What happens when one of the world’s largest food producers reimagines its entire supply chain? At BRF, a Brazil-based multinational operating in over 117 countries, that question led to a bold answer: fully embrace predictive analytics and AI-driven planning—at scale.
With over 13,000 SKUs and a highly complex logistics ecosystem, BRF faced the same challenges many in the food industry struggle with:
- fragmented planning systems
- supply volatility
- rigid forecasting
- and lack of real-time visibility
The solution came in the form of SAP Integrated Business Planning (IBP) combined with AI-powered forecasting models—allowing the company to not only streamline its operations but to rethink them entirely.
From Manual Planning to Machine Learning
BRF’s legacy planning approach was slow and linear. Planning steps were siloed, decisions were reactive, and adapting to changes (like unexpected weather patterns or port disruptions) often took days.
After integrating SAP IBP, BRF achieved:
- A unified planning environment that connects demand, supply, and inventory decisions
- Significant acceleration, shrinking the planning cycle from days to minutes
- AI-forecasting models capable of learning from historical data and adapting based on weather, geography, and seasonality
- Traceability improvements, crucial for food safety and regulatory compliance
Most importantly, BRF could now simulate “what-if” scenarios to proactively manage risks like raw material shortages, factory shutdowns, or shipping delays.
Why This Matters Beyond Food
While BRF operates in the food industry, its transformation offers a clear signal to every logistics-intensive business: the future of supply chains is intelligent, integrated, and visible.
And here’s where the conversation expands.
Predictive software, no matter how powerful, is only half the equation. Knowing what should happen doesn’t guarantee what actually happens—especially once products leave the warehouse.
Connecting the Dots: Planning is Digital, But Shipping is Physical
Here’s the critical gap many businesses overlook:
- AI forecasts what’s expected.
- But real-world variables—impact, temperature, humidity, mishandling—can still compromise shipments mid-transit.
At IOG, this is where we come in.
Companies that digitize their planning workflows with tools like SAP IBP are increasingly pairing them with physical monitoring systems—such as shock indicators, data loggers, and environmental sensors. These tools offer:
- Real-time feedback on shipping conditions
- Alerts when damage or out-of-range temperatures occur
- Documentation for accountability and insurance claims
In short: if you’re planning smart, you should be shipping smart.
The Full Circle of Logistics Intelligence
BRF’s story is a showcase of what’s possible when forecasting, planning, and scenario modeling are brought into one intelligent system.
But to truly “close the loop” in a modern supply chain, companies also need continuous visibility during transit.
Planning + Monitoring = True Supply Chain Intelligence
This combined approach ensures that not only are you predicting disruptions before they happen—but also catching them in real-time if they still occur.
Final Takeaway
As global supply chains continue to evolve, the companies that lead the way will be those who integrate software intelligence with physical transparency.
Whether you’re in food, pharma, electronics, or industrial manufacturing, the message is clear: It’s not just about forecasting what’s next. It’s about making sure what’s next arrives intact, traceable, and on time.
