Unit 981: Demand Forecasting and Supply Chain Planning

1. Introduction to Demand Forecasting

• Importance of demand forecasting in supply chain management
• Benefits of accurate demand forecasting
• Role of forecasting in efficient planning and decision-making

2. Methods of Demand Forecasting

2.1 Qualitative Methods

• Market research techniques
• Expert opinion and Delphi method
• Customer surveys and focus groups

2.2 Quantitative Methods

• Time series analysis overview
• Regression analysis basics
• Overview of causal models

3. Factors Influencing Demand

• Internal factors: pricing, product portfolio, promotions
• External factors:
  • Economic conditions (GDP, inflation, unemployment)
  • Consumer preferences and behavior changes
  • Market trends and innovation
  • Seasonality and cyclical demand patterns
  • Competitive landscape and market share shifts

4. Forecasting Accuracy and Error Measurement

• Importance of measuring forecasting accuracy
• Key metrics:
  • Mean Absolute Percentage Error (MAPE)
  • Tracking signal
  • Forecast bias
• Implications of forecast errors on supply chain performance

5. Demand Forecasting Techniques

5.1 Moving Averages

• Simple moving average calculation and use cases
• Weighted moving averages

5.2 Exponential Smoothing

• Single, double, and triple exponential smoothing
• Trend and seasonality adjustments

5.3 Trend Projection

• Identifying and extrapolating trends

5.4 Causal Models

• Using regression and other statistical models to link demand drivers

6. Collaborative Planning, Forecasting, and Replenishment (CPFR)

• Concept and objectives of CPFR
• Benefits of collaboration between trading partners
• Steps and process flow in CPFR
• Case examples illustrating CPFR implementation

7. Inventory Management and Demand Forecasting

• Relationship between demand forecasting and inventory control
• Role of safety stock and buffer inventory
• Reorder point calculation and its dependence on forecast accuracy
• Techniques to optimize inventory levels using forecast data

8. Demand Planning and Sales & Operations Planning (S&OP) Process

• Overview of S&OP framework
• Integrating demand forecasting within S&OP
• Aligning production, inventory, and demand plans
• Cross-functional collaboration for effective S&OP

9. Technology and Tools for Demand Forecasting

• Introduction to forecasting software solutions
• Role of Artificial Intelligence (AI) and Machine Learning (ML) in forecasting
• Automation of forecasting processes
• Enhancing decision-making with predictive analytics

10. Case Studies and Best Practices in Demand Forecasting

• Analysis of real-world industry case studies
• Best practices for effective forecasting and planning
• Lessons learned from successful and unsuccessful implementations
• Strategies for continuous improvement in demand forecasting