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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Comprehending Artificial Intelligence: core concepts and use cases
- AI in logistics and fuel distribution: potential and impact
- No-code AI tools: Excel AI, ChatGPT, Power BI, and more
- Real-world examples from the transport and fuel industries
Module 2: Structuring and Analyzing Operational Data
- Pinpointing essential logistics and supply datasets (routes, tanks, deliveries)
- Preparing volumetric control and inventory data for AI integration
- Data cleansing, formatting, and validation using Excel
- Generating dynamic tables and pivot charts to derive insights
Module 3: AI-Assisted Fuel Demand Forecasting
- Understanding demand forecasting and its contributing factors
- Employing Excel’s AI capabilities and ChatGPT for predictive analysis
- Projecting short-term (1–2 week) fuel demand patterns
- Practical task: constructing a simple forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Fundamental concepts in route optimization and scheduling
- Leveraging AI tools to recommend optimal routes and delivery orders
- Utilizing Excel and ChatGPT for route planning with specific constraints
- Practical exercise: generating route alternatives for delivery units
Module 5: Cost Estimation and Logistics Optimization
- Recognizing cost factors: distance, tolls, fuel consumption, and freight
- Applying AI models to estimate logistics expenses
- Evaluating manual versus AI-assisted cost planning
- Developing cost calculation templates with dynamic inputs
Module 6: Dashboards and KPI Visualization
- Overview of Power BI and Excel dashboards
- Creating visual reports for logistics and supply KPIs
- Incorporating data from volumetric control systems
- Hands-on session: building a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Workflows
- Automating repetitive reporting and data aggregation tasks
- Utilizing Power Automate or Excel macros for task automation
- Setting up alert systems for inventory or delivery limits
- Real-world example: AI-triggered alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Developing a sequential AI implementation roadmap
- Defining pilot use cases and success indicators
- Expanding AI-assisted processes across teams
- Fostering ongoing improvement and knowledge sharing practices
Summary and Future Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No previous experience with Artificial Intelligence is necessary
Target Audience
- Logistics and supply professionals in the fuel transportation and sales sector
- Operations and inventory coordinators
- Supervisors and planners overseeing fleet routes and fuel deliveries
