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Duration 14 hours
Course Outline
Module 1: AI Fundamentals in Logistics and Supply
- Comprehending Artificial Intelligence: core concepts and real-world applications
- AI in logistics and fuel distribution: potential benefits and operational impact
- Exploring no-code AI tools: Excel AI, ChatGPT, Power BI, and more
- Case studies from the transportation and fuel sectors
Module 2: Organizing and Interpreting Operational Data
- Recognizing critical logistics and supply datasets (routes, tanks, deliveries)
- Structuring volumetric control and inventory data for AI processing
- Data cleaning, formatting, and validation techniques in Excel
- Building dynamic tables and pivot charts to generate actionable insights
Module 3: AI-Driven Forecasting for Fuel Demand
- Understanding demand forecasting and key influencing factors
- Leveraging Excel’s AI capabilities and ChatGPT for predictive analysis
- Predicting short-term (1–2 week) fuel demand patterns
- Practical task: developing a simple forecast model using existing data
Module 4: Route Planning and Resource Efficiency
- Core concepts in route optimization and scheduling
- Utilizing AI tools to recommend optimal routes and delivery sequences
- Applying Excel and ChatGPT for route planning under real-world constraints
- Hands-on activity: generating route alternatives for delivery units
Module 5: Cost Analysis and Logistics Efficiency
- Identifying cost factors: distance, tolls, fuel consumption, and freight
- Employing AI models to calculate logistics expenses
- Evaluating manual versus AI-assisted cost planning methods
- Designing cost calculation templates with dynamic input parameters
Module 6: Dashboards and KPI Visualization
- Overview of Power BI and Excel dashboard features
- Creating visual reports for logistics and supply KPIs
- Integrating data from volumetric control systems
- Practical exercise: building a real-time logistics performance dashboard
Module 7: Embedding AI into Logistics Processes
- 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 deadlines
- Real-world example: AI-driven alerts for tank refill scheduling
Module 8: 90-Day AI Implementation Plan for Logistics and Supply
- Constructing a phased AI adoption roadmap
- Selecting pilot projects and defining success indicators
- Expanding AI-assisted workflows across teams
- Fostering a culture of continuous improvement and knowledge exchange
Conclusion and Future Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets is essential
- No previous experience with Artificial Intelligence is necessary
Target Audience
- Logistics and supply specialists in the fuel transportation and retail industry
- Operations and inventory coordination staff
- Supervisors and planners responsible for fleet routing and fuel delivery
