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Course Outline
Introduction to S&OP
- Understanding Sales and Operations Planning
- Core advantages and challenges associated with 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
- Addressing seasonality, trends, and demand variability
Data Analytics for S&OP
- Identifying data sources and analyzing demand signals
- Utilizing Excel and Power BI for demand planning
- Developing data-driven forecasting models
Optimizing Forecast Accuracy
- Detecting forecast errors and bias
- Strategies to elevate forecast precision
- Best practices for aligning cross-functional teams
Inventory and Supply Planning
- Balancing inventory levels against demand fluctuations
- Refining replenishment strategies
- Managing perishable versus non-perishable products
Cross-Functional Collaboration
- Aligning sales, operations, and finance within S&OP
- Building consensus during forecasting and planning phases
- Effective communication strategies in S&OP meetings
Technology and Tools for S&OP
- Overview of contemporary S&OP software solutions
- Deploying digital dashboards for real-time decision-making
- Case studies highlighting 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
- Foundational knowledge of supply chain management principles
- Practical experience with demand planning and forecasting methods
- Competency in using 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.