Supply Chain Analytics & BI Training Course

This course equips participants with the knowledge and practical skills required to apply Business Intelligence (BI) and analytics in supply chain management. It focuses on demand forecasting, inventory optimization, procurement analytics, logistics performance, supplier management, and end-to-end supply chain visibility. Participants will learn how to improve efficiency, reduce costs, and enhance decision-making across supply chain operations using data-driven insights.

Target Groups

• Supply chain and logistics managers
• Procurement and purchasing officers
• Operations and warehouse managers
• Business intelligence and data analysts
• Inventory and demand planning specialists
• Manufacturing and production planners
• Government and NGO supply chain officers
• Students and professionals in supply chain management, logistics, and analytics

Course Objectives

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

• Understand principles of supply chain analytics and BI
• Analyze end-to-end supply chain performance using data
• Improve demand forecasting and inventory planning
• Optimize procurement and supplier performance
• Enhance logistics and distribution efficiency
• Develop supply chain dashboards and reports
• Identify bottlenecks and inefficiencies in supply chains
• Support strategic supply chain decision-making
• Reduce operational costs through data insights
• Improve supply chain resilience and responsiveness

Course Modules

Module 1: Introduction to Supply Chain Analytics and BI

• Overview of supply chain management systems
• Role of BI in supply chain optimization
• Key supply chain processes and data flows
• Types of supply chain data
• Importance of data-driven supply chain decisions

Module 2: Supply Chain Data and KPIs

• Key supply chain performance indicators (KPIs)
• Procurement, inventory, and logistics metrics
• Service level and fulfillment rate analysis
• Cost and efficiency indicators
• Designing KPI frameworks for supply chains

Module 3: Demand Forecasting and Planning

• Fundamentals of demand forecasting
• Time series and trend analysis for demand
• Forecast accuracy and error measurement
• Seasonal demand patterns
• Improving demand planning using analytics

Module 4: Inventory Management Analytics

• Inventory control systems and models
• Stock optimization techniques
• Safety stock and reorder point analysis
• Inventory turnover and aging analysis
• Reducing stockouts and overstocking

Module 5: Procurement and Supplier Analytics

• Supplier performance evaluation
• Procurement spend analysis
• Vendor risk assessment and scoring
• Contract compliance monitoring
• Strategic sourcing using data insights

Module 6: Logistics and Distribution Analytics

• Transportation and delivery performance metrics
• Route optimization and cost reduction
• Warehouse performance analysis
• Last-mile delivery analytics
• Improving logistics efficiency

Module 7: Supply Chain Risk and Resilience Analytics

• Identifying supply chain risks
• Disruption analysis and mitigation strategies
• Building resilient supply chains
• Risk monitoring dashboards
• Scenario planning and simulation models

Module 8: Supply Chain Dashboards and Visualization

• Designing supply chain control towers
• Real-time monitoring dashboards
• Visualizing supply chain KPIs
• Storytelling with operational data
• Executive reporting for decision-makers

Module 9: BI Tools for Supply Chain Analytics

• Overview of BI tools in supply chain management
• Integrating ERP and SCM systems
• Real-time data tracking and reporting
• Automated supply chain analytics workflows
• Using Microsoft Excel for inventory tracking, procurement analysis, and supply chain reporting

Module 10: Capstone Project and Case Studies

• Development of an end-to-end supply chain analytics dashboard
• Case studies on supply chain optimization success stories
• Group exercises on demand forecasting and inventory optimization
• Simulated supply chain disruption and recovery scenarios
• Emerging trends in supply chain analytics, including AI-driven forecasting, predictive logistics, autonomous supply chains, IoT-enabled tracking systems, and real-time decision intelligence platforms