Description:
This program equips supply chain professionals with the skills to collect, analyze, and interpret supply chain data to drive efficiency, reduce costs, and improve decision-making. Participants learn to use data analytics, visualization tools, and predictive modeling to optimize supply chain operations, including inventory management, procurement, logistics, and demand forecasting.

Learning Objectives:

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

• Understand the role of data analytics in supply chain management
• Collect, clean, and manage supply chain data from multiple sources
• Apply statistical and analytical techniques to identify trends, patterns, and anomalies
• Develop dashboards and visualizations to communicate insights effectively
• Use predictive analytics to improve forecasting, inventory, and logistics planning
• Support strategic and operational decision-making with data-driven insights
• Identify opportunities for process improvement and cost reduction
• Ensure compliance and data accuracy in supply chain reporting

Target Audience:

• Supply Chain Analysts
• Logistics and Procurement Professionals
• Operations Managers
• Inventory and Warehouse Managers
• Data Analysts in Supply Chain Functions
• IT Professionals supporting Supply Chain Analytics

Training Contents:

Module 1: Introduction to Supply Chain Analytics

• Overview of supply chain management functions
• Importance of data-driven decision-making
• Key performance indicators (KPIs) in supply chain

Module 2: Data Collection and Management

• Identifying relevant data sources (ERP, WMS, TMS, procurement systems)
• Data cleaning, validation, and preprocessing
• Data integration from multiple sources

Module 3: Descriptive and Diagnostic Analytics

• Descriptive statistics for supply chain data
• Variance, trend, and root cause analysis
• Understanding demand, inventory, and production metrics

Module 4: Predictive Analytics for Supply Chain

• Forecasting demand using statistical models
• Inventory optimization using predictive models
• Risk and scenario analysis for supply chain disruptions

Module 5: Prescriptive Analytics and Optimization

• Recommending optimal decisions using analytics
• AI and machine learning applications in supply chain
• Route and logistics optimization
• Supplier selection and procurement optimization

Module 6: Visualization and Reporting

• Using dashboards and visualization tools (Power BI, Tableau, Qlik)
• Creating actionable reports for management
• Communicating insights to non-technical stakeholders

Module 7: Advanced Analytics Applications

• Network optimization and capacity planning
• Lean supply chain and cost reduction analytics
• Sustainability and ESG reporting in supply chain

Module 8: Tools, Technologies, and Case Studies

• Supply chain analytics software and platforms
• Real-world case studies and projects
• Hands-on exercises with sample supply chain datasets

Training Delivery Methods:

• Instructor-led lectures
• Hands-on exercises with analytics tools
• Group discussions and problem-solving workshops
• Case studies and scenario-based exercises
• Assessments, quizzes, and a final project

Duration:

• 3–5 days (24–40 hours) depending on depth and hands-on exercises

Certification:

• Certificate of Completion: Certified Supply Chain Data Analyst (CSCDA)
• Optional alignment with professional credentials: APICS CPIM, CIPS, or Six Sigma Green Belt