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Duration 14 hours
Course Outline
Module 1: Foundations of AI in Logistics and Supply
- Exploring Artificial Intelligence: Key concepts and use cases
- AI in fuel distribution and logistics: Potential benefits and strategic impact
- Overview of no-code AI tools: Excel AI capabilities, ChatGPT, Power BI, and more
- Real-world examples from the transport and fuel sectors
Module 2: Organizing and Interpreting Operational Data
- Recognizing critical logistics and supply datasets (including routes, tanks, and deliveries)
- Preparing volumetric control and inventory data for AI integration
- Data hygiene, formatting, and validation techniques in Excel
- Generating insights through dynamic tables and pivot charts
Module 3: AI-Driven Fuel Demand Forecasting
- Understanding demand prediction and key influencing factors
- Leveraging Excel’s AI features and ChatGPT for predictive modeling
- Projecting short-term (1–2 week) fuel demand patterns
- Practical task: Creating a basic forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Core principles of route optimization and scheduling
- Using AI tools to recommend efficient routes and delivery sequences
- Applying Excel and ChatGPT for route planning under real-world constraints
- Hands-on activity: Generating route alternatives for delivery vehicles
Module 5: Cost Estimation and Logistics Efficiency
- Identifying key cost components: distance, tolls, fuel usage, and freight
- Employing AI models for accurate logistics cost projections
- Contrasting manual versus AI-assisted cost planning methods
- Developing cost calculation templates with variable inputs
Module 6: Dashboards and KPI Visualization
- Basics of Power BI and Excel-based dashboard creation
- Designing visual reports for logistics and supply chain KPIs
- Incorporating data from volumetric control systems
- Practical session: Building a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Operations
- Automating routine reporting and data aggregation tasks
- Utilizing Power Automate or Excel macros for workflow automation
- Setting up alert systems for inventory levels and delivery milestones
- Case study: Implementing AI-triggered alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Strategy for Logistics and Supply
- Constructing a phased AI implementation roadmap
- Selecting pilot projects and defining success indicators
- Expanding AI-assisted processes across teams
- Implementing continuous improvement and knowledge-sharing frameworks
Conclusion and Future Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No prior background in Artificial Intelligence is necessary
Target Audience
- Logistics and supply chain specialists within the fuel transport and retail sectors
- Operations and inventory coordination professionals
- Supervisors and planners responsible for fleet routing and fuel distribution
