ATP Netting

The core calculation follows a strict time-phased sequence: Projected Available Balance (PAB) = Prior Period PAB + Scheduled Receipts - Gross Demand. This equation runs bucket-by-bucket across the ATP Horizon. If PAB drops below zero, the system flags a potential stockout. The calculation respects the Demand Time Fence (DTF) , where actual orders consume the forecast, preventing double-counting of requirements.

Netting logic aggregates data into discrete time buckets. Supply includes:

• On-hand inventory
• Open purchase orders (In-Transit Inventory)
• Firm planned production orders
• Safety Stock (treated as untouchable demand)

Demand includes:

• Sales orders (hard demand)
• Forecast (soft demand, consumed inside the DTF)
• Inter-plant transfers
• Safety stock requirements

Two distinct methodologies exist:

Periodic Netting: Calculates PAB strictly within a single time bucket. Excess supply in one period does not automatically cover a shortage in the next.

Cumulative ATP: Sums available supply across multiple periods. A large order can be promised against the total supply available over a future timeframe, enabling bulk order commitments without splitting. This is critical for Global ATP checks across a network.

Netting is intrinsically linked to pegging. Demand Pegging traces a specific supply receipt (e.g., a PO) to the exact sales order consuming it. Supply Pegging performs the reverse, linking a customer order to its fulfilling supply elements. This bidirectional traceability enables impact analysis: if a supplier delays a shipment, the system instantly identifies every customer order at risk, triggering Backorder Processing or re-promising workflows.

Basic netting assumes infinite capacity. Constraint-Based ATP extends the logic by feeding the netting output into a constraint solver that simultaneously evaluates:

• Material availability (from netting)
• Finite Capacity Scheduling of work centers
• Transportation lane capacities

If a resource bottleneck is detected, the solver iteratively adjusts the promise date. This contrasts with Rule-Based ATP, which applies a static sequence of sourcing rules without dynamic capacity validation.

The netting calculation is not a static batch job. Modern Order Promising Engines re-execute netting in real-time when:

• A new sales order is placed
• A purchase order receipt is confirmed
• A production order is completed or delayed
• Safety Lead Time buffers are consumed

This continuous re-netting ensures the Projected Available Balance always reflects the current state, enabling accurate Order Reservation and preventing overselling.