Amber is an electrical car sharing company, focusing on business users, offering almost 200 cars at more than 50 hubs in the Netherlands. Amber worked together with Itility to create a prediction model.

Not having enough cars available at a hub to meet demand will mean Amber will be missing revenue (and even paying extra by providing a taxi), but more importantly it will mean disappointed customers. On the other hand, having too many cars at a hub means they are not driving around and will cost money instead of earning it. Because of this, it’s very important to make accurate predictions of demand-per-hub for every shift, to be able to distribute the cars among hubs in the most optimal way.

We’ve created a decision-tree based model that takes into account data from many internal and public sources, such as historical Amber usage data, weather forecasts, traffic information, etc.

The model runs every six hours and results are emailed to the operators at Amber, providing them with a forecast for each hub at the moment they are starting to plan the next shift.