# Capable-to-Promise > Site directory and reading guidance: [llms.txt](https://wiki.skusavvy.com/llms.txt). Canonical URL: https://wiki.skusavvy.com/article/capable-to-promise Published: 2026-11-08T00:04:30.499Z Last updated: 2026-11-08T00:30:39.942Z Category: Supply Chain > This article is AI-assisted reference material. Verify important or time-sensitive claims against the cited sources; AI review does not establish independent factual verification. ## Overview **Capable-to-promise (CTP)** is an order-promising method that estimates whether, and when, a customer order can be fulfilled by considering the resources needed to make or obtain the product. Depending on the implementation, the assessment can include component availability, production capacity, supplier lead times, and distribution constraints. Its purpose is to produce a feasible commitment rather than a date based solely on finished-goods inventory. CTP is related to, but broader than, [available-to-promise (ATP)](https://learn.microsoft.com/en-us/dynamics365/supply-chain/sales-marketing/delivery-dates-available-promise-calculations), which generally evaluates uncommitted inventory and planned supply. The [ASCM supply chain dictionary](https://www.ascm.org/learning-development/certifications-credentials/dictionary/) defines CTP as the process of committing orders against available capacity as well as inventory. In some manufacturing systems, including [Microsoft Dynamics 365 Supply Chain Management](https://learn.microsoft.com/en-us/dynamics365/supply-chain/master-planning/capable-to-promise), CTP can create planned production or purchase orders for unmet demand during order entry. Actual definitions and calculations vary by software and business policy. Reliable [inventory visibility](https://www.skusavvy.com/features/inventory-visibility) is an important input, but inventory data alone does not establish production capability. ## Origins of the Term The name combines **capable**, referring to the ability to supply or produce through manufacturing or procurement, with **promise**, the commitment offered to a customer. The abbreviation CTP distinguishes this capacity-aware assessment from ATP terminology. The underlying idea—that an order should be accepted only against resources that can actually be made available—developed with production planning and master scheduling. [Material requirements planning (MRP)](https://www.ibm.com/think/topics/material-requirements-planning) provided a systematic way to calculate time-phased material needs, while later Advanced Planning and Scheduling (APS) systems extended planning to finite capacity and material constraints together. [Academic work on order promising](https://doi.org/10.1016/S0925-5273(01)00188-7) treats CTP as a finite-capacity extension of ATP. The explicit term became common in APS and ERP discussions during the 1990s; vendor marketing often contrasted real-time, resource-constrained promising with batch ATP, but the precise date of first commercial use is not settled in the public literature. ## Historical Development - **Before computerized planning:** Manufacturers used manual schedules, stock records, paper bills of materials, and planner judgment to quote order lead times. As product structures and order volumes grew, those methods often overloaded shops and missed dates. This description is contextual rather than tied to a single documented event. - **1960s–1970s:** Computerized MRP translated master-schedule requirements into time-phased material needs. Joseph Orlicky’s 1975 book *Material Requirements Planning: The New Way of Life in Production and Inventory Management* (McGraw-Hill) was an influential statement of the method. Classic MRP improved material planning but generally treated capacity as unlimited at the explosion step; capacity was checked separately. See IBM’s [MRP overview](https://www.ibm.com/think/topics/material-requirements-planning). - **1980s–1990s:** Manufacturing Resource Planning (MRP II), associated with Oliver Wight and widely adopted in the 1980s, and Enterprise Resource Planning (ERP), a label popularized in the 1990s, integrated production, inventory, rough-cut capacity planning, and financial data more broadly. During the 1990s, commercial APS products made finite-capacity scheduling and multi-site supply evaluation practical for order promising. The [advanced planning literature](https://doi.org/10.1007/978-3-642-55309-7) describes the optimization and heuristic methods used in those systems; it does not by itself establish when CTP first became computationally routine. - **2000s onward:** Order-management and omnichannel systems extended promising across multi-echelon networks, connecting bills of materials, purchasing lead times, and fulfillment constraints where the software supports those checks. [SkuSavvy’s inventory-sync documentation](https://www.skusavvy.com/docs/guides/shopify/inventory-sync) describes synchronization of inventory across sales channels. That stock layer can feed a promise calculation, but it is not itself a finite-capacity CTP engine. ## Core Concepts ### Inputs and Feasibility A CTP calculation starts with the requested item or configuration, quantity, destination, and requested delivery date. It then evaluates eligible supply and the activities needed to complete the order. Typical inputs include: - Uncommitted finished goods and scheduled receipts, by location and date. - Bills of materials (BOMs), component quantities, approved substitutes, and supplier lead times. - Routings, work-center calendars, setups, tooling, and available labor, where manufacturing capacity is in scope. - Existing orders, reservations, allocation rules, and planning priorities. - Warehouse processing time, packing throughput, shipping cutoffs, and transit times, when the promise includes dispatch or delivery. Time-phased calculations must account for existing commitments rather than adding all future supply to current stock. How receipts, demand, and delivery dates are treated varies by system; Microsoft’s [delivery-date calculation documentation](https://learn.microsoft.com/en-us/dynamics365/supply-chain/sales-marketing/delivery-dates-available-promise-calculations) illustrates those policy choices, and its [CTP documentation](https://learn.microsoft.com/en-us/dynamics365/supply-chain/master-planning/capable-to-promise) describes one manufacturing implementation. In distribution or light assembly, [warehouse kitting workflows](https://www.skusavvy.com/docs/guides/warehouse/kitting) affect staging time for kits. Accurate [inventory reconciliation](https://www.skusavvy.com/docs/guides/warehouse/inventory-reconciliation) reduces the risk that a calculation relies on incorrect on-hand quantities. ### Calculation and Commitment Implementations differ, but a common CTP sequence is: 1. **ATP check:** Determine whether uncommitted finished goods, and sometimes scheduled receipts, can cover the quantity by the requested date. 2. **Material feasibility:** If there is a shortfall, explode the relevant BOM and test whether components are on hand, already scheduled, or procurable inside the planning horizon. 3. **Capacity check:** Place required operations on resource calendars without exceeding the modeled capacity, using forward scheduling from a start point, backward scheduling from a due date, or a mix defined by the planner. 4. **Promise synthesis:** Return the earliest feasible completion, ship, or delivery date—depending on what the business has defined as the promise—or alternatives such as a partial quantity or another site. A quoted date is not automatically a reservation. Policy must state when components and capacity are only tentatively held and when they become firm allocations. **Illustrative example (not a universal rule):** A customer requests 100 pumps for Friday. Forty uncommitted finished units are on hand. Components for the other 60 are expected Wednesday, and the routing needs eight hours on one bench that is open on Thursday. If packing and transit together take one day, Friday can be feasible only if both the stock and the new production are reserved and the transit assumption holds. If transit takes two days or the bench is already loaded, the feasible date moves later. Real systems also have to model yields, changeovers, calendars, and competing orders. ## Types and Related Methods - **ATP (available-to-promise):** Commits against existing or planned supply, especially for make-to-stock items. Scope and netting rules differ by product. - **CTP (capable-to-promise):** Extends promising to the materials and capacity required to create additional supply. It is most relevant for make-to-order and assemble-to-order products, and for make-to-stock items when new production must be scheduled. - **Profitable-to-promise (sometimes abbreviated PTP):** A less standardized extension that weighs margin, expediting cost, overtime, or penalties before accepting a date. It is discussed in planning literature and vendor material, but it is not a single industry standard. - **Finite-capacity scheduling:** Places work into resource time buckets without exceeding modeled capacity. CTP uses this kind of check when capacity, not only materials, limits the promise. - **Static lead-time quoting:** Adds a catalog lead time to the order date. It is simple but ignores current bottlenecks and load. A platform can show [available inventory](https://www.skusavvy.com/features/inventory-visibility) without modeling production lines. Where a capacity plan does exist, execution still depends on [order-management processes](https://www.skusavvy.com/order-management-system) that reserve stock, release work, and prevent the same supply from being promised twice. ## Industry Applications and Intended Benefits CTP is used where the sellable item is configured, assembled, or produced to order, including capital equipment, electronics, contract packaging, and custom goods. Public sources do not support a single market-share figure. Typical uses include: - **Configurable products:** Checking whether selected options, long-lead components, and constrained operations can meet a quoted date. - **Light assembly and kitting:** Comparing component balances and kit-build time with the requested ship date. Component replenishment discussed in [supply chain planning strategies](https://www.skusavvy.com/blog/supply-chain-planning-strategies) is an input to that check, not a substitute for finite scheduling. - **Contract packaging:** Testing changeover time and packaging-material availability before accepting a rush order. Reported aims include higher promise reliability, less dependence on finished-goods safety stock, and fewer date changes after the order is accepted. Those outcomes depend on data quality and on whether the promise is actually reserved. [Purchase-order management](https://www.skusavvy.com/purchase-order-management) and [warehouse fulfillment workflows](https://www.skusavvy.com/docs/guides/warehouse/order-fulfillment) support buying and shipping the goods; they do not, by themselves, perform cross-plant finite-capacity CTP. ## Challenges and Practices 1. **Define the promise.** State whether the date means production completion, warehouse dispatch, or customer delivery, and whether split shipments are allowed. 2. **Keep master data current.** Wrong BOMs, routings, yields, or supplier lead times make an otherwise correct algorithm promise an infeasible date. Physical checks such as cycle counting support the inventory side of that data. 3. **Model the real constraints.** Detailed finite scheduling is most useful on bottleneck resources and long-lead components. Modeling every minor operation can slow quoting without improving the date. 4. **Handle concurrent quotes.** Two users can otherwise be offered the same capacity or component lot. Temporary holds with expiration limits are a common control; the timeout itself is a business rule, not a universal standard. 5. **Measure attainment.** Compare promised and actual dates and separate causes such as supplier delay, downtime, and warehouse delay. [Order-tracking workflows](https://www.skusavvy.com/docs/guides/orders/order-tracking) can show execution status after the promise; they do not recalculate capacity. 6. **Replan when facts change.** Shortages, breakdowns, and inserted orders can invalidate earlier commitments. Escalation rules should say who may re-promise and how released capacity is reallocated. ## Source links - [Delivery date control and available-to-promise calculations]() - [SkuSavvy Inventory Visibility]() - [ASCM Supply Chain Dictionary]() - [What is Material Requirements Planning?]() - [Supply Chain Management and Advanced Planning]() - [SkuSavvy Shopify Inventory Sync]() - [SkuSavvy Inventory Reconciliation]() - [SkuSavvy Order Management System]() - [SkuSavvy Purchase Order Management]() - [SkuSavvy Order Fulfillment Guide]() - [SkuSavvy Order Tracking Guide]() - [Order Promising in Supply Chain Management: An Advanced Planning Perspective]() - [SkuSavvy Warehouse Kitting Guide]() - [SkuSavvy Supply Chain Planning Strategies]() - [Capable to promise (CTP) - Dynamics 365 Supply Chain Management]()