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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Understanding Artificial Intelligence: core concepts and uses
- AI in logistics and fuel distribution: potential benefits and impact
- No-code AI tools: Excel AI, ChatGPT, Power BI, and other platforms
- Real-world examples from the transport and fuel sectors
Module 2: Organizing and Analyzing Operational Data
- Recognizing critical logistics and supply datasets (routes, tanks, deliveries)
- Structuring volumetric control and inventory data for AI integration
- Data cleaning, formatting, and validation techniques in Excel
- Building dynamic tables and pivot charts to generate insights
Module 3: AI-Supported Fuel Demand Forecasting
- Understanding demand forecasting and key influencing factors
- Applying Excel’s AI capabilities and ChatGPT for predictive analytics
- Predicting short-term (1–2 week) fuel demand patterns
- Practical task: developing a simple forecasting model using current data
Module 4: Route Planning and Resource Optimization
- Core principles of route optimization and scheduling
- Using AI tools to recommend optimal routes and delivery sequences
- Applying Excel and ChatGPT for route planning with actual constraints
- Practical activity: generating route alternatives for delivery units
Module 5: Cost Estimation and Logistics Efficiency
- Identifying cost factors: distance, tolls, fuel usage, and freight
- Leveraging AI models to predict logistics costs
- Evaluating manual versus AI-assisted cost planning methods
- Creating cost calculation templates with dynamic inputs
Module 6: Dashboards and KPI Visualization
- Overview of Power BI and Excel dashboards
- Designing visual reports for logistics and supply KPIs
- Integrating data from volumetric control systems
- Practical task: building a real-time logistics performance dashboard
Module 7: Embedding AI into Logistics Workflows
- Automating routine reporting and data consolidation tasks
- Utilizing Power Automate or Excel macros for task automation
- Setting up alert systems for inventory or delivery thresholds
- Practical example: AI-driven alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Strategy for Logistics and Supply
- Creating a step-by-step AI implementation roadmap
- Selecting pilot use cases and defining success metrics
- Expanding AI-assisted workflows across teams
- Fostering continuous improvement and knowledge sharing practices
Summary and Next Steps
Requirements
- Foundational skills in Microsoft Excel or Google Sheets
- No previous experience with Artificial Intelligence is necessary
Target Audience
- Logistics and supply chain professionals in the fuel transport and retail industry
- Operations and inventory coordinators
- Supervisors and planners overseeing fleet routing and fuel deliveries
