Supply Chain Analytics & Metrics Training Course

This course equips participants with the analytical skills and practical knowledge required to measure, analyze, and optimize supply chain performance using data-driven approaches. It focuses on key supply chain metrics, data collection and visualization techniques, predictive analytics, performance dashboards, and decision-making frameworks. Participants will learn how to transform supply chain data into actionable insights that improve efficiency, reduce costs, and enhance overall operational performance.

Target Groups

• Supply chain analysts and managers
• Procurement and logistics professionals
• Operations and warehouse managers
• Data analysts and business intelligence professionals
• Inventory and demand planning officers
• Finance and performance management staff
• Business intelligence and reporting officers
• Consultants in supply chain and operations
• Students in supply chain, analytics, or business fields

Course Objectives

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

• Understand key supply chain metrics and KPIs
• Collect, clean, and analyze supply chain data effectively
• Develop and use supply chain dashboards and reports
• Apply descriptive and predictive analytics in supply chain management
• Measure performance across procurement, logistics, and inventory functions
• Identify inefficiencies and improvement opportunities using data
• Support data-driven decision-making in operations
• Improve supply chain visibility and transparency
• Apply forecasting techniques for demand and supply planning
• Optimize supply chain performance using analytics tools

Course Modules

Module 1: Introduction to Supply Chain Analytics

• Overview of supply chain analytics
• Importance of data-driven decision-making
• Types of analytics: descriptive, diagnostic, predictive, prescriptive
• Role of analytics in supply chain optimization
• Key components of supply chain data systems

Module 2: Supply Chain Key Performance Indicators (KPIs)

• Definition and importance of KPIs
• Procurement, inventory, and logistics KPIs
• Service level and customer satisfaction metrics
• Cost and efficiency indicators
• KPI selection and alignment with business goals

Module 3: Data Collection and Management in Supply Chain

• Sources of supply chain data
• Data quality and validation techniques
• Data integration from multiple systems
• Data governance and management practices
• Introduction to ERP and supply chain systems

Module 4: Data Analysis Techniques for Supply Chain

• Descriptive statistical analysis
• Trend and pattern analysis
• Root cause analysis
• Comparative performance analysis
• Introduction to analytical tools and software

Module 5: Supply Chain Dashboards and Visualization

• Principles of effective data visualization
• Designing supply chain dashboards
• Key dashboard components and layout
• Use of charts, graphs, and heat maps
• Tools for visualization (Excel, Power BI, Tableau)

Module 6: Demand Forecasting and Predictive Analytics

• Fundamentals of demand forecasting
• Time series analysis techniques
• Regression-based forecasting models
• Forecast accuracy measurement
• Applications of predictive analytics in supply chain

Module 7: Inventory and Logistics Analytics

• Inventory turnover and optimization metrics
• Stock level analysis and safety stock calculations
• Transportation and distribution metrics
• Warehouse performance analysis
• Reducing logistics costs through analytics

Module 8: Supplier and Procurement Analytics

• Supplier performance measurement
• Spend analysis techniques
• Supplier risk analytics
• Procurement efficiency metrics
• Category and sourcing analytics

Module 9: Supply Chain Performance Optimization

• Identifying bottlenecks in supply chain processes
• Process improvement using analytics insights
• Cost optimization strategies
• Lean and agile supply chain principles
• Continuous performance improvement frameworks

Module 10: Capstone Project and Case Studies

• Real-world supply chain analytics scenarios
• Group project: building a supply chain dashboard
• Case study analysis of supply chain performance improvements
• Predictive analytics simulation exercise
• Emerging trends in AI-driven supply chain analytics and automation