Big data based knowledge management vs. traditional knowledge management: A people, process and technology perspective

MUHAMMAD SALEEM SUMBAL, MURAD ALI, UMAR FAROOQ SAHIBZADA, FAISAL NAWAZ MIR, ADEEL TARIQ, HINA MUNIR

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Value creation is one of the core aspects of Big Data. This concept of value creation can be linked to the efficient knowledge management within the organizations, in terms of knowledge creation, sharing and application, through which organizations can enhance their organizational performance. Little work has been done on the linkage of value creation from big data and the knowledge management capability of the organizations in terms of people, processes and technology which play a crucial role in effective knowledge management. This study contributes towards the existing body of knowledge by exploring this linkage of people, process and technology in relation to big data through the lens of knowledge management, by conducting a qualitative study in the oil and gas industry. The findings reveal that the KM capability of the organizations through big data can be explained through the Complex domain of Cynefin framework which involves probing, sensing and responding in which there are no right answers and instructive patterns (predictive knowledge) emerging from big data could be right or wrong depending upon the complexity of the situation. The useful and tested predictive knowledge by experts (people) can then emerge as good or best practice falling into complicated and simple domains of Cynefin framework.

Original languageEnglish
Pages (from-to)1053-1065
Number of pages13
JournalJournal of Information Science and Engineering
Volume37
Issue number5
DOIs
Publication statusPublished - 1 Sep 2021
Externally publishedYes

Keywords

  • Big data
  • Cynefin framework
  • Knowledge application
  • Knowledge creation
  • Knowledge management
  • Technology

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Hardware and Architecture
  • Library and Information Sciences
  • Computational Theory and Mathematics

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