Integration of Knowledge Management and Business Intelligence for Lean Organizational Learning by the Digital Worker

Integration of Knowledge Management and Business Intelligence for Lean Organizational Learning by the Digital Worker

Selvi Kannan (Victoria University, Australia) and Shah J. Miah (The University of Newcastle, Australia)
DOI: 10.4018/978-1-5225-5718-0.ch007
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The polarization of global labor market, hunt for talent, need to adapt quickly to changing environment is pressuring businesses more than ever before on their performance. This is further snowballed with the development of digitalization, automation, robotization, and artificial intelligence that offer approaches for addressing enormous industry challenges. These challenges create a push for organizational decision makers to rethink on the management of work. Knowledge management (KM) is understood to encourage content management, collaboration with inclusion of organizational behavioral science, and of course technologies. Complementing BI with knowledge management (KM) system in an organization can account for lean and accelerated performance. In this chapter, the authors present their position and insights in the integration of KM and BI suited for the worker in the digital world which possibly encourages lifelong learning with the focus on adaptability.
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The objective of this chapter is to understand the relationship between business intelligence (BI) and knowledge management (KM) to address accelerated organizational performance. Hence, leading the discussions into how BI and KM can extend into lean organizational teaching and learning.

Knowledge Society framed by Drucker (1992) was understood in the scholarly world as the contemporary society. The challenge of the contemporary society can be described how organizations need to swiftly utilize their capabilities and networks to survive in the fast-paced digital world. As Davenport et al (1998) posit that intelligent knowledge is the power to survival in the competitive space. The complexity of this challenge is that expertise and new talent are shaped by the automation technologies. Essentially, it is driving organizations to look closer how the knowledge held and networks formed by individuals can be enhanced through effective KM with BI integrated for a more effective and shorter-oriented time for teaching and learning.

Managing knowledge and relevant management networks are relatively critical to organizations, thus it is important to posit a theoretical discussion on how business intelligence (BI) can be integrated with the knowledge teaching management (KTM) system in organization to optimise learning an organizational worker. Focusing on the on the role of technology, Alavi and Leidner’s (2001) framework provides insight on perspectives of knowledge that can be optimised for learning. This framework lends toward supporting an integrated BI and KTM system. The framework of perspectives by Alavi and Leider (2001) drawn from the works of Huber (1991) and Nonaka (1994) can be seen in the table below.

Table 1.
Perspectives of knowledge for KMT (adapted from Alavi & Leider, 2001)
Perspectives of KnowledgeKM System for Teaching & Learning
State of MindA space where experiences are shared and enabled.
An ObjectPermitting the gathering, storage, distribution and renewal.
A ProcessActs as link between two or more for the relationship of teaching and learning. Permitting a way of flow.
A Condition of Access to InformationAbility to query, locate and access information with the diverse thought patterns and approaches.
A CapabilityTo enhance cognition and journey into insights.

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