Logistical Nightmare becomes a Delivery Dream Scenario Case Study | OQLIS Data Analytics

Logistical Nightmare becomes a Delivery Dream Scenario

Logistics and Transportation Case Study

A leading South African Logistics and Transportation Company manages the trans-modal movement of coal from Phalaborwa (South Africa) to the destination at the Port of Maputo, Mozambique, with an annual average movement of over a thousand tons.

This multi-modal approach requires the combined efforts of three of the subsidiaries. The leading company that arranges 3rd party primary transporters from the mine in Phalaborwa to stockpile in Ressano. Another party manages the receipt of bulk stock at Ressano with weighbridge operations and front loaders to transfer the bulk stock from the stockpile on railway wagons. A 3rd company operates the locomotives with transportation wagons carrying bulk stock from the Ressano depot to Maputo port for transfer to the vessel or temporary stockpile in Maputo terminal.

“In Supply Chain, where efficiency and accuracy are paramount, our partnership with OQLIS has assisted us and empowered us to provide these solutions.”
- Leading Supply Chain Software Head of Operations

The Challenge
The client needed a “single pane of glass” view of the entire operation, as involving various specialised divisions is critical to successful delivery. Such a project would generate big data, and they needed a system that would be able to carry massive amounts of data.

They needed a digital twin as a representation of the physical movement and process of bulk stock moving from the origin (pit) to the point of discharge (port) to represent its brick-and-mortar counterpart in the real world.

The complexity of managing the volume transactions covering 1 082 682 tons per year with a multi-national parastatal railroad, 29 567 truckloads, and 44 transporters representing 1400 trucks is immense.

The solution
By plugging in OQLIS Data Intelligence software into their various systems, the client received a coveted industry award and enjoyed the following benefits:

A predictive and accurate view of stock departure and arrival at each supply chain stage solved through predictive AI.
Complete transparency on stock variances with an improved ratio for truck shortages based on loading vs offloading weight, due to real-time stock visibility.
Automated reports to transporters and end clients receiving stock. First-time track & trace visibility on rail locomotive/wagon movements of stock.

Realising the value of access to historical, real-time, and predictive data, this was the customer’s response: “We could not get the output we did, without this tool!” – Leading Supply Chain Software COO & Founder.