Available-to-Promise (ATP)
Available-to-Promise (ATP) is the availability check inside an ERP system that answers, in real time, how much of an item can be firmly committed for a given date. It looks past what is physically on the shelf: planned receipts count toward availability, and quantities already promised to other orders count against it. The output is the number a salesperson can state without checking with anyone.
The calculation
Conceptually ATP is a running balance across a time axis. On the plus side sit physical on-hand stock and planned receipts — open purchase orders, production orders, inbound transfers. On the minus side sit commitments: sales orders already confirmed, reservations, allocations. What remains in each time bucket is promisable without breaking an existing commitment.
Two variants exist and behave differently. Discrete ATP evaluates each period separately, so a shortage in week two cannot be covered by surplus in week three. Cumulative ATP carries surplus forward, which produces friendlier dates and is less conservative. Which one your system uses is a configuration decision that quietly determines how often you disappoint customers.
ATP, CTP and the difference that matters
ATP asks whether the goods exist or are already scheduled to exist. Capable-to-Promise (CTP) goes further: if the stock is not there, could we make it, given free capacity and available materials? CTP therefore reaches into capacity planning and is substantially more computation-intensive, which is why it typically lives in APS systems rather than in core order entry.
For a distributor, ATP is usually enough. For a make-to-order manufacturer, ATP alone answers the wrong question — the honest response to "when can I have it" depends on the shop floor, not the warehouse. Companies that promise from ATP while producing to order are the ones whose promised dates and actual ship dates diverge systematically.
Where it sits in the process
The check runs at order entry, which is the point where a promise becomes expensive to break. Done well, it prevents the pattern where sales commits, production discovers the conflict, and someone calls the customer back. Done badly — stale data, optimistic supplier dates, no allocation logic — it produces confident promises that are wrong, which is worse than no promise at all.
Most enterprise and mid-market systems ship rule-based ATP with backorder handling: SAP S/4HANA with advanced ATP, NetSuite, Dynamics 365 Supply Chain Management, and the distribution-focused systems where availability accuracy is the product. Depth varies considerably at the edges — multi-site sourcing, substitution rules, allocation by customer tier — and those edges are where evaluation should focus.