Logistics Network Optimisation

We worked with QLD Cotton to build an optimisation engine to assist in the strategic decision making required around their logistics network

Queensland Cotton

“Biarri delivered a quantitative model which presented the facts in a way that allowed us to analyse our transport and logistics network and address a number of important strategic questions. We found using Biarri is a good way to take subjectivity and opinion out of your key decisions. Get Biarri to “do the maths” and make the right decision based on the facts.”

Damian Bryce
Chief Financial Officer, Olam Queensland Cotton, a subsidiary of Olam

Business Need

Queensland Cotton is a major supplier of premium cotton to the world’s textile markets. Their supply chain and logistics processes play a key role in linking cotton producers and spinning mill customers in an efficient, and effective way.

Queensland Cotton required a way to stay on top the supply chain and logistical complexity in order to maintain their competitive advantage. They recognised that the network needed to address large seasonal variations, which added a whole new level of complexity that simple excel tools couldn’t handle. In order for the Queensland Cotton management team to reduce costs, and increase insights in their data, they required a tool that empowered their logistical decision making.

Our Approach

  • Our team worked closely with Queensland Cotton do determine what was driving their decisions, what seasonal variables were contributing to costs, and what they really required to make better logistical decisions.
  • When these core variables had been agreed on, we were able to easily identify the data, and formulate the problem mathematically and get the solution before we started building the software.
  • This mathematical approach transitioned into the cloud based software build phase and we were able to rapidly build the engine on top of the Biarri Workbench.

The Results

  • The solution build allowed Queensland Cotton to deliver the lowest cost, and optimised network for many seasonal volume variations.
  • It also allowed Queensland Cotton to find optimal warehouse locations and best transport modes.

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