Delivering a premium sea freight service using IoT

Sea freight is historically a low margin business with containers frequently lost or opened without authorization. With a global fleet of 520 sea freight vessels, this top 3 shipping company had installed IoT devices on its containers to transmit geolocation and door open/close data .  But the vast amounts of raw data was meaningless in isolation from the company’s business data such as the container’s destination or contents. An application built in Olympe gave the company the capability to identify and mitigate disruptions, and thereby offer their customers a premium shipping service.

The shipping company had 150+ agencies worldwide responsible for local shipping operations and disruption handling. But an IoT data feed indicating that a container door had been opened was irrelevant unless cross-checked with business rules about whether that door was authorized to be open, and whether they consequently needed to take mitigating action. Developing a system that connected IoT with the business rules and inventory database in-house was difficult because of the low speed and high cost of the company’s development cycles.


With Olympe’s dual development environment, business owners at the company programmed rules visually while the IT team simultaneously coded functionality.  Within days they developed a number of disruption alert dashboards for the operations center covering the worldwide supply chain. The team connected real-time data from 3 legacy back-end systems to feed the dashboards A  fully functional prototype processing live data feeds was ready within 3 working weeks. Then, new functionalities, such as UI applications for new user types, were added and the project was scaled to production in just 3 months.


The shipping company reduced its operational cost of managing container-related disruptions by 20-30%. This helped the company bring a higher level of service to their clients and therefore justify 10% higher prices for the premium service.

3 weeks

A fully functional prototype processing live data feeds was ready within 3 working weeks


Reduction in cost of managing anomalies in containers


Incremental revenue potential from faster and more accurate performance of smart containers