Oracle adds AI-driven inventory management to cloud SCM suite

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Oracle has announced the introduction of Advanced Inventory Management within its Oracle Fusion Cloud Supply Chain and Manufacturing (SCM) suite to help organisations manage warehouse operations, inventory tasks, and order fulfilment with the assistance of embedded AI capabilities.

The new solution, referred to as Oracle Fusion Cloud Advanced Inventory Management, is intended for sectors such as healthcare and manufacturing, where there is a requirement for intelligent inventory control without the extensive features and complexity associated with comprehensive warehouse management systems.

Advanced Inventory Management is delivered as a component of Oracle Fusion Cloud Inventory Management. The company states it enables organisations to more efficiently oversee tasks, streamline transactions, speed up fulfilment cycles, and enhance warehouse operations. The product incorporates several new features with a focus on automating and optimising inventory processes by utilising artificial intelligence and real-time analytics.

Srini Rajagopal, Vice President, Logistics Product Strategy at Oracle, commented on the issues faced by companies using manual and older inventory systems:

“Organisations that rely on outdated and manual inventory processes struggle to keep pace with evolving supply chain demands, contributing to errors, higher inventory costs, and delayed fulfilment. Oracle Advanced Inventory Management is designed for healthcare, manufacturing, and distribution organizations that need more than simple inventory transaction execution, but do not require the complexity of a full-scale warehouse management system. It enables these organizations to automate and streamline operations and drive greater efficiency,” said Srini Rajagopal, vice president, logistics product strategy, Oracle.

Core features of Oracle Advanced Inventory Management include streamlined task assignment and execution, which aims to reduce duplication and speed up the completion of tasks by delegating pick slips, periodic automatic replenishment (PAR) counts, cycle counts, physical counts, and deliveries to the correct staff members.

The solution also incorporates simplified inventory transactions. This feature allows the use of license plate numbers to process receiving, shipping, transfers, and counting, with inventory levels updated in real time, all managed from within Oracle Inventory Management.

To support timely order fulfilment and minimise handling, real-time cross-docking alerts notify warehouse staff about opportunities to meet pending demand without placing goods in storage. By grouping shipments based on load numbers, the product supports shipment consolidation, which can lower transportation expenditures by allowing multiple orders to be delivered in a single container or truck.

The system offers suggested put-away locations to warehouse staff, an aspect intended to streamline storage decisions and maximise use of available space.

The new capabilities include AI-driven inventory automation, designed to further increase operating efficiency by optimising stock levels, prompting replenishment actions, and automating standard inventory tasks through the use of Oracle’s embedded AI features.

Oracle states that its Inventory Management, Advanced Inventory Management, and Warehouse Management modules collectively form a complete set of solutions supporting organisations at every level of inventory management requirement. This includes environments ranging from basic stockroom operations and manufacturing assembly lines to more complex external warehouse and distribution centre processes.

Oracle Cloud SCM enables customers to create continuity throughout their supply chain procedures and adapt promptly to fluctuations in demand, supply, or market environment. Embedded AI in these products acts as an assistant that analyses operational data, generates relevant content, and augments or automates tasks to support improved business outcomes and strengthen the resilience of supply networks.



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