Download - Icac 2 Rev
Knowledge based assets for competitive success
KNOWLEDGE CREATION & CAPTURE
Session 2
Dr. Daniel Chandran Faculty of Information TechnologyUniversity of Technology, Sydney
August 2009
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Objectives
• Knowledge Creation– Characteristics– Dimensions– Models
• Knowledge Creation Process• Knowledge Architecture• Knowledge Capture• Knowledge Audit• Technologies for knowledge management systems
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1. Why have Japanese companies become successful?
2. How do Japanese companies bring about continuous innovation?
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“Knowledge” as a competitive force
Knowledge Creation
Continuous innovation
Competitive Advantage
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Why Organizations Launch KM Programs
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Knowledge Creation
• KM is not a technology; it is an activity enabled by technology and produced by people– how people share knowledge that will add value to the
growth of business– Today’s knowledge may not solve tomorrow’s
knowledge
• Alternative way of creating knowledge is via teamwork
• A team compares job experience to job outcome—translates experience into knowledge
• Such newly acquired knowledge is carried to the next job
• Maturation over time with a specific job turns experience into expertise
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Knowledge Creation & Knowledge Transfer Via Teams
Team performs
a job
Knowledge captured
and codified in a form usable by others
New experience/ knowledge
gained
Outcome compared to action
Outcome is
realized
Initial knowled
ge
New knowledge reusable by same team on next job
Series of specificTasks carried out inA specific order
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Impediments to knowledge sharing
Vocational reinforcers
Attitude
Personality
Company strategies and
policies
Organizational culture
Knowledge sharing
Work Norms
CompensationRecognitionAbility utilizationCreativityGood work environmentAutonomyJob securityMoral valuesAdvancementVarietyAchievementIndependenceSocial status
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Characteristics of Knowledge Creation
• Express the inexpressible• Heavy reliance on figurative language and
symbolism • Use of metaphor or analogy in product
development • To disseminate knowledge, an individual’s
personal knowledge has to be shared with others
• New knowledge is born in the midst of ambiguity and redundancy
• SIS• Unlearn Old ideas.
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Types of Knowledge
Tacit Knowledge(Subjective)
Explicit Knowledge (Objective)
Knowledge of experience (body) – tends to be tacit, physical and subjective
Knowledge of rationality (mind) – tends to be explicit, meta physical and objective
Simultaneous Knowledge (here and now) – specific, practical context
Sequential Knowledge (there and then) – about past events or objects
Analog Knowledge (practice) – sharing between individuals through communication
Digital Knowledge(theory) – sequentially created by ‘digital’ activity
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Nonaka’s Model of Knowledge Creation
TACIT TO TACIT(SOCIALIZATION)
E.G. TEAM MEETINGS AND
DISCUSSIONSINFORMAL MEETINGS TO
SOLVE DIFFICULT PROBLEMS
TACIT TO EXPLICIT(EXTERNALIZATION)
E.G., DIALOG WITHIN TEAM ANSWER QUESTIONS
EXPLICIT TO TACIT(INTERNALIZATION)
E.G., LEARN FROM A REPORT“RE-EXPERIENCE” WHAT THE
OTHERS EXPERIENCED
EXPLICIT TO EXPLICIT(COMBINATION)
E.G., E-MAIL A REPORT
Experience among people in face-to-face meetings
Articulation among people through dialog
Best supported by technology
Taking explicit knowledge and deducing new ideas
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Knowledge Spiral
Socialisation Externalisation
Internalisation Combination
Learning by Doing
Field Building
Linking ExplicitKnowledge
Sympathised knowledge
Conceptualknowledge
Systemic knowledge
Operationalknowledge
Yieldconcepts
Yield PrototypesAbout Project Management,Production Process &
Policy Implemen-tation
Yield Mental Models and Tech
skills Dialogue
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NONAKA’s Spiral Process as grounded theory
Socialization
Explaining an
d
elaborat
ing on
existing knowled
ge
ExternalizationConverting
unstructured
information into
explicit structures
Internalization
Evaluating newly
created explicit data
Combination
Combining stored
explicit d
ata in
to
new fo
rms
requires easy ways to exchange experiences, develop trust, share values
Dialoging - sharing of mental models, articulation of concepts, development of common terms. Usually consciously constructed.
Exercising - communicate artifacts and embody in working context. Reflect on outcomes.
Systemising - visualizing interactions, constructing artifacts, combine explicit knowledge.
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Knowledge Creation Process (KCP)
TACIT KNOWLEDGE EXPLICIT KNOWLEDGE
IN ORGANISATION IN ORGANISATION
CREATINGCONCEPTS
JUSTIFYINGCONCEPTS
SHARINGTACIT
KNOWLEDGE
BUILDING ANARCHETYPE
CROSS LEVELING KNOWLEDGE
SOCIALISATION EXTERNALISATION COMBINATION
INTERNALISATION
TACIT KNOWLEDGEFROM USERS
INTERNALISATIONBY USERS
EXPLICITKNOWLEDGE
AS PRODUCTS/SERVICES
ENABLING CONDITIONSIntention
AutonomyRedundancy etc
Market
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Phase I-Sharing Tacit Knowledge
• Start the focus on Tacit Knowledge• Individuals are the main source of Tacit Knowledge• Build mutual trust• Create a “field” where individuals can work
– Self organising team facilitates organisational knowledge creation
– Management sets challenging goals – Management endows high degree of autonomy– Autonomous team sets its own task boundaries
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II - Creating Concepts
• Interaction between TK and EK• The team articulates it through further dialogue
in the form of collective reflection• The tacit mental model is verbalised into words
and phrases• Crystallised into explicit concepts• This phase employs figurative language such as
metaphors and analogies• Corresponds to externalisation
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III- Justifying Concepts
• Justify new concepts created by individuals/team– Determine the newly created concepts are
truly worthwhile for the organisation and society
• Criteria for justification– Both qualitative and quantitative– cost, profit margin, degree to which a product
can contribute to the firm’s growth
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IV – Building an archetype
• Justified concept is converted into tangible or concrete – an archetype
• Can be a prototype for a new product• Can be a model operating mechanism for a
service• Built by combining newly created EK with
existing EK• It is a complex phase – requires cooperation of
various departments within the organisation
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V- Cross-Leveling of Knowledge
• Organisational knowledge creation is a never-ending process
• New concept created, justified and modeled moves to a new cycle of knowledge creation at a new ontological level
• Intra-organizationally it can trigger a new cycle expanding horizontally and vertically across the organisation
• Inter-organizationally it can mobilize knowledge of affiliated companies, customers, suppliers, competitors through interaction
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Identifying Knowledge Content Centers
Marketing
HumanResources
Customer Service
Sales
. Strategies
. Tools
. R & D
. Advertising . Complaint rate. Satisfaction information
. Job openings. Benefits
. Competition data. Sales volume. Leader sales information
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A HELP DESK SITUATION
Client
Contact person
Experts
Service request Find solution
Knowledge about where knowledge can be found
Organizationaldatabase
Supporting Clients - Emphasis on Knowledge
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Knowledge Capture
• Transfer of problem-solving expertise from some knowledge source to a repository or a program
• A process by which the expert’s thoughts and experiences are captured
• Includes capturing knowledge from other sources such as books, technical manuscripts, etc.
• A knowledge developer collaborates with an expert to convert expertise into a coded program
• Knowing how experts know what they know
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Strategic Directions for Knowledge Management
Codification
Personalization
People-to-people
Are the two opposite or complimentary?
Reward for contributing to knowledge repository
Reward for sharing knowledge
ESSENTIAL FEATURES
RepositoryCollaborative service
Retrieval serviceInterface
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Aligning KM and Business StrategyStrategic Knowledge Gap Analysis
What your companyMust know
What your companyCan do
What your companyknows
What your companyMust do
Strategy-knowledge Link
Knowledge-Strategy Link
Knowledge Gap Strategic Gap
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Ernst and Young Process
Reviews PowerPacks
Knowledgeobjects
Knowledgeobject
development
E-mail submissions
Discussion database and document repository
Proposal templates
Subject matter objects
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“Build it, and they will come”
“Knowledge is actively managed”
“Our best knowledge guides
our activities”
“Knowledge is a by-product”
Result:
Global Communications
Result:
Relevant quality content, where and when needed
Result:
People Guided by Knowledge
Result:
Organizational Memory
KnowledgeKnowledgeOutfittingOutfitting
PerformancePerformanceIntegrationIntegration
KnowledgeKnowledgeSharingSharing
1992-1994 1996-2000 21st Century1994-1996
EnablingEnablingInfrastructureInfrastructure
Accenture’s Knowledge Management Journey
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Accenture’s Four Pillars of Knowledge Management
Strategy
TechnologyPeople
Process
•How do you create a culture for sharing?
•Which people need to be empowered to contribute the right knowledge?
•Are priorities aligned with measurements?
•Which factors are critical for my business that can be addressed through knowledge management?
•Which knowledge adds the most value, and what investments are required to realize this value?
•What are the highest priority initiatives?
•What tools are currently in place?
•What tools are needed to enable the environment?
•How do you fill the gap?
•Are the right processes in place to:
•capture, refine, and create knowledge?
•disseminate, share, and apply knowledge to deliver business value?
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The Accenture: Knowledge Xchange
Capturingknowledge in
14 Global libraries
Knowledge centerResearchHelp desk
Content management
Clientcenter
Knowledge specialist
Knowledge champion
FRAMEWORK
Process integrationSocialization (mindset
change)Utilization (easy access)Automation (enterprise wide
access)
Managed vocabularySearch and browse
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Accenturewww.ac.com
Capturing Knowledge
Practicespecificdatabase
ClassificationStorage and
delivery
Subject specialist
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Key propositions
• KM initiatives have to be aligned with corporate goals
• Top management involvement and commitment are important
• Systematic collaboration of all employees involved in the transformation have to be supported
• Efficient and effective knowledge sharing and creation have to be practiced continuously to overcome barriers
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Benefits of KMS
Process OutcomesCommunication• enhanced communication• faster communication• more visible opinions of staff• increased staff participationEfficiency• reduced problem-solving
time• shortening proposal times• faster results• faster delivery to market• greater overall efficiency
Organisational outcomesFinancial• increased sales• decreased cost• higher profitabilityMarketing• Better service• Customer focus• targeted marketing• proactive marketingGeneral• Personnel reduction• improved project management• consistent proposals to multi- national clients
IT & KM
• IT is crucial to the success of every KM System
• IT enables KM by providing the enterprise architecture on which it is built
Portals
Portals are virtual workplaces that:• Promote knowledge sharing among different categories of end users
e.g. customers, partners and employees• Provide access to stored structured data
e.g. data warehouses, database systems• Organize unstructured data
e.g. paper documents, electronic documents etc
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Benefits of Knowledge Portals
ProductivityLocating Documents
CollaborationBetter DecisionsQuality of Data
Sharing KnowledgeIdentifying Experts
E-mail TrafficBandwidth Use
Time in MeetingsPhone Calls
Response TimesRedundant EffortsOperating CostsTime to market
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Portal Features and Benefits
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Intelligent Agents
• Intelligent agents are tools that can be applied in numerous ways in the context of EKPs.
• They are an intermediary between the enterprise and its customer in virtual destinations
• Intelligent agents are still in their infancy.• Agents are software entities that are able to execute a wide range
of functional tasks such as searching, comparing, learning, negotiating and collaborating
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Portal Vendors
Vendor KM PortalProduct
Feature Summary Best Uses
Lotus/IBM Lotus Raven 1.0 (in beta)
• Intelligent taxonomy• QuickPlace collaboration tool • Assigns value to data based on how often it is used• Portal replication• Facilitates content management
• Self-creating and refining taxonomies• Personnel resources linked to data sources• Advanced collaboration• Easy portal repurposing• Rapid application development with associated KM packages
Open Text
MyLivelink Portal 1.0 with Livelink 8.5.1 KM software
• Integrated work flow • Quick integration of features • Quick portal deployment
• Integrated KM• Document management and work flow• Custom collaboration spaces (personal, project, or enterprise)
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Vendor KM Portal Feature Summary Best Uses
Plumtree Plumtree Corporate Portal 4.0
• Automatic population • E-mail, voice, and wireless notification • Integration with LDAP directories • E-room tools
• Easy and extensive content and application integration• Scalability• Advanced security • Trainable taxonomies• Various data access• Customization and extensibility
Woolamai WebMeta Engine 1.0
• Quick integration • Flexible portal interface• Knowledge taxonomy adapts to data views• Data-mining functionality• Web site statistics
• Usability• Tracking site statistics• Content streaming to wireless devices
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Other Supporting Technologies
• Artificial Intelligence– Assist in identifying expertise– Elicit knowledge automatically and semi-automatically– Provide interfacing through natural language processors– Enable intelligent searches through intelligent agents.
• Intelligent agents are software systems that learn how users work and provide assistance in their daily tasks.
• Knowledge Discovery in Databases (KDD) is a process used to search for and extract useful information from volumes of documents and data. It includes tasks such as:– knowledge extraction– data archaeology– data exploration– data pattern processing– data dredging– information harvesting
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Other Supporting Technologies
• Data mining the process of searching for previously unknown information or relationships in large databases, is ideal for extracting knowledge from databases, documents, e-mail, etc.
• Model warehouses & model marts extend the role of data mining and knowledge discovery by acting as repositories of knowledge created from prior knowledge-discovery operations
• Extensible Markup Language (XML) enables standardized representations of data structures, so that data can be processed appropriately by heterogeneous systems without case-by-case programming.