The Predictive Analytics & Demand Forecasting in Logistics course in Geneva is a specialized training course designed to help professionals use data-driven strategies to optimize logistics operations and forecast demand.
From:
27-07-2026
From:
19-10-2026
Course Overview
Accurate demand forecasting is the foundation of effective logistics management. This Predictive Analytics & Demand Forecasting in Logistics Training Course helps participants understand how advanced analytics and forecasting tools improve planning, resource allocation, and supply chain responsiveness.
The course covers forecasting methods, predictive modeling, data analytics, and technology applications in logistics. Through real-world case studies and applied exercises, participants will learn to use analytics for better decision-making and operational performance.
By the end of this program, professionals will be equipped to align demand forecasts with logistics strategies, reduce uncertainty, and support sustainable supply chain efficiency.
Course Benefits
Understand predictive analytics applications in logistics.
Improve demand forecasting accuracy with advanced models.
Align forecasts with supply chain and logistics planning.
Reduce risks and inefficiencies through data insights.
Apply digital tools to enhance logistics performance.
Course Objectives
Define the role of demand forecasting in logistics operations.
Apply statistical and predictive forecasting models.
Use analytics to identify demand patterns and trends.
Integrate forecasts with supply chain planning systems.
Evaluate technology solutions for predictive logistics.
Reduce uncertainty and improve service levels.
Benchmark forecasting practices with global leaders.
Training Methodology
The course combines expert-led lectures, case studies, interactive discussions, and forecasting simulations. Participants will work with practical forecasting models and analytics tools.
Target Audience
Logistics and supply chain managers.
Demand planning and forecasting professionals.
Operations and inventory managers.
Analysts seeking data-driven logistics skills.
Target Competencies
Predictive analytics in logistics.
Demand forecasting accuracy.
Data-driven decision-making.
Supply chain planning integration.
Course Outline
Unit 1: Foundations of Demand Forecasting in Logistics
Role of forecasting in logistics and supply chains.
Key challenges in demand prediction.
Types of forecasting methods.
Industry examples of forecasting impact.
Unit 2: Forecasting Models and Techniques
Time-series and regression models.
Moving averages and exponential smoothing.
Quantitative vs. qualitative forecasting.
Practical exercises in model selection.
Unit 3: Predictive Analytics Applications
Using data analytics for forecasting accuracy.
Identifying demand drivers and variables.
Leveraging big data in logistics forecasting.
Predictive case studies.
Unit 4: Technology and Forecasting Tools
ERP, AI, and machine learning in forecasting.
Digital dashboards and visualization tools.
Real-time forecasting platforms.
Integration with logistics systems.
Unit 5: Performance Measurement and Best Practices
KPIs for forecasting accuracy.
Reducing risks and uncertainty.
Benchmarking against industry leaders.
Building resilient forecasting systems.
Ready to harness data for smarter logistics planning?
Join the Predictive Analytics & Demand Forecasting in Logistics Training Course with EuroQuest International Training and strengthen your ability to plan with accuracy and agility.
The Predictive Analytics & Demand Forecasting in Logistics Training Courses in Geneva provide professionals with a robust, data-driven framework for anticipating demand patterns, optimizing supply chain operations, and enhancing strategic decision-making. Designed for logistics analysts, supply chain managers, operations planners, and data specialists, these programs focus on advanced analytical tools and forecasting techniques that strengthen efficiency and reliability across logistics networks.
Participants explore the foundational and advanced principles of predictive analytics, including statistical modeling, machine learning applications, trend analysis, and data visualization. The courses emphasize how data-based insights support more accurate planning, improved resource allocation, and reduced operational risk. Through hands-on exercises and case studies, participants learn to apply forecasting methods such as time-series analysis, regression modeling, and scenario simulation to real-world logistics challenges.
These demand forecasting training programs in Geneva also highlight the integration of forecasting outputs into operational planning processes, including inventory optimization, transportation scheduling, workforce planning, and supplier coordination. The curriculum stresses the importance of data quality, cross-functional collaboration, and technology-enabled decision-making to ensure forecasting systems remain accurate and actionable.
Learning in Geneva, a global hub for trade, logistics coordination, and international business leadership, enriches the program with diverse perspectives and best practices from multinational supply chain environments. Participants gain insight into emerging technologies, sustainability considerations, and cross-border logistics complexities that influence modern forecasting strategies.
Upon completing this specialization, professionals emerge equipped with the analytical skills and strategic understanding needed to implement predictive analytics and demand forecasting within their organizations. They gain the ability to leverage data to anticipate change, reduce uncertainty, and optimize logistics performance—driving efficiency, resilience, and competitive advantage in today’s dynamic global supply chain landscape.