LINX Cargo Care Group uses AI to do the heavy lifting

National supply chain and logistics group powers digital transformation with Microsoft

SYDNEY – October 16, 2018 – LINX Cargo Care Group has flicked the switch on a new cloud technology platform, enabling the use of innovative technologies like artificial intelligence (AI) and driving company-wide digital transformation.

The national supply chain and logistics provider partnered with Microsoft to implement the Azure cloud platform and Azure Databricks; a collaborative Apache Spark-based analytics service which is designed to accelerate AI solutions.

This includes the creation of a new knowledge-based bot that frees support staff from answering repetitive user questions. The bot, which is able to perform text categorisations, was created by integrating Azure Databricks with Azure Cosmos DB and Microsoft.

It follows the recent purchase of 70 per cent of LINX Cargo Care Group by a consortium of investment firms.

LINX Cargo Care Group General Manager of IT, Thomas Gianniodis, says: “We wanted to innovate rapidly and offer better service at a lower cost – and in the process, drive a new culture by showing the business how easy change can be. The new platform allows us to do things we couldn’t in our old platform without additional, expensive tools.”

Bringing data to life

The new platform provides greater visibility over financial, payroll and operational data, helping staff make better use of these insights.

Previously, data sets from different parts of the business weren’t standardised and couldn’t be loaded.

LINX now uses Azure Data Factory to integrate structured, unstructured and streaming data from disparate systems with Azure Data Lake Storage to create a repository. Azure Databricks runs on top of the data lake to perform analytics while Microsoft Power BI is used for reporting.

It’s also replaced a manual invoicing system with a new project to help staff monitor customer invoicing. The new system features a dashboard which shows what’s been paid, what’s still owed, the gap and payment history. This reveals useful patterns.

“Using Azure Databricks, we created a dashboard in three days,” Gianniodis says. “That would have taken three weeks to build manually.”

A second phase of this system will use predictive capabilities in Azure Databricks to unpick payment patterns and determine what behaviour it needs to change for them to pay on time.

“By using Azure Databricks analytics to understand payment patterns, our customer service reps will be able to make targeted, proactive collection phone calls rather than reactive ones,” Giannoiodis says. “We expect to recover 90 per cent of outstanding funds by their due dates and thereby return capital to our investors.”

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