Predictive Analytics in Oracle Fusion Cloud ERP: Leveraging Historical Data for Business Forecasting
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P110Keywords:
Predictive Analytics, Oracle Fusion Cloud, Machine Learning, Business Forecasting, Supply Chain Demand Forecasting, BudgetingAbstract
Enterprise Resource Planning (ERP) systems have come out of the traditional transactional systems to intelligent systems that can support advanced business decision making. In this paper I would be discussing the implantation of predictive analytics in the Oracle Fusion Cloud ERP to increase the accuracy and timeliness of enterprise forecasting. Using past financial, supply, and budget data, as well as relating it to the analytical potential of Oracle Analytics Cloud (OAC) the proposed framework will allow developing the machine learning models specific to the core business functions. The models applied to these issues are time-series analysis using ARIMA to forecast cash flows and ensemble to balance between decision-making under time pressure and the costs of such approaches using Random Forest and deep learning approaches, such as Long Sheet Memory (LSTM) networks.The experimental assessment shows that machine learning-through forecasting gives enormous improvement of accuracy levels in prediction as opposed to conventional rule- based methods, as the error rates are minor and the ability of the planning is both reliable and dependable too. The findings demonstrate the ease with which predictive analytics can be integrated into the routing of ERP processes using automated OAC dashboards and pipelines and deliver real-time information and actionable intelligence to decision-makers. In addition to technical input, the study highlights the significance of the forecasting ERP systems to a wider business mind, such as enhanced liquidity management, resilience in the supply chain, and resource optimization. In totality, the study will offer a stepwork guideline to businesses keen on implementation of predictive analytics in cloud-based ERP settings to set the foundations of informed, versatile, and reactive businesses management
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