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Integrating Data Mining within a Strategic Knowledge Management Framework: A Platform for Sustainable Competitive Advantage within the
Australian Minerals and Metals Mining Sector
Sanaz Moayer
Fang Huang
Scott Gardner
School of Management and Governance,
Murdoch University, Perth, Australia
ICBIAKM 2015: The 17th International Conference on Business Intelligence, Analytics, and Knowledge Management
Paris, France
Contents
Introduction Objective of the Paper Definition of Knowledge Management and Its benefits Review of Existing Knowledge Management Models Strategic Application of Data Mining and Its benefits Competitive Advantage Data Mining, Business Intelligence, and Knowledge Management Conclusion
Introduction
-Knowledge is a valuable intangible asset.-Knowledge Management (KM) is a key part in creating Competitive Advantage.-Information Technology (IT) has a strategic support role in exploiting the composite knowledge capacity.-Data Mining (DM) tools add value throughout an organisation’s network within the broader KM framework
Objective of the Paper
To explore the linkages between strategic engagement of human knowledge and powerful technological platforms
Achieve competitive Advantage
Definition of Knowledge Management
KM definition by Jashapara (2011, p.14):
“The effective knowledge processes associated with exploration, exploitation and sharing of human knowledge (tacit and explicit)
that use appropriate technology and cultural environments to enhance an organisation’s intellectual capital and performance”.
Benefits of Knowledge Management
KM benefits (Duvall, 2002):
retention of expertisecapturing and sharing best practicesupporting customers and customer servicesaiding decision makingand increasing profit
Strategic Knowledge Management in Australian Mining Industry
Mining Technology Service (MTS)
A platform for finding, acquiring, developing, sharing, preserving, evaluating, and applying knowledge to support
the competitive advantage
Review of Existing Knowledge Management ModelsModel Features
The von Krogh and Roos Model of organisational Epistemology Individual knowledgeSocial knowledge
The Nonaka and Takeuchi Knowledge Spiral Model
Knowledge creation
Knowledge conversion (Socialisation, externalisation, combination, internalisation), ‘Ba’ safe space, Knowledge assets.
Hedlund and Nonaka’s Knowledge Management Model
Articulated knowledge- Individual
Tacit knowledge- Individual
Articulated knowledge- Group
Tacit knowledge- Group
Articulated knowledge- Organisation
Tacit knowledge- Organisation
Articulated knowledge- Inter- Organisational Domain
Tacit knowledge- Inter- Organisational Domain
The Choo Sense-making KM Model Sense makingKnowledge creationDecision making
The Wiig Model for Building and Using Knowledge Public KnowledgeShared experiencePersonal knowledge
The Boisot knowledge category Model
Propriety knowledgePersonal knowledgePublic knowledgeCommon sense
The Boisot I-Space KM Model Codified- UncodifiedAbstract- ConcreteDiffused- Undiffused
Review of Existing Knowledge Management Models cont.
Model Features
Skandia Intellectual Capital Model of Knowledge Management
EquityHuman Capital
Customer Capital(Customer Base, Relationsips, Potential)
Innovation CapitalProcess Capital
Demerest’s Knowledge Management Model
Knowledge constructionKnowledge embodiment
Knowledge dissemination
Use
Frid’s Knowledge Management Model
Knowledge ChaoticKnowledge AwareKnowledge FocusedKnowledge ManagedKnowledge Centric
Stankosky and Baldanza’s Knowledge Management Framework
LearningLeadership
Organisation, structure & culture
Technology
Kogut and Zander’s Knowledge Management Model
Knowledge CreationKnowledge Transfer
Process & Transformation Of Knowledge
Knowledge capabilities
Individual “Unsocial sociality”
Complex Adaptive System Model of KM
Creating new ideasSolving problemsMaking decisions
Taking actions to achieve desired results
Major Steps of Knowledge Management
Knowledge Creation Knowledge Storage Knowledge Transfer Knowledge Application
Holzner & Marks (1979) Consciousness Extension Transformation Implementation
Pentland (1995) Construction Organising - Storage Distribution Application
Nonaka & Takeuchi (1995) Construction Organising - Storage Distribution Application
Alavi & Leidner (2001) Knowledge Creation Knowledge Storage Knowledge Transfer Knowledge Application
Darroch (2003) Acquisition ----- Dissemination Use knowledge
Chen (2005) Knowledge Creation Knowledge Conversion Knowledge Circulation Knowledge Completion
Lee (2005) Creation Accumulation Sharing Utilisation & Internalisation
Adapted from Alavi & Leidner (2001)
Four Major steps of Knowledge Management
Four Knowledge Management Stages (Alavi & Leidner, 2001):
Knowledge Creation Knowledge Storage knowledge Transfer Knowledge Application
Strategic Application of Data Mining
Extract
Transform
Load
Store and manage
Provide data access Analyse Present
Benefit of Data Mining
Business Level (Bal, Bal and Demirhan, 2011): recognition of services and products which are important to customers profiling of appropriate offerings to meet particular customer needs highlighting areas of current and future customer interests, which in turn leads to new products and services.
Focusing on unstructured problems
Deliver the right products/services to right customers through the right delivery channels
Competitive Advantage
Competitive Advantage approaches:
Positioning school (MBV):Porter’s Five Forces Model
Resource based school (RBV):VRIN Model
Data Mining, Business Intelligence, and Knowledge Management
Achieve Sustainable Competitive Advantage
Knowledge Management
Business Intelligence
Data Mining
Conclusion
Sustainable competitive Advantage
Knowledge management (exploring tacit & explicit knowledge; Organisational learning… )
Data management Business intelligence Data Mining …
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Thank You & Comments
ICBIAKM 2015: 17th International Conference on Business Intelligence, Analytics, and Knowledge Management
Paris, France
July 2015