Shelf life doesn’t wait for the S&OP cycle.
Yield you cannot assume, an input that is not uniform, a clock running on every lot, and a customer base that reorders weekly. The planning horizon that matters is days, and most planning systems were built for months.
Beef and protein processing · Dairy · Bakery · Produce and fresh · Prepared foods · Beverage
Where the decision stalls.
Yield variance breaks the plan the day it is made
Carcass yield, batch strength and moisture all move. A schedule built on standard yields is wrong by the first shift, and the correction happens in a spreadsheet.
Shelf life turns excess into write-off, not carrying cost
In most industries slow-moving inventory costs you working capital. Here it becomes markdown or waste on a fixed date, so the allocation decision has a deadline attached.
Price and demand move together, weekly
Regional demand, competitor pricing, feed and input costs and weather all move inside the cycle. By the time a static price list reaches the sales team it is stale.
Multi-plant, multi-channel, huge SKU counts
Dozens of facilities, many sales channels, tens of thousands of SKUs. No planner can hold the tradeoff between a channel commitment and a plant constraint in their head.
One story: allocating a short lot across channels
A yield miss leaves you short on a high-demand cut on a Tuesday. Three channels have standing commitments, one of them contractual. The decision has to be made before the lot ages, and it has to be defensible to the account you disappoint.
External Demand Sensing
Reads regional demand, competitor movement, weather and input cost signals so the short position is sized against what demand is actually doing this week, not last month.
Multi-Echelon Inventory Optimization
Costs the reallocation across plants and DCs net of shelf life, so the option that protects service does not create a write-off somewhere else.
Customer Promise Intelligence
Ranks the channels against your own commitment rules and returns which customer gets protected, what it costs, and what the alternative would have cost.
One reconciled recommendation, ranked, with the trigger, the alternatives considered, the constraint that applied and the expected impact attached — ready to approve, edit or reject. Not three separate alerts from three separate systems.
JBS — 65 plants, 17 sales channels, 150,000+ customers — cut its regional demand and pricing forecast cycle from 28 hours to under one hour, and now simulates pricing across 60,000+ SKUs in minutes.
The coordinated agent system across demand, production, S&OP and pricing increased JBS’s profitability by $200 million in Year 1. The deployment is documented publicly by Databricks.
Start with your version of this decision.
Thirty minutes on the decision that costs your operation the most, mapped across the systems you actually run.