Unit 1110: Demand Planning and Forecasting

1. Introduction to Demand Planning and Forecasting

1.1 Importance in Supply Chain Management

• Role of demand planning in supply chain success
• Impact on inventory, production, and customer satisfaction

1.2 Key Concepts and Terminology

• Demand planning vs. forecasting
• Demand signals, lead times, and safety stock
• Demand variability and uncertainty

2. Forecasting Methods

2.1 Quantitative Forecasting Methods

• Time Series Analysis
  • Moving averages
  • Exponential smoothing
  • Seasonal decomposition
• Regression Analysis
  • Simple linear regression
  • Multiple regression

2.2 Qualitative Forecasting Methods

• Market Research
• Delphi Method
• Expert Opinion
• Customer Surveys

2.3 Selecting Appropriate Forecasting Methods

• When to use quantitative vs qualitative methods
• Combining methods for improved accuracy

3. Demand Management

3.1 Role in Forecasting

• Aligning demand with supply capabilities
• Demand shaping and influencing techniques

3.2 Managing Demand Variability

• Demand smoothing
• Promotions and pricing strategies
• Lead time management

3.3 Improving Forecast Accuracy

• Data quality and cleansing
• Collaboration with stakeholders
• Continuous monitoring and adjustment

4. Forecast Accuracy and Error Measurement

4.1 Metrics for Evaluation

• Mean Absolute Error (MAE)
• Mean Absolute Percentage Error (MAPE)
• Root Mean Squared Error (RMSE)

4.2 Identifying Sources of Forecast Error

• Data issues
• Model selection errors
• External factors

4.3 Techniques to Improve Forecasting Performance

• Model refinement
• Incorporating feedback loops
• Use of advanced analytics

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

5.1 Overview of CPFR

• Definition and purpose
• Key participants and roles

5.2 CPFR Process Steps

• Strategy and planning
• Demand and supply management
• Execution and analysis

5.3 Benefits and Challenges

• Improved forecast accuracy
• Enhanced supply chain visibility
• Collaboration barriers

6. Demand Planning Software and Tools

6.1 Forecasting Software Solutions

• Features and capabilities
• Examples (e.g., SAP IBP, Oracle Demantra)

6.2 Inventory Management Systems

• Integration with demand planning
• Real-time data tracking

6.3 Advanced Analytics and AI Tools

• Machine learning applications
• Predictive analytics platforms

7. Sales and Operations Planning (S&OP)

7.1 Integration with Demand Planning

• Cross-functional coordination
• Aligning sales, marketing, production, and finance

7.2 S&OP Process Framework

• Data gathering
• Demand review
• Supply review
• Reconciliation and executive review

7.3 Benefits of S&OP

• Improved decision making
• Balanced demand and supply
• Enhanced organizational alignment

8. Demand Forecasting in E-commerce and Omnichannel Retail

8.1 Unique Challenges

• High demand variability and seasonality
• Online consumer behavior dynamics
• Multi-channel inventory management

8.2 Strategies and Techniques

• Use of real-time data and analytics
• Integrating online and offline sales data
• Managing promotions and flash sales

8.3 Case Studies and Examples

• Successful forecasting models in e-commerce
• Handling peak demand periods