Oracle names three S&OP trends

S&OP trends

Software company Oracle named three S&OP trends during Supply Chain Media’s S&OP Selection Day. The application of artificial intelligence (AI) and machine learning (ML) is one of the most important developments, according to Glen Campbell, Supply Chain Strategy Director at Oracle.

Campbell explained why the application of AI and ML is so relevant for S&OP: “AI can add a lot of value, especially in planning processes where it is necessary to calculate the spare parts needs or sales patterns of new products.”

As the second trend, he named the convergence of planning and execution: “This is a crucial step because companies need to be able to switch quickly between long-term and short-term planning. You also need a system that supports this – one that can calculate requirements for the coming months and also support operational decisions, such as allocating scarce inventory to customers.” Research shows that 60% of companies cannot yet make this link between operations and strategy with their current S&OP process.

Closer collaboration with upstream supply chain partners

The third S&OP trend Campbell identified was the growing tendency for companies to work more closely with upstream supply chain partners. He described this increased attention to multi-tier collaboration and visibility as a positive development. “For a long time, companies did not look beyond direct suppliers in their planning process. During the pandemic and the associated shortages of raw materials and components, they discovered that those links at the start of the chain are actually where the greatest risks lie.”

To address this, companies should integrate all their ‘Tier n’ suppliers into a single supply chain platform so that risks can be spotted earlier and timely action can be taken. Therefore, the wide availability of such platforms is a sign of real progress, in Campbell’s view. “When I did the first S&OP implementations 20 years ago, three-quarters of companies were still working with Excel. When I think back to how many errors this produced and the endless discussions we had about data reliability… That was really disastrous.”

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