Introduction
Traditional inventory management methods are no longer sufficient in today’s rapidly evolving supply chains. Companies must adopt dynamic, AI-driven inventory control strategies to maintain optimal stock levels, minimize costs, and improve service levels.
This course explores real-time inventory tracking, AI-powered forecasting, demand-driven replenishment, and adaptive control techniques. Participants will gain hands-on experience with machine learning models, IoT-based inventory monitoring, and predictive analytics to build resilient and agile supply chains.
Course Objectives
By the end of this course, participants will be able to:
✅ Implement real-time, data-driven inventory control techniques.
✅ Apply AI and machine learning for dynamic demand forecasting.
✅ Use IoT, RFID, and digital twins for inventory visibility.
✅ Optimize inventory levels with adaptive replenishment models.
✅ Reduce stockouts, excess inventory, and holding costs using analytics.
✅ Implement multi-echelon inventory management for supply chain efficiency.
✅ Leverage blockchain for transparent, automated inventory transactions.
Who Should Attend?
This course is ideal for:
- Inventory & Supply Chain Managers
- Operations & Logistics Professionals
- Procurement & Demand Planning Specialists
- Warehouse & Distribution Center Managers
- Retail & E-Commerce Inventory Analysts
- Manufacturing & Production Planning Experts
- Data Analysts & IT Professionals in Supply Chain
Day 1: Fundamentals of Dynamic Inventory Control
- The Shift from Static to Dynamic Inventory Management
- Why traditional models fail in modern supply chains
- Dynamic control principles & real-time adjustments
- Key Inventory Control Metrics & KPIs
- Service level optimization, stock turnover, and inventory accuracy
- Measuring & reducing carrying costs
- Demand Variability & Its Impact on Inventory Strategies
- Handling fluctuating demand & uncertainty
- Introduction to demand-driven inventory optimization
Day 2: AI & Machine Learning in Inventory Control
- AI-Powered Demand Forecasting & Inventory Planning
- Predictive analytics for demand fluctuations
- Case Study: How Amazon & Walmart use AI for inventory control
- Machine Learning Models for Inventory Optimization
- Regression, clustering, and neural networks in forecasting
- AI-based dynamic reorder point calculations
- Automated Inventory Decision-Making with AI
- Case Study: Tesla’s AI-driven inventory management
- Adaptive learning algorithms for real-time stock adjustments
Day 3: Real-Time Inventory Visibility & Replenishment
- IoT, RFID, & Smart Sensors in Inventory Management
- Live tracking of stock levels, expiration dates, and movement
- Automated inventory audits using smart technologies
- Dynamic Replenishment & Just-In-Time (JIT) Strategies
- Demand-driven supply & flexible stock policies
- Case Study: Zara’s fast fashion inventory model
- Multi-Echelon Inventory Optimization (MEIO)
- Balancing stock across multiple locations
- Simulation models for inventory planning
Day 4: Blockchain, Risk Management & Automation
- Blockchain for Inventory Transparency & Security
- Smart contracts for automated inventory tracking
- Preventing fraud, counterfeiting, and supply chain disruptions
- Risk-Based Inventory Control & Contingency Planning
- Scenario modeling for demand shocks
- Inventory buffer strategies for supply chain resilience
- Warehouse Automation & Robotics in Inventory Control
- Using AI-driven robots for stock handling
- Drones & AGVs for real-time inventory monitoring
Day 5: Future Trends, Case Studies & Certification
- Emerging Trends in Dynamic Inventory Management
- AI-driven autonomous inventory control systems
- Digital twins & augmented reality in warehouse operations
- Case Studies: Best Practices in Inventory Control
- Apple’s precision inventory model vs. Toyota’s lean inventory
- How Alibaba manages dynamic inventory across global markets
- Capstone Project & Certification
- Participants design a real-time inventory optimization strategy
- Final assessment and feedback session
- Certification: Certified Dynamic Inventory Specialist (CDIS™)
Certification
Upon successful completion, participants will receive the Certified Dynamic Inventory Specialist (CDIS™) credential, validating their expertise in AI-driven forecasting, real-time tracking, adaptive replenishment, and automated inventory management, preparing them for leadership roles in modern supply chain operations.
Key Takeaways
✔ Master real-time, AI-driven inventory control methods.
✔ Optimize stock levels using predictive analytics & demand forecasting.
✔ Implement IoT, RFID, blockchain, and automation in inventory management.
✔ Reduce holding costs, stockouts, and excess inventory with dynamic strategies.
✔ Earn an industry-recognized certification for career advancement.