The Challenge

A restaurant chain delivers freshly products to their customers. One of the challenges of the company is to understand food demand in stores and restaurants.  ​

Twice a week, restaurant managers are required to order products for next day delivery. This is a tricky task for any managers to simply anticipate the need of their clients. ​

The goal is to help restaurant managers in forecasting the demand, and to consistently achieve a good balance between food waste and shortage.

The Solution

To better predict required stocks in stores and restaurants, we used Machine learning (ML), to learn from sales tickets data. ​

In collaboration with IDLabs, a deep learning neural network was developed to predict the quantity, per product, that individual restaurant should purchase for the coming days.​

The overall solution was fully integrated, and automated within a cloud environment (Microsoft Azure). ​

The Result

Thanks to the fully automated solutions, more accurate forecasting on food demand in the restaurants is possible. ​

The result is more than just a tool to assist restaurant managers, as our solution allows for food waste reduction and increase in revenues. ​