Lokalise has introduced a practical workflow designed to automate context management in localization, addressing the significant time lost due to scattered context. The process begins with auditing existing content, identifying where context currently resides, and determining who is responsible for providing clarification. This initial step aims to expose the hidden inefficiencies in localization workflows.

The importance of this approach lies in its potential to streamline operations and reduce rework. By standardizing what constitutes “good context” and centralizing it within the translation management system (TMS), teams can ensure that translators have access to all necessary information, including visual and structural context. This automation not only minimizes manual uploads and communication overhead but also facilitates the use of AI for pre-translation, ultimately enhancing productivity.

Localization professionals should consider implementing this structured approach to context management. By measuring the impact on rework and developer time, teams can demonstrate the value of improved context, leading to more efficient workflows and better translation outcomes.

Source: lokalise.com