Who should attend
All individuals who have a role in Supply Chain and Logistics:
- All Leaders and Professionals
- Management Professionals
- Team Leaders
- Technical Staff
- Operation Personnel
About the course
This highly-interactive Oxford training seminar will provide the adequate knowledge of hot to tackle the issues within the Supply Chains of today and the future.
It will help people involved in Supply Chain and Logistics learn skills and techniques that enable them to be able to predict the requirements of the market while at the same time applying techniques that help team members optimize their activities, costs and service provision.
This Oxford training seminar will examine the latest ways to apply the Big Data Analytics techniques for Optimization of Supply Chains as well as Logistics operations and help reduce the lead time, operational costs and get into the Industry 4.0 without delay.
Specifically you will learn to:
- Identify Big Data sources in Supply Chain and Logistics?
- Apply methods for Big Data analysis and its use for forecasting
- Use a Big Data analysis results for a dynamic simulation basis
- Focus on both increasing of market share and profit as well as cost reduction
- Improve the decision making in real time, by forecasting the events based on complex behaviour
- Define the role of Supply Chain and Logistics within the Industry 4.0
- Recognise the sources and collection techniques of Big Data in Supply Chain
- Apply appropriate techniques for the analysis of Big Data within the Supply Chain
- Learn the statistical techniques for Big Data Analysis
- Optimize the Supply Chain and Logistics processes using the Big Data Analysis results
- Model a customer behaviour and future requirements
- Integrate the RFID data gathering, vehicle tracking and dynamic simulation software
Read more about Business Analytics
Read more about Transportation and Logistics
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.