Client’s challenge:

A freight service provider faced challenges with high operational costs and inefficiencies in its delivery routes, which were affecting overall performance.

What we did:

To address these issues, operational data from various sources, including GPS tracking systems, fuel consumption records, vehicle types, and delivery area records, was collected and analyzed using PowerBI.

Through this analysis, inefficiencies in the delivery routes were identified. Advanced algorithms were then developed and implemented to optimize these routes, offering tailored recommendations for different delivery areas and vehicle types.

The results:
The provider experienced a 15% reduction in fuel costs and a 10% improvement in delivery times. These enhancements not only reduced operational expenses but also boosted customer satisfaction, showcasing the effectiveness of a data-driven approach to resolving operational challenges.

Client’s challenge:

A freight service provider needed to evenly distribute their workload across all days of the week to avoid peak and quiet periods without disrupting delivery efficiency.

What we did:
We analyzed the provider’s data to identify patterns and proposed a solution to group customers by suburbs and balance deliveries daily. Validated the changes with routing software and communicated the plan effectively to stakeholders and the provider's management team.

The results:

The changes stabilized staffing levels throughout the week, earned efficiency bonuses, and strengthened the business relationship, showcasing effective communication and strategic problem-solving.

Client’s challenge:

After implementing a new GPS tracking system, MTData, the staff at a freight service provider found themselves manually entering key data such as job hours, kilometers traveled, time on site, and proof of delivery. Additionally, the system did not fully cover fatigue management, creating operational gaps.

What we did:

We supported the built of the Transport Management Interface (TMI) between Translogix and MTData. Working closely with stakeholders to gather requirements and understand operational needs, we developed a custom python script to automate data entry (hours, KMs, etc) process from MTData's API into Translogix, which the TMI did not include.

Additionally, we conducted in-depth training sessions for frontline staff, walking them through the new interface and ensuring they understood how to use it effectively.

We extracted details to build a custom Gantt chart for fatigue management using Python and Playwright.

The results:

Seamless data flow: The integration between Translogix and MTData resulted in real-time updates on fleet management and job status, significantly improving operational efficiency and transparency.

The automation utilising Python and API endpoints automated data entry, saving labor costs for manual input.

Through training and ongoing support, BFS staff became proficient in using the new system, leading t o faster job processing and fewer errors in data entry.

Real time data from MTData allowed BFS to track job performance and vehicle usage more accurately, leading to better decision-making.

Complete fatigue management.