The plant absorbs the difference.
Most regional plants are planned at a cadence their operation cannot answer: planning runs monthly against a demand signal that moves weekly, and the plant absorbs the difference through informal expediting. The cost of that absorption has usually never been measured.
Closing that gap is a scheduling and data problem before it is a capital one, and it pays back faster than any equipment line. On one building-materials engagement, writing the rescheduling rules with the schedulers on paper — before any code — is what got the plant to adopt the change.
Where plant performance leaks.
Planning cadence mismatch
A monthly plan against weekly demand movement, with the gap absorbed informally on the floor.
Every deviation escalates
No rule exists for rescheduling within tolerance, so the plant manager decides everything personally.
Expediting cost invisible
Overtime, changeovers and premium freight are absorbed into overheads and never attributed to the plan failure that caused them.
OEE reported, not used
A number is produced monthly and no downtime reason code drives a maintenance or scheduling decision.
Shop floor data on paper
Production, scrap and downtime are recorded on sheets and keyed in the next day, too late to act on.
Material shortages found at the line
The schedule assumes availability that the warehouse cannot confirm until the job starts.
What the engagement actually includes.
Measure the real cadence
How often demand actually moves against how often the plan is refreshed, and what the plant spends absorbing the difference.
Write the rescheduling rules
On paper, with the schedulers: reschedule within tolerance, escalate outside it, log every decision. The paper rules are the deliverable that earns adoption.
Shop floor data capture
Production, downtime, scrap and labour captured at the line as it happens, with reason codes that a maintenance or scheduling decision can act on.
Scheduling engine
Finite capacity scheduling against real constraints — material, labour, changeover, maintenance windows — refreshed at the cadence the plant runs at.
Bounded scheduling agents
Where the rules are stable, agents apply them within tolerance and escalate outside it — every decision logged and readable by an auditor, replaceable within a week.
Cost the absorption
Overtime, changeovers and premium freight attributed to the planning failures that caused them, so the trade-off becomes visible to the people making it.
Paper rules, then the schedule, then the agents.
Rules are written on paper before any code. These are the components the plant then runs on.
Ranges observed on Al Jawad engagements. Your targets are agreed in assessment, before the work starts.
Is this an AI project?
No. It is a scheduling problem that AI happens to be the right tool for in one part. The paper rules are the deliverable; the agents are an implementation detail — and saying so out loud is what got one plant to adopt them.
Do we need shop floor hardware?
Usually a tablet or terminal per line is enough to start. Machine integration comes later, where the downtime data justifies it.
How quickly does adherence improve?
Typically within two planning cycles once the rescheduling rules are live, because most adherence loss comes from decisions waiting rather than capacity.
Will the schedulers accept it?
If the rules are written with them before any code, yes. If a system arrives with rules they never saw, no — and that is the most common failure mode.
Start a conversation.
Choose the one that fits where you are. None of them is a sales call. Each is an advisory conversation calibrated to a specific question.