Financial Planning and Forecasting Systems in Oracle Cloud ERP & EPM: Predictive Models for Enterprise Planning
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I2P112Keywords:
Oracle Cloud ERP, Oracle EPM, Predictive Analytics, Enterprise Planning, Financial Forecasting, AI-Driven FinanceAbstract
The process of enterprise financial planning is also radically changing with companies moving out of on-premise spreadsheet-based processes to cloud-native and analytics-based services. Some of the options available are the Oracle CloudERP and Enterprise Planning Management (EPM) systems, which can serve as one base of bringing together transactional financial information with strategic planning, allowing made decisions to be made in predictive or scenario mode. Nevertheless, numerous businesses are still confronted with some limitations such as disintegrated data points, inflexibility of budget processes, weak predictability, and the failure to quickly adapt to market fluctuations. The paper will deal with these drawbacks by presenting a predictive financial planning and forecasting architecture based on the close cooperation of the Oracle Cloud ERP and Oracle EPM. The suggested approach is founded on the past financial operations, operational key performance indicators and external economic indicators to come up with futuristic predictions through an aggregate of statistical time-series models, and machine learning methods. To operationalize these models in enterprise planning processes, advanced analytics services in the Oracle Cloud Infrastructure such as autonomous data management, among other embedded predictive capabilities in planning, are used. The methodology focuses on end-to-end data integration, automated model execution, scenario analysis and what-if analysis, and deployment that governs. Experimental performance based on an enterprise case study reflects that the accuracy of the forecast, budget variance events reduce and planning cycle time decreases as your results are accomplished by the traditional methods. This work is significant as it introduces an efficient predictive planning framework that is Oracle centric to facilitate operations financing and strategic decision making that provides a scalable and secure reference model on the next generation enterprise financial planning systems.
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