Why delays pile up
In a make-to-order shop, a single disruption — a rush order, a breakdown, material that doesn’t arrive — cascades onto every other order. If the reaction is slow (reshuffling Excel by hand) or the plan ignores real capacity, late deliveries accumulate before anyone sees it coming.
What moves the needle
- Prioritize on weighted tardiness: not every order weighs the same; the plan should protect first the ones that cost most when late.
- Finite capacity: a plan that respects real capacity doesn’t make false date promises.
- Reschedule fast: absorbing the incident the same day avoids the cascade.
- See risk early: knowing today which orders are at risk lets you act (overtime, subcontract, renegotiate).
Measure it, don’t assume it
Before optimizing, save your current planning as a baseline and compare: percentage of past-due orders, total and weighted tardiness, setup hours, overtime and planning time. A solution is only justified if it consistently beats simple rules like «earliest due date first».
FAQ
How much can they drop?
It depends on your starting point. That’s why it’s measured against a baseline on your own data: the value has to be demonstrable, not promised.
Useful if I already prioritize by due date?
Prioritizing by due date (EDD) is a good start, but it ignores capacity, setups and the cost of each delay. That’s where the gains are.