COURSE OVERVIEW

 

This practical and highly-interactive course includes various practical sessions and exercises. Theory learnt will be applied using our state-of-the-art simulators. 

 

This course is designed to provide delegates with a detailed and up-to-date overview of Big Data Analytics for Supply Chain Optimization. It covers the key characteristics and importance of big data in modern supply chain management; the role of data-driven decision-making and challenges and opportunities in big data analytics; the big data sources in supply chain, logistics and methods for big data analysis and forecasting; the data storage and processing technologies; the importance of data accuracy, consistency and completeness; and ensuring data security and compliance. 

 

Further, the course will also discuss the supply chain data through visualization; identifying hidden patterns in logistics and inventory and using Python and R for basic data exploration; the advanced forecasting techniques with big data; predicting stock levels and demand fluctuations and reducing stockouts and excess inventory costs; identifying  and mitigating risks using data analytics; and the scenario analysis and risk prediction models, supplier risk assessment and early warning systems and real-time monitoring of disruptions. 

During this interactive course, participants will learn how social media impacts supply chain decisions; the sentiment analysis tools and techniques; the digital twins and virtual supply chain models; optimizing supply chain networks using big data; the profit maximization and cost reduction, predictive maintenance and asset management in supply chain; the importance of real-time analytics in logistics and manufacturing; the AI and machine learning for supply chain decision-making; how blockchain ensures traceability and trust and the challenges and adoption barriers; the new market opportunities using analytics, designing effective supply chain KPIs, using dashboards for real-time monitoring and integrating data sources for holistic insights; the emerging technologies in supply chain analytics; and implementing big data analytics in the organization.