Procurement Glossary
Production control: definition, methods and importance in Procurement
November 19, 2025
Production control is a central component of operational corporate management that encompasses the coordination and monitoring of all production-relevant processes. In Procurement , it plays a decisive role in ensuring the availability of materials and optimizing supply chains. Find out below what production control means, which methods are used and how it influences the procurement process.
Key Facts
- Production control coordinates material, capacity and scheduling planning to optimize production processes
- It encompasses both operational management and strategic planning aspects of production
- Modern systems use real-time data and AI-based algorithms for precise predictions
- Integration with purchasing processes enables proactive supplier management and inventory optimization
- Effective production control reduces throughput times by up to 30% and significantly lowers storage costs
Contents
Definition: Production control
Production control refers to the systematic planning, coordination and monitoring of all production-related activities to achieve defined performance targets.
Core elements of production control
Production control comprises several central components that are closely interlinked:
- Capacity planning: coordination of available resources with production requirements
- Material requirements planning: determining and securing the required raw materials and components
- Scheduling: coordination of production and delivery dates
- Quality control: monitoring and ensuring product quality
Production control vs. production planning
While production planning makes strategic and tactical decisions for longer periods of time, production control focuses on operational implementation and short-term adjustments. Scheduling forms the interface between the two areas.
Importance of production control in Procurement
In the procurement context, effective production control enables precise forecasting of material requirements and optimizes collaboration with suppliers. It supports purchasing planning with reliable demand forecasts and contributes to purchasing optimization.
Methods and procedures for production control systems
Modern production control relies on proven methods and innovative technologies to optimize manufacturing processes.
Push and pull principles
Production control distinguishes between push and pull systems. Push systems are based on forecasts and push material through production, while pull systems are demand-driven. Demand sensing supports both approaches by precisely detecting demand.
MRP and Advanced Planning Systems
Material Requirements Planning (MRP) forms the foundation of modern production control. Advanced Planning Systems extend this functionality:
- Simultaneous capacity and material planning
- Optimization algorithms for complex production structures
- Integration of supplier data and capacities
Digital control methods
Digital technologies are revolutionizing production control through real-time data analysis and automated decision-making. Exception management automatically identifies deviations and initiates corrective measures.
Tacto Intelligence
Combines deep procurement knowledge with the most powerful AI agents for strong Procurement.
Key figures for controlling
Effective production control requires the continuous monitoring of relevant performance indicators to evaluate and optimize processes.
Efficiency and productivity indicators
Key performance indicators measure the operational performance of production control:
- Overall Equipment Effectiveness (OEE): Overall equipment effectiveness
- Lead time: Time from order entry to completion
- Capacity utilization: ratio of used to available capacity
- First-pass yield: proportion of faultless products in the first run
Planning accuracy and adherence to deadlines
The quality of production control is reflected in planning accuracy. Important indicators are adherence to delivery dates, deviations from plan and forecast accuracy. The schedule deviation analysis identifies systematic weaknesses.
Cost and inventory key figures
Financial key figures evaluate the economic efficiency of the control system. These include inventory turnover, inventory range and production costs per unit. These metrics support strategic alignment and reveal optimization potential.
Risks, dependencies and countermeasures
Production control involves various risks that can be minimized by taking appropriate measures.
Planning risks and forecast uncertainties
Inaccurate demand forecasts lead to over- or underproduction with corresponding costs. Volatile markets exacerbate this problem. Countermeasures include robust forecast management systems and flexible production capacities.
System failures and data quality
IT system failures can paralyze the entire production control system. Incomplete or incorrect data leads to suboptimal decisions. Redundant systems, regular data validation and manual backup processes significantly reduce these risks.
Supplier dependencies
Strong dependencies on individual suppliers jeopardize production continuity. Delivery failures or quality problems can affect the entire control system. A diversified supplier base, security capacities and alternative procurement sources minimize these dependencies.
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Practical example
An automotive supplier implements an integrated production control system to optimize its manufacturing processes. The system links customer requirements with production capacities and supplier data in real time. Thanks to automated demand determination and dynamic capacity planning, the company reduces throughput times by 25% and stock levels by 30%. The integration of supplier data enables proactive procurement and prevents production downtimes.
- Real-time integration of customer, production and supplier data
- Automated determination of demand and capacity matching
- Proactive supplier management to avoid bottlenecks
Current developments and effects
Production control is undergoing a fundamental change due to new technologies and changing market requirements.
AI-supported production control
Artificial intelligence is transforming production control through machine learning and predictive analytics. AI systems analyse historical data, recognize patterns and automatically optimize production parameters. This leads to more precise forecasts and reduced planning errors.
Industry 4.0 and IoT integration
The networking of production systems enables granular real-time control. IoT sensors continuously provide data on machine statuses, material flows and quality parameters. This transparency supports delivery date tracking and improves the ability to respond to disruptions.
Sustainability integration
Modern production control increasingly takes sustainability criteria into account. Energy efficiency, CO2 footprint and resource conservation are integrated as optimization parameters. This also influences supplier selection and supports process optimization in Procurement.
Conclusion
Production control is a critical success factor for operational excellence and competitiveness. The integration of modern technologies such as AI and IoT opens up new opportunities for increasing efficiency and optimizing costs. Companies that strategically develop their production management and dovetail it closely with Procurement create sustainable competitive advantages. Continuous adaptation to changing market requirements remains crucial for long-term success.
FAQ
What is the difference between production planning and production control?
Production planning deals with strategic and tactical decisions for longer periods of time, while production control focuses on operational implementation and short-term adjustments in day-to-day business. Control translates the plans into concrete actions and reacts to deviations.
What role does production control play in Procurement?
Production control provides precise demand forecasts and deadlines for Procurement. It enables needs-based procurement, reduces storage costs and improves supplier coordination. The integration of production and procurement data creates synergies along the entire value chain.
How do companies measure the success of their production control?
Success is measured by key performance indicators such as on-time delivery, throughput times, capacity utilization and planning accuracy. Other important indicators are inventory turnover, production costs and overall equipment effectiveness (OEE). These metrics show operational efficiency and optimization potential.
Which technologies are shaping modern production control?
Modern systems use AI and machine learning for predictive analytics, IoT sensors for real-time data and cloud computing for scalable computing power. Advanced planning systems integrate complex optimization algorithms, while digital twins enable virtual production simulations.
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