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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

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