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Case Study

Utilizing Multiple Data Sources to Achieve a Robust Drawback Program
J.M. Rodgers increased a major tire manufacturer's drawback refunds more than 20x by capturing six years of previously unclaimed exports.


One of the world’s largest and leading tire companies.


A major tire manufacturer attempted to set up a drawback program with a competitor. However, the complexity of their vast data feeds—owing to their considerable shipment volume—proved to be overwhelming to the provider. As a result, they could not make consistent and coherent matches that came close to the estimate and needed to find a better-suited provider for data manipulation.


J.M. Rodgers requested the client provide all the information and data they had provided to the current provider to provide a comprehensive analysis of how we could manage the program to collect all available drawback potential. Our IT team went beyond a simple breakdown of the provided data. The team, accustomed to dealing with large and complex data sets, started by identifying and fixing errors in the data. Then, by using existing parts dictionaries, they figured out what parts and classifications belonged to different shipments, filling in gaps manually when necessary.

By correlating that with AES reports from ACE and connecting those transactions against their invoices, forwarder documents, and ITN data, we were able to use the augmented data to identify previously unmatched drawback-eligible transactions. As a result, a considerable number of matches that weren’t previously found were able to be made due to our ability to identify hidden opportunities in a morass of data.


The client’s initial estimate of drawback refunds was around $3 million. However, with the solutions to their complex supply chain data implemented by JMR’s drawback team fully utilizing new TFTEA regulations, J.M. Rodgers has, so far, claimed almost $70 million with six years of export data.