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 Duration 14 hours

Course Outline

Introduction to S&OP

  • Defining Sales and Operations Planning
  • Key advantages and potential challenges within S&OP
  • Understanding the S&OP cycle and its role in supply chain integration

Demand Forecasting Techniques

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

Data Analytics for S&OP

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

Improving Forecast Accuracy

  • Detecting forecast errors and identifying bias
  • Strategies to enhance forecast precision
  • Best practices for aligning cross-functional teams

Inventory and Supply Planning

  • Balancing inventory levels against demand changes
  • Refining replenishment strategies
  • Managing the distinct needs of perishable versus non-perishable products

Cross-Functional Collaboration

  • Aligning sales, operations, and finance within the S&OP framework
  • Building consensus in forecasting and planning processes
  • Communication strategies for effective S&OP meetings

Technology and Tools for S&OP

  • Overview of contemporary S&OP software solutions
  • Implementing digital dashboards for real-time insights
  • Reviewing case studies of successful S&OP implementations

Continuous Improvement in S&OP

  • Monitoring and iterating on the S&OP process
  • Tracking key performance indicators (KPIs)
  • Tactics to achieve a 95% forecast accuracy rate

Summary and Future Actions

Requirements

  • Foundational knowledge of supply chain management concepts
  • Prior exposure to demand planning and forecasting methods
  • Proficiency in Excel or relevant supply chain analytics platforms

Target Audience

  • Demand planners
  • Supply chain specialists
  • Operations managers

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