About Rogier
Rogier is a seasoned Data Scientist and Machine Learning Engineer with experience in a broad range of projects. Before switching to consultancy at Xebia Data, he finished a PhD in Particle Physics. With a passion for applying data science to solve real-world problems, he is driven by the desire to make a positive impact on society through his work. He strongly believes in the power of knowledge sharing and understands the importance of building a skilled team around a project.
The Talk
Scaling up Albert Heijn’s AI-powered demand forecasting
In this session, Lonneke and Rogier will share how Albert Heijn has transformed its approach to demand forecasting by embracing AI technology.
For a retailer like Albert Heijn, having the right amount of stock is essential to ensure customers find what they need while minimizing food waste. Traditionally, this delicate balance relied heavily on manual adjustments. However, three years ago, Albert Heijn began using AI to enhance its ability to predict customer demand, allowing for more accurate and dynamic forecasts.
Lonneke and Rogier will walk you through the journey of scaling AI predictions across a large organization. They will delve into the practicalities of moving from manually handling six products to automatically managing forecasts for over 30,000 items. Along the way, they’ll discuss the challenges faced in deploying machine learning at scale, including technical hurdles and organizational shifts. You’ll gain a better understanding of the key factors that influence successful machine learning integration, and the session will highlight a notable 5% increase in forecast accuracy that has positively impacted operations.