As companies face significant supply chain challenges, from component shortages to disrupted shipping routes, changing global trade agreements and volatile customer demand, smarter approaches are in high demand. Naturally this extends to the use of AI in supply chain management.
Oracle is one vendor reacting to the supply chain problem with various upgrades announced in the last few months. February saw it add updates to Transportation Management and Global Trade Management within Oracle Fusion Cloud Supply Chain and Manufacturing (SCM), aimed at optimizing logistics operations by increasing visibility, reducing costs, automating regulatory compliance and improving decision-making.
At its CloudWorld event in London, meanwhile, new AI capabilities were unveiled with prebuilt analytics in SCM to help organizations connect insights from different areas of their supply chain and respond to changes faster.
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Any end users unconvinced by the use of AI in supply chain let alone anywhere in their ERP systems may find comfort in the thoughts of Richard Pepper, president of the UK Oracle User Group (UKOUG): “This isn’t just a liberal sprinkling of GenAI for the sake of ticking boxes and the ability to sell more licenses. It’s a step change in the way that Oracle SCM works.”
What users need, he explains, is a wealth of data and insights to help anticipate supply chain disruptions before they occur. This allows businesses to implement pre-emptive measures, minimizing potential impacts on operations and customer satisfaction.
Pepper points to end user appeal in March’s launch of Oracle Smart Operations, a function in SCM which provides real-time insights, predictive analytics, and intelligent automation capabilities, thereby reducing manual intervention and the likelihood of human error.
“This is especially useful for those supply chains that rely on timeliness and accuracy or delivery. Take Just In Time (JIT) manufacturing for instance and the need to have materials ready for assembly at a car plant or distribution within a retail organization from distribution centers to shops.”
Automated processes in any setting with any platform leads to fewer errors, less waste, and optimized use of resources, all of which contribute to cost savings. These savings can then be reinvested into other areas of the business, driving further growth and innovation.
Pepper adds that when products are free of supply chain issues they can be delivered on time, at a lower cost, and with fewer errors. The result? Companies can build stronger relationships with their customers, fostering loyalty and driving repeat business.
AI in supply chain for manufacturing
At CloudWorld London, ERP Today dug deeper into Oracle’s vision for AI in supply chain and automation in general, hearing from Rajan Krishnan, Oracle’s group vice president.
Both Krishnan and UKOUG’s Pepper point to the various facets of SCM designed with the shop floor in mind, features like Operator Workbench which offer a unified interface for essential daily data, while Digital Work Instructions enhance assembly operations for better quality and consistency.
“In Oracle Cloud Maintenance,” Pepper explains, “new functionalities merge maintenance and real-time asset data, aiding in ongoing monitoring and predictive upkeep, with Maintenance Technician Workbench facilitating task access and collaboration for technicians.”
At CloudWorld, Krishnan delved into the use case of digital twins that can emerge from using daily data stream and predictive capabilities. Such twins house a virtual version of the shop floor, helping operatives troubleshoot and carry out predictive maintenance even before a machine or part breaks down.
“But even with a digital twin, manufacturing education systems (MES) and everything else that’s available today, there’s still so many multiple technologies which the shop floor technician has to deal with.”
“Where AI components come in is [automating] item descriptions, supplier negotiations, summaries and supplier recommendations for operators and supervisors,” Krishnan continues.
In other words, having a digital twin on one hand is useful, but if a part is close to breaking down, time is still wasted in the supply chain on procuring parts for the physical machines in the real world. Oracle argues this is where the AI fix acts as the perfect complement to business information modeling in industrial settings.
Having AI in supply chain for businesses therefore could help them quickly adapt their supply chains to the changing global business environment. Logistics professionals may benefit from agile, smart and efficient processes in their ERP to help them successfully navigate regulatory compliance, reducing the likelihood of trade bottlenecks and mitigate the impact of ongoing shipping disruptions.
What ERP Insiders need to know
The below updates to Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) give an example of AI in supply chain as implementable in an ERP instance.
- Item description generation: Helps product specialists quickly generate standardized product descriptions that highlight SEO keywords. With generative AI support for item descriptions in Oracle Product Lifecycle Management, organizations can save time, reduce errors, and improve the overall quality of product descriptions to increase customer engagement and boost sales.
- Supplier recommendations: Help procurement professionals quickly and efficiently add suppliers to their organization’s supply chain. With generative AI-powered supplier recommendations embedded in Oracle Procurement, organizations can use information such as product descriptions and purchase categories to identify suppliers, improve sourcing efficiency, help lower costs, and reduce supplier risk.
- Negotiation summaries: Help procurement professionals quickly generate a customized cover page summary for a specific negotiation. With generative AI-powered assisted authoring embedded in Oracle Procurement, organizations can accelerate negotiations, increase savings, reduce risk, and maximize supplier outcomes.
