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Course Outline
Foundations of S&OP
- Defining Sales and Operations Planning.
- Key advantages and common challenges associated with S&OP.
- The S&OP cycle and its alignment with broader supply chain planning.
Demand Forecasting Methodologies
- Statistical approaches, including moving averages and exponential smoothing.
- The role of machine learning and AI in predicting demand.
- Addressing seasonality, trends, and inherent demand variability.
Data Analytics in S&OP
- Identifying data sources and analysing demand signals.
- Applying Excel and Power BI for effective demand planning.
- Developing data-driven forecasting models.
Refining Forecast Precision
- Detecting forecast errors and systemic bias.
- Strategies to enhance overall forecast accuracy.
- Best practices for synchronising cross-functional teams.
Inventory and Supply Strategy
- Balancing inventory levels against demand fluctuations.
- Optimising replenishment workflows.
- Distinguishing management approaches for perishable versus non-perishable items.
Cross-Functional Synergy
- Aligning sales, operations, and finance within the S&OP framework.
- Fostering consensus during forecasting and planning stages.
- Communication best practices for S&OP meetings.
S&OP Technology and Tooling
- An overview of contemporary S&OP software solutions.
- Deploying digital dashboards for real-time decision support.
- Case studies highlighting successful S&OP deployments.
Continuous S&OP Improvement
- Monitoring and iterating the S&OP process.
- Tracking key performance indicators (KPIs).
- Strategies for attaining 95% forecast accuracy.
Concluding Summary and Future Actions
Requirements
- A solid grasp of supply chain management fundamentals.
- Practical experience with demand planning and forecasting methodologies.
- Foundational proficiency in Excel or dedicated 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.
