top of page

Success stories

Business Case Waste Collector

Advanced last mile logistics, waste collection

The subsidiary of one 35 largest stock traded companies in Spain (IBEX35) contacted us to optimize their last-mile operations: the  collection of used oils from restaurants and other establishments in the food industry. Aware that most operating costs were related to the movement of vehicles from the establishments to their warehouses, they asked us to work on increasing the productivity of each vehicle.

Chefs in Action
The challenge

To reduce the cost of collection per ton recovered by the subsidiary on an IBEX35 corporation specialized in door-to-door waste collection, improving the quality of service for its customers.

The data

10 years of waste collection operations, including collection points, addresses, articles, quantities, dates, vehicles and routes. Vehicle and collection operating parameters. Cost structure.

The  model

"We had to design our operations in a different way. we are not able to compete in price or product, so our innovation is focused on improving our operations



Predictive models of waste generation by collection point and type of waste using neural networks. Optimization of the selection of daily collection points and routes (sequences, dispatch and day allocation)


The client was able to increase the number of average pickups by one  39% (of  16.5 a day to 23), complying with the temporary windows of the clients and reducing the number of urgent collection notices.

Innitium is currently working on the implementation of a reinforcement learning model to optimize the daily selection of collection points

HVAC maintenance

A leading provider of heating, ventilation and air conditioning equipment installation and maintenance services fcontacted us to optimize its operations in Madrid, with hundreds of daily services.

Image by Theme Photos

"We knew that our technicians had  downtime and that there was potential to introduce more daily services. Now we are capable of not only monitoring our plan, but also reprogramming it, ensuring, at the same time, quality service to customers and high utilization of our technicians.

The challenge

The company needed to improve the quality of service to end customers, increase the use of technicians (eliminating  downtime) and reduce the cost of fleet operation.

The data

More than 10 years of service operations, a combination of urgent and planned services.

The model

We introduced dynamic routing, capable of responding to intra-day changes that occurred as a result of traffic, variations in service times, availability of drivers and new orders.

The result

The project is in the implementation phase. Simulations have shown that there is potential to improve technician utilization by 24% and mileage by 17%.


Operations manager

bottom of page