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Duration 14 hours
Course Outline
Module 1: Introduction to Artificial Intelligence in Logistics and Supply
- Fundamental concepts and strategic applications of Artificial Intelligence
- Strategic opportunities and operational impact of AI in logistics and fuel distribution
- No-code AI solutions including Excel AI, ChatGPT, Power BI, and related platforms
- Operational case studies from the transportation and fuel sectors
Module 2: Structuring and Analyzing Operational Data
- Identification of critical logistics and supply datasets (routes, tank capacities, delivery schedules)
- Organization of volumetric control and inventory records for AI integration
- Data hygiene, formatting, and validation procedures in Excel
- Construction of dynamic tables and pivot charts for analytical insight
Module 3: AI-Assisted Forecasting for Fuel Demand
- Principles of demand forecasting and key influencing variables
- Application of Excel AI features and ChatGPT for predictive modeling
- Prediction of short-term (1–2 week) fuel demand patterns
- Practical exercise: development of a basic forecast model using existing datasets
Module 4: Route Planning and Resource Optimization
- Core principles of route optimization and scheduling methodologies
- Utilization of AI tools to determine optimal routes and delivery sequences
- Implementation of Excel and ChatGPT for route planning within real-world constraints
- Practical activity: generation of route alternatives for delivery units
Module 5: Cost Estimation and Logistics Optimization
- Identification of cost factors: distance, tolls, fuel consumption, and freight expenses
- Application of AI models for logistics cost estimation
- Evaluation of manual versus AI-assisted cost planning processes
- Development of cost calculation templates with dynamic input variables
Module 6: Dashboards and KPI Visualization
- Introduction to Power BI and Excel dashboard capabilities
- Design of visual reports for logistics and supply Key Performance Indicators (KPIs)
- Integration of data from volumetric control systems
- Practical session: creation of a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Workflows
- Automation of recurring reporting and data consolidation tasks
- Implementation of Power Automate or Excel macros for process automation
- Development of alert mechanisms for inventory or delivery thresholds
- Operational example: AI-driven alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Development of a phased AI implementation roadmap
- Selection of pilot use cases and definition of success metrics
- Expansion of AI-assisted workflows across organizational teams
- Establishment of continuous improvement and knowledge-sharing protocols
Summary and Next Steps
Requirements
- Proficiency in Microsoft Excel or Google Sheets
- No prior experience with Artificial Intelligence is required
Target Audience
- Logistics and supply professionals in the fuel transportation and sales industry
- Operations and inventory coordinators
- Supervisors and planners managing fleet routes and fuel delivery
