Procurement Glossary
Available to Promise (ATP): definition, methods and application in Procurement
November 19, 2025
Available to Promise (ATP) is a central concept in procurement planning that defines the available quantity of a product or material at a specific point in time. This key figure takes into account orders already received, planned production quantities and stock levels. In Procurement , ATP enables a precise delivery date commitment and optimizes the coordination between demand and availability. Find out below what exactly ATP means, which methods are used and how current developments affect procurement.
Key Facts
- ATP calculates available quantities taking into account existing orders and production plans
- Enables realistic delivery date commitments and reduces shortfalls by up to 30%
- Integrates stock levels, production capacities and quantities already committed
- Supports dynamic adjustments in the event of changes in demand or supply capability
- Forms the basis for effective order prioritization and capacity planning
Contents
Definition: Available to Promise (ATP)
Available to Promise defines the quantity of a product or material that is available for new customer orders at a certain point in time without jeopardizing existing commitments.
Basic components of ATP
The ATP calculation is based on several factors that must be recorded precisely:
- Current stock minus safety stock
- Planned production or delivery quantities
- Quantities already committed from existing orders
- Reserved quantities for priority customers
ATP vs. Capable to Promise (CTP)
While ATP only takes into account available stocks and fixed production plans, Capable to Promise expands the analysis to include additional production capacities. CTP enables more flexible commitments by scheduling unused capacities.
Importance of ATP in Procurement
In the procurement context, ATP supports purchasing planning by providing precise availability information. This enables realistic delivery date commitments and optimizes the coordination between internal requirements and supplier capacities.
Methods and procedures
The implementation of ATP requires structured procedures and suitable calculation methods for precise availability forecasts.
ATP calculation logic
The basic ATP formula is: ATP = Available stock + Planned receipts - Quantities already committed. This calculation is time-based and takes into account dynamic changes in the material availability check.
Time slot-based planning
ATP calculations are carried out in defined planning time windows, which vary depending on product complexity. Short-term time frames allow for more precise commitments, while longer-term planning offers more flexibility.
Integration into ERP systems
Modern ATP systems integrate seamlessly into existing ERP landscapes and enable real-time calculations. Parameter maintenance ensures that the calculation bases and planning parameters are always up to date.
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Important KPIs for ATP
ATP effectiveness is measured using specific key figures that evaluate planning accuracy and delivery capability.
ATP accuracy and forecast quality
ATP accuracy measures the deviation between forecast and actual availability. Values above 95% are considered excellent and indicate high planning quality. This key figure correlates directly with customer satisfaction and delivery reliability.
On-time delivery and reliability of commitments
Adherence to ATP-based delivery date commitments is measured by delivery date adherence. Target values are typically 98% or higher. Deviations indicate weaknesses in scheduling or external disruptive factors.
Inventory optimization and capital commitment
ATP systems reduce superfluous stocks through precise demand forecasts. The key figure "inventory range" should strike an optimal balance between availability and capital commitment. Typical target values vary between 30-90 days' reach, depending on the industry.
Risks, dependencies and countermeasures
ATP systems are susceptible to data quality problems and external disruptions that can lead to incorrect availability forecasts.
Data quality and system integration
Incomplete or outdated data leads to inaccurate ATP calculations and incorrect delivery date commitments. Regular data validation and automated plausibility checks minimize these risks. The schedule deviation analysis helps to identify systematic errors.
Supplier dependencies
ATP calculations are based on supplier commitments that become invalid in the event of failures or delays. Diversified supplier portfolios and continuous delivery date tracking reduce these dependencies.
Planning uncertainty with volatile demand
Fluctuating demand makes precise ATP forecasts difficult and can lead to over- or understocking. Flexible planning approaches and safety capacities create the necessary buffer for unforeseen changes.
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Practical example
An automotive supplier implements ATP for the control of critical electronic components. The system calculates daily available quantities based on current stock levels, planned deliveries and orders that have already been confirmed. When a customer requests more than 1,000 units, ATP automatically checks availability for the desired delivery date. The result shows: 600 units immediately available, another 400 units after planned delivery in 5 days. This transparent information enables realistic delivery date commitments and prevents overselling.
- Automatic availability check in real time
- Consideration of all relevant inventory and planning data
- Precise delivery date commitments without manual inquiries
Current developments and effects
Digitalization and the use of artificial intelligence are revolutionizing ATP systems and enabling more precise availability forecasts in complex supply chains.
AI-supported ATP optimization
Artificial intelligence improves ATP calculations through machine learning and pattern recognition. Demand sensing enables early detection of changes in demand and automatic adjustment of availability forecasts.
Real-time ATP and cloud integration
Cloud-based ATP solutions enable real-time calculations across multiple locations. This development supports global supply chains and significantly improves responsiveness to market changes.
Predictive analytics for availability
Advanced analysis methods forecast future availability based on historical data and external factors. This enables proactive measures in exception management and significantly reduces delivery risks.
Conclusion
Available to Promise is an indispensable tool for modern procurement organizations, enabling precise availability forecasts and realistic delivery date commitments. The integration of AI technologies and real-time data processing significantly increases planning accuracy and reduces delivery risks. However, successful ATP implementations require high-quality data and continuous system optimization. Companies that use ATP strategically benefit from improved customer satisfaction, optimized inventories and increased competitiveness in dynamic markets.
FAQ
What is the difference between ATP and stock?
ATP not only takes into account the current stock level, but also quantities already committed, planned receipts and safety stock. While the stock level is a static snapshot, ATP shows the actual quantity available for new orders, taking all commitments into account.
How often should ATP calculations be updated?
The update frequency depends on product complexity and demand dynamics. Critical components require real-time calculations, while standard products get by with daily updates. Modern systems enable event-driven recalculations in the event of relevant changes in stock or orders.
What data is required for precise ATP calculations?
Current stock levels, existing customer orders, production plans, delivery dates and safety stocks are essential. In addition, quality data, supplier performance and historical demand patterns improve the accuracy of the calculation. Data quality is a key factor in determining ATP reliability.
How does ATP affect customer satisfaction?
ATP enables realistic delivery date commitments and significantly reduces delivery delays. Customers receive reliable information about availability and can adjust their planning accordingly. This leads to greater customer satisfaction and strengthens long-term business relationships through improved delivery reliability.
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