AI, IoT and Data-Driven Supply Chain Analytics

This course explains how organizations use advanced technologies to improve supply chain performance. It covers AI-driven analytics and machine learning for forecasting production, transportation, and inventory. IoT devices boost transparency and tracking across the value chain. The course focuses on practical tools for enhancing visibility, decision-making, and resilience in complex global supply chains. Participants will learn to use real-time data from connected sensors and systems to monitor logistics, forecast demand, manage risks, and allocate resources better.

Who Should Attend?

This course is designed for supply chain and operations directors, logistics and procurement managers, data analysts, business intelligence professionals, manufacturing, distribution, and retail managers, digital transformation and IT managers. It is equally valuable for supply chain consultants and project managers, risk, quality and performance managers, policy advisors, smart industry strategists and business leaders seeking to drive efficiency through data-driven decision-making.

Course Outcomes

Delegates will gain the skills and knowledge to: 

• Develop frameworks for real-time supply chain visibility using connected IoT devices.
• Utilize AI and machine learning to automate logistics planning and reduce operational risks.
• Integrate IoT sensors for condition monitoring, asset tracking, and quality control.
• Implement data-driven decision-making processes for procurement and distribution.
• Build dashboards and KPI frameworks for performance monitoring and scenario planning.
• Enhance sustainability and transparency through data-enabled supply chain mapping.
• Design a roadmap for digital supply chain transformation aligned with organizational strategy.

Key Course Highlights

At the end of the course, you will understand;

• The foundational technologies behind AI, IoT, and data analytics in supply chain ecosystems.
• Data governance, cybersecurity, and ethical considerations in digital supply chain management.
• How interconnected systems create real-time operational visibility and responsiveness.
• The role of predictive analytics in minimizing uncertainty and optimizing performance.
• The integration of big data platforms for real-time decision support and control.
• The value of blockchain, sensors, and automation in enhancing traceability and accountability.
• How AI algorithms improve demand sensing, pricing, and logistics routing accuracy.
• The architecture of smart factories and connected logistics networks.

Course Booking

Please use the “book now” or “inquire” buttons on this page to either book your space or make further enquiries.