AI-Driven Supply Chain Optimization Training Course

Module 1: The AI-Powered Supply Chain Landscape

• Understanding the shift from reactive to proactive supply chain management
• Overview of the AI stack: From IoT sensors to cloud-based decision engines
• Identifying high-impact AI use cases: Planning, execution, and visibility
• The role of Digital Twins in simulating complex supply chain scenarios
• Overcoming silos: Integrating data across the end-to-end value chain
• Practical session: Performing a "Supply Chain Digital Maturity" audit on a sample business case

Module 2: Data Engineering for Global Logistics

• Consolidating heterogeneous data: ERP, CRM, and external market signals
• Feature engineering for supply chain: Lead times, seasonality, and volatility metrics
• Handling unstructured data: Natural Language Processing (NLP) for contract analysis
• Real-time data streaming: Integrating IoT and GPS telemetry into analytics
• Data cleaning protocols for global shipping and customs documentation
• Practical session: Building a unified data pipeline for multi-source logistics records

Module 3: Predictive Demand and Sales Forecasting

• Time-series analysis for seasonal demand peaks and trend identification
• Utilizing machine learning to integrate external drivers: Weather, social media, and economics
• Managing the "Bullwhip Effect" through synchronized demand sensing
• Deep learning for short-term vs. long-term strategic forecasting
• Accuracy metrics: Moving from MAPE to weighted bias and service-level impact
• Practical session: Developing a demand forecasting model using Gradient Boosting Machines

Module 4: Intelligent Inventory Management and Optimization

• Dynamic safety stock calculation using probabilistic machine learning
• Multi-echelon Inventory Optimization (MEIO) in complex distribution networks
• Predicting product obsolescence and managing perishable inventory
• Automated replenishment systems: Integrating AI logic with warehouse ERPs
• ABC analysis 2.0: AI-driven SKU classification and prioritization
• Practical session: Implementing an AI-driven safety stock optimizer for a retail dataset

Module 5: AI in Procurement and Supplier Relationship Management

• Automated supplier selection and performance scoring using predictive analytics
• Price volatility prediction for raw materials and commodities
• Using NLP for automated contract risk assessment and spend analysis
• AI-driven negotiation support: Analyzing historical supplier behavior
• Promoting diversity and sustainability in the supplier base through data science
• Practical session: Building a supplier risk-scoring engine based on historical performance data

Module 6: Warehouse Automation and Vision-Based Systems

• Computer Vision for automated inventory counting and shelf monitoring
• AI-driven warehouse slotting: Optimizing layout for picking efficiency
• Coordinating autonomous mobile robots (AMRs) for material handling
• Predicting warehouse labor requirements based on forecasted order volumes
• Using AI to reduce picking errors and improve worker safety
• Practical session: Designing a prototype for an AI-driven warehouse slotting strategy

Module 7: Strategic Network Design and Location Intelligence

• Geospatial analysis for optimal distribution center and hub placement
• Simulating the impact of network changes on lead times and total cost
• Greenfield and Brownfield analysis using genetic algorithms
• Balancing carbon footprint vs. transportation cost in network design
• Multi-objective optimization for global supply chain footprinting
• Practical session: Using location intelligence tools to determine the optimal site for a new hub

Module 8: Logistics and Last-Mile Route Optimization

• Dynamic vehicle routing: Solving the Traveling Salesperson Problem (TSP) with AI
• Real-time traffic and weather integration for accurate ETA prediction
• Crowd-sourced delivery and gig-economy labor optimization
• Autonomous last-mile delivery: Drones and sidewalk robots
• Managing "Green Logistics": Optimizing for fuel efficiency and electric vehicle constraints
• Practical session: Implementing a route optimization algorithm for a fleet of delivery vehicles

Module 9: Supply Chain Risk Management and Resilience

• Predictive modeling for global disruptions: Port strikes, pandemics, and geopolitics
• Real-time visibility: Early warning systems for shipment delays
• Scenario planning and "What-if" analysis for supply chain stress testing
• AI-driven insurance and claims processing in global trade
• Diversification strategies: Using AI to find alternative sourcing routes instantly
• Practical session: Simulating a major port disruption and using AI to re-route a global cargo network

Module 10: Ethical AI, Sustainability, and Future Trends

• Navigating data privacy and security in cross-border data sharing
• Addressing bias in procurement and logistics algorithms
• Circular supply chains: Using AI to manage returns and product life-cycles
• The impact of Generative AI and LLMs on supply chain orchestration
• Building a long-term roadmap for autonomous supply chain maturity
• Practical session: Drafting a sustainability-focused AI ethics policy for a global logistics firm

Requirements:

• Participants should be reasonably proficient in English.
• Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588