Food and Agriculture
Cargill: simplifying the salt-plant driver check-in process
Built a new driver check-in system for the salt plant, cutting process touchpoints to improve productivity and hit delivery deadlines.
Cargill
Simplifying the Driver Check-in Process to Better Meet Deadlines
To better meet deliverable deadlines, the client sought to simplify and streamline the driver check-in process. Opportunities existed to improve planning for shipping on time, provide an upgraded experience for drivers, and minimize safety incidents at the plant. Since it was critical to understand the pain points of every stakeholder in the supply chain, Mindset created Concept Maps of the entire check-in process. By introducing a system that incorporated a unified view of real-time data from disparate systems, the client achieved faster and more accurate decision making, higher customer satisfaction, and improved productivity.
Faster
decision making
Higher
customer satisfaction
Improved
productivity
If we built this today
Concept · not delivered scopeSense demand before the season turns.
This is a forward-looking concept, not the scope we delivered on this engagement. It is the build we would reach for now, grounded in SAP that ships today.
This was analytics-and-data work in food and agriculture, the kind of engagement where the real job is turning scattered operational and supply signals into planning decisions a team can actually trust.
The data product
Cloud ERP Intelligence
Grounds the agent in governed supply and order data from across the business so a forecast suggestion is built on the same numbers everyone reports against, not a side spreadsheet. A supply-chain data product on SAP Business Data Cloud feeds the signals it senses on.
Intelligent Application on SAP Business Data Cloud
The Joule agent
Demand Sensing Assistant
Reads near-term demand signals, open orders, and inventory positions against the plan, then proposes adjustments to forecasts and replenishment when the numbers start drifting. It flags where commodity volatility or a shifting season is about to leave you long or short.
SAP IBP, SAP S/4HANA Supply Chain · PROPOSE · Forecast accuracy and inventory turns
The Fiori app
Joule AI-Assisted Supply Optimization in SAP IBP
Joule sits inside the planning workspace and explains where the plan and the signals disagree, then drafts the rebalancing move for a planner to confirm. You stay in the tool your team already plans in.
Embedded in SAP IBP with Joule
We'd mine the real planning process in SAP Signavio first, map the system landscape in SAP LeanIX, and lean on MIND accelerators to carry the old analytics work into the new agent-grounded model.
A look at the work
