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Course Outline
Introduction to S&OP
- What is Sales and Operations Planning?
- Key benefits and challenges of S&OP
- The S&OP cycle and its integration with supply chain planning
Demand Forecasting Techniques
- Statistical forecasting methods (moving averages, exponential smoothing)
- Machine learning and AI in demand forecasting
- Handling seasonality, trends, and demand variability
Data Analytics for S&OP
- Data sources and demand signal analysis
- Using Excel and Power BI for demand planning
- Building data-driven forecasting models
Optimizing Forecast Accuracy
- Identifying forecast errors and bias
- Techniques to improve forecast accuracy
- Best practices for aligning cross-functional teams
Inventory and Supply Planning
- Balancing inventory levels with demand fluctuations
- Optimizing replenishment strategies
- Managing perishable vs. non-perishable products
Cross-Functional Collaboration
- Aligning sales, operations, and finance in S&OP
- Building consensus in forecasting and planning
- Effective communication strategies in S&OP meetings
Technology and Tools for S&OP
- Overview of modern S&OP software
- Implementing digital dashboards for real-time decision-making
- Case studies on successful S&OP implementations
Continuous Improvement in S&OP
- Monitoring and refining the S&OP process
- Measuring key performance indicators (KPIs)
- Strategies for achieving a 95% forecast accuracy
Summary and Next Steps
Requirements
- An understanding of supply chain management principles
- Experience with demand planning and forecasting techniques
- Basic proficiency in using Excel or supply chain analytics tools
Audience
- Demand planners
- Supply chain professionals
- Operations managers
14 Hours
