knowledge based assets for competitive success - knowledge creation & capture
TRANSCRIPT
Knowledge based assets for competitive success
KNOWLEDGE CREATION & CAPTURE
Session 2
Dr. Daniel ChandranFaculty 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 bringabout 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 performsa job
Knowledge captured and codified in a form usable
by others
New experience/ knowledge
gained
Outcome compared to action
Outcome is realized
Initial knowledg
e
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
Digital Knowledge(theory) – sequentially created by ‘digital’activity
Analog Knowledge (practice) – sharing between individuals through communication
Sequential Knowledge (there and then) –about past events or objects
Simultaneous Knowledge (here and now) – specific, practical context
Knowledge of rationality (mind) – tends to be explicit, meta physical and objective
Knowledge of experience (body) – tends to be tacit, physical and subjective
Explicit Knowledge(Objective)
Tacit Knowledge(Subjective)
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Nonaka’s Model of Knowledge Creation
TACIT TO TACIT(SOCIALIZATION)
E.G. TEAM MEETINGS ANDDISCUSSIONS
INFORMAL MEETINGS TO SOLVE DIFFICULT PROBLEMS
TACIT TO EXPLICIT(EXTERNALIZATION)
E.G., DIALOG WITHIN TEAMANSWER 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
Systemicknowledge
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 and
elaborati
ng on
existing knowledge
ExternalizationConverting
unstructured
information into
explicit structures
Internalization
Evaluating newly
created explicit data
Combination
Combining stored
explicit data
into
new forms
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 KNOWLEDGEIN 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
. Satisfactioninformation
. Job openings
. Benefits
. Competitiondata
. Sales volume
. Leader salesinformation
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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
Classification Storage anddelivery
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 KMSOrganisational 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
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
IT & KM
• IT is crucial to the success of every KM System
• IT enables KM by providing the enterprise architectureon 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 datae.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 customerin 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
• Integrated KM• Document management and work flow• Custom collaboration spaces (personal, project, or enterprise)
• Integrated work flow • Quick integration of features • Quick portal deployment
MyLivelink Portal 1.0 with Livelink 8.5.1 KM software
Open Text
• Self-creating and refining taxonomies• Personnel resources linked to data sources• Advanced collaboration• Easy portal repurposing• Rapid application development with associated KM packages
• Intelligent taxonomy• QuickPlacecollaboration tool • Assigns value to data based on how often it is used• Portal replication• Facilitates content management
Lotus Raven 1.0 (in beta)
Lotus/IBM
Best UsesFeature SummaryKM PortalProduct
Vendor
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Best UsesFeature SummaryKM PortalVendor
• Usability• Tracking site statistics• Content streaming to wireless devices
• Quick integration • Flexible portal interface• Knowledge taxonomy adapts to data views• Data-mining functionality• Web site statistics
WebMetaEngine 1.0
Woolamai
• Easy and extensive content and application integration• Scalability• Advanced security • Trainable taxonomies• Various data access• Customization and extensibility
• Automatic population • E-mail, voice, and wireless notification • Integration with LDAP directories • E-room tools
PlumtreeCorporate Portal 4.0
Plumtree
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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.