Analyzing Predictive Analytics Techniques for Enhancing Demand Planning in Industrial Supply Chain Management

1. Introduction 1.1 Background of Supply Chain Management 1.2 Importance of Demand Planning 1.3 Objectives of the Study 2. Overview of Predictive Analytics 2.1 Definition and Scope 2.2 Historical Development 2.3 Key Techniques 3. Industrial Supply Chain Management 3.1 Components and Structure 3.2 Challenges in Demand Planning 3.3 Role of Technology 4. Predictive Analytics in Demand Planning 4.1 Application Techniques 4.2 Case Studies 4.3 Benefits Observed 5. Comparative Analysis of Techniques 5.1 Statistical Methods 5.2 Machine Learning Approaches 5.3 Hybrid Models 6. Enhancing Demand Planning Strategies 6.1 Integration with Supply Chain Processes 6.2 Real-time Data Utilization 6.3 Risk Management 7. Case Studies and Practical Implications 7.1 Industry Case Examples 7.2 Lessons Learned 7.3 Future Implications 8. Conclusion and Recommendations 8.1 Summary of Findings 8.2 Recommendations for Industry 8.3 Directions for Future Research