The New Language of Demand Planning
How AI is Transforming Demand Planning
Our insightful webinar on the role of AI in demand planning offers rich insights where industry experts and AI specialists explore the transformative power of artificial intelligence in demand planning. Discover how AI in demand forecasting can enhance accuracy, efficiency, and scalability in your predictive processes.
Who will benefit
Are you a CSCO, COO, CFO, CTO, CIO or a VP/Director leading supply chain, operations, or logistics? This exclusive webinar is tailored for leaders like you, driving innovation and efficiency across industries like Manufacturing, Retail, Consumer packaged goods, E-commerce, and Logistics.
Key Highlights
- How Demand planning has evolved
- Introduction to AI in Demand Planning
- Live Demonstration: AI Tools in Action - Logility
- Case Studies: AI-Driven Demand Planning Success Stories
- Future Trends: The Evolution of Generative AI in Demand Planning
- Closing Remarks and Next Steps
The Takeaways
- Understand the critical role of demand planning in today's business environment.
- Learn how AI technologies can revolutionize demand forecasting.
- Gain insights from real-world case studies of AI implementation.
- See AI tools in action with a live demonstration.
- Discover best practices for integrating AI into your demand planning processes.
- Explore future trends and stay ahead in the evolving landscape of AI in demand planning.
Agenda for the webinar flow is as follows:-
How can Korcomptenz help?
Korcomptenz offers comprehensive AI solutions with a sharp focus on understanding demand planning, fostering innovation, and delivering projects that align with the organization’s strategic goals. Our approach includes:
- Comprehensively Assess, Ideate and Innovate
- Ideation and Concept Development
- Technology Implementation, Integration, and Custom Solution Development
- Training & Support
FAQ
What is AI-driven demand forecasting?
AI-driven demand forecasting utilizes artificial intelligence and machine learning algorithms to predict future demand for products or services. By analyzing historical data, market trends, and external factors, AI tools like Logility can provide more accurate and dynamic forecasts compared to traditional methods.
How does AI improve demand planning accuracy?
What are the benefits of implementing AI in demand planning?
Implementing AI in demand planning offers several advantages:
Enhanced Forecast Accuracy: AI algorithms analyze diverse data sources to provide precise demand predictions.
Real-Time Insights: AI processes data continuously, offering up-to-date insights for better decision-making.
Scalability: AI systems can handle large datasets, making them suitable for businesses of all sizes.
Cost Reduction: Improved forecasting leads to optimized inventory levels and reduced operational costs.
What industries can benefit the most from AI-driven demand planning?
Retail: Optimizing stock levels and reducing markdowns.
Manufacturing: Enhancing production planning and inventory management.
Consumer Goods: Aligning supply with fluctuating consumer demand.
Logistics: Improving route planning and resource allocation.
What future trends can we expect in AI-driven demand planning?
Increased Use of Real-Time Data: Utilizing IoT and real-time analytics for immediate insights.
Advanced Predictive Analytics: Employing more sophisticated algorithms for better foresight.
Greater Personalization: Tailoring demand forecasts to specific customer segments.
Integration with Other Technologies: Combining AI with blockchain or advanced robotics for enhanced supply chain management.
AI-driven demand forecasting utilizes artificial intelligence and machine learning algorithms to predict future demand for products or services. By analyzing historical data, market trends, and external factors, AI tools like Logility can provide more accurate and dynamic forecasts compared to traditional methods.
Implementing AI in demand planning offers several advantages:
Enhanced Forecast Accuracy: AI algorithms analyze diverse data sources to provide precise demand predictions.
Real-Time Insights: AI processes data continuously, offering up-to-date insights for better decision-making.
Scalability: AI systems can handle large datasets, making them suitable for businesses of all sizes.
Cost Reduction: Improved forecasting leads to optimized inventory levels and reduced operational costs.
Retail: Optimizing stock levels and reducing markdowns.
Manufacturing: Enhancing production planning and inventory management.
Consumer Goods: Aligning supply with fluctuating consumer demand.
Logistics: Improving route planning and resource allocation.
Increased Use of Real-Time Data: Utilizing IoT and real-time analytics for immediate insights.
Advanced Predictive Analytics: Employing more sophisticated algorithms for better foresight.
Greater Personalization: Tailoring demand forecasts to specific customer segments.
Integration with Other Technologies: Combining AI with blockchain or advanced robotics for enhanced supply chain management.
Speakers
Justin Wallace
Americas Logility
Richard Troxell
Americas Logility
Maharaja Pachaiyappan
Korcomptenz Inc
Rohan Iruthayaraj
Korcomptenz Inc