Procurement Glossary
Capable to Promise (CTP): definition and application in Procurement
November 19, 2025
Capable to Promise (CTP) is an advanced planning process that helps companies to determine realistic delivery dates based on available capacities and materials. In contrast to static availability checks, Capable to Promise dynamically considers the entire supply chain and enables precise delivery date commitments. Find out below what CTP means exactly, which methods are used and how current developments affect purchasing practice.
Key Facts
- CTP combines material availability, production capacities and supplier capacities for realistic deadline commitments
- Differs from ATP through dynamic consideration of future planning changes
- Reduces delivery delays by up to 30% through more precise capacity planning
- Integrates seamlessly into ERP systems and supply chain management solutions
- Enables proactive customer advice through transparent availability information
Contents
Definition: Capable to Promise (CTP)
Capable to Promise extends the classic availability check to include a dynamic capacity assessment along the entire value chain.
Core components of CTP
CTP is based on three essential elements: the material availability check, the production capacity assessment and the supplier capacity analysis. These components are linked together in real time to determine precise delivery dates.
- Dynamic material requirements planning
- Capacity balancing across several production stages
- Integration of supplier availabilities
CTP vs. Available to Promise
While Available to Promise only takes existing stocks into account, CTP includes future production and procurement possibilities. This enables more flexible delivery date commitments, even for products that are not currently available.
Importance of CTP in Procurement
For purchasing organizations, CTP offers decisive advantages for delivery date commitments and capacity planning. By accurately predicting delivery dates, buyers can proactively negotiate with suppliers and identify bottlenecks at an early stage.
Methods and procedures
The implementation of CTP requires structured procedures and proven methods to optimize the use of available data.
Data integration and system connection
Successful CTP implementations are based on the seamless integration of different data sources. Master Production Schedule and supplier data must be synchronized in real time.
- ERP system integration for material master data
- Supplier portal connection for capacity information
- Production planning system coupling
Capacity modeling
Precise modeling of production and supplier capacities is at the heart of effective CTP systems. Capacity is continuously compared with suppliers.
Exception Management
Systematic exception management identifies deviations between planned and actual capacities. Automated alerts enable quick reactions to changes in planning.
Tacto Intelligence
Combines deep procurement knowledge with the most powerful AI agents for strong Procurement.
Important KPIs for CTP
Measuring the success of CTP implementations requires specific metrics that evaluate both accuracy and efficiency.
Date commitment accuracy
The deviation between promised and actual delivery dates is the most important indicator of CTP quality. Schedule deviation analysis should be carried out regularly.
- On-time delivery rate (OTDR)
- Average schedule deviation in days
- Proportion of late deliveries
System performance and response time
CTP calculations must be available within a reasonable time in order to support operational decisions. Planning time windows define the required response times.
Capacity utilization and efficiency
The optimal use of available capacities demonstrates the effectiveness of the CTP system. Safety capacities must be appropriately dimensioned to ensure flexibility.
Risks, dependencies and countermeasures
The implementation and operation of CTP systems entail specific challenges that need to be addressed systematically.
Data quality and system dependencies
Inaccurate or outdated master data can lead to incorrect CTP calculations. Regular parameter maintenance and data validation are essential for reliable results.
- Automated data quality checks
- Redundant data sources for backup
- Regular system audits
Complexity of capacity modeling
Overly complex models can lead to performance problems and results that are difficult to understand. Detailed planning of purchasing capacities requires the right level of detail.
Change management challenges
The introduction of CTP fundamentally changes established planning processes. Employee training and step-by-step implementation minimize resistance and the risk of errors in scheduling.
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Practical example
An automotive supplier implements CTP for the scheduling of customer-specific components. The system integrates material availability, production capacities and supplier capacities in real time. For a customer request for 10,000 units, CTP automatically checks all bottlenecks and suggests the earliest possible delivery date. Thanks to precise planning, on-time delivery has increased from 78% to 94%.
- Automatic determination of material requirements based on parts lists
- Capacity balancing across all production stages
- Integration of supplier availability via EDI
- Continuous monitoring and adjustment of deadlines
Current developments and effects
The further development of CTP systems is significantly influenced by technological innovations and changing market requirements.
AI-supported forecasting models
Artificial intelligence is revolutionizing the accuracy of CTP calculations through machine learning from historical data. Demand sensing enables more precise demand forecasts in real time.
- Predictive analytics for capacity bottlenecks
- Automated parameter adjustment
- Self-learning algorithms for delivery times
Cloud-based CTP solutions
Cloud technologies enable scalable CTP implementations with lower investment costs. This simplifies integration into existing sales and operations planning processes.
Real-Time Supply Chain Visibility
Modern CTP systems offer real-time insights into the entire supply chain. This makes delivery date tracking proactive and enables early corrective measures to be taken in the event of deviations.
Conclusion
Capable to Promise represents a decisive evolutionary step in scheduling, enabling precise delivery date commitments through the integration of capacity and material availability. The technology offers considerable potential for improving delivery reliability and reducing planning uncertainties. However, successful implementations require a clean data basis and systematic change management. As AI integration progresses, CTP is increasingly becoming a strategic competitive advantage for modern purchasing organizations.
FAQ
What distinguishes CTP from conventional availability checks?
CTP not only takes into account current stocks, but also future production and procurement possibilities. This results in more realistic scheduling commitments that take dynamic capacity changes into account and offer better planning reliability.
What data does a CTP system need?
CTP requires material master data, bills of materials, production capacities, supplier capacities, current stocks and planning horizons. Data quality is crucial for precise calculations and should be validated regularly.
How long does the implementation of CTP take?
The implementation period varies between 6-18 months depending on the size of the company and the complexity of the system. Critical success factors are clean master data, clear process definitions and comprehensive employee training for sustainable use.
What cost savings are possible with CTP?
Companies report a 15-25% reduction in stock levels, 20-30% fewer rush orders and 10-15% improvement in delivery reliability. ROI amortization typically occurs within 12-24 months after full implementation.
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