Course Outline

Module 1: Introduction to AI in Logistics and Supply

  • Understanding Artificial Intelligence: concepts and applications
  • AI in logistics and fuel distribution: opportunities and impact
  • No-code AI tools: Excel AI, ChatGPT, Power BI, and others
  • Practical examples from the transportation and fuel industry

Module 2: Structuring and Analyzing Operational Data

  • Identifying key logistics and supply datasets (routes, tanks, deliveries)
  • Organizing volumetric control and inventory data for AI use
  • Data cleaning, formatting, and validation in Excel
  • Creating dynamic tables and pivot charts for insight generation

Module 3: AI-Assisted Forecasting for Fuel Demand

  • Understanding demand forecasting and influencing variables
  • Using Excel’s AI features and ChatGPT for predictive analysis
  • Forecasting short-term (1–2 week) fuel demand trends
  • Practical exercise: building a simple forecast model with existing data

Module 4: Route Planning and Resource Optimization

  • Key concepts in route optimization and scheduling
  • Using AI tools to suggest optimal routes and delivery sequences
  • Applying Excel and ChatGPT for route planning with real constraints
  • Hands-on activity: generating route options for delivery units

Module 5: Cost Estimation and Logistics Optimization

  • Identifying cost drivers: distance, tolls, fuel consumption, freight
  • Using AI models to estimate logistics costs
  • Comparing manual vs. AI-assisted cost planning
  • Building cost calculation templates with dynamic inputs

Module 6: Dashboards and KPI Visualization

  • Introduction to Power BI and Excel dashboards
  • Designing visual reports for logistics and supply KPIs
  • Integrating data from volumetric control systems
  • Hands-on: creating a real-time logistics performance dashboard

Module 7: Integrating AI into Logistics Workflows

  • Automating repetitive reporting and data consolidation tasks
  • Using Power Automate or Excel macros for task automation
  • Creating alert systems for inventory or delivery thresholds
  • Practical example: AI-based alert for tank refill scheduling

Module 8: 90-Day AI Adoption Plan for Logistics and Supply

  • Building a step-by-step AI implementation roadmap
  • Identifying pilot use cases and success metrics
  • Scaling AI-assisted workflows across teams
  • Establishing continuous improvement and knowledge-sharing practices

Summary and Next Steps

Requirements

  • Basic proficiency with Microsoft Excel or Google Sheets
  • No prior experience with Artificial Intelligence required

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
 14 Hours

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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