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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).
- The role of machine learning and AI in demand forecasting.
- Managing seasonality, trends, and demand variability.
Data Analytics for S&OP
- Data sources and demand signal analysis.
- Using Excel and Power BI for demand planning.
- Developing data-driven forecasting models.
Optimizing Forecast Accuracy
- Identifying forecast errors and bias.
- Techniques to enhance forecast accuracy.
- Best practices for aligning cross-functional teams.
Inventory and Supply Planning
- Balancing inventory levels with demand fluctuations.
- Optimizing replenishment strategies.
- Managing perishable versus non-perishable products.
Cross-Functional Collaboration
- Aligning sales, operations, and finance within S&OP.
- Building consensus in forecasting and planning.
- Effective communication strategies for 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 95% forecast accuracy.
Summary and Next Steps
Requirements
- A solid understanding of supply chain management principles.
- Experience with demand planning and forecasting techniques.
- Basic proficiency in using Excel or supply chain analytics tools.
Target Audience
- Demand planners.
- Supply chain professionals.
- Operations managers.
14 Hours
Testimonials (1)
The input fm other industries through the trainer.
