Title: Optimizing Operational Efficiency Through Business Intelligence and Data-Driven Strategic Decision-Making
Authors: Kolade Olusola Ogunsola, Emmanuel Damilare Balogun, Adebanji Samuel Ogunmokun
Volume: 9
Issue: 3
Pages: 124-132
Publication Date: 2025/03/28
Abstract:
This study explores the role of Business Intelligence (BI) tools and data-driven decision-making frameworks in optimizing operational efficiency and improving strategic decision-making in modern organizations. With an increasing reliance on data to drive business outcomes, BI tools have become essential for providing real-time insights that enhance decision-making, improve processes, and boost productivity. The research delves into various BI technologies such as Power BI, Tableau, and SAP BusinessObjects, examining their applications across different industries, including manufacturing, retail, and healthcare. Through case studies and real-world applications, the study highlights how BI tools have led to tangible improvements in organizational performance. Furthermore, the paper identifies the challenges businesses face in adopting BI systems, including data quality issues, high implementation costs, and organizational resistance, and offers practical recommendations to overcome these obstacles. The findings underscore the importance of integrating data-driven decision-making frameworks into business operations for companies to gain a competitive advantage. The paper concludes with a discussion on future research directions, including the development of AI-powered BI tools, the potential of real-time analytics, and the role of cloud-based BI platforms.