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Duration 14 hours
Course Outline
Module 1: Foundations of AI in Logistics and Supply
- Core concepts and practical applications of Artificial Intelligence
- The role of AI in logistics and fuel distribution: opportunities and impacts
- Overview of no-code AI tools, including Excel AI, ChatGPT, and Power BI
- Real-world examples from the transportation and fuel sectors
Module 2: Organizing and Analyzing Operational Data
- Identifying critical logistics and supply datasets, such as routes, tanks, and deliveries
- Structuring volumetric control and inventory data for AI processing
- Techniques for data cleaning, formatting, and validation in Excel
- Generating insights through dynamic tables and pivot charts
Module 3: AI-Driven Fuel Demand Forecasting
- Understanding demand forecasting and key influencing variables
- Applying Excel’s AI features and ChatGPT for predictive analysis
- Predicting short-term fuel demand trends (1–2 weeks)
- Practical task: Developing a basic forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Fundamental principles of route optimization and scheduling
- Utilizing AI tools to recommend optimal routes and delivery sequences
- Implementing route planning with Excel and ChatGPT under real-world constraints
- Activity: Generating route alternatives for delivery units
Module 5: Logistics Cost Estimation and Optimization
- Identifying key cost factors, including distance, tolls, fuel usage, and freight
- Employing AI models to project logistics expenses
- Evaluating manual versus AI-assisted cost planning methods
- Creating cost calculation templates with dynamic input fields
Module 6: Dashboards and KPI Visualization
- Introduction to creating dashboards in Power BI and Excel
- Designing visual reports for logistics and supply chain KPIs
- Incorporating data from volumetric control systems
- Exercise: Building a real-time logistics performance dashboard
Module 7: Embedding AI in Logistics Workflows
- Automating routine reporting and data aggregation tasks
- Using Power Automate or Excel macros for process automation
- Setting up alert systems for inventory levels or delivery milestones
- Case study: Implementing AI-based alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Strategy for Logistics and Supply
- Developing a phased AI implementation roadmap
- Selecting pilot use cases and defining success metrics
- Expanding AI-assisted processes across teams
- Establishing frameworks for continuous improvement and knowledge sharing
Conclusion and Future Directions
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No prior background in Artificial Intelligence is necessary
Target Audience
- Professionals in logistics and supply within the fuel transportation and sales sectors
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routing and fuel distribution
