Food and Agriculture SAP BTP SAP Fiori
Cargill: cutting agricultural bid-process effort 30% with design thinking
Used Design Thinking to build a shared bid process: a pricing tool, a real-time bid-entry app, and a season dashboard.
How Design Thinking Cut Agricultural Bid Process Effort by 30%
Designing an Efficient, Transparent Bid Process System
The client’s bid process had many challenges, including lengthy costing times, numerous handoffs between teams, and a significant number of manual steps creating and updating offline documents. To increase the overall efficiency and transparency of the bid process, Mindset utilized Design Thinking innovation methodology. The solution involved the creation and implementation of a shared, cross-team system. This included a digital Pricing Tool, real-time Bid Entry app, improved Bid Costing workflow, and Season Dashboard. In total, the new system enabled a 30% reduction in the effort required to analyze issues, request information and correct issues.
10%
improvement
30%
reduction
in process efficiency
in effort required to request information, analyze, and correct issues
If we built this today
Concept · not delivered scopeSense demand before the harvest moves.
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 custom BTP and Fiori analytics work to give a food and agriculture producer and distributor a clearer read on supply and demand across a perishable, weather-driven network, and in 2026 a lot of that read gets a Joule agent watching it for you.
The data product
Cloud ERP Intelligence
Grounds the agent in governed supply and demand data joined across orders, inventory, and fulfillment so the proposals come from one trusted picture, not a stitched-together spreadsheet. A supply-chain data product on SAP Business Data Cloud feeds the planning signals.
Intelligent Application on SAP Business Data Cloud
The Joule agent
Demand Sensing Assistant
Reads short-term sales signals, open orders, inventory positions, and logistics lead times, then proposes where demand is shifting and which shipments to pull forward before product ages out. It hands the planner a ranked set of moves with the reasoning attached.
SAP S/4HANA, SAP Integrated Business Planning, SAP BTP · PROPOSE · forecast accuracy and on-time-in-full
The Fiori app
Joule AI-Assisted Supply Optimization in SAP IBP
Planners stay in their planning views and ask Joule to explain a forecast swing or test a rebalancing move, with the AI assistance running inside SAP IBP rather than a side tool. For order-level work it pairs with the standard backorder processing apps.
Embedded in SAP IBP planning, reachable from the Fiori launchpad
If we picked this up today we would mine the real planning and order-to-ship process in SAP Signavio first, map the BTP and integration footprint in SAP LeanIX, and let MIND accelerators carry the old custom analytics over to the new agent-grounded setup.
A look at the work
