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Predictive analytics (PA) is used for a variety of objectives, including optimisation, planning, strategy development, and resource management, all to improve performance. PA also helps organisations and customers communicate more effectively. Managers may increase customer satisfaction by integrating data on consumer preferences and experiences. Despite increased interest in PA technologies, there is still a considerable study gap in understanding its influence on small and medium-sized enterprises (SMEs) operational efficiency and revenue growth in Sub-Saharan Africa. Hence, the survival of SMEs as key drivers of economic growth and development in Sub-Saharan necessitated this study. The study investigates the influence of predictive analytics on operational efficiency and revenue growth of SMEs in Accra, Ghana, and Lagos, Nigeria. Acknowledging both cities as main commercial centres in their respective nations Using a cross-sectional and survey research approaches, the study sent 150 copies of questionnaire to SMEs in each of the cities using purposive sampling techniques, therefore guaranteeing a focus on key economic centres. Under the guidance of four research assistants in each city monitoring distribution and collection, data were gathered online over two months. The results showed that predictive analytics has positive and significant effect on both operational efficiency and revenues growth of SMEs. The study recommended that SMEs should give training to their staff top priority as well as build the required infrastructure to make the best use of predictive analytics. This entails not just purchasing cutting-edge analytics tools and technology but also making sure staff members have the ability to understand and act upon data-driven insights. Building a solid basis in predictive analytics can help SMEs better use data to maximise operations, foresee trends, and make wise strategic choices, thereby promoting higher efficiency and income development
Opoku et al. (Wed,) studied this question.