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Case Study: Yum! Restaurant International

Large-Scale XML Localisation Under a Tight Deadline — From Team Setup to Delivery

About Yum! Brands
Yum! Brands is one of the world's largest restaurant companies, operating more than 63,000 locations across 155 countries under the KFC, Taco Bell, Pizza Hut, and Habit Burger & Grill brands. Yum! Restaurants International Limited is the UK-registered international operations entity of the group.
 
The Project
Yum! Restaurant International approached Alafranga with a large-scale XML localisation project requiring delivery within a tight deadline — with the work arriving towards the end of the year, when capacity constraints are typically at their highest.

Approximately 400,000 words of XML content delivered under a tight year-end deadline — assembled, configured, translated, revised, and delivered as a single coordinated operation.
The content was structured XML — not a straightforward document format. XML localisation requires a specifically configured translation environment to handle tags, attributes, and string structures correctly. A generic CAT tool setup would have introduced errors at the file level before a single word was translated.

How It Was Delivered
 
  • Team assembly
    Alafranga assembled a team of four to five specialist translators rapidly — selected for both linguistic quality and familiarity with SDL Trados Studio's collaborative workflow environment.
  • Shared TM infrastructure
    All translators were connected to a single shared Translation Memory in SDL Trados Studio. This meant every segment translated by one linguist was immediately available to the rest of the team — eliminating duplication, enforcing consistency, and maximising the leverage of repeated strings across the file set.

  • Custom XML configuration
    Because the source files were XML, standard CAT tool settings would not have handled the file structure correctly. Alafranga commissioned a custom XML configuration from a specialist SDL Trados contact at Transperfect — paying for this directly — to ensure the files were parsed, segmented, and delivered without structural errors.

  • Quality control
    Speed did not replace process. A structured revision and quality control workflow ran alongside translation — ensuring that the final delivery met Alafranga's standard output requirements despite the compressed timeline.



We work in SDL Trados and MemoQ, with client-specific translation memories and glossaries maintained across every project. For large-volume programmes or projects with multiple simultaneous translators, we bring in Smartcat for real-time TM synchronisation across the full team. Where AI-assisted translation is under consideration, we run feasibility and quality tests before committing to a workflow. Not every content type is a good fit for AI drafting.

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