About the Course
Modern supply chains are evolving from reactive, intuition-based operations into proactive, data-driven ecosystems. The transition from simple production oversight to advanced predictive analytics allows organizations to anticipate market disruptions, optimize inventory levels, and eliminate costly bottlenecks before they occur.
This course explores the full spectrum of supply chain analytics, moving from descriptive historical reports to machine-learning-driven predictive and prescriptive models. Participants will learn how to leverage IoT data, route optimization algorithms, demand forecasting techniques, and digital twins to build resilient, efficient, and future-ready supply networks.
Course Objective
- To understand the maturity stages of supply chain analytics, from descriptive reporting to predictive and prescriptive optimization
- To apply machine learning and data science techniques to improve demand forecasting, reduce the bullwhip effect, and optimize inventory
- To leverage emerging technologies such as IoT sensors, digital twins, and route optimization algorithms to drive operational resilience
Course Outline
- The Evolution of Supply Chain Analytics- Shifting from reactive production tracking to predictive end-to-end visibility
- The four stages of analytics: Descriptive, Diagnostic, Predictive, and Prescriptive
- Predictive Demand Forecasting and Inventory Optimization- Using machine learning to analyze multi-variable market trends and seasonality
- Mitigating the Bullwhip Effect through shared data and point-of-sale visibility
- IoT and Predictive Maintenance in Logistics and Operations- Leveraging real-time sensor streams to forecast machinery failures before downtime occurs
- Monitoring cargo conditions, temperature sensitivity, and asset health in transit
- Route Optimization and Last-Mile Efficiency- Algorithmic route planning factoring in traffic, fleet capacity, and fuel constraints
- Building agile delivery networks responsive to real-time disruptions
- Digital Twins and Advanced Supply Chain Simulations- Creating virtual replicas of physical supply chains to stress-test risk scenarios
- Overcoming data siloes, legacy integration hurdles, and data quality challenges
Target Participants
This course is designed for:
- Supply chain managers, logistics directors, and procurement specialists
- Data analysts and operations research professionals working in manufacturing and distribution
- Operations leaders looking to integrate machine learning and IoT into legacy systems
- Business leaders seeking to reduce inventory carrying costs and mitigate disruption risks
Certificate Requirements
- Completion of recorded webinar + quiz
- Pass the 10-item multiple choice with 80% mark
- Comment your feedback on the main page of the course
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