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Global Academic Journal of Economics and Business
Volume-8 | Issue-05
Original Research Article
An Sap S/4hana and Power Bi-Based Decision-Support Framework for Financial Performance Management in Saudi Manufacturing Companies
Muhammad Yasir Bashir
Published : Sept. 22, 2026
DOI : https://doi.org/10.36348/gajeb.2026.v08i05.024
Abstract
Financial performance management in manufacturing increasingly depends on the ability to combine transaction integrity with timely analytical interpretation. This review develops a decision-support framework that links SAP S/4HANA with Microsoft Power BI for Saudi manufacturing companies seeking stronger profitability, liquidity, cost control, working-capital discipline and investment visibility. The study uses a structured integrative review of literature published from 2020 to 2025, supplemented by recent Saudi industrial policy and technology documentation. Evidence is organized around five themes: digital ERP capabilities, business intelligence and dashboard design, data integration and governance, management-accounting decision support, and the institutional requirements of Saudi industrial transformation. The synthesis indicates that ERP value is not created by transaction automation alone. It becomes strategically useful when governed financial and operational data are transformed into decision-relevant measures, visualized at appropriate levels of granularity, and embedded in recurring planning and review routines. SAP S/4HANA provides the transactional and semantic core, while Power BI extends accessibility through interactive reporting, drill-down analysis, variance diagnostics and cross-functional views. The proposed framework therefore connects source transactions, governed data models, financial KPI logic, visual analytics, managerial interpretation and corrective action in a closed loop. For Saudi manufacturers, this architecture is particularly relevant to Vision 2030 priorities concerning industrial competitiveness, digital transformation, localization and private-sector productivity. The review concludes that successful implementation requires data ownership, metric discipline, secure integration, finance-business partnering and phased adoption rather than technology deployment in isolation.

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