Business Intelligence for Entrepreneurial Growth: A Knowledge Management Approach at the Department of Small Business Development

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Abstract

This article explores the integration of Business Intelligence (BI) as a Knowledge Management (KM) tool within the Department of Small Business Development (DSBD) to address challenges facing South African entrepreneurs. These challenges include limited business training programs, inadequate monitoring and evaluation systems, insufficient supply-driven business initiatives, and predominantly urban-centric support for entrepreneurs. By adopting a knowledge-centric approach, this research investigates how BI can serve as a transformative tool to enhance data-driven decision-making, foster knowledge retention, and improve resource allocation to support the entrepreneurial ecosystem.Methodology/Design/Approach The research adopts a qualitative approach, utilizing semi-structured interviews with twenty Business Development Officers and a review of relevant documents. The data were analysed thematically to identify how BI tools are currently used and to develop a model for improved support mechanisms.Findings This study highlights the role of BI in creating actionable insights, enhancing learning and innovation, and supporting effective knowledge-sharing practices. The findings aim to contribute to developing a robust KM framework that leverages BI to empower entrepreneurs, mitigate growth barriers, and foster a sustainable environment for small business success.Conclusion The article concludes that integrating BI with KM offers DSBD a powerful framework for delivering responsive, data-informed support to entrepreneurs. This approach not only enhances the department's capacity to make informed decisions but also fosters sustainable growth within the entrepreneurial ecosystem.Limitations Given its qualitative scope and focus on DSBD officers, the study may have limitations in terms of broader applicability. Future research should consider perspectives from a wider range of stakeholders to further validate and adapt the model.

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