 Knowledge is abundant, but the ability to use it is
scarce.
 Producing knowledge resists organization.
 Much of it walks out the door at the end of the day.
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• Concepts, methodologies
• Facts, beliefs, truths & laws
• Know what, Know how, Know why
• Judgments & expectations, insights
• Relationships, leverage points
• Intuition & feelings
• Meaning and sense making
Forms of Knowledge
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 Data are facts, numbers or individual entities without
context or purpose.
 Information is data that has been organized into a
meaningful context (to aid decision making).
Data and Information
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KM versus Data Management
 Data / information management
 Processing large volumes of facts with little human
interaction
 Puts data into organized frameworks
 Knowledge Management
 Requires human interaction – material must be
organized to facilitate human access to it.
 KM provides links between organized frameworks.
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Knowledge Workers
 Dominant group of workers in the 21st century.
 Specialists with job-specific skills.
 Have significant formal education or formal training.
 Are self-directed learners
 Require multiple, continuous learning opportunities to
maintain their specialized knowledge
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• Knowledge repositories
• Neural systems
• Data-mining tools
• Contact software
• Intranets
• Extranets
• Water Cooler Technology
Knowledge Technology
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Knowledge Repositories
 Tool used to store information
 Also known as data warehouses
 Examples:
 Discussion databases
 Best practices repository
 Lessons Learned
 Learning Histories
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Knowledge Repositories
 Like a data base but for knowledge
 Often mechanistic, technical approach
 Requires tools or interfaces to
 Enter knowledge into repository
 Store, index, sort the knowledge
 Retrieve relevant knowledge when query
 Simplest would be keyword searches
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Common Ideas
 Corporate “intranet” as knowledge repository
 (Intranet is internal network build using Internet technologies such as web,
search engines)
 Internal users (as with Notes systems next time)
 External users (Knowledge@Wharton/HBS Working
Knowledge)
 Create a “corporate portal” interface
 Bring together resources, news of all times
 May be dynamic, personalizable
 Could converge with EIS/”Digital Dashboard” idea
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Neural Systems
 Performance support tools for workers who need
information immediately
 Example: Case based reasoning
 Characteristics of a problem are entered into a system,
classified based on a huge statistical database of cases,
offers up potential solution. This case and it’s resolution
is then added to the database.
 Help Desks
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Data Mining
 Attempt by the system to translate huge amounts of data
into knowledge
 Analyzes patterns
 some examples…..
 Credit Card Companies red-flagging purchases out of
the “norm”
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Contact Software
 Facilitates interaction among individuals to encourage
sharing
 Email
 Intranet chat rooms
 Groupware
 Whiteboards
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Intranets
 Usually the first stage of KM implementation for most
companies
 HR forms, online resources, work product status…
 Plan it with the user in mind: access, flexibility and
navigation
 Putting your cafeteria menu on the intranet does not count
as KM
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Extranets
 Centralized electronic repository of information
 Accessed by clients
 Advertising, newsletters, client specific information, status
of orders….
 Interactive tools for collaboration
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Water Cooler Technology
 A majority of knowledge sharing takes place during
informal conversation around the water cooler
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What does it take?
 20% Right Technology
 80% Cultural change
 Behavior of the leaders
 What type of learning is valued
 Informal structure of the company
 How are mistakes handled
 What is rewarded and what is punished
 How is information shared
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KM vs Information Management
 One expert calls idea that “knowledge management is
about managing knowledge, while information management
is about managing information” a “myth”
 She says knowledge and information are the same “stuff”
but that “[IM] focuses on finding the stuff and moving it
around, while the [KM] is also concerned about how people
create and use the stuff.
 Also “knowledge management deals with a far broader
range of approaches to communicating and using both
knowledge and information.
Source: Ruth Williams (PWC consultant) on CIO.com, 18 October 1999
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KM and Artificial Intelligence
 Within computer field, knowledge first talked about in
Artificial Intelligence (AI)
 Trying to build systems to reason about the world, hold
beliefs
 Requires integrated knowledge base to work against
 Deep understanding of context (“frames”, “scripts”)
needed to understand actions or dialog
 So “knowledge representation” is an important (and
unsolved) challenge
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Expert Systems
 Idea is to capture knowledge of wisdom as a set of rules
 Feed into standard “expert system shell”
 Produced automated expert-in-a-box
 Very hyped during 1980s
 Huge applications expected in medial diagnosis, etc.
 Reality disappoints
 Rules need constant changing
 Expertise is “tacit” and hard to extract from human and
formalize
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Problems with Implementation
 In too many instances, knowledge management initiatives
start in the information technology department ultimately
focusing on the IT infrastructure, and what the IT people
deem important. As a result many of these efforts focus on
information rather than knowledge.
 It is difficult to evaluate learning or to place a value on
intangibles such as knowledge, especially tacit knowledge.
Some types of knowledge take years to digest so that the
benefits of learning may not appear until some time in the
future.
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Organizational Knowledge
 Both explicit and tacit
 Explicit knowledge can be formalized and codified,
embodied in standard process, documented and taught
 Tacit knowledge is unconscious and cannot easily be
transmitted by formal description-requires interaction
and modeling to be transmitted
 Both individual and collective
 Embodied in individual expertise
 Embodied in communities of practice
 Embodied in collectives ofexpertisesthat work
collaboratively
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Explicit and Tacit Knowledge
 Explicit knowledge – what is recorded; easily identified,
articulated, shared and employed
 Tacit knowledge – personal; wisdom and experience;
context-specific; more difficult to extract and codify
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Tacit Knowledge
 Idea associated with Michael Polanyi
 Hungarian scientist turned philosopher
 Several influential ideas about knowledge
 See knowledge is social, public, often personal. Bound
up with contexts, experience
 Says that important knowledge is often tacit rather than
explicit
 Bound up with processes, actions, situations
 Not articulated in conscious, verbal form
 Can do something, but can’t explain how
 Challenge: how to capture this?
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Sharing Tacit Knowledge
 One line of thinking:
 Tacit knowledge is transmitted in hall way chats,
experience working on projects, etc.
 So, can be captured by channeling discussions into
“collaborate workplace” online
 Instead of verbal or email
 Make on-line community groups
 Threaded discussions
 Searchable archives
 Places to post documents and hints
 Lessons from successes and failures
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Intellectual Assets
 Social capital – relationships with customers, employees,
business partners and external experts
 Structural capital – patents; brand names; systems and
processes; management philosophy
 Human capital – education; experience; skills; attitudes
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Intellectual Capital
 From accounting viewpoint, how to represent value of
intangible items
 Big buzzword in late 1990s
 Partly motivated by justifying absurd stock market premiums during boom
 From 1998 paper “If the market does not fall substantially… in 1999-2000 I
believe we have a serious indication that something has in face happened in
the US economy…”
 Quantifying invisible knowledge assets makes prices look more reasonable
 Equivalent to “human resource”, “information resources”,
etc.
 Knowledge and expertise of how to do things
 Bound up with people and culture, not physical assets
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Further Attributes of Knowledge
 Know-how
 Know-why
 Know-what
 Know-who
 Know-where
 Know-when
(Collison and Parcell, 2001)
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Organizational vs Individual Knowledge
 Two issues:
 Corporate knowledge owned by individuals
 Knowledge resides in silos
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Components of KM Programs
 People – communities and networks
 Processes – knowledge-enabled
 Technology – collaboration, knowledge leverage tools
 Content – best practices, internal and external intelligence
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Activities of Managing Knowledge
 Create
 Discover
 Capture
 Distil
 Validate
 Share
 Adapt
 Adopt
 Transfer
 Apply
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Knowledge Management Approaches
 Self-service – intranet portals; yellow pages;
people finder
 Networks and Community of Practice –
knowledge sharing; learning communities
 Facilitated transfer – internal consultants;
dedicated facilitators; known experts
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Sustainable Knowledge Management
 Unconscious incompetence
 Conscious incompetence
 Conscious competence
 Unconscious competence
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LEADERSHIP ORGANIZATION TECHNOLOGY LEARNING
People Processes Technology
Infrastructure Management and Maintenance
Business
Strategy
Implementation /
Operational Plans
• Business Process /
Best Practices
• Capabilities
• Environmental
Influences
• Value Added
Baldanza, 1999
Input
Process
Output
Efficiency Effectiveness
KM Starts with
the Business
Strategy
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 Organizational Culture 80%
 Lack of Ownership 64%
 Info/Comms Technology 55%
 Non-Standardized Processes 53%
 Organizational Structure 54%
 Top Management Commitment 46%
 Rewards / Recognition 46%
 Individual vice Team Emphasis 45%
 Staff Turnover 30%
Barriers to Knowledge Management Success
Ernst & Young KM International Survey, 1996 (431 senior executive responses)
Results From International Survey:
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Approaches to Knowledge Management
 Store, share, organize knowledge
 Knowledge Repository
 Like DBMS for “higher level” knowledge
 Manufacture knowledge from mining operational data
 Create/apply knowledge through online infrastructure for
teamwork
 Team Collaboration tools
 Specialist Community Building
 Related tasks in different areas of organization
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Getting Started
 Identify what your most valuable knowledge is
 Identify where that knowledge is
 Create a knowledge map (skills, expertise, experience)
 Build an intranet, use groupware
 Buy more water coolers
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Approach
Concept Definition Opportunity/Threat
Modelling
Value
Assessment
Framework
• What is this ?
• How do we prioritise the
opportunities
• How do we deal with
potential dis-continuities
(threats)
• How do we assess
the value
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The Knowledge Value Chain
We must recognise that there is a value chain for
“Knowledge” in just the same way that Michael Porter
(1985) proposed that business functions be organised in
terms of the value added to customers.
Creation
Preservation
Integration Transmission Application
 Within the value chain, business processes and KM processes
interweave and at the touch points, create the “Points of
Confluence” that require integration of KM practices
It can be argued that part of the societal role of a university
is to nurture and protect this value chain
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Mapping to the Points of Confluence
Which KM processes are active at the points of confluence
in the Knowledge Value Chain and what are we looking for ?
Preservation
Integration Transmission Application Creation
Catalogue & Store Publish
Discovery
Locate &
Retrieve
• 24x7 Secure Storage
• Data Warehouses
• Document Management
• Digital Archiving
• Netcasting
• Portals
• Low barriers to access
• Information Request Brokers
• Search Engines
• Content extraction
• Intelligent Agents
• Query Tools
• Collaboration Space
• Neural Networks
• Visualisation
• Case-based Reasoning
• Rule-based Systems
• Meta-data standards
• Semantic models
Business
Processes
Business
Processes
Business
Processes
Business
Processes
Business
Processes
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Conceptual Architecture
Knowledge Portal
Discovery Services Collaboration Services
Knowledge map
Knowledge Repository
E-mail, file servers, Internet / intranet services
WP
Interface
Knowledge
Management services
Taxonomy
Information and
process management
Infrastructure
Information and
Knowledge Sources
Email
World Wide
Web People
Corporate
Databases
Collaboration Services
Discovery services
Knowledge Map
Knowledge Repository
supports knowledge sharing
helps users to retrieve and analyse the information in the corporate memory
provides a corporate schema for knowledge classifications
provides the information management functions for captured knowledge
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Commercial Organizations and KM
1. Improvement in operating efficiency of business
processes which benefit from having access to superior
information at the point of need e.g customer-facing
and marketing processes, product development etc
2. A knowledge-empowered organization
3. A way of addressing concerns over the loss of corporate
memory arising from the increasing mobility of labor
“If we only knew half of what we know, we would be twice as profitable”
- Carla Fiorini, CEO Hewlett Packard Corp
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 Find Information More Quickly
 Make Better Decisions Faster
 Gain Insight
 Reuse Work and Ideas
 Create
 Ease Access to People
 Increase Span of Experts
 Learning Organization
 Increase Collaboration
 Increase Synergy
 Learning Organization With an Attitude
 Work Enrichment
 Increase Operational Effectiveness
 Shrink Delivery Times
 Increase Rate of Innovation
 Increase Competitive Positioning
 Shrink Response Time
Support
Strategic
Direction
Job
Effectiveness
Enterprise
Effectiveness
Non-Traditional Benefits
Knowledge Share/Leverage
Traditional Benefits
Knowledge Sharing +
Value Maxim
isation
Return on Investing in KM
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Preserving “Invisible Equity”
1.99
8.95
1.98
3.58
5.38
3.12
Assets Finance
Current
Assets
Non-
Current
Assets
Current
Liabilities
Non Current
Liabilities
Visible
Shareholder
Equity
Invisible
Equity
10.93
• The “Invisible Balance Sheet”
• Management Value-Add
Market Value $14.05 Billion
This illustration was developed using data taken from the CWO Balance Sheet of 31
March 2001
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Universities and KM
1. Improving the velocity of information
2. Increasing the impact of research (freedom of access)
3. Long-term curatorship
Similar drivers towards business performance, but the real
value lies in enhanced research outcomes.
The collaborative efforts of universities towards Knowledge
Management are likely to provide an ‘accelerator’ effect for
research in each participating institution.
This, dis-intermediation of the current publishing business model,
is something that will need to be carefully considered.
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Universities and KM
Relevance to the core mission:
 Protection of the Knowledge Value Chain can be directly
related to the core mission of universities and the role
they play in society.
 Loosening of the traditional bonds between faculty,
students and institution brought about by the impact of
Information Technology, may require even greater
emphasis on the management of knowledge
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Key Elements to Engineering a KM System
Theory: A formulation of apparent relationships or
underlying principles of certain observed phenomena
which has been verified to some degree.
Webster’s New World Dictionary
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SYSTEMS
THINKING
SYSTEMS
ANALYSIS
SYSTEMS
MANAGEMENT
SYSTEMS
ENGINEERING /
BPR
INFORMATION
SYSTEMS
ENGINEERING
AND
MANAGEMENT
KNOWLEDGE
MANAGEMENT
ENGINEERING
THE ENTERPRISE
INTEGRATIVE MANAGEMENT / ENGINEERING
KNOWLEDGE MANAGEMENT INFRASTRUCTURE
SYSTEMS APPROACH
INPUT PROCESS OUTPUT
Knowledge Management Engineering Overview
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INPUTS PROCESS OUTPUTS
FEEDBACK
Stankosky 2001
FEEDBACK
Knowledge Engineering, Integration, and Management
Enhanced
organizational
performance
 Efficiency
 Effectiveness
 Innovation
Enhanced
organizational
performance
 Efficiency
 Effectiveness
 Innovation
Integrative Management
 Management  Plans  Systems Approach  Teams
 Methods and Standards  Information Systems  Enterprise
Assess  Design  Plan  Implement
Integrative Management
 Management  Plans  Systems Approach  Teams
 Methods and Standards  Information Systems  Enterprise
Assess  Design  Plan  Implement
Assess  Design  Plan  Implement
 Assure  Generation
 Codification  Transfer  Use
Codification Personalization
KM Technologies
• Collaborative
• Distributive
• Codified
Organization
Formal Informal
Functions
Processes
Intellectual Assets
(Operational)
 Assure  Generation
 Codification  Transfer  Use
Codification Personalization
Codification Personalization
KM Technologies
• Collaborative
• Distributive
• Codified
Organization
Formal Informal
KM Technologies
• Collaborative
• Distributive
• Codified
KM Technologies
• Collaborative
• Distributive
• Codified
Organization
Formal Informal
Organization
Organization
Formal Informal
Formal
Formal Informal
Informal
Functions
Processes
Functions
Processes
Intellectual Assets
(Operational)
Intellectual Assets
(Operational)
72
© 2004 Superfactory™. All Rights Reserved.
 Embodies a theory for knowledge management, with
validated key elements as design inputs
 Enterprise-wide approach in the design of a knowledge
management system
 Systems’ perspective throughout the various phases of
system design
 Integrates both integrative management and systems
engineering disciplines into a single construct to ensure
successful design, implementation, and management of a
knowledge management system.
Knowledge Engineering Summary
If taking a true systems approach, a knowledge management system will
enhance efficiency, effectiveness, and innovation through leveraging its
enterprise’s intellectual assets.

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Knowledge_Management system important notes

  • 1. 1 © 2004 Superfactory™. All Rights Reserved. Knowledge Management and Learning Organizations Superfactory Excellence Program™ www.superfactory.com
  • 2. 2 © 2004 Superfactory™. All Rights Reserved. Outline 1. Why the Interest? 2. Knowledge Management 1. Trends in Knowledge Management 2. Forms of Knowledge 3. Intellectual Capital 4. Challenges & Critical Success Factors 3. Learning Organizations 1. Team Learning & Personal Mastery
  • 3. 3 © 2004 Superfactory™. All Rights Reserved. “The basic economic resource is no longer capital, nor natural resources, nor labor. It is and will be knowledge.” Peter Drucker
  • 4. 4 © 2004 Superfactory™. All Rights Reserved. Why the Interest?  Opinion leaders  Perceived growth in knowledge  Bandwagon effect  Become part of everyday parlance  Skills shortage  Recognition of growing difference between tangible and intangible assets
  • 5. 5 © 2004 Superfactory™. All Rights Reserved. Opinion Leaders  When the rate of change outside the firm is greater than the rate of change inside the firm, the end is in sight. Jack Welch - CEO General Electric  The rate at which individuals and organizations learn may be the only source of sustainable competitive advantage. Ray Stata - CEO Analog Devices  Any organization can change, but change without the benefit of learning is risky and inefficient. Sal Belardo
  • 6. 6 © 2004 Superfactory™. All Rights Reserved. Exponential Growth in Knowledge  By the year 2020 knowledge will double every 73 days or less  World Wide Web is doubling every 90 days  Internet is doubling every 250 days  Moore s Law The power of silicon technology doubles every 18 months  Metcalfe s Law The value to those connected to a network increases by n square
  • 7. 7 © 2004 Superfactory™. All Rights Reserved. Bandwagon Effect  General Electric, ABB, Siemens, BMW, Toyota, Monsanto, Teltech, Roche, Microsoft, Andersen Consulting, McKinsey & Company, A.D. Little, 3M, Otican, Pfizer, Skandia, Steelcase, US West, British petroleum, etc.
  • 8. 8 © 2004 Superfactory™. All Rights Reserved. Part of Everyday Parlance  Go to Amazon.com, and look at the number of books devoted to the subject  Search the journal databases  Look at the number of Ph.D. thesis titles
  • 9. 9 © 2004 Superfactory™. All Rights Reserved. Skills Shortage  The less translation that occurs within someone’s head, the better. There is a 17% turnover in our business every year. That means that every five years we lose most of our knowledge. A knowledge management system must capture this personal knowledge and translate it into institutional knowledge. - Roger Siboni KPMG Peat Marwick
  • 10. 10 © 2004 Superfactory™. All Rights Reserved. Tangible vs Intangible Benefits  The difference between market value and net assets in growing. Think of this difference as intangible assets or various types of intellectual capital customer capital, investor capital, structural capital, human capital.
  • 11. 11 © 2004 Superfactory™. All Rights Reserved. “Knowledge management is leveraging relevant intellectual assets to enhance organizational performance.” What is knowledge management? Stankosky, 2002 Knowledge Management
  • 12. 12 © 2004 Superfactory™. All Rights Reserved. The systematic process of creating, maintaining and nurturing an organization to make the best use of knowledge to create business value and generate competitive advantage. Knowledge Management another useful definition
  • 13. 13 © 2004 Superfactory™. All Rights Reserved. “Management” of Knowledge  Knowledge management is an integrated systematic approach to identifying, managing and sharing all of an enterprise’s information assets, including databases, documents, policies, and procedures, as well as previously unarticulated expertise and experience held by individual workers. Fundamentally it is about making the collective information and experience of an enterprise available to individual worker.
  • 14. 14 © 2004 Superfactory™. All Rights Reserved. Knowledge Management Some Definitions  Policies, procedures and technologies employed for operating a continuously updated linked pair of networked databases. (Anthes)  Bringing tacit knowledge to the surface, consolidating it in forms by which it is more widely accessible, and promoting its continuing creation. (Birket)  Process of capturing, distributing and effectively using knowledge. (Davenport)  Knowledge management is the process of capturing a company s collective expertise wherever it resides-in databases, on paper, or in people s head-and distributing it to wherever it can help produce the biggest payoff. Knowledge management is getting the right knowledge to the right person at the right time .(Info Week 10/20/97)
  • 15. 15 © 2004 Superfactory™. All Rights Reserved. The creative process through which additional economic value is extracted from the stock of knowledge (OECD, 2001) Redefining Business Innovation
  • 16. 16 © 2004 Superfactory™. All Rights Reserved. Why Knowledge Management?  Organizing existing corporate knowledge  New ways to share tacit knowledge  Support for research and knowledge generation  New ways to share explicit knowledge  Smart tools to aid decision making
  • 17. 17 © 2004 Superfactory™. All Rights Reserved.  The cutting edge of organizational success (Nonaka, 1991)  The engine transforming global economies (Bell, 1973, 1978)  Leading us toward a new type of work with new types of workers (Blackler, Reed and Whitaker, 1993)  The element that will lead to the demise of private enterprise capitalism (Heilbruner, 1976)  The sum total of value-added in an enterprise (Peters, 1993)  The “mobile and heterogeneous [resource that will end the] hegemony of financial capital [and allow employees to] seize power” (Sveiby & Lloyd, 1987) Why Knowledge Management? Knowledge is fast becoming a primary factor of production (e.g., Handy, 1989, 1994; Peter, 1993; Drucker, 1992) Knowledge is: Knowledge results in: Conclusion  The “learning organization” (Mayo & Lank, 1995)  The “brain-based organization” (Harari, 1994)  Intellectual capital” (Stewart, 1994)  “Learning partnerships” (Lorange, 1995)  Obsolete capitalists economies and radically different societies (Drucker, 1993) Source: Theseus International Management Institute, February 2000
  • 18. 18 © 2004 Superfactory™. All Rights Reserved. Knowledge Management Trends  Survey of 200 Large Firms found:  82% have KM underway in their organization  50% have KM staff & budget  27% have a Chief Knowledge Officer (Conference Board)  Survey of nations leading CEOs:  Second top priority “Improving KM” (88%) (Foundation for Malcolm Baldrige Award)
  • 19. 19 © 2004 Superfactory™. All Rights Reserved. Knowledge Management Trends  By 2001, enterprises that lack ongoing KM infrastructure will lag KM-enabled competitors by 30-40% in speed of deployment for new competitive programs and products (Gartner Group)
  • 20. 20 © 2004 Superfactory™. All Rights Reserved. Dow Chemical: $100m Silicon Graphics: $2.8m Texas Instruments: $500m (cost avoidance) Computer Sciences Corp: $5.8b Chevron: $150m Cemex: (average delivery time 20 minutes) Ford: 3 month reduction in cycle time Cisco: One hour virtual financial close KM Pays Off True KM Implementation and Results
  • 21. 21 © 2004 Superfactory™. All Rights Reserved. Knowledge is the human capacity (potential & actual ability) to take effective action in varied and uncertain situations.
  • 22. 22 © 2004 Superfactory™. All Rights Reserved. Wisdom is a state of the human mind characterized by profound understanding and deep insight. It is often, but not necessarily, accompanied by extensive formal knowledge. Meeker, Joseph, “What is Wisdom”, LANDSCAPE, Vol. 25, No. 1, Jan 1981.
  • 23. 23 © 2004 Superfactory™. All Rights Reserved. Use of Knowledge  Knowledge Identification: Where is the knowledge? Who has it? What type of knowledge is it?  Knowledge Elicitation: How can we acquire it? What tools can we use?  Knowledge Dissemination: In order for it to be disseminated, it must be represented so that it can be stored and processed.  Knowledge Utilization: We must be able to evaluate the benefits of its use.
  • 24. 24 © 2004 Superfactory™. All Rights Reserved. Paradoxes of Knowledge  Using knowledge does not consume it but it does get obsolete.  Transferring knowledge does not lose it but market mechanisms allow ownership.  Knowledge is abundant, but the ability to use it is scarce.  Producing knowledge resists organization.  Much of it walks out the door at the end of the day.
  • 25. 25 © 2004 Superfactory™. All Rights Reserved. • Concepts, methodologies • Facts, beliefs, truths & laws • Know what, Know how, Know why • Judgments & expectations, insights • Relationships, leverage points • Intuition & feelings • Meaning and sense making Forms of Knowledge
  • 26. 26 © 2004 Superfactory™. All Rights Reserved.  Data are facts, numbers or individual entities without context or purpose.  Information is data that has been organized into a meaningful context (to aid decision making). Data and Information
  • 27. 27 © 2004 Superfactory™. All Rights Reserved. KM versus Data Management  Data / information management  Processing large volumes of facts with little human interaction  Puts data into organized frameworks  Knowledge Management  Requires human interaction – material must be organized to facilitate human access to it.  KM provides links between organized frameworks.
  • 28. 28 © 2004 Superfactory™. All Rights Reserved. Knowledge Workers  Dominant group of workers in the 21st century.  Specialists with job-specific skills.  Have significant formal education or formal training.  Are self-directed learners  Require multiple, continuous learning opportunities to maintain their specialized knowledge
  • 29. 29 © 2004 Superfactory™. All Rights Reserved. • Knowledge repositories • Neural systems • Data-mining tools • Contact software • Intranets • Extranets • Water Cooler Technology Knowledge Technology
  • 30. 30 © 2004 Superfactory™. All Rights Reserved. Knowledge Repositories  Tool used to store information  Also known as data warehouses  Examples:  Discussion databases  Best practices repository  Lessons Learned  Learning Histories
  • 31. 31 © 2004 Superfactory™. All Rights Reserved. Knowledge Repositories  Like a data base but for knowledge  Often mechanistic, technical approach  Requires tools or interfaces to  Enter knowledge into repository  Store, index, sort the knowledge  Retrieve relevant knowledge when query  Simplest would be keyword searches
  • 32. 32 © 2004 Superfactory™. All Rights Reserved. Common Ideas  Corporate “intranet” as knowledge repository  (Intranet is internal network build using Internet technologies such as web, search engines)  Internal users (as with Notes systems next time)  External users (Knowledge@Wharton/HBS Working Knowledge)  Create a “corporate portal” interface  Bring together resources, news of all times  May be dynamic, personalizable  Could converge with EIS/”Digital Dashboard” idea
  • 33. 33 © 2004 Superfactory™. All Rights Reserved. Neural Systems  Performance support tools for workers who need information immediately  Example: Case based reasoning  Characteristics of a problem are entered into a system, classified based on a huge statistical database of cases, offers up potential solution. This case and it’s resolution is then added to the database.  Help Desks
  • 34. 34 © 2004 Superfactory™. All Rights Reserved. Data Mining  Attempt by the system to translate huge amounts of data into knowledge  Analyzes patterns  some examples…..  Credit Card Companies red-flagging purchases out of the “norm”
  • 35. 35 © 2004 Superfactory™. All Rights Reserved. Contact Software  Facilitates interaction among individuals to encourage sharing  Email  Intranet chat rooms  Groupware  Whiteboards
  • 36. 36 © 2004 Superfactory™. All Rights Reserved. Intranets  Usually the first stage of KM implementation for most companies  HR forms, online resources, work product status…  Plan it with the user in mind: access, flexibility and navigation  Putting your cafeteria menu on the intranet does not count as KM
  • 37. 37 © 2004 Superfactory™. All Rights Reserved. Extranets  Centralized electronic repository of information  Accessed by clients  Advertising, newsletters, client specific information, status of orders….  Interactive tools for collaboration
  • 38. 38 © 2004 Superfactory™. All Rights Reserved. Water Cooler Technology  A majority of knowledge sharing takes place during informal conversation around the water cooler
  • 39. 39 © 2004 Superfactory™. All Rights Reserved. What does it take?  20% Right Technology  80% Cultural change  Behavior of the leaders  What type of learning is valued  Informal structure of the company  How are mistakes handled  What is rewarded and what is punished  How is information shared
  • 40. 40 © 2004 Superfactory™. All Rights Reserved. KM vs Information Management  One expert calls idea that “knowledge management is about managing knowledge, while information management is about managing information” a “myth”  She says knowledge and information are the same “stuff” but that “[IM] focuses on finding the stuff and moving it around, while the [KM] is also concerned about how people create and use the stuff.  Also “knowledge management deals with a far broader range of approaches to communicating and using both knowledge and information. Source: Ruth Williams (PWC consultant) on CIO.com, 18 October 1999
  • 41. 41 © 2004 Superfactory™. All Rights Reserved. KM and Artificial Intelligence  Within computer field, knowledge first talked about in Artificial Intelligence (AI)  Trying to build systems to reason about the world, hold beliefs  Requires integrated knowledge base to work against  Deep understanding of context (“frames”, “scripts”) needed to understand actions or dialog  So “knowledge representation” is an important (and unsolved) challenge
  • 42. 42 © 2004 Superfactory™. All Rights Reserved. Expert Systems  Idea is to capture knowledge of wisdom as a set of rules  Feed into standard “expert system shell”  Produced automated expert-in-a-box  Very hyped during 1980s  Huge applications expected in medial diagnosis, etc.  Reality disappoints  Rules need constant changing  Expertise is “tacit” and hard to extract from human and formalize
  • 43. 43 © 2004 Superfactory™. All Rights Reserved. Problems with Implementation  In too many instances, knowledge management initiatives start in the information technology department ultimately focusing on the IT infrastructure, and what the IT people deem important. As a result many of these efforts focus on information rather than knowledge.  It is difficult to evaluate learning or to place a value on intangibles such as knowledge, especially tacit knowledge. Some types of knowledge take years to digest so that the benefits of learning may not appear until some time in the future.
  • 44. 44 © 2004 Superfactory™. All Rights Reserved. Organizational Knowledge  Both explicit and tacit  Explicit knowledge can be formalized and codified, embodied in standard process, documented and taught  Tacit knowledge is unconscious and cannot easily be transmitted by formal description-requires interaction and modeling to be transmitted  Both individual and collective  Embodied in individual expertise  Embodied in communities of practice  Embodied in collectives ofexpertisesthat work collaboratively
  • 45. 45 © 2004 Superfactory™. All Rights Reserved. Explicit and Tacit Knowledge  Explicit knowledge – what is recorded; easily identified, articulated, shared and employed  Tacit knowledge – personal; wisdom and experience; context-specific; more difficult to extract and codify
  • 46. 46 © 2004 Superfactory™. All Rights Reserved. Tacit Knowledge  Idea associated with Michael Polanyi  Hungarian scientist turned philosopher  Several influential ideas about knowledge  See knowledge is social, public, often personal. Bound up with contexts, experience  Says that important knowledge is often tacit rather than explicit  Bound up with processes, actions, situations  Not articulated in conscious, verbal form  Can do something, but can’t explain how  Challenge: how to capture this?
  • 47. 47 © 2004 Superfactory™. All Rights Reserved. Sharing Tacit Knowledge  One line of thinking:  Tacit knowledge is transmitted in hall way chats, experience working on projects, etc.  So, can be captured by channeling discussions into “collaborate workplace” online  Instead of verbal or email  Make on-line community groups  Threaded discussions  Searchable archives  Places to post documents and hints  Lessons from successes and failures
  • 48. 48 © 2004 Superfactory™. All Rights Reserved. Intellectual Assets  Social capital – relationships with customers, employees, business partners and external experts  Structural capital – patents; brand names; systems and processes; management philosophy  Human capital – education; experience; skills; attitudes
  • 49. 49 © 2004 Superfactory™. All Rights Reserved. Intellectual Capital  From accounting viewpoint, how to represent value of intangible items  Big buzzword in late 1990s  Partly motivated by justifying absurd stock market premiums during boom  From 1998 paper “If the market does not fall substantially… in 1999-2000 I believe we have a serious indication that something has in face happened in the US economy…”  Quantifying invisible knowledge assets makes prices look more reasonable  Equivalent to “human resource”, “information resources”, etc.  Knowledge and expertise of how to do things  Bound up with people and culture, not physical assets
  • 50. 50 © 2004 Superfactory™. All Rights Reserved. Further Attributes of Knowledge  Know-how  Know-why  Know-what  Know-who  Know-where  Know-when (Collison and Parcell, 2001)
  • 51. 51 © 2004 Superfactory™. All Rights Reserved. Organizational vs Individual Knowledge  Two issues:  Corporate knowledge owned by individuals  Knowledge resides in silos
  • 52. 52 © 2004 Superfactory™. All Rights Reserved. Components of KM Programs  People – communities and networks  Processes – knowledge-enabled  Technology – collaboration, knowledge leverage tools  Content – best practices, internal and external intelligence
  • 53. 53 © 2004 Superfactory™. All Rights Reserved. Activities of Managing Knowledge  Create  Discover  Capture  Distil  Validate  Share  Adapt  Adopt  Transfer  Apply
  • 54. 54 © 2004 Superfactory™. All Rights Reserved. Knowledge Management Approaches  Self-service – intranet portals; yellow pages; people finder  Networks and Community of Practice – knowledge sharing; learning communities  Facilitated transfer – internal consultants; dedicated facilitators; known experts
  • 55. 55 © 2004 Superfactory™. All Rights Reserved. Sustainable Knowledge Management  Unconscious incompetence  Conscious incompetence  Conscious competence  Unconscious competence
  • 56. 56 © 2004 Superfactory™. All Rights Reserved. LEADERSHIP ORGANIZATION TECHNOLOGY LEARNING People Processes Technology Infrastructure Management and Maintenance Business Strategy Implementation / Operational Plans • Business Process / Best Practices • Capabilities • Environmental Influences • Value Added Baldanza, 1999 Input Process Output Efficiency Effectiveness KM Starts with the Business Strategy
  • 57. 57 © 2004 Superfactory™. All Rights Reserved.  Organizational Culture 80%  Lack of Ownership 64%  Info/Comms Technology 55%  Non-Standardized Processes 53%  Organizational Structure 54%  Top Management Commitment 46%  Rewards / Recognition 46%  Individual vice Team Emphasis 45%  Staff Turnover 30% Barriers to Knowledge Management Success Ernst & Young KM International Survey, 1996 (431 senior executive responses) Results From International Survey:
  • 58. 58 © 2004 Superfactory™. All Rights Reserved. Approaches to Knowledge Management  Store, share, organize knowledge  Knowledge Repository  Like DBMS for “higher level” knowledge  Manufacture knowledge from mining operational data  Create/apply knowledge through online infrastructure for teamwork  Team Collaboration tools  Specialist Community Building  Related tasks in different areas of organization
  • 59. 59 © 2004 Superfactory™. All Rights Reserved. Getting Started  Identify what your most valuable knowledge is  Identify where that knowledge is  Create a knowledge map (skills, expertise, experience)  Build an intranet, use groupware  Buy more water coolers
  • 60. 60 © 2004 Superfactory™. All Rights Reserved. Approach Concept Definition Opportunity/Threat Modelling Value Assessment Framework • What is this ? • How do we prioritise the opportunities • How do we deal with potential dis-continuities (threats) • How do we assess the value
  • 61. 61 © 2004 Superfactory™. All Rights Reserved. The Knowledge Value Chain We must recognise that there is a value chain for “Knowledge” in just the same way that Michael Porter (1985) proposed that business functions be organised in terms of the value added to customers. Creation Preservation Integration Transmission Application  Within the value chain, business processes and KM processes interweave and at the touch points, create the “Points of Confluence” that require integration of KM practices It can be argued that part of the societal role of a university is to nurture and protect this value chain
  • 62. 62 © 2004 Superfactory™. All Rights Reserved. Mapping to the Points of Confluence Which KM processes are active at the points of confluence in the Knowledge Value Chain and what are we looking for ? Preservation Integration Transmission Application Creation Catalogue & Store Publish Discovery Locate & Retrieve • 24x7 Secure Storage • Data Warehouses • Document Management • Digital Archiving • Netcasting • Portals • Low barriers to access • Information Request Brokers • Search Engines • Content extraction • Intelligent Agents • Query Tools • Collaboration Space • Neural Networks • Visualisation • Case-based Reasoning • Rule-based Systems • Meta-data standards • Semantic models Business Processes Business Processes Business Processes Business Processes Business Processes
  • 63. 63 © 2004 Superfactory™. All Rights Reserved. Conceptual Architecture Knowledge Portal Discovery Services Collaboration Services Knowledge map Knowledge Repository E-mail, file servers, Internet / intranet services WP Interface Knowledge Management services Taxonomy Information and process management Infrastructure Information and Knowledge Sources Email World Wide Web People Corporate Databases Collaboration Services Discovery services Knowledge Map Knowledge Repository supports knowledge sharing helps users to retrieve and analyse the information in the corporate memory provides a corporate schema for knowledge classifications provides the information management functions for captured knowledge
  • 64. 64 © 2004 Superfactory™. All Rights Reserved. Commercial Organizations and KM 1. Improvement in operating efficiency of business processes which benefit from having access to superior information at the point of need e.g customer-facing and marketing processes, product development etc 2. A knowledge-empowered organization 3. A way of addressing concerns over the loss of corporate memory arising from the increasing mobility of labor “If we only knew half of what we know, we would be twice as profitable” - Carla Fiorini, CEO Hewlett Packard Corp
  • 65. 65 © 2004 Superfactory™. All Rights Reserved.  Find Information More Quickly  Make Better Decisions Faster  Gain Insight  Reuse Work and Ideas  Create  Ease Access to People  Increase Span of Experts  Learning Organization  Increase Collaboration  Increase Synergy  Learning Organization With an Attitude  Work Enrichment  Increase Operational Effectiveness  Shrink Delivery Times  Increase Rate of Innovation  Increase Competitive Positioning  Shrink Response Time Support Strategic Direction Job Effectiveness Enterprise Effectiveness Non-Traditional Benefits Knowledge Share/Leverage Traditional Benefits Knowledge Sharing + Value Maxim isation Return on Investing in KM
  • 66. 66 © 2004 Superfactory™. All Rights Reserved. Preserving “Invisible Equity” 1.99 8.95 1.98 3.58 5.38 3.12 Assets Finance Current Assets Non- Current Assets Current Liabilities Non Current Liabilities Visible Shareholder Equity Invisible Equity 10.93 • The “Invisible Balance Sheet” • Management Value-Add Market Value $14.05 Billion This illustration was developed using data taken from the CWO Balance Sheet of 31 March 2001
  • 67. 67 © 2004 Superfactory™. All Rights Reserved. Universities and KM 1. Improving the velocity of information 2. Increasing the impact of research (freedom of access) 3. Long-term curatorship Similar drivers towards business performance, but the real value lies in enhanced research outcomes. The collaborative efforts of universities towards Knowledge Management are likely to provide an ‘accelerator’ effect for research in each participating institution. This, dis-intermediation of the current publishing business model, is something that will need to be carefully considered.
  • 68. 68 © 2004 Superfactory™. All Rights Reserved. Universities and KM Relevance to the core mission:  Protection of the Knowledge Value Chain can be directly related to the core mission of universities and the role they play in society.  Loosening of the traditional bonds between faculty, students and institution brought about by the impact of Information Technology, may require even greater emphasis on the management of knowledge
  • 69. 69 © 2004 Superfactory™. All Rights Reserved. Key Elements to Engineering a KM System Theory: A formulation of apparent relationships or underlying principles of certain observed phenomena which has been verified to some degree. Webster’s New World Dictionary
  • 70. 70 © 2004 Superfactory™. All Rights Reserved. SYSTEMS THINKING SYSTEMS ANALYSIS SYSTEMS MANAGEMENT SYSTEMS ENGINEERING / BPR INFORMATION SYSTEMS ENGINEERING AND MANAGEMENT KNOWLEDGE MANAGEMENT ENGINEERING THE ENTERPRISE INTEGRATIVE MANAGEMENT / ENGINEERING KNOWLEDGE MANAGEMENT INFRASTRUCTURE SYSTEMS APPROACH INPUT PROCESS OUTPUT Knowledge Management Engineering Overview
  • 71. 71 © 2004 Superfactory™. All Rights Reserved. INPUTS PROCESS OUTPUTS FEEDBACK Stankosky 2001 FEEDBACK Knowledge Engineering, Integration, and Management Enhanced organizational performance  Efficiency  Effectiveness  Innovation Enhanced organizational performance  Efficiency  Effectiveness  Innovation Integrative Management  Management  Plans  Systems Approach  Teams  Methods and Standards  Information Systems  Enterprise Assess  Design  Plan  Implement Integrative Management  Management  Plans  Systems Approach  Teams  Methods and Standards  Information Systems  Enterprise Assess  Design  Plan  Implement Assess  Design  Plan  Implement  Assure  Generation  Codification  Transfer  Use Codification Personalization KM Technologies • Collaborative • Distributive • Codified Organization Formal Informal Functions Processes Intellectual Assets (Operational)  Assure  Generation  Codification  Transfer  Use Codification Personalization Codification Personalization KM Technologies • Collaborative • Distributive • Codified Organization Formal Informal KM Technologies • Collaborative • Distributive • Codified KM Technologies • Collaborative • Distributive • Codified Organization Formal Informal Organization Organization Formal Informal Formal Formal Informal Informal Functions Processes Functions Processes Intellectual Assets (Operational) Intellectual Assets (Operational)
  • 72. 72 © 2004 Superfactory™. All Rights Reserved.  Embodies a theory for knowledge management, with validated key elements as design inputs  Enterprise-wide approach in the design of a knowledge management system  Systems’ perspective throughout the various phases of system design  Integrates both integrative management and systems engineering disciplines into a single construct to ensure successful design, implementation, and management of a knowledge management system. Knowledge Engineering Summary If taking a true systems approach, a knowledge management system will enhance efficiency, effectiveness, and innovation through leveraging its enterprise’s intellectual assets.