review · South African journal of information management
Background: Business analytics knowledge is a tacit resource that serves as a driving force in aiding data-driven decisions for organisational competitive advantage and efficient and effective service delivery. It is vital to explore the factors which impact knowledge sharing within data analytics teams. Objectives: The study aimed to identify the prominent information systems capabilities and knowledge sharing factors which are vital for improved business analytics within the public enterprise organisations. Method: Through a systematic literature review, this study examines the mechanisms by which knowledge retention can be achieved. Data were collected from AIS eLibrary, AJIS, Web of Science, Scopus and ScienceDirect databases. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Results: The knowledge possessed by subject matter experts (SMEs) is business domain knowledge, which cannot be easily accessed unless it is retained within various knowledge repositories within the organisation. Such a situation results in public organisations losing out on their intellectual capital. The study findings reveal that social factors such as knowledge sharing, knowledge retention, scarcity in sourcing the right skills, analytics competence and analytics culture, trust, play significant roles in improving business analytics. Conclusion: To reap the benefits, both social and technical factors should be considered as part of a social activity system, rather than being applied in isolation. This article discusses the best practices that public enterprise organisations should consider from a social perspective for improved business analytics. Contribution: The study contributes to the body of knowledge through addressing the existing gap experienced by public enterprise organisations through investigating prominent factors influencing information systems capabilities and knowledge sharing for improved business analytics.
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DOI: 10.4102/sajim.v28i1.2109
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