Unlocking competitive advantage in emerging markets through advanced business analytics frameworks
1 Bowling Green State University, Ohio USA.
2 Independent Researcher, USA.
3 Independent Researcher, UK.
4 Labatt Breweries of Canada.
Review Article
GSC Advanced Research and Reviews, 2024, 21(02), 419–426.
Article DOI: 10.30574/gscarr.2024.21.2.0455
Publication history:
Received on 15 October 2024; revised on 20 November 2024; accepted on 23 November 2024
Abstract:
This paper explores the transformative potential of advanced business analytics frameworks in unlocking competitive advantages for businesses operating in emerging markets. It begins by highlighting the significant benefits of advanced analytics tools and techniques, such as predictive and prescriptive analytics, big data, and machine learning, in understanding market trends, consumer behavior, and operational efficiency. Despite these benefits, businesses in emerging markets face substantial challenges, including inadequate technological infrastructure, a shortage of skilled professionals, high implementation costs, and data quality issues. The paper outlines the key implications for businesses seeking to gain a competitive edge, emphasizing the importance of agility, customer-centric strategies, and operational efficiencies. It then provides strategic recommendations for effectively implementing advanced business analytics frameworks, including investing in technological infrastructure, building a skilled workforce, improving data quality and accessibility, adopting scalable solutions, focusing on data privacy and security, leveraging AI and machine learning, embracing edge computing and IoT, and fostering a culture of innovation. By addressing these challenges and following these recommendations, businesses can harness the power of advanced analytics to achieve sustainable growth and maintain a competitive advantage in the dynamic environments of emerging markets.
Keywords:
Advanced business analytics; Emerging markets; Competitive advantage; Predictive analytics; Operational efficiency; Data-driven strategies
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
