Provided by Selonis
When rates change overnight, companies have 48 hours to model alternatives and can act before competitors secure the best option. At Celosphere 2025 in Munich, companies demonstrated how they are turning their disruption into competitive advantage, with quantitative results that separate the winners from the losers.
Binmar International: A global plastics and chemicals distributor built a real-time digital twin of its $3 billion supply chain, reducing default rushes by more than 20% and improving delivery agility across its global operations.
Florida Crystal: One of America’s largest sugarcane producers secured millions of dollars in working capital and strengthened supply chain resiliency by eliminating manual rework across finance, procurement, and inbound supply. AI pilots are now extending their results to invoice processing, predictive maintenance, and order management.
asos: The e-commerce fashion giant connected its end-to-end supply chain for complete transparency, reducing process variation, speeding time to market, and improving customer experience at scale.
The common denominator here is process intelligence that fills gaps that traditional ERP systems cannot fill, connecting operational points across ERP, finance, and logistics systems when the moment matters.
“The question is not whether there will be disruption,” says Peter Budweiser, general manager of supply chain at Celonis. “The question is, can the system see the problem fast enough to fix it?”
This visibility gap costs the average company double-digit millions of dollars in working capital and competitiveness. With 54% of supply chain leaders facing disruption every day, the pressure shifts to AI agents that perform real actions, such as issuing purchase orders, rerouting shipments, and adjusting inventory. But autonomous agents working with stale or siled data can make multimillion-dollar mistakes when pricing structures change overnight.
Tariffs, as old as trade itself, have become the ultimate stress test for enterprise AI, revealing whether companies truly understand their supply chains and whether their AI can be trusted to act.
Modern ERP: Rich data, little insight
Supply chain leaders face the paradox of being hungry for insight and drowning in data. Traditional enterprise systems (SAP, Oracle, PeopleSoft) meticulously capture every transaction.
SAP records the purchase order. Oracle tracks shipments. Warehouse systems record the movement of inventory. Each performs its function, but when rates change and companies need to model all three alternative procurement scenarios simultaneously, the data remains siled.
“What has changed is the speed with which disruptions cascade,” says Manik Sharma, Head of Supply Chain GTM AI at Celonis. “Traditional ERP systems were not built for today’s volatility.”
Companies create thousands of reports showing what happened in the last quarter. They struggle to answer what will happen if tariffs go up 25% tomorrow and they have to change suppliers within a few days.
Tariffs: 48 hours of competition
Global trade volatility has transformed tariffs from a predictable cost into a strategic weapon. When new rates drop with unprecedented frequency, input costs across suppliers skyrocket, finance teams scramble to calculate the impact on margins, and procurement races occur to identify substitutes buried in disconnected systems where no one knows whether switching suppliers will delay shipments or violate contracts.
By 48 hours, competitors who have already modeled the scenario will have switched suppliers, while latecomers face capacity constraints and premium pricing.
Process intelligence changes that dynamic by allowing companies to continually model “what if” scenarios and show leaders how rate changes cascade to suppliers, contracts, production lines, warehouses, and customers. If interest rates rise, businesses can move within hours instead of days.
No AI without PI: Why process intelligence is non-negotiable for supply chains
AI and supply chain are interdependent. AI requires operational context, and supply chains need AI to respond to volatility. But this is the truth. There is no AI without PI. Without process intelligence, AI agents operate blindly.
The ongoing wave of SAP migrations shows why. An estimated 85-90% of SAP customers are still migrating from ECC to S/4HANA. Migrating to a new database does not solve supply chain visibility. Faster access to the same fragmented data.
Kerry Brown, change evangelist at Celonis, sees this across the industry.
“Organizations are moving from PeopleSoft to Oracle, or EBS to Fusion. The majority are in SAP,” she explains. “But what they really need isn’t a new ERP. They need to understand how work actually flows between their existing systems.”
It requires an end-to-end operational context. Process intelligence accomplishes this by allowing businesses to extract and connect event data across systems, showing how processes are performed in real-time.
This distinction becomes important when deploying autonomous agents. When visibility is fragmented, autonomous agents can easily make decisions that appear rational locally, but cause confusion downstream. Real-time context allows AI to operate with clarity and precision, allowing supply chains to stay ahead of fee disruptions.
Digital twin: Powering real-time response
The companies featured in Celosphere all apply the same principles: understanding how processes run across systems in real time. Celonis PI creates a digital twin on top of your existing systems by linking orders, shipments, invoices, and payments end-to-end using process intelligence graphs. Gain visibility into dependencies that traditional integrations miss. Delays in SAP immediately reveal the impact across Oracle, warehouse scheduling, and customer delivery commitments.
“The platform is powered by a business context that integrates process data across systems and departments and enables AI agents to effectively transform operations,” said Daniel Brown, chief product officer at Celonis.
With this cross-system awareness, Celonis coordinates actions across complex workflows involving AI agents, humans, and automation. This is especially important when tariffs require quick decisions about suppliers, shipments, and customers.
Zero-copy integration allows instant modeling
A key advancement announced at Celosphere, zero-copy integration with Databricks, removes another barrier. Traditionally, analyzing supply chain data required copying it from source systems to a central warehouse, resulting in data delays.
Celonis Data Core integrates directly with platforms like Databricks and Microsoft Fabric to query billions of records in near real-time without duplication. When trade policy changes, companies model alternatives instantly, rather than after an overnight data update cycle.
Enhanced task mining extends this by connecting desktop activity (keystrokes, mouse clicks, screen scrolling) to business processes. This will reveal manual activities that are not visible in the system logs. It’s the spreadsheet gymnastics, email negotiations, and phone calls that keep the supply chain moving during emergency changes.
Competitive advantage in volatile markets
Most companies cannot and should not remove and replace systems running critical operations. Process intelligence offers an alternative path to configuring workflows from existing systems, deploying AI where it creates value, and continuously adapting to changing conditions. This “process liberation” movement frees enterprises from rigid architectures without forcing wholesale replacement.
As global trade volatility intensifies, modeled companies will move faster, make smarter decisions, and turn tariff disruption into a competitive advantage while keeping their existing ERP running.
When the next wave of tariffs hits, and it probably will, companies won’t have days to react. There will be hours. The question is not whether ERP captures data. What matters is whether the system connects the dots fast enough.
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