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)
  • Machine learning and AI in demand forecasting
  • Handling seasonality, trends, and demand variability

Data Analytics for S&OP

  • Data sources and demand signal analysis
  • Using Excel and Power BI for demand planning
  • Building data-driven forecasting models

Optimizing Forecast Accuracy

  • Identifying forecast errors and bias
  • Techniques to improve forecast accuracy
  • Best practices for aligning cross-functional teams

Inventory and Supply Planning

  • Balancing inventory levels with demand fluctuations
  • Optimizing replenishment strategies
  • Managing perishable vs. non-perishable products

Cross-Functional Collaboration

  • Aligning sales, operations, and finance in S&OP
  • Building consensus in forecasting and planning
  • Effective communication strategies in 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 a 95% forecast accuracy

Summary and Next Steps

Requirements

  • An understanding of supply chain management principles
  • Experience with demand planning and forecasting techniques
  • Basic proficiency in using Excel or supply chain analytics tools

Audience

  • Demand planners
  • Supply chain professionals
  • Operations managers
 14 Hours

Testimonials (2)

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