The document provides an overview of knowledge management concepts from several perspectives:
1) It distinguishes between data, information, knowledge, wisdom and discusses the relationships between them.
2) It examines tacit and explicit knowledge and the processes of moving between the two.
3) It explores individual and organizational learning and knowledge acquisition.
4) It introduces knowledge management processes and discusses challenges organizations face in managing knowledge.
I have completed my Post graduate diploma program in design from National Institute of Design in Design for digital exp. I am keenly interested in projects related on user experience design, research methodology and development, product usability, service design and Interaction &interface design. I preferably would also like to do research and design process for innovative e- learning system, tools and techniques.
I am very passionate to read articles and materials on ancient civilization, culture, people and arts& crafts of different countries.
Confluence Adoption: Techniques for Growing Your WikiAtlassian
Whether you're starting small, or aiming big, it helps to have a good set of ideas to aid adoption. This session discusses some of the best tools in the wiki adoption toolbox - from where to start, to how best to grow.
Atlassian Speaker: Bill Arconati
Customer Speaker: Michael Mielke of Deutsche Bahn
Key Takeaways:
* Success patterns for wiki adoption
* Roles and activities to aid a successful deployment
* What to try, what to avoid
Why MarkLogic: Addressing the Challenges of Unstructured Information with Pur...MarkLogic Corporation
This paper describes why MarkLogic Server helps organizations leverage unstructured information more effectively. It is intended for technology executives and project leaders who recognize the potential value possible by taking better advantage of the estimated 70 to 90 percent of today's "unstructured" information. For commercial organizations, this may lead to competitive advantage or new business opportunities, while government agencies may obtain greater mission advantage.
This paper is also relevant for readers who recognize the most commonly used tools today are not optimized to leverage unstructured information since most were designed for structured data. With the right tools, there is an opportunity for significant improvement with regard to agility, efficiency, flexibility, performance, and scalability.
Semantics empowered Physical-Cyber-Social Systems for EarthCubeAmit Sheth
Presentation at the EarthCube Face Face-to-Face Workshop of Semantics & Ontologies Workgroup: April 30-May 1, 2012, Ballston, VA.
Workshop site: http://earthcube.ning.com/group/semantics-and-ontologies/page/workshops
For more recent material on this topic, see: http://wiki.knoesis.org/index.php/PCS
Modern learning models require linking experiences in training environments with experiences in the real-world. However, data about real-world experiences is notoriously hard to collect. Social spaces bring new opportunities to tackle this challenge, supplying digital traces where people talk about their real-world experiences. These traces can become valuable resource, especially in ill-defined domains that embed multiple interpretations. The paper presents a unique approach to aggregate content from social spaces into a semantic-enriched data browser to facilitate informal learning in ill-defined domains. This work pioneers a new way to exploit digital traces about real-world experiences as authentic examples in informal learning contexts. An exploratory study is used to determine both strengths and areas needing attention. The results suggest that semantics can be successfully used in social spaces for informal learning – especially when combined with carefully designed nudges.
Focus is on understanding Information Professionals and how they connect with solution providers.
This was presented at the Document Management Solution Providers Executive Forum (http://www.aiim.org/dmspef).
Want to get involved in our big data/big content efforts? Direct Tweet me at jmancini77 -- I also did a blog post on this topic -- http://www.digitallandfill.org/2012/03/big-data-and-big-content-just-hype-or-a-real-opportunity.html
Big Data [sorry] & Data Science: What Does a Data Scientist Do?Data Science London
What 'kind of things' does a data scientist do? What are the foundations and principles of data science? What is a Data Product? What does the data science process looks like? Learning from data: Data Modeling or Algorithmic Modeling? - talk by Carlos Somohano @ds_ldn at The Cloud and Big Data: HDInsight on Azure London 25/01/13
I have completed my Post graduate diploma program in design from National Institute of Design in Design for digital exp. I am keenly interested in projects related on user experience design, research methodology and development, product usability, service design and Interaction &interface design. I preferably would also like to do research and design process for innovative e- learning system, tools and techniques.
I am very passionate to read articles and materials on ancient civilization, culture, people and arts& crafts of different countries.
Confluence Adoption: Techniques for Growing Your WikiAtlassian
Whether you're starting small, or aiming big, it helps to have a good set of ideas to aid adoption. This session discusses some of the best tools in the wiki adoption toolbox - from where to start, to how best to grow.
Atlassian Speaker: Bill Arconati
Customer Speaker: Michael Mielke of Deutsche Bahn
Key Takeaways:
* Success patterns for wiki adoption
* Roles and activities to aid a successful deployment
* What to try, what to avoid
Why MarkLogic: Addressing the Challenges of Unstructured Information with Pur...MarkLogic Corporation
This paper describes why MarkLogic Server helps organizations leverage unstructured information more effectively. It is intended for technology executives and project leaders who recognize the potential value possible by taking better advantage of the estimated 70 to 90 percent of today's "unstructured" information. For commercial organizations, this may lead to competitive advantage or new business opportunities, while government agencies may obtain greater mission advantage.
This paper is also relevant for readers who recognize the most commonly used tools today are not optimized to leverage unstructured information since most were designed for structured data. With the right tools, there is an opportunity for significant improvement with regard to agility, efficiency, flexibility, performance, and scalability.
Semantics empowered Physical-Cyber-Social Systems for EarthCubeAmit Sheth
Presentation at the EarthCube Face Face-to-Face Workshop of Semantics & Ontologies Workgroup: April 30-May 1, 2012, Ballston, VA.
Workshop site: http://earthcube.ning.com/group/semantics-and-ontologies/page/workshops
For more recent material on this topic, see: http://wiki.knoesis.org/index.php/PCS
Modern learning models require linking experiences in training environments with experiences in the real-world. However, data about real-world experiences is notoriously hard to collect. Social spaces bring new opportunities to tackle this challenge, supplying digital traces where people talk about their real-world experiences. These traces can become valuable resource, especially in ill-defined domains that embed multiple interpretations. The paper presents a unique approach to aggregate content from social spaces into a semantic-enriched data browser to facilitate informal learning in ill-defined domains. This work pioneers a new way to exploit digital traces about real-world experiences as authentic examples in informal learning contexts. An exploratory study is used to determine both strengths and areas needing attention. The results suggest that semantics can be successfully used in social spaces for informal learning – especially when combined with carefully designed nudges.
Focus is on understanding Information Professionals and how they connect with solution providers.
This was presented at the Document Management Solution Providers Executive Forum (http://www.aiim.org/dmspef).
Want to get involved in our big data/big content efforts? Direct Tweet me at jmancini77 -- I also did a blog post on this topic -- http://www.digitallandfill.org/2012/03/big-data-and-big-content-just-hype-or-a-real-opportunity.html
Big Data [sorry] & Data Science: What Does a Data Scientist Do?Data Science London
What 'kind of things' does a data scientist do? What are the foundations and principles of data science? What is a Data Product? What does the data science process looks like? Learning from data: Data Modeling or Algorithmic Modeling? - talk by Carlos Somohano @ds_ldn at The Cloud and Big Data: HDInsight on Azure London 25/01/13
IBM Information Management - Efter stormen: Uppnå konkurrenskraft och sänkta ...IBM Sverige
En lärdom som kan dras av den finansiella krisen är att vi måste bli bättre på att förutse framtiden och planera nästa steg. IBM Cognos lösningar för beslutsstöd hjälper dig att använda och analysera affärsinformation för att få insikt i verksamheten och framtiden. Vi berättar hur du kan använda information tillsammans med avancerade analyser för att simulera olika strategier för framgång. Presentationen hålls på engelska av
Juha Teljo, Information Agenda Expert, IBM
Denna presentation hölls på ett seminariepass för Information Management under IBM Software Day 2010.
Keynote at 2012 Semantic Technology and Business Conference
Scale, Structure, and Semantics
Daniel Tunkelang, LinkedIn
Science fiction has a mixed track record when it comes to anticipating technological innovations. While Jules Verne fared well with with his predictions of submarine and space technology, artificial intelligence hasn't produced anything like Arthur C. Clarke's HAL 9000.
Instead, we've managed to elicit intelligence from machines through unexpected means. Search engines have achieved remarkable success in organizing the world's information by crawling the web, indexing documents, and exploiting link structure to establish authoritativeness. At LinkedIn, we apply large-scale analytics to terabytes of semistructured data to deliver products and insights that serve our 150M+ members. Semantics emerge when we apply the right analytical techniques to a sufficient quality and quantity of data.
In this talk, I will describe how LinkedIn's huge and rich graph of relationship data that powers the products our users love. I believe that the lessons we have learned apply broadly to other semantic applications. While quantity and quality of data are the key challenges to delivering a semantically rich experience, the key is to create the right ecosystem that incents people to give you good data, which then forms the basis for great data products.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
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It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
1. Alex Domínguez
alexdfar@yahoo.com
jadoming@mail.unitec.mx
www.unitec.mx
Lecture notes, Grenoble Graduate School of Business,
France, May 2008.
2. Contents
From the point of view of non-IT management, the main objective of this course is to
• Understand the relationship between knowledge, information and data
• Understand why knowledge management is an issue today, when it never was
before
• Understand how to specify and implement a knowledge management project in an
organisation
1. Symbols, 3. The Problem
2. On 4. The Learning 5. Knowledge
Data and of KM in
Knowledge Organisations Sharing
Information Organisations
7.
10. KM 8. Communities 6. Social
9. Storytelling Organisation’s
Technology of Practice Networks
Culture
13. KM 14. The Chief
12. Business
11. KM Strategy Framework and Knowledge
Case for KM
Processes Officer
2
3. Information Technology Requirements
Hardware
• Lap Top computer, if possible
• Speakers
Software applications
• Acrobat Reader – Version 7 or higher
• Windows Media Player – Version 9 or higher
• MindManager software (you can download a 21-days
free trial version on www.mindjet.com)
Telecommunications
• Internet Connection
3
4. Bibliography
Books
• Groff, T.R. Introduction to Knowledge Management: KM in Business. Butherworth-
Heinemann, UK, 2003.
• MacDonald, J. Understanding Knowledge Management in a Week. Institute of
Management. Hodder &Stoughton, UK, 1999.
• O‟Dell, C. The Executive‟s Role in Knowledge Management. APQC Publications, USA,
2004.
• Liebowitz, J. (Editor). Knowledge Management Handbook. CRC Press, USA, 1999.
• Rumizen, M.C. The Complete Idiot‟s Guide to Knowledge Management. Alpha Books,
USA, 2003.
• Skyrme, D.J. Knowledge Networking: Creating the Collaborative Enterprise.
Butherworth-Heinemann, UK, 1999.
• Tiwana, A. The Knowledge Management Toolkit. 2nd Edition. Prentice-Hall, PTR, USA,
2002.
Websites
• BRINT: Knowledge Management: www.brint.com/km/
• Knowledge Board, Your Global Community: http://www.knowledgeboard.com/
• Knowledge Connections, Home of the I3 Update: www.skyrme.com/index.htm
• The Gurteen Knowledge Website: http://www.gurteen.com/
• The Knowledge Management Advantage: www.providersedge.com/kma/index.html
• The Knowledge Management Resource Centre: www.kmresource.com/
4
5. Symbols, Data, and Information
From facts to symbols
Observer Fact or event Poor / no comprehension
Poor / no understanding
Symbols are objects,
characters, figures, sounds or
colors used to represent Abstraction /
abstract ideas or concepts Representation
At the lowest level of comprehension / understanding, a
symbol has no structure
5
6. Symbols, Data, and Information
From symbols to data
1. S aSb
{a, b} S S aSb aaSbb aababb
2. S ba
Symbols Start Production rules A structured symbol generated
(no order) symbol (syntax rules) by production rules
{ba, abab, aababb, aaababbb, …}
Set of structured symbols
(ordered symbols)
Data are the representation of symbols (facts, concepts, text, numbers,
sounds, pictures, …) in an organised manner suitable for communication or
processing by human or automatic means
Data give answer to “what”
At the first level of comprehension / understanding, data have no meaning
6
7. Symbols, Data, and Information
From data to information
Condensate Calculate
Data
The five C‟s filter converts
data to information
Correct Contextualise
Categorise Information
Information is data endowed with relevance and purpose; i.e., meaning
Information gives answer to “what”, “who”, “where”, and “when”
At the second level of comprehension / understanding, information has no an
established practice
7
8. Symbols, Data, and Information
Organisation and immediacy of information
Think of information as data that makes the difference
Internal
Location
Conversati
Cultural
Hierarchy Alphabet onal
5 degrees
The of
information
organisation immediacy
of
information
News Reference
Category Time
8
9. Symbols, Data, and Information
Information and the Principle of Uncertainty
Information about a fact reduces the uncertainty of that fact
The Principle of Uncertainty
Any interaction between an observer and the observed changes both. The
more an observer probes, the more difficult it is for him to obtain
INFORMATION about the initial STATE of what he observers and the more
are his observations contaminated by his own efforts
9
10. Paper: Project Management in Noisy
Environments
Objective
Dimension the importance of information in business
DIRECTIONS
Create multidisciplinary
Before lecture: Read the
international teams
paper
(3 people)
Discuss the paper in your
Review the paper
own team
(5 minutes)
(10 minutes)
Explain your conclusions to
Free discussion
other teams
(10 minutes)
(3 minutes by team)
10
11. On Knowledge
From information to knowledge
Knowledge of a fact is when information of that fact is put in practice or used
in many situations
Information in
situation 1
Information in Information in
Knowledge
situation 4 situation 2
Information in
situation 3
11
12. On Knowledge
Knowledge properties
Consistent
Precise and
Shareable
non-redundant
Diffusive Trustable
Time
Transportable
independent
Substitutable Universal
Compressible Expandable
12
13. On Knowledge
Types of knowledge: Tacit and explicit
Tacit knowledge is personal, context-specific knowledge that is difficult to
formulate
Explicit knowledge is that can be codified and transmitted in a systematic and
formal language
Explicit Knowledge
What we
What we
know
know
we do not
we know
know
Tacit Knowledge
What we What we
do not do not
know we do not
we know know
Knowledge Assets Knowledge Gaps 13
14. On Knowledge
Types of knowledge: Tacit and explicit
Characteristics Tacit Knowledge Explicit Knowledge
Nature Personal, context-specific Can be codified and explicated
Difficult to formalise, record, encode, or Can be codified and transmitted in a
Formalisation
articulate systematic and formal language
Development Developed through explication of tacit
Developed through trial and error
Process understanding and interpretation of information
Stored in documents, databases, Web pages,
Location Stored in the heads of people
e-mails, charts, etc.
Conversion Converted to explicit through
Processes externalisation (metaphors and analogy)
Hard to manage, share, or support with
IT Support Well supported by existing IT
IT
Medium Can be transferred through conventional
Needs a rich communication mediums
Enabled electronic channels
14
15. On Knowledge
From tacit to explicit knowledge
15
16. On Knowledge
Where do we acquire knowledge?
Procedures
• New sequence
of operations
or rules
Principles
Tools and
• New concepts
and values Methods
applicable to • Conceptual
decision skills
making Knowledge
is acquired
from
Structures Processes
• Structure or • New sequence
location of of phases of a
organisation project
16
17. On Knowledge
The 3 basic processes of knowledge
Acquire Acquisition Acquire
• The process of development
and creation of insights, skills,
Corroborate and relationships Corroborate
• IT tools: Databases, Capture
Tools (i.e., Mind Manager)
Organise Organise
Secure Secure
Analyse Analyse
Utilisation Sharing
Utilise • Leaning is integrated on • Disseminating and Share
daily basis making available what is
• IT tools: Collaborative already known
tools (e-mail, chat • IT tools: Communications
applications, etc.) Networks
17
18. On Knowledge
Forms of knowledge
Know-how – a skill,
procedures
Know-where – a sense Know-who – who can
of place, where is best help me with this
to do something question or task
Know-when – a sense Know-what – structural
of timing, and rhythm knowledge, patterns
Know-why – a deeper
kind of knowledge
understanding the wider
context
18
19. On Knowledge
Knowledge versus learning
Learning:
The acquisition and integration of knowledge so that it may be used and
applied
Knowledge:
memorisation of
facts or terms
Comprehension:
Evaluation: translating or
placing a value paraphrasing
judgment on data information or
rules
Types
of
learning
Synthesis: Application: using
constructing a new information in new
idea from parts of situations,
others applying rules
Analysis:
breaking
information down
into discrete parts
19
20. On Knowledge
Knowledge and individual learning
Knowledge begins with the individual
Professional
development
and
marketability Curiosity
and
Growth
intellectual
enjoyment
Survive and Motivators Gain edge
meet basic for over
needs Learning competitors
Knowledge workers must be lifelong learners
• Skills must be continually renewed or become obsolete
• New skills must be acquired
• To respond to change and use new technologies, people
must be enabled to learn how to create, innovate and
employ new processes
20
21. On Knowledge
Optimal characteristics of learners
Motivation to try potentially better processes
New or improved skill or ability desired
Trust in abilities and validity of those providing knowledge
Flexibility and agility
Curiosity
Safe environment
Flow State
• A sense of highly focused attention
• Mental enjoyment of the activity for its own sake
• A sense of being outside of time
• A match between the challenge at hand and one's skill
21
22. On Knowledge
Knowledge and models of reality
A model is an abstraction of the reality
Facts Symbols Data
• Representation • Representation • Structured
of reality of facts symbols
Knowledge Information
• Information put • Data with
in practice meaning
Knowledge about a fact produces a model of
the real event that generates that fact
The Principle of Incomplete Knowledge:
The model embodied in a system is necessarily incomplete
22
23. On Knowledge
Paradigms
A paradigm is a a pattern or model; a collection of assumptions, concepts,
practices, and values that constitutes a way of viewing reality, especially for
an intellectual community that shares them
Number of C
solved
problems
B
A
Paradigm
formation
Time 23
24. On Knowledge
Born of new paradigms (paradigm shift)
24
25. On Knowledge
Paradigm shift and paralysis
Image shows the way in which a paradigm shift could cause
one to see the same information in an entirely different way
Perhaps the greatest barrier to a paradigm shift, in some cases, is the reality
of paradigm paralysis, the inability to see beyond the current models of
thinking
Examples on Paradigm Shift and Paralysis in Information Management
(alternative link: http://www.youtube.com/watch?v=vxmuhzLzubM)
25
26. On Knowledge
The Principle of Darkness
The Principle of Darkness:
Even though the knowledge of a part of the reality is incomplete,
it can be MANAGED effectively (black box theory)
Input KNOWLEDGE Output
(black box)
Knowledge gives answer to “what”, “who”, “where”, “when”, “how”, and “why”
At this third level of comprehension / understanding, knowledge does not
have rules to distinguish and generate new knowledge
26
27. On Knowledge
What is Knowledge Management?
Knowledge Management (KM) is the explicit and systematic
management of vital knowledge and its associated processes of
creating, gathering, organising, diffusion, use and exploitation, in
pursuit of defined objectives
Create
Gather
Organise
KM Processes
Diffuse
Use
Exploit
27
28. On Knowledge
What KM is not about
KM is not knowledge engineering
KM is about processes, not just digital
networks
KM is not building a smarter intranet
KM is not about a one-time investment
KM is not about enterprise-wide
“infobanks”
28
29. On Knowledge
From knowledge to wisdom
Knowledge of a fact is when information of that fact is put in practice or used
in many situations
Wisdom is the ultimate level of understanding
This level is achieved when there are enough patterns and meta-patterns
that that can be synthesised them and then used them in novel ways
29
30. On Knowledge
From facts to wisdom: a final map
30
31. On Knowledge
Importance of KM to your organisation
31
32. On Knowledge
Lessons learned – Discover what you know
32
33. KM practice: Managing your knowledge
Directions
• Each practice is 20 minutes long + 10 minutes for group discussion
• MindManager software is needed (you can download a 21-days free trial version on
www.mindjet.com)
• Notice: No previous experience in using MindManager is needed
Practice 1 - Understand your knowledge processing styles
• Think about how you acquire information and make decisions
• Mindmap your preferred ways of gaining knowledge
• Mindmap what thinking processes and preferences guide your decision-making
Practice 2 - What sort of information manager are you?
• Review a recent significant project or decision
• Mindmap what information you felt you needed to do your best, how you went about
finding it, how you processed it, and how it affected the outcome of your task
• What have you now done with this information and how might you use it again?
• After reviewing the check list, would you do something different next time you are in
a similar situation?
33
34. The Problem of KM in Organisation
Organisational isles of information and
knowledge
Functional Areas Organisational Levels Organisational Isles of
Information and
Knowledge
34
35. The Problem of KM in Organisation
Knowledge transfer velocity and viscosity
Tacit knowledge is more viscous than explicit knowledge
Knowledge velocity Knowledge viscosity
concerns concerns
• How quickly the • The richness or
knowledge moves thickness of the
(knowledge speed) knowledge transferred
• Whether the • Its resistance to flow
knowledge gets to the
appropriate
organisational
members (knowledge
direction)
Reduce knowledge viscosity by converting tacit knowledge to explicit
knowledge whenever possible (e.g., standard operating procedures, best
practices and lessons learned)
35
36. The Problem of KM in Organisation
Organisational culture
Observable symbols,
ceremonies, stories,
slogans, behaviours,
dress, physical settings
Underlying values,
assumptions, beliefs,
attitudes, feelings
36
37. The Problem of KM in Organisation
Organisational growth
Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
Large Entrepreneurial Collective Formalisation Elaboration
Split into small
organisations
Evolution
continuation
Growth through
Decline
Coordination
Staff Crisis
Organisational Size
Growth through
Delegation Control Crisis
Growth through The Limiting Absorption
Direction
Autonomy Crisis Principle for Knowledge:
In order to absorb more
knowledge, an organisation
Leadership crisis must change and have
evolution
Growth through
Creativity
Small 37
38. The Problem of KM in Organisation
Resistance to change
ACTIVE
PASSIVE
38
39. The Problem of KM in Organisation
Where is knowledge into organisations?
Intellectual Capital Customer
knowledge
• Human Capital - • The most vital
• In the minds of individuals (knowledge, knowledge in
most Knowledge in
competencies, experience, know-how, Knowledge
organisations products and
etc.) assets
services
• Structural Capital • Measuring and
• Smarter
• That which is left after employees go managing your
solutions,
home for the night (processes, intellectual
customised to
information systems, databases, etc.) capital
users' needs
• Customer Capital
• Customer relationships, brands,
trademarks, etc. Knowledge in Knowledge into Knowledge in
relationships Organisations people
• Deep personal • Nurturing and
knowledge that harnessing
underpins brainpower, your
successful most precious
collaboration asset
Organisational
Knowledge in
memory
processes
• Drawing on
• Applying the
lessons from the
best know-how
past or
while performing
elsewhere in the
core tasks
organisation
39
40. The Learning Organisations
Organisational learning
Organisational Learning
• It is a process of knowledge acquisition or generation of an organisation,
performed through individuals, which can be accomplished by teams
• It is based on organisational memory that is expanded, which can improve
organisational actions
Organisational
Learning Types
External (from
Internal (within an
outside to inside
organisation)
organisations)
Learning of implicit Learning of explicit Learning of implicit Learning of explicit
knowledge knowledge knowledge knowledge
Individual work in an
Insiders that turn into Individual work in a
Prepared material unstructured
outsiders structured approach
approach
Team work in an
Outsiders that Team work in a
Unprepared material unstructured
become insiders structured approach
approach
40
41. The Learning Organisations
Levels of organisational learning
Single-loop Double-loop
learning learning
This occurs when errors are detected and corrected and This occurs when, in addition to detection and correction of
organisations carry on with their present policies and goals errors, the organisation is involved in the questioning and
modification of existing norms, procedures, policies, and
objectives
Deutero-learning
This occurs when organisations learn how to carry out single-
loop and double- loop learning
41
42. The Learning Organisations
Learning organisation
The term learning organisation refers to an organisation‟s
capability of learning from its past experience
(1) Meaning -
Determining a
vision of the
learning
organisation
To build a
learning
organisation,
it must tackle
three critical
issues:
(3) (2)
Measurement Management
- Assessing - Determining
the rate and how the
level of organisation
learning is to work
42
43. The Learning Organisations
Some components of a learning organisation
Systematic
Problem Solving
(using
methodologies)
Transferring
knowledge quickly Experimentation
and efficiently with new
through out the approaches
organisation
Benchmarking / Learning from past
Best practices experience
43
44. The Learning Organisations
How a learning organisation looks like
Organisational Learning
system learns as a Organisation
whole
Tolerance for
complexity
and
uncertainly
People in
Learning is a organisation
continuous, recognise that Leadership
process that is ongoing, Climate of
involved and
openness and
integrated with organisation- “curiosity”
supporting
learning
work wide learning
is critical
Resources
committed to Systems
quality perspective
learning
Perceived
Processes for
performance
Organisation maximising
gap between
measures flow of data,
current and
progress information,
desired
and people 44
performance
45. The Learning Organisations
The learning organisation: the 5 disciplines
Personal Mastery
• Clarify personal vision
• Focus energy
• See reality objectively
Mental Models Systems Thinking
• Identify assumptions • Seeing wholes
• Open to change • Identifying patterns
Team Learning Shared Vision
• Synergy (2+2=5) • Create shared
• Dialog, conversation commitment
(not speechmaking) • Identify what we want
45
47. The Learning Organisations
Sorting out the “M”s – Domains & Relationships
Knowledge Mgmt
Intellectual Capital
• Tacit/Implicit Knowledge
• Explicit Knowledge
Social Capital
Information “Resources” Information Mgmt • Communities/Networks
(lifecycle mgmt) • Collaboration
Mgmt Content • Culture
Mgmt
Technology Records Mgmt Human Capital
Data Mgmt • Organisational Learning
Mgmt (repositories) • Succession Planning
(infrastructure) • Business Processes
Document Mgmt
• Versions
Application • Workflow Information Services
• Library
Mgmt • Research
• Knowledge repositories
(static) Content (dynamic)
Taxonomies/Metadata
Facilitative IT Tools 47
48. The Learning Organisations
Relationship among IT, IM and KM
Human Capital
Social Capital The Essence of
Knowledge
Corporate Capital Management
Enabler
Data The Essence of
Successes Relationships
Info Information
Lessons Learned
Mapping Management
Enabler
Technology
Innovation
The Essence of
Capability Connectivity Software Information
Capacity Hardware Technology
Enabler
Incentives Infrastructure
Education IPTs Physical
Training Assets
48
49. The Learning Organisations
The essence of KM
Tacit INTELLECTUAL CAPITAL Explicit
HUMAN SOCIAL CORPORATE
CAPITAL CAPITAL CAPITAL
(Individual) (Team) (Organisation)
– Expertise – Networks – Intellectual
– Experience – Relationships Property
– Capability – Interactions – Processes
– Capacity – Language – Databases
– Creativity – Patterning – Flexibility
– Adaptability
ENTERPRISE
KNOWLEDGE
49
50. Case – Learning organisations versus places to
learn
Think about your experience in a university. Then think about that university as a learning organisation
(make a distinction between a “place to learn” and a “learning organisation”).
Say your point of view about the following topics (consider the learning environment and try to be impartial
in your answers):
• Climate of openness and “curiosity”
• Tolerance for complexity and uncertainly
• Leadership involved and supporting learning
• Perceived performance gap between current and desired performance
• Resources committed to quality learning
• Organisation measures progress
• Systems perspective
• Processes for maximising flow of data, information, and people
Do you think that a learning organisation needs a place to learn? Before you give an answer, analyse the
following video
Telefónica- Creating a Talent Pipeline
(alternative link: http://www.youtube.com/watch?v=O-x_9KVr4Kg )
DIRECTIONS
Create multidisciplinary
Before lecture: Think about Review the case
international teams
this case (5 minutes)
(3 people)
Explain your conclusions to Discuss the case in your own
Free discussion
other teams team
(10 minutes)
(3 minutes by team) (10 minutes) 50
51. Knowledge Sharing
Knowledge sharing - Interplay of four factors
People
Technology Processes
Learning
51
52. Knowledge Sharing
Knowledge sharing needs all of these
People Places Things
Create Where people Structured and
knowledge with: can: unstructured
Share ideas content:
Colleagues
Form Create
Experts communities
Classify
Customers Learn
Capture
Partners and Create answers
friends to problems Share
52
53. Knowledge Sharing
Why knowledge sharing?
Knowledge sharing leverages expertise and organisational
know-how to improve . . .
Responsiveness Innovation Competency Efficiency
. . . helping enterprises do work more effectively and achieve
corporate goals
53
54. Knowledge Sharing
What knowledge is sharing?
• Knowledge that has been articulated
Explicit • Organisation
• Mission
knowledge • Hardware/software
• Knowledge that can be articulated but
Implicit is not
• Analysing tasks involved in a
knowledge process
Tacit • Knowledge that cannot be articulated
• Ability to recognise a person‟s face
knowledge
54
55. Knowledge Sharing
How is knowledge captured and shared?
Individual Collaboration Organisational
knowledge networks knowledge-base
TACIT TO EXPLICIT
55
56. Knowledge Sharing
What happens when the K-line is crossed?
Enlightened Enterprise
“Enlightened
Innovation
workplace” where
Shared explicit Shared tacit
knowledge knowledge
knowledge is shared
Context
K-line Shift
Old business
Traditional Enterprise
“Traditional workplace”
Gated explicit Hoarded tacit where knowledge is not
knowledge knowledge shared
56
57. Knowledge Sharing
Sharing or not sharing?
Why do people share?
• They take pride in their expertise
• They enjoy interacting with peers
• They wish to learn
• They expect others to reciprocate
• They want to contribute to the
common good
• Their culture encourages sharing
• They are loyal to the organisation
Why does not people
share?
• It is not convenient
• They do not know what they know
• They do not know the value of
what they know
• They believe knowledge hoarding
is job security
• They do not get credit for it
• They do not have the time
57
58. Knowledge Sharing
How to share knowledge?
Share your
knowledge and
encourage your
peers to do the
same
Do not stigmatise
Network with your
others for not
peers
knowing
Value and reward
Seek expert advice
the continuous
throughout the
pursuit of
enterprise
knowledge
58
59. Knowledge Sharing
Lessons learned – Organisational “does / does
not” for knowledge sharing
Organisation does
How organisations implement
• Integrate into
Knowledge Management
• Business strategy
• Daily work
Intranet 47%
• Provide
Repository 33%
• Consistent and continual championship /
Decision-support 33%
leadership
Groupware 33%
• A trusting organisational environment
People networks 24%
• Time to engage in knowledge sharing
Map links to expertise 18%
• Appropriate incentives for participation
• Institutionalise organisational, lifelong
Source: ASTD Research
learning
Organisation does not
• Create compensation systems that do not
support knowledge sharing and teamwork
• Build a “Grand Database in the Sky”
• Allow technology to dictate development
• Failure to coordinate and involve entire
organisation
59
60. Knowledge Sharing
Organisational challenges to KM/KS
Culture
clashes
60
61. Videocase: Igloo - Global Issues Network
1. What can you say about the following 4 factors?
• People
• Processes
• Learning
• Technology
2. How does people create and transform
knowledge from tacit to implicit?
3. How is knowledge captured and shared?
4. How and where can people share knowledge?
5. How is content structured?
6. What can you say about responsiveness,
innovation, competency and efficiency?
7. Say some examples of how the ideas described
should be used into an organisation
Igloo - Global Issues Network
(alternative link: http://www.youtube.com/watch?v=xdVmGBPGbg4)
DIRECTIONS
Create multidisciplinary
Before lecture: Watch the Review the video
international teams
video (10 minutes)
(3 people)
Explain your conclusions to Discuss the video in your own
Free discussion
other teams team
(10 minutes) 61
(3 minutes by team) (10 minutes)
62. Social Networks
Knowledge networks and knowledge flows
Knowledge networks
explain the flow or diffusion
of knowledge across a
network of individuals
Transactive Memory
Systems are
knowledge
repositories that Cognitive knowledge
provide individuals networks essentially
with access to more answer “who knows
knowledge than any who knows what?”
one individual could
possibly possess
alone
62
63. Social Networks
Social Network Analysis (SNA)
SNA is focused on uncovering the patterns of people's interconnectedness and
interactions
• The success or failure of organisations and societies may depend on these
patterns
• Analysis can produce understanding as well as action
SN use
Content is
people to
used to
find
find people
content
63
64. Social Networks
Why do a SNA?
To build better
networks, we
have to
communicate
more
I already know Everybody should
what is going on be connected to
in my network everybody else
Six Myths
about
Informal
Networks*
Central people
who have become
We can not do
bottlenecks
much to aid
should make
informal networks
themselves more
accessible
How people fit in
is a matter of
personality (which
can not be
changed)
*Rob Cross, Nitin Nohria, and Andrew Parker, MIT Sloan Management Review, Spring 2002 64
66. Organisational Culture
What is culture?
Tradition and
history,
cultural
strength
Shared values Jargon
Culture
Physical
environment,
Belief systems
cultural
artifacts,
Rituals,
Status
folkways,
symbols
mores, norms
66
67. Organisational Culture
How employees absorb culture
Stories
The ability of an organisation
to learn, develop memory, Social
Rituals
and share knowledge is learning
dependent on its culture
Over time organisations
learn what works and what
does not work
Reward /
Symbols
punishment
Generally when a IT project
fails, it is because the
technology does not match
the organisation‟s culture
Heroes Language
67
68. Organisational Culture
Cultural typologies
Strong culture is said to exist where staff respond to stimulus because of
their alignment to organisational values
Weak culture is said to exist where there is little alignment with
organisational values and control must be exercised through extensive
procedures and bureaucracy
Deal & Kennedy - Risk and feedback
• Focus on executive decision making
Reinmann & Wiener - Values
• Focus on values and source of values
Schein - Every organisation is unique
• Culture is the most difficult organisational attribute to change
Sonnenfeld - Academy, club, baseball team, fortress
• Focus on attraction of personalities
68
69. Organisational Culture
Aspects and steps that determine KM success
Understand
organisational culture
Culture – Process view
• Ways to facilitate collaborative Analyse it
processes, learning dynamics
and problem solving
Technology – Object view Get into the network and
understand the characters
• Focus on databases or other
storage devices, mechanisms
for sharing knowledge Manage it
products such as documents,
and terms such as knowledge
transfer
Change it
69
70. Organisational Culture
Any KM programme requires a Change
Management approach
Attempts to introduce changes
that are radically different than
the existing culture usually are
not successful
CURRENT
STATE
Values Norms Practices
Attempts to introduce changes
that are generally consistent
with the current culture
usually are successful
70
71. Videocase: Duracell Xcells (Industrial)
1.How does Duracell define quality?
2.Describe the process used by Duracell to
get the concept of quality
3.What can you say about shared values?
4.Is the culture of Duracell a strong or
weak?
5.What is the type of culture implicit in
Duracell?
6.Why could Duracell change its
organisational culture?
Duracell Xcells (Industrial)
(alternative link http://www.youtube.com/watch?v=vBkGZ124Tjk)
DIRECTIONS
Create multidisciplinary
Before lecture: Watch the Review the video
international teams
video (10 minutes)
(3 people)
Explain your conclusions to Discuss the video in your own
Free discussion
other teams team
(10 minutes) 71
(3 minutes by team) (10 minutes)
72. Communities of Practice
Communities of Practice (COP)
A COP is a group of self-governing people whose practice is aligned with
strategic imperatives and are challenged to create shareholder value by
generating knowledge and increasing capabilities
Define Community Project
• Identify community elements
• Set context
• Outline project
Establish Community
Components
• Identify issues and approaches
• Plan project tasks
Launch Community
Establish Community
• Develop sense of community
Assess: Progress & Value
• Solicit feedback on
development 72
73. Communities of Practice
Components and benefits of COPs
Governance
• Community conventions & norms
Accelerates the generation of capabilities
Membership
• Community participants
Improves and enhances meta-capabilities
Technology
• Enabling infrastructure
Shapes a “boundary-less” culture for
User support greater synergy
• Maximising collaborative tools
Content Connects people into a network for greater
• Community knowledge base speed
Learning
• Capability to participate in community Promotes innovation through collaboration
and problem-solving situated in work
Facilitation
• Moving the community forward; realising purpose Prevents knowledge loss from the
organisation through exchange of cross-
Communication plan generational expertise
• Establishing credibility, sharing the value proposition
73
74. Storytelling
Storytelling
Storytelling is the skilled delivery of stories use to present anecdotal evidence,
clarify a point, support a point of view and crystallise ideas
Storytelling is the connecting device between data and reality
Stories can share a "truth" that data can not
Storytelling can help bridge the gap between data and knowledge
It also could be the result of integrating information
Knowledge managers use storytelling as a device and tool for sharing
knowledge
Communicate quickly
Communicate naturally
Communicate truthfully
Potential Benefits Communicate collaboratively
Communicate persuasively
Communicate intuitively
74
Communicate movingly
75. Storytelling
Six steps in storytelling
Definition of objectives; assignment of commentators
Plan and interviewees; selection of the events
Collecting personal views; searching for „puzzle
Interview stones‟
Extract Selection of momentous statements
Preparation of the
Write experience document
Feedback of the
Validate citations to the
interviewees
Propagate
75
76. Videocase: Cisco on Change Management
1. What are the main stages of CISCO
Change Road Map?
2. What are the main reasons to implement
change?
3. What is the team project?
4. What are the team components? (issues,
approaches, plan, and project tasks)
5. How is the team launched?
6. How is it developed a sense of team?
7. How was it assed the progress and value
of the team?
8. Is the team a COP?
Cisco – Change Management Training Video
(alternative link: http://www.youtube.com/watch?v=bG5na7JD7rE)
DIRECTIONS
Create multidisciplinary
Before lecture: Watch the Review the video
international teams
video (10 minutes)
(3 people)
Explain your conclusions to Discuss the video in your own
Free discussion
other teams team
(10 minutes)
(3 minutes by team) (10 minutes)
76
78. Technology aspect of KM
78
Data Analysis
(Data Warehouse and
Business Intelligence)
Messaging and Collaboration
Enabling Technologies
Real Time
Collaboration Complete Intranet
Content
Management
Portals and Search
Communities,
Teams and Experts
Pre-Requisites
KM Technology
79. KM Technology
Messaging and collaboration
Tacit Explicit
Desktop
Knowledge Knowledge • Easy-to-use productivity
• Comfortable e-mail systems
• Web browser
• Simple search functionalities
KM
Information Services
Base
• Collaboration services
• Web services
• Indexing services
Share
System
& Reuse • Central-storage
79