Home→Courses→Supply Chain Analytics and Optimization Training Course
Logistics and Supply Chain Management
Supply Chain Analytics and Optimization Training Course
Introduction
In today's hyper-competitive global market, mastering Supply Chain Analytics and Optimization is critical for any organization aiming to improve operational efficiency, reduce costs, and maximize customer satisfaction. Supply Chain Analytics and Optimization Training Course equips participants with the analytical skills and technological insights needed to analyze, forecast, and optimize end-to-end supply chain operations using real-time data, machine learning, and advanced software tools such as SAP, Python, and Tableau. With increasing volatility in demand and supply networks, professionals must integrate data-driven strategies with predictive analytics and optimization models to maintain agility and resilience.
This course empowers supply chain professionals, data analysts, and decision-makers with practical knowledge in demand forecasting, inventory optimization, transportation modeling, network design, and risk management. Each module integrates cutting-edge tools, real-world case studies, and simulation-based learning to provide actionable insights for strategic and tactical supply chain decisions. Whether in manufacturing, retail, logistics, or e-commerce, the course enhances decision-making across sourcing, planning, and distribution processes to drive supply chain visibility, profitability, and sustainability.
Programme Curriculum
Supply Chain Analytics and Optimization Training Course
Introduction
In today's hyper-competitive global market, mastering Supply Chain Analytics and Optimization is critical for any organization aiming to improve operational efficiency, reduce costs, and maximize customer satisfaction. Supply Chain Analytics and Optimization Training Course equips participants with the analytical skills and technological insights needed to analyze, forecast, and optimize end-to-end supply chain operations using real-time data, machine learning, and advanced software tools such as SAP, Python, and Tableau. With increasing volatility in demand and supply networks, professionals must integrate data-driven strategies with predictive analytics and optimization models to maintain agility and resilience.
This course empowers supply chain professionals, data analysts, and decision-makers with practical knowledge in demand forecasting, inventory optimization, transportation modeling, network design, and risk management. Each module integrates cutting-edge tools, real-world case studies, and simulation-based learning to provide actionable insights for strategic and tactical supply chain decisions. Whether in manufacturing, retail, logistics, or e-commerce, the course enhances decision-making across sourcing, planning, and distribution processes to drive supply chain visibility, profitability, and sustainability.
Course Objectives
Understand the role of Supply Chain Analytics in modern business operations.
Apply descriptive, predictive, and prescriptive analytics to supply chain problems.
Utilize Big Data tools and machine learning algorithms for demand forecasting.
Optimize inventory management using simulation and statistical models.
Analyze transportation networks for cost and service efficiency.
Implement supply chain risk management strategies using scenario analysis.
Use network design models to enhance supply chain responsiveness.
Apply data visualization tools like Tableau to communicate supply chain metrics.
Integrate ERP systems (e.g., SAP, Oracle) for seamless analytics implementation.
Assess the environmental impact using sustainable supply chain metrics.
Leverage AI and IoT for real-time supply chain monitoring and optimization.
Perform cost-to-serve analysis for improved profitability.
Build an end-to-end data-driven decision-making framework.
Target Audiences
Supply Chain Managers
Data Analysts and Data Scientists
Logistics and Operations Professionals
Procurement and Inventory Managers
IT and ERP Professionals
Business Intelligence Analysts
Manufacturing and Retail Professionals
MBA and Postgraduate Students in SCM or Analytics
Course Duration: 5 days
Course Modules
Module 1: Fundamentals of Supply Chain Analytics
Introduction to supply chain systems and flows
Types of analytics: descriptive, predictive, prescriptive
Role of data in supply chain decision-making
Key metrics and performance indicators (KPIs)
Tools and platforms overview (Excel, Python, Tableau)
Case Study: Analytics adoption in a global electronics supply chain
Module 2: Demand Forecasting and Planning
Forecasting techniques: time-series, regression, ML
Handling seasonality and variability
Collaborative planning with suppliers and customers
Integrating forecast with ERP systems
KPI dashboards for forecast accuracy
Case Study: Forecasting demand in the apparel retail industry
Module 3: Inventory Analytics and Optimization
Inventory classifications and policies
EOQ, safety stock, and reorder point calculations
Multi-echelon inventory optimization
Inventory turnover analysis
Using Python for inventory simulation
Case Study: Reducing excess stock in a pharmaceutical supply chain
Module 4: Transportation and Logistics Optimization
Route optimization algorithms (TSP, VRP)
Carrier selection and freight analysis
Last-mile delivery modeling
Cross-docking and consolidation strategies
Cost-to-serve analysis
Case Study: Optimizing delivery routes for an e-commerce firm
Module 5: Network Design and Facility Location
Facility location modeling techniques
Supply chain network structure and design
Trade-offs between cost, time, and flexibility
Scenario planning and capacity analysis
Linear and mixed-integer programming for design
Case Study: Designing a distribution network for a food company
Module 6: Risk Analytics in the Supply Chain
Identifying and quantifying supply chain risks
Probabilistic and stochastic modeling
Resilience and contingency planning
Supplier risk evaluation tools
Stress testing and scenario simulations
Case Study: Managing supply chain disruptions during COVID-19
Module 7: Advanced Tools: Machine Learning, AI & IoT
Machine learning for demand sensing and prediction
IoT sensors for real-time visibility
AI applications in procurement and warehouse automation
Integrating ML models with ERP systems
Ethical considerations and data privacy
Case Study: Using AI for warehouse operations in automotive supply chains
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to FINESKILL TRAINING CENTER account, as indicated in the invoice so as to enable us prepare better for you.