Predictive analytics, operational efficiency, and revenue growth in SMEs in Africa

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

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-30
DOI
https://doi.org/10.5281/zenodo.14964628
Primary Topic
Foot and Ankle Surgery
Type
article
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article

Predictive analytics, operational efficiency, and revenue growth in SMEs in Africa

Zenodo (CERN European Organization for Nuclear Research)
Foot and Ankle Surgery
article

Predictive analytics, operational efficiency, and revenue growth in SMEs in Africa

article en

Abstract

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

Zenodo (CERN European Organization for Nuclear Research)
University of Ibadan (NG), Grand Valley State University (US), Stanford University (US)
Openalex Percentile: Top 52%
Foot and Ankle Surgery
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Predictive analytics, operational efficiency, and revenue growth in SMEs in Africa · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS