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Course Outline
Introduction to S&OP
- Defining Sales and Operations Planning
- Primary advantages and obstacles of S&OP
- The S&OP cycle and its integration with supply chain planning
Demand Forecasting Techniques
- Statistical forecasting approaches (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
- Leveraging Excel and Power BI for demand planning
- Developing data-driven forecasting models
Optimizing Forecast Accuracy
- Recognizing forecast errors and bias
- Methods to elevate forecast precision
- Best practices for harmonizing cross-functional teams
Inventory and Supply Planning
- Balancing inventory levels against demand changes
- Refining replenishment strategies
- Managing the distinction between perishable and non-perishable products
Cross-Functional Collaboration
- Aligning sales, operations, and finance within S&OP
- 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
- 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
- Tracking key performance indicators (KPIs)
- Strategies for achieving 95% forecast accuracy
Summary and Next Steps
Requirements
- Familiarity with supply chain management principles
- Practical experience with demand planning and forecasting methodologies
- Competency in using Excel or supply chain analytics software
Target Audience
- Demand planners
- Supply chain specialists
- Operations managers
14 Hours
Testimonials (1)
The input fm other industries through the trainer.