Business Intelligence for Supply Chain Analytics Training Course

Description

This course equips participants with practical skills to apply Business Intelligence (BI) tools and analytics techniques to improve supply chain visibility, efficiency, and decision-making. It focuses on procurement analytics, demand forecasting, inventory optimization, logistics performance, supplier analysis, and end-to-end supply chain monitoring. Participants will learn how to transform supply chain data into actionable insights that reduce costs, improve service levels, and enhance operational resilience.

Target Groups

Supply chain and logistics managers
Procurement and purchasing officers
Inventory and warehouse managers
Operations and production planners
Business intelligence and data analysts
Demand and planning specialists
Finance and cost management teams
Manufacturing and distribution professionals
Public and private sector supply chain teams

Course Objectives

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

Understand BI applications in supply chain management
Analyze supply chain performance using key metrics and KPIs
Improve demand forecasting and inventory planning
Evaluate supplier performance and procurement efficiency
Optimize logistics and distribution processes
Build supply chain dashboards and reporting systems
Identify bottlenecks and inefficiencies using data
Enhance end-to-end supply chain visibility
Support data-driven procurement and operational decisions
Strengthen supply chain resilience and cost control

Course Modules

Module 1: Introduction to Supply Chain Analytics & BI

Overview of supply chain management and BI
Role of analytics in modern supply chains
End-to-end supply chain visibility concepts
Key supply chain metrics and KPIs
Data-driven supply chain decision-making

Module 2: Supply Chain Data Sources and Integration

ERP, procurement, and logistics systems data
Warehouse and inventory data sources
Transportation and shipment tracking data
Data integration and consolidation techniques
Data quality management in supply chains

Module 3: Demand Forecasting and Planning Analytics

Demand forecasting methods and models
Seasonal and trend analysis
Sales and operations planning (S&OP)
Forecast accuracy measurement
Scenario planning and demand variability

Module 4: Inventory Optimization and Management

Inventory classification (ABC analysis)
Safety stock and reorder point analysis
Inventory turnover and holding cost analysis
Stock optimization strategies
Reducing excess and stockouts

Module 5: Procurement and Supplier Analytics

Supplier performance evaluation metrics
Cost analysis and procurement efficiency
Supplier risk assessment
Contract and spend analysis
Strategic sourcing insights using BI

Module 6: Logistics and Distribution Analytics

Transportation performance metrics
Delivery time and route optimization
Freight cost analysis
Warehouse performance tracking
Last-mile delivery analytics

Module 7: Supply Chain Dashboards and Reporting

Designing supply chain control towers
Real-time monitoring dashboards
KPI visualization and tracking
Exception-based reporting systems
Executive supply chain reporting

Module 8: Performance Optimization and Cost Reduction

Identifying inefficiencies in supply chains
Cost-to-serve analysis
Process optimization techniques
Lean supply chain principles
Data-driven cost reduction strategies

Module 9: Risk Management and Supply Chain Resilience

Identifying supply chain risks
Disruption prediction and mitigation
Supplier and logistics risk monitoring
Scenario planning for disruptions
Building resilient supply chains using analytics

Module 10: Capstone Project and Case Studies

Building an end-to-end supply chain analytics dashboard
Case studies of supply chain optimization using BI
Demand forecasting and inventory optimization exercise
Supplier performance analysis project
Emerging trends: AI-driven supply chain analytics, real-time visibility platforms, predictive logistics optimization, autonomous supply chain systems, and intelligent control tower solutions