In the world of enterprise resource planning (ERP), Oracle stands as a powerhouse, offering a range of solutions across various sectors. However, the challenge of integrating Oracle data, especially for supply chain use cases, is extremely complex. Unlike SAP data, which benefits from the Cortex framework’s support, Oracle data integration lacks a standardized reference architecture or readily available packaged solution. This gap in the landscape means higher costs, increased risk, and a significant barrier to leveraging advanced AI and analytics capabilities.
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What Companies With Oracle Data Are Seeking
Despite these obstacles, the demand for AI-driven insights from Oracle data is growing. Companies are increasingly asking, “How can we baseline our supply chain and improve through insight derived from our Oracle-based ERPs?”
Oracle environments often lack external datasets and AI integration, leading to a deficiency in critical insights. Questions that businesses are eager to answer include:
→ How can we improve our On-Time In-Full (OTIF) delivery rates?
→ What are the bottlenecks in our supply chain processes?
→ Can we predict and mitigate supply chain disruptions?
→ How do we optimize inventory levels across multiple warehouses?
→ What strategies can we employ to enhance vendor performance?
Answering these questions requires process mining — a method that entails connecting various business systems, such as EBS, Warehouse Management System (WMS), and Oracle Transport Management (OTM) system, and analyzing this integrated data to extract meaningful insights.
Planning in a Box: Transforming Oracle Data to Unlock Real-Time Supply Chain Insights
Planning in a Box is a decision intelligence platform uniquely engineered to navigate the complexities of Oracle data systems. At its core, the platform is designed to simplify the intricate web of data extraction, transformation, and analysis. It goes beyond integration, focusing on extracting nuanced insights critical for real-time decision-making in supply chain management.
By connecting data points from various Oracle sources, Planning in a Box ensures a coherent, unified data flow. The platform’s advanced analytics are designed to delve into this integrated data, identifying trends, anticipating bottlenecks, and proposing actionable strategies to boost overall supply chain performance.
Case Study: Supply Chain Baseline and Optimization Through Oracle Data Mining
A global conglomerate with a multifaceted supply chain sought to upgrade its operational tracking from manual processes to automated dashboards. This initiative was driven by the need for real-time monitoring of warehouse activities, covering inbound and outbound logistics, as well as transportation. The company faced the challenge of integrating several Oracle systems to achieve this goal:
- Oracle Warehouse Management System
- Oracle E-Business Suite (EBS)
- Oracle Transportation Management (OTM)
The key objectives were establishing live connectivity between Oracle WMS and EBS and ensuring seamless integration of essential data for accurate On-Time In-Full (OTIF) metrics, crucial for enhancing supply chain efficiency.