Available-to-Promise (ATP)

The foundational calculation that subtracts gross demand (sales orders, reservations) from scheduled receipts (purchase orders, production runs) and on-hand inventory to compute a projected available balance. This netting logic runs synchronously during order entry to provide an immediate, date-specific promise without creating a stockout. The calculation respects the Demand Time Fence (DTF), where actual orders fully consume the forecast.

A Global ATP capability that searches for availability across a network of plants, distribution centers, and in-transit inventory. The search follows configurable sourcing rules that dictate the sequence of supply locations to evaluate. Multi-sourcing optimization evaluates all possible combinations to minimize total landed cost. The system can also traverse the supersession chain to automatically substitute discontinued items with their defined replacements.

Advanced ATP systems extend beyond material availability to evaluate capacity and transportation constraints simultaneously. Constraint-Based ATP uses a constraint solver to generate a feasible delivery date that respects finite capacity scheduling limits on work centers, labor, and tooling. This prevents over-promising against a bottleneck resource and ensures the committed date is executable on the factory floor.

The system enforces allocation management policies that reserve inventory for specific customers, channels, or product segments before the ATP check runs. During order entry, order reservation creates a hard or soft link between a specific quantity of supply and the customer demand, guaranteeing availability. Rule-Based ATP applies configurable business rules—such as customer hierarchies or sourcing priorities—to determine how constrained supply is allocated.

When an order cannot be fully promised from a single location by the requested date, the system triggers backorder processing workflows. This includes order splitting, which divides a single order line into multiple shipments from different locations or at different times to optimize fulfillment speed. The system automatically re-promises backordered quantities as new supply becomes available, maintaining a prioritized queue of unfulfilled demand.

An ATP Simulation environment allows planners to test hypothetical supply or demand changes without affecting live commitments. Planners can model scenarios such as a delayed purchase order, a surge in demand, or a plant shutdown to assess the impact on order promising outcomes. This capability supports proactive risk management and enables data-driven decisions before changes are committed to the operational system.

Extends ATP beyond on-hand inventory to evaluate production capacity and material availability. CTP determines if a product can be manufactured and delivered by a requested date, creating a feasible production schedule in real-time. - Key Check: Bill of materials explosion and routing analysis - Use Case: Make-to-order environments where finished goods are not stocked - Benefit: Prevents overpromising when inventory is zero but production is possible

Evaluates the financial viability of an order before committing inventory. PTP balances fulfillment costs, margin, and customer lifetime value to accept or reject orders dynamically. - Key Inputs: Cost-to-serve model, freight rates, payment terms - Decision Logic: Accept, re-price, or propose alternative fulfillment - Outcome: Protects margin in low-inventory, high-demand scenarios

The process of linking a specific supply receipt (purchase order, production run) to a specific customer order. This creates end-to-end traceability for impact analysis. - Forward Pegging: Tracks where supply is allocated - Backward Pegging: Identifies which supply fulfills a demand - Critical For: Assessing the blast radius of a supply disruption

Searches for availability across a network of multiple plants and distribution centers to find the optimal fulfillment location. Global ATP evaluates sourcing rules, transportation costs, and lead times simultaneously. - Capability: Multi-site inventory visibility in a single check - Optimization: Minimizes total landed cost or delivery time - Enables: Omnichannel scenarios like ship-from-store

An advanced promising method using a constraint solver to simultaneously evaluate material, capacity, and transportation limitations. Unlike rule-based approaches, it finds a globally feasible solution. - Variables: Machine throughput, labor shifts, carrier capacity - Output: A realistic, executable delivery date - Differentiator: Avoids sequential bottleneck failures

The core calculation that subtracts gross demand requirements from scheduled receipts and on-hand inventory to compute the projected available balance. - Formula: Projected Available = Prior Period Available + Scheduled Receipts - Gross Requirements - Time Buckets: Calculated daily or weekly over the ATP horizon - Variants: Discrete ATP vs. Cumulative ATP for large order evaluation