Machine learning and artificial intelligence not only present themselves through Alexa, Siri or Cortana but are buzzwords for disruptive transformation in industrial sectors. A similar potential is attributed to quantum computing which is still in an early stage of development but simultaneously growing rapidly.

Our presentation pursues to show you a story of the development of an algorithm that contains both technologies. Therefore, we have created a very clever detective recognizing anomalies and differentiating into wrong and right.

Keywords are generative adversarial networks and quantum classical hybrid autoencoder.

To get away from the theory, we want to inform you about our practice as consultants, developers as well as project “PlanQK” where we have developed our algorithm.

Queue vadis? How machine learning helps to optimize the shopping experience at the Lidl checkout zone.

At Lidl Analytics, we build data science solutions to tackle business questions that occur along the entire value chain of the organization using a data-driven perspective. Our talk will focus on one of the most central parts of every shopping trip: queueing and paying at the tills.

We will show how we at Lidl Analytics tackle two fundamental aspects of stores’ till processes using state-of-the-art machine learning solutions.

On the one hand, we showcase a project that uses time series forecasting and discrete event simulation to predict the future demand at tills in the upcoming weeks to aid fine-granular shift planning.
On the other hand, we discuss an interactive dashboard that helps to anticipate and find the optimal number of installed tills in a store to avoid long queues already at the store planning stage by estimating queueing times and checkout capacities for different till combinations.