Integrating advanced information analysis techniques to enhance operational efficiency in business administration practices

Tim, Ekaette and Babalola, Ayodeji and Kossidze, Abla Akpene and Goriparthi, Sai Vidhya (2025) Integrating advanced information analysis techniques to enhance operational efficiency in business administration practices. World Journal of Advanced Research and Reviews, 25 (1). pp. 1275-1293. ISSN 2581 9615

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Abstract

Advanced techniques of information analysis, with their implementation, have become the basis of the economic efficiency of modern business management. In the face of ever-compounding complexity in markets and even more growing competition, applying data-driven tools and methodologies can have transformative power to simplify processes, optimize resource utilization, and improve decision-maker effectiveness. This article discusses how operational excellence across a number of business administration practices is driven by advanced information analysis. It elaborates on defeat analytical methods, like predictive modeling, data visualization, and machine learning algorithms, and illustrates their usage in process optimization and inefficiency identification. Data on resource performance is made available for actionable insights, empowering real-time fine-tuning of resource allocation and, in future iterations, automating provisioning adjustments based on usage trends. They also enable organizations to react to the changing market landscape swiftly, without incurring unnecessary costs or redundancies. Although case studies differ from industry to industry, such as retail, manufacturing, or financial services, the practical outcomes of how information analysis helps in improving operational efficiency can also be seen across the board. From supply chain optimization to customer relationship management, evidence of how advanced analytics helps reduce bottlenecks, forecast trends, and align operations with strategic objectives continues to grow. Furthermore, ethical implications, including data privacy and algorithmic bias, are considered to secure the responsible implementation of these technologies. The discoveries highlight the significance of establishing a data-driven culture in organizations. By enabling teams with the know-how and capabilities for higher-level analytics, organizations can make sustainable efficiency improvements and gain an advantage in the broad environment, which is changing quickly. This article delivers practical steps managers can take to utilize advanced information analysis systems in their businesses.

Item Type: Article
Uncontrolled Keywords: Information analysis; Business administration; Operational efficiency; Predictive modelling; Data visualization; Machine learning
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Depositing User: Editor WJARR
Date Deposited: 09 Jul 2025 16:43
Last Modified: 09 Jul 2025 16:43
URI: https://eprint.scholarsrepository.com/id/eprint/233

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