ATP (Available-to-Promise): A beginner's guide

Available-to-Promise (ATP) is a practical, customer-facing tool used by retailers, distributors, and manufacturers to answer a simple but critical question: "If a customer orders X units today, when can we deliver them?" At its heart, ATP calculates what stock is free to promise — taking into account on-hand inventory, reserved quantities, incoming replenishment, and other commitments — so businesses can provide accurate delivery dates and avoid overpromising.

This beginner-friendly overview explains how ATP works, why it matters, and a clear, real-world example to make the concept tangible.

How ATP works — the basics

• Core data inputs: ATP relies on three primary data elements: current on-hand inventory, outstanding customer commitments or reservations, and expected receipts (purchase orders, inbound transfers, or production orders) with their estimated arrival dates.
• Promise calculation: When a new order is entered, the ATP calculation compares requested quantity to the net available inventory over time. If enough uncommitted stock exists today, ATP assigns the order to current inventory and promises immediate or near-term delivery. If not, ATP checks future receipts and computes the earliest date by which enough stock will be available to fulfill the order.
• Rules and constraints: ATP is governed by business rules — for example, some inventory may be blocked (quality hold), certain channels may have priority allocations, or minimum order quantities and lot sizes may affect what can be promised.

Why ATP matters

• Improved customer experience: Accurate promised delivery dates increase trust, reduce cancellations, and lower the rate of disappointed customers.
• Reduced manual effort: ATP automates the hardest part of order promising, replacing time-consuming phone calls and manual calculations with real-time responses.
• Fewer stockouts and oversells: ATP helps prevent committing inventory that’s already spoken for, reducing backorders and the scramble to expedite replacements.
• Better sales-operations coordination: Sales teams can confidently quote dates that operations can meet, lowering friction between departments.

Simple example

Imagine an e-commerce seller has 10 units of Product A in their warehouse. Two online orders were previously accepted and allocated 6 units in total, leaving 4 units unallocated (on-hand minus reservations). A new customer orders 5 units. ATP checks available inventory and sees only 4 units free today. It then looks at incoming receipts: a replenishment of 20 units is scheduled to arrive in 3 days. Based on that, ATP will promise a shipment in 3 days (or it may promise 4 units immediate and 1 unit later if partial shipments are allowed). The system might also reflect rules such as priority customers who get immediate allocation.

Variants and related concepts

• Hard ATP vs soft ATP: Hard ATP enforces physical constraints strictly (no promise if inventory is reserved), while soft ATP may consider planned production or flexible allocations.
• Capable-to-Promise (CTP): an advanced version of ATP that considers production capacity and scheduling, not just inventory and receipts. For make-to-order products, CTP is more relevant.

How ATP integrates with systems

ATP is commonly implemented within/WMS (Warehouse Management System), ERP (Enterprise Resource Planning), or specialized order promising engines. Integration points include inventory master data, incoming order streams, purchase order information, and delivery scheduling. Real-time or near-real-time inventory visibility makes ATP most effective — manual or stale inventory counts lead to incorrect promises.

Practical tips for beginners

• Start small: Implement ATP for a subset of SKU families (e.g., high-value or fast-moving items) to build confidence and processes.
• Keep data clean: Accurate on-hand numbers and timely receipts are essential. Frequent cycle counts and good inbound processing help ATP be reliable.
• Define clear rules: Determine whether partial shipments are acceptable, how to handle backorders, and if special customers get allocation priority.
• Communicate transparently: If a promised date relies on future receipts, show that date to customers and provide status updates.

Limitations and caution

ATP is only as good as the data and rules behind it. Common limitations include variable supplier lead times, unreported damages, and complex allocation policies that may not be fully modeled. For products built-to-order or with long production lead times, consider CTP or integrate production schedules into the promise logic.

Final thought



For beginners, think of ATP as the company’s honest availability calculator: it mathematically balances what you have, what you’ve promised, and what’s coming in, to give a realistic delivery commitment to customers. When implemented with good data and simple rules, ATP can dramatically improve customer satisfaction and operational smoothness.