Planning Analytics meets Machine Learning

For analysts or controllers of financial / logistic / production / supply chain planning processes, forecasting is often done manually. If this is automated, it can save a great deal of time and also generate more accurate forecasts. In this webinar we will explore the benefits of a predictive planning approach in comparison to manual planning. This can be achieved with Machine Learning or Deep Learning models.

Join us for an interactive session with live demos as we take a specific use case, build a Machine Learning model with a visual interface and Python. Next we will automate the process and integrate this into a planning tool in real-time, so a non-technical user can benefit from ML-based predictions.

Speakers:

Maximilian Burkardt is a Technical Specialist with a special focus on Planning Analytics. He has a technical background in Data Science and more than 6 years of industry experience in Retail and Supply Chain. Maximilian combines both his expertise and experience to generate business value for customers.

Alexander Richthammer is a Data Science Specialist with a background in Psychology & Sociology, specializing in Statistics. Alexander has 17 years of practical experience in Machine Learning and Predictive Analytics. He helps organizations to identify and implement successful Machine Learning projects.