ADVANCED DECISION INTELLIGENCE FOR FINANCIAL AND OPERATIONAL RESILIENCE IN SAUDI PHARMACEUTICAL MANUFACTURING UNDER VISION 2030: INTEGRATING SAP S/4HANA, POWER BI, PREDICTIVE FORECASTING AND WORKING-CAPITAL ANALYTICS
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Abstract
Saudi pharmaceutical manufacturing is being asked to localise more value, protect medicine availability and improve productivity while operating under demand volatility, imported-input exposure, strict quality controls and cash tied up in inventory and receivables. This review develops an integrated decision intelligence model for connecting enterprise transactions with predictive and financial analytics. It focuses on four complementary capabilities: SAP S/4HANA as the governed transactional backbone; Power BI as a role-based visual decision layer; predictive forecasting as an anticipatory mechanism for demand, supply and production variability; and working-capital analytics as the financial discipline linking resilience choices to liquidity. A structured integrative review of 30 sources published between 2020 and 2025 was synthesised through thematic coding, comparative analysis and evidence-quality appraisal. The synthesis shows that resilience does not arise from technology adoption alone. It depends on a closed decision loop in which reliable master and transactional data are converted into forecasts, exceptions, scenarios, managerial actions and measurable learning. For pharmaceutical plants, the highest-value integration points are demand and inventory planning, supplier risk, production and quality execution, expiry exposure, receivables, payables and cash-conversion management.
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Muhammad Yasir Bashir (2026); ADVANCED DECISION INTELLIGENCE FOR FINANCIAL AND OPERATIONAL RESILIENCE IN SAUDI PHARMACEUTICAL MANUFACTURING UNDER VISION 2030: INTEGRATING SAP S/4HANA, POWER BI, PREDICTIVE FORECASTING AND WORKING-CAPITAL ANALYTICS, International Journal of Advanced Research (IJAR), 14 (09), 502-512, ISSN 2320-5407.
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