This session: 26–30 Jul 2027
This Mastering Forecasting and Demand Planning Best Practices session in Vienna (Austria) runs from Monday 26 July to Friday 30 July 2027 (week 30, Q3 2027). It is the only date in Vienna (Austria) in 2027, at a fee of 5,200 £. Registration is open for this date. It is held in person.
| Dates | Monday 26 Jul – Friday 30 Jul 2027 |
|---|---|
| Week | 30 of 2027 |
| Duration | 5 days |
| Fee | 5,200 £ |
| Status | Open for registration |
| Format | In person |
Course Overview
Course Description
This comprehensive 1-week course equips supply chain professionals with cutting-edge forecasting techniques and demand planning best practices. Participants will learn to leverage advanced analytics, AI technologies, and collaborative strategies to enhance forecast accuracy and optimize supply chain performance. The course covers integrated business planning, demand sensing, and risk management to drive operational efficiency and business growth.
Learning Objectives
- Master advanced forecasting methods and demand planning techniques
- Implement integrated business planning and collaborative forecasting strategies
- Leverage AI and machine learning for improved forecast accuracy
- Develop skills in demand segmentation and risk management
- Apply best practices in data analysis and performance monitoring
Course Modules
Day 1: Foundations of Demand Forecasting
- Introduction to demand planning and forecasting
- Historical data analysis and baseline forecasting
- Qualitative vs. quantitative forecasting methods
- Integrated Business Planning (IBP) fundamentals
Day 2: Advanced Analytics and AI in Forecasting
- Leveraging machine learning algorithms for demand prediction
- Predictive analytics and demand sensing techniques
- Incorporating external data sources for enhanced accuracy
- AI-driven forecasting tools and applications
Day 3: Collaborative Planning and Demand Segmentation
- Strategies for cross-functional collaboration
- Demand segmentation for precision forecasting
- Market research and Delphi method integration
- Aligning forecasts with sales and marketing insights
Day 4: Risk Management and Scenario Planning
- Identifying and mitigating forecast risks
- Scenario planning and contingency strategies
- Inventory optimization techniques
- Balancing service levels and cost efficiency
Day 5: Performance Monitoring and Continuous Improvement
- Key performance indicators for demand planning
- Forecast accuracy measurement and improvement
- Implementing a robust forecasting cadence
- Best practices for ongoing forecast evaluation and adjustment
Practical Wins for Participants
- Develop a customized demand planning framework for your organization
- Create an action plan to implement AI-driven forecasting techniques
- Design a collaborative forecasting process to enhance cross-functional alignment
- Construct a risk management strategy to improve forecast resilience
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