A REFERENCE MODEL FOR BUSINESS ANALYTICS-BASED DECISION-MAKING PROCESSES IN RAIL TRANSPORT MANUFACTURING COMPANIES IN SOUTH AFRICA

Genevieve Bakam (), Khumbulani Mpofu () and Charles Mbohwa ()
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Genevieve Bakam: Tshwane University of Technology, Pretoria, South Africa
Khumbulani Mpofu: Tshwane University of Technology, Pretoria, South Africa
Charles Mbohwa: Tshwane University of Technology, Pretoria, South Africa

Business Excellence and Management, 2025, vol. 15, issue 1, 97-113

Abstract: In addition to digital transformation, businesses have reviewed their business strategies and decision-making techniques to develop a competitive advantage in the transport manufacturing sector. It happens that innovative business approaches face some limitations compromising business survival in the long term. This study investigates the importance of adopting a reference model for business analytics-based decision-making processes in rail transport manufacturing companies. This study follows a qualitative research design using secondary data published in various annual reports to define the thematic analysis around descriptive, prescriptive, and predictive analytics for enhanced business analytics-based decision-making solutions. Results indicate that improved business decisions should be based on the combination of company strategies, technology innovation and business analytics techniques for goals alignment, innovative solutions and data visualisation. Additionally, descriptive, prescriptive, and predictive analytics are generated in a predefined format to suit business, socioeconomic and environmental requirements like product localisation, company equity, financial support of black businesses, skills development, local community empowerment, and environmental protection. Business analytics-based decisions enable cost control, differentiated business decisions for competitive advantage, and strategy upgrades in addition to customer satisfaction, profitability growth and long-term sustainability. The proposed reference model shows the link between company strategies, data analysis, and technology impact in generating enhanced analytics powering the decision-making process in transport manufacturing to ensure the revitalisation of future transport in South Africa. Recommendations highlight that the South African government should improve technology infrastructure and skills development to limit resistance to digital transformation enabling business analytics.

Keywords: Reference model; Business analytics; Decision-making process; Transport manufacturing; South Africa (search for similar items in EconPapers)
Date: 2025
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