This is Part 2 of a series focusing on long tail localization.
Traditionally, translation management systems (TMS) have been able to effectively address their customers’ needs by radically simplifying the admissible choice of workflow patterns.
This was a viable solution in the past, where each of the relatively small producers had to cover the whole localization cycle not being able to effectively rely on standardized interchange with their competitor’s tools. This worked as long as there was at least one major tools provider independent of any single language service provider. However, the comprehensive TMS of the past is not able to address the generalized workflow needs of next-generation localization.
In next-generation localization, the traditional bulk localization model is one of many, and moreover one of steadily dropping importance. The bulk localization scenario kept losing significance even in the originating corporate buyer sphere where it first originated, most importantly due to the sheer efficiency of the advanced leveraging methods. Basically, translation memory was driven to the utmost limits of its usefulness through features such as structural and ID-based guaranteed leveraging, sub-segment lookups and candidate recomposition. . .