Data Analytics for Operations, Supply Chain & Logistics Training Course

This course trains participants to apply data analytics for optimizing operations, supply chain, and logistics performance. It emphasizes building predictive models, BI dashboards, and real-time monitoring tools to enhance efficiency, reduce costs, and strengthen resilience in global supply chains.

Target Groups

• Supply chain and logistics professionals
• Operations and production managers
• Procurement and inventory specialists
• Business analysts in supply chain functions
• Risk and compliance officers
• Consultants in supply chain optimization
• Students pursuing operations, logistics, or business analytics

Course Objectives

By the end of this course, participants will be able to:

1. Understand the role of analytics in operations and supply chain management.
2. Apply BI tools to procurement, logistics, and inventory.
3. Use predictive analytics for demand forecasting and risk assessment.
4. Develop dashboards for monitoring supply chain KPIs.
5. Optimize transportation, warehousing, and distribution using data.
6. Strengthen supply chain resilience and agility with analytics.
7. Align analytics with sustainability and ESG objectives.
8. Apply best practices in global supply chain analytics.

Course Modules

Module 1: Introduction to Operations & Supply Chain Analytics

• Role of analytics in supply chain management
• Key BI applications in logistics and operations
• Benefits and challenges of adoption
• Case for data-driven supply chains

Module 2: Data Management for Supply Chain Analytics

• Sources of supply chain and logistics data
• Data integration across procurement, inventory, and logistics
• Ensuring quality and governance of supply chain data
• Overcoming challenges in fragmented systems

Module 3: Procurement and Supplier Analytics

• Supplier performance dashboards
• Predictive models for supplier selection
• Risk and compliance in procurement
• Cost optimization using analytics

Module 4: Logistics and Transportation Analytics

• Real-time tracking of shipments
• Route optimization with BI tools
• Fuel efficiency and cost reduction
• Predictive insights for logistics disruptions

Module 5: Inventory Management Optimization

• Demand forecasting for inventory planning
• Reducing stock-outs and overstocking
• Warehouse performance monitoring
• Cost reduction through inventory analytics

Module 6: Operations and Production Analytics

• Production efficiency monitoring
• Predictive maintenance in manufacturing
• Workforce productivity analytics
• Case studies in operational optimization

Module 7: Risk and Resilience in Supply Chains

• Identifying supply chain risks with analytics
• Scenario modeling for disruptions
• Early warning indicators for resilience
• BI dashboards for risk management

Module 8: Sustainability and ESG in Supply Chains

• Tracking carbon footprint in logistics
• Reducing waste and emissions with BI
• ESG reporting for supply chain operations
• Aligning analytics with sustainability goals

Module 9: Tools and Technology for Supply Chain Analytics

• BI tools for supply chain (Power BI, Tableau, Qlik, SAP)
• IoT and blockchain in logistics data management
• AI and machine learning in predictive supply chain analytics
• Cloud-based platforms for global supply chain monitoring

Module 10: Case Studies and Applications

• Real-world applications of supply chain analytics
• Industry-specific case studies (retail, manufacturing, shipping)
• Hands-on exercises with supply chain dashboards
• Best practices for BI-driven supply chain excellence