Hoque, Mohd Jahidul and Ofuegbe, Samuel B. and Rahim, Muhammad and Ifti, Naim Rahman (2024) Artificial Intelligence-Based Decision Support Systems for Business Process Optimization: A Data-Driven Framework for Enhancing Organizational Efficiency and Strategic Decision-Making. American Journal of Technology Advancement, 1 (12). ISSN 2997-9382

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Abstract

Artificial Intelligence decision support system is playing a vital role in business process optimization and increasing the efficiency of the organization by making the decision based on data. The goal of this research is to uncover patterns and relationships between operational data, and to discover performance indicators for business processes, to enable strategic managerial decisions. The research goals are to explore operational cost distributions, to assess utilization of the workforce, to analyze relationships between important business performance measures and to build an operational efficiency framework to support strategic decision making. This study employed a quantitative exploratory research design; a secondary data obtained from Mendeley Data published in 2023. The dataset was cleaned, streamlined and analyzed using exploratory data analysis, descriptive statistical analysis, correlation analysis and visualization tools such as box plots, scatter plots, correlation heatmaps and an operational efficiency dashboard, within R Studio. The results show across a wide range of costs for operating the business, mainly in terms of costs on skill investment and overtime costs but also on digitization costs. Correlation analysis reveals the significant relationships between workforce allocation and operational costs, as well as between operational costs and business performance measures, while resource utilization shows a positive correlation with operational workload. The operational dashboard also shows the following key performance indicators: workload, objective value and unserved task costs. Overall, it is shown that data driven exploratory analysis is successful in supporting the work of an artificial intelligence-based decision support system, especially in the aspects of resource allocation, business process optimization and strengthening the organizational decisions making process.

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence, Decision Support, Business, Optimization, Data, Strategic
Subjects:	H Social Sciences
Depositing User:	admin eprints
Date Deposited:	04 Nov 2026 07:29
Last Modified:	04 Nov 2026 07:29
URI:	http://eprints.umsida.ac.id/id/eprint/17414

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