The Predictive Data Analytics for Supply Chain Performance course in Amsterdam equips professionals with the skills to leverage data analytics for forecasting and optimizing supply chain performance.
From:
23-02-2026
From:
11-05-2026
Course Overview
Supply chains generate massive amounts of data, and organizations that leverage predictive analytics gain a competitive edge. Predictive models help anticipate demand shifts, reduce risks, optimize inventory, and improve overall performance.
This Predictive Data Analytics for Supply Chain Performance Training Course introduces participants to advanced analytics methods, including forecasting models, machine learning applications, and scenario simulations. Participants will learn how to translate data into actionable insights that drive efficiency, resilience, and profitability.
Through interactive workshops, case studies, and real-world simulations, participants will apply predictive tools to improve supply chain agility and strategic planning.
Course Benefits
Anticipate demand and supply fluctuations with predictive tools.
Optimize inventory and resource allocation.
Strengthen decision-making with data-driven insights.
Reduce risks by forecasting disruptions and bottlenecks.
Enhance overall supply chain visibility and resilience.
Course Objectives
Understand predictive analytics concepts in supply chains.
Apply forecasting models for demand and supply planning.
Leverage machine learning for predictive insights.
Use scenario simulations for risk and resilience planning.
Align predictive analytics with supply chain strategies.
Build dashboards and visualizations for decision support.
Develop a roadmap for implementing predictive analytics.
Training Methodology
The course uses a mix of lectures, hands-on exercises with analytics tools, case studies, and simulations. Participants will engage in predictive modeling workshops and real-time data analysis activities.
Target Audience
Supply chain and logistics managers.
Data and business analysts.
Procurement and operations managers.
Executives driving digital supply chain transformation.
Target Competencies
Predictive data analytics.
Forecasting and demand planning.
Machine learning applications in supply chains.
Risk and resilience modeling.
Course Outline
Unit 1: Introduction to Predictive Analytics in Supply Chains
Role of predictive analytics in modern supply chains.
Key differences between descriptive, diagnostic, and predictive analytics.
Benefits and challenges of predictive applications.
Case examples of predictive analytics success.
Unit 2: Forecasting Demand and Supply
Fundamentals of forecasting models.
Time series analysis and regression.
Using historical data to anticipate trends.
Practical exercise: demand forecast simulation.
Unit 3: Machine Learning for Supply Chain Performance
Applying machine learning algorithms for prediction.
Use cases: supplier risk, lead time variability, and inventory optimization.
Data requirements and preparation for ML models.
Ethical considerations in AI-driven supply chains.
Unit 4: Risk and Resilience Analytics
Identifying risks with predictive modeling.
Scenario planning for disruptions and delays.
Simulating supply chain resilience strategies.
Case study: predictive risk mitigation.
Unit 5: Predictive Inventory and Resource Optimization
Linking predictive analytics with inventory control.
Reducing excess stock and preventing shortages.
Optimizing resource allocation with data insights.
Workshop: predictive inventory modeling.
Unit 6: Building Dashboards and Visualization Tools
Designing dashboards for predictive KPIs.
Real-time data visualization for decision-making.
Integrating predictive analytics into ERP/SCM platforms.
Hands-on activity: building a performance dashboard.
Unit 7: Future of Predictive Supply Chain Analytics
Emerging trends in AI, IoT, and big data.
Predictive analytics in circular and sustainable supply chains.
Scaling predictive analytics across global operations.
Roadmap for continuous improvement.
Ready to future-proof your supply chain?
Join the Predictive Data Analytics for Supply Chain Performance Training Course with EuroQuest International Training and lead with data-driven foresight.
The Predictive Data Analytics for Supply Chain Performance Training Courses in Amsterdam provide professionals with advanced analytical capabilities to forecast trends, anticipate disruptions, and optimize supply chain operations through data-driven insights. Designed for supply chain managers, data analysts, and logistics professionals, these programs bridge the gap between analytical modeling and strategic supply chain decision-making.
Participants gain an in-depth understanding of predictive analytics and its application to supply chain management. The courses cover techniques such as demand forecasting, regression analysis, machine learning models, and scenario planning—demonstrating how predictive tools enhance accuracy in planning and resource allocation. Through hands-on exercises and case studies, participants learn to interpret large datasets, identify performance patterns, and use analytics platforms to optimize procurement, production, and distribution decisions.
These supply chain analytics training programs in Amsterdam blend theoretical insight with practical application, focusing on how organizations can leverage predictive models to improve resilience, reduce costs, and enhance service reliability. The curriculum emphasizes the integration of technology and data intelligence into traditional supply chain systems, showcasing how predictive analysis supports risk management, capacity planning, and performance benchmarking across complex supply networks.
Attending these training courses in Amsterdam offers professionals the opportunity to collaborate with international experts and peers in one of Europe’s leading innovation and logistics hubs. The city’s dynamic business environment and strong emphasis on data-driven innovation create an ideal setting for mastering analytics in supply chain management. By completing this specialization, participants will be equipped to implement predictive analytics tools that transform operational efficiency, strengthen decision-making, and drive continuous improvement—enabling their organizations to stay competitive in a rapidly evolving global marketplace.