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Course Outline
Introduction to S&OP
- Understanding Sales and Operations Planning.
- Key advantages and challenges associated with S&OP.
- The S&OP cycle and its integration with supply chain planning.
Demand Forecasting Techniques
- Statistical forecasting methods (including moving averages and exponential smoothing).
- The role of machine learning and AI in demand forecasting.
- Managing seasonality, trends, and demand variability.
Data Analytics for S&OP
- Identifying data sources and analyzing demand signals.
- Leveraging Excel and Power BI for demand planning.
- Developing data-driven forecasting models.
Optimizing Forecast Accuracy
- Detecting forecast errors and bias.
- Techniques to enhance forecast precision.
- Best practices for aligning cross-functional teams.
Inventory and Supply Planning
- Balancing inventory levels against demand fluctuations.
- Optimizing replenishment strategies.
- Managing the distinction between perishable and non-perishable products.
Cross-Functional Collaboration
- Aligning sales, operations, and finance within the S&OP framework.
- Fostering consensus in forecasting and planning.
- Effective communication strategies for S&OP meetings.
Technology and Tools for S&OP
- Overview of contemporary S&OP software solutions.
- Implementing digital dashboards for real-time decision-making.
- Case studies showcasing 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 foundational understanding of supply chain management principles.
- Practical experience with demand planning and forecasting techniques.
- Basic proficiency in utilizing Excel or supply chain analytics software.
Target Audience
- Demand planners
- Supply chain professionals
- Operations managers
14 Hours
Testimonials (1)
The input fm other industries through the trainer.