Accelerating Logistics Services with ACI Migration
About The Project
As one of the leading international logistics companies, efficiency is everything. The company was in need of a way to improve the efficiency of its ACI (Advanced Cargo Information System) with better user experience, performance, and overall frictionless processing of goods because any delay in processing could mean a negative influence on customer satisfaction.
The Challenges
The old, outdated cargo information system called for an overhaul because it was, according to the company, starting to affect their ability to scale up as well as their day-to-day operations. Looking up cargo information was not intuitive, and the software had a dated, unintuitive UI that discouraged customers from making queries.
And on top of it, cargo information was not updated in real-time as synchronization between inventories and warehouses was an issue.
The Solutions
After collecting requirements from our clients and discussing the best way forward, it was clear that a full system migration was the solution – however, it wasn’t an easy undertaking. Their cargo database alone consisted of hundreds of thousands of entries, and migrating them safely over to a new system was a time-consuming and challenging task.
In terms of user experience, we also made sure that the new system provides a vastly better user experience that is both intuitive and engaging.
To safely migrate the system, Ekotek Technology co-worked with a Japan-based IT solution provider to figure out the best way to move the legacy system to the new one.
The project was joined by over 20 team members and divided into 4 phases: 1. Requirement Definition 2. Development 3. Migration Test 4. Deployment
The Results
Within 4 months, Ekotek has helped our client fully migrate their existing cargo management system over to the latest one with real-time cargo tracking.
- Post-migration, data integrity was fully maintained which allowed the company to resume operations in an efficient manner
- AWS enables substantial operational and maintenance savings while delivering improved data availability and overall system performance
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