Materials Planning & Forecasting for Spare Parts Management – Barcelona (Spain), 11–15 Oct 2027

Course Description

This intensive 1-week course focuses on advanced materials planning and forecasting techniques for effective spare parts management. Participants will learn to optimize inventory levels, reduce costs, and improve service levels using cutting-edge methodologies and best practices in demand forecasting, inventory classification, and supply chain management.

Learning Objectives

• Master advanced demand forecasting techniques for intermittent and erratic demand patterns
• Develop effective inventory classification and management strategies for spare parts
• Implement best practices in materials planning and supply chain optimization
• Utilize data analytics and machine learning for improved decision-making
• Enhance service levels while minimizing inventory costs

Course Modules

Day 1: Foundations of Spare Parts Management

• Introduction to spare parts management challenges
• Demand patterns and characteristics of spare parts
• Inventory classification methods (ABC, XYZ, VED)
• Key performance indicators for spare parts management

Day 2: Advanced Demand Forecasting Techniques

• Time series analysis and causal models
• Intermittent demand forecasting (Croston's method, Bootstrap method)
• Machine learning approaches for demand prediction
• Forecast accuracy measurement and improvement

Day 3: Inventory Optimization Strategies

• Safety stock calculation methods
• Reorder point and order quantity determination
• Multi-echelon inventory optimization
• Slow-moving and obsolete inventory management

Day 4: Materials Planning and Supply Chain Management

• Materials Requirements Planning (MRP) for spare parts
• Vendor-managed inventory and collaborative planning
• Risk management in spare parts supply chains
• Lean and agile strategies for spare parts management

Day 5: Implementation and Continuous Improvement

• Data analytics and business intelligence tools
• Integration of forecasting and planning systems
• Performance monitoring and continuous improvement
• Case studies and best practices in spare parts management

Practical Wins for Participants

• Reduce inventory costs by 15-25% through improved forecasting and optimization
• Increase service levels by 5-10% with enhanced materials planning strategies
• Implement data-driven decision-making processes for spare parts management
• Develop a roadmap for continuous improvement in inventory management