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 Duration 14 hours

Course Outline

Introduction to S&OP

  • Defining Sales and Operations Planning.
  • Exploring the primary benefits and challenges of S&OP.
  • Understanding the S&OP cycle and its role in supply chain planning.

Demand Forecasting Techniques

  • Statistical forecasting approaches (e.g., moving averages, exponential smoothing).
  • The role of machine learning and AI in forecasting.
  • Managing seasonality, trends, and demand fluctuations.

Data Analytics for S&OP

  • Analyzing data sources and demand signals.
  • Leveraging Excel and Power BI for planning activities.
  • Constructing data-driven forecasting models.

Optimizing Forecast Accuracy

  • Detecting forecast errors and biases.
  • Strategies for enhancing forecast precision.
  • Aligning cross-functional teams effectively.

Inventory and Supply Planning

  • Aligning inventory levels with demand shifts.
  • Refining replenishment strategies.
  • Handling perishable versus non-perishable inventory.

Cross-Functional Collaboration

  • Coordinating sales, operations, and finance within the S&OP framework.
  • Reaching consensus on forecasts and plans.
  • Communication best practices for S&OP meetings.

Technology and Tools for S&OP

  • Surveying modern S&OP software solutions.
  • Setting up digital dashboards for real-time insights.
  • Reviewing case studies of successful S&OP rollouts.

Continuous Improvement in S&OP

  • Monitoring and iterating on the S&OP process.
  • Tracking key performance indicators (KPIs).
  • Pathways to achieving 95% forecast accuracy.

Summary and Next Steps

Requirements

  • Foundational knowledge of supply chain management principles.
  • Prior experience with demand planning and forecasting methods.
  • Basic competency in Excel or supply chain analytics platforms.

Target Audience

  • Demand Planners
  • Supply Chain Professionals
  • Operations Managers

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