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In recent years, there’s been a lot of buzz around “headless” systems – whether for content creation and management or for the translation workflows that feed the global customer experience. The concept being that rather than having a traditional front- and back-end (publishing and creation), these systems allow content to be magically managed, extracted, repurposed, and delivered through a myriad of end points, from mobile apps to corporate websites integrated with a partner’s own custom publication. Content creators work within the tools of their choice; automated processes make sure their work is translated to the appropriate languages; publishing and delivery systems select and share the right content, in the right place, and at the exact best time. It’s advertised as a global, multichannel content environment. Sounds perfect? At the conceptual level, yes it does. It’s the reality of “reusable content” that people have been striving for since beginning to structure content with SGML and its cumbersome content models. Sounds too good to be true? It is, if you only think about the concept, and not what happens before chopping off a head. Way too good to be true if you don’t spend enough time architecting and planning the end-to-end infrastructure, connections, and monitoring points. It’s a bit like a city’s transit systems with automated vehicles and trains: the doors need to open only when the carriage is standing at the right spot in a station, otherwise someone will get hurt. A headless system relies on the work behind the scenes: the content model, the workflows and processes, the alerts and triggers, the automation. None of this happens by itself – yes, AI and machine learning is increasing in use, for example to identify the most appropriate machine translation engines and/or linguists, but – so far – it’s not pervasive throughout the content lifecycle. (Other than by those SEO-geared web bots that publish badly-curated and translated content purely to expose you to pages of inane ads.) Even when AI is one day able to select, then perfectly-translate content, and publish or share it, it will still need planning – and human oversight. If you’ve read the 2011 novel, "The Fear Index", by Robert Harris or seen the recent Sky TV series, based on the story, you’ve seen a dystopian view of a system that’s controlled by artificial intelligence. It becomes a Frankenstein’s monster, thinking – misguidedly – for itself, like a genius but without morals. Doing the “right” thing – but being completely wrong. We’re not suggesting that a headless content- or translation-management system is anywhere near this level of risk – yet – but you do need to take steps to make sure your headless systems are guided by an active and engaged human brain. Headless components can be risky if not monitored to prevent them from making excessive or unanticipated requests for services or launching undesired actions. Many localization problems arise when localization teams fail to verify output from these systems after they completed the translations. As a result, they require careful set-up, planning, and monitoring – especially if multiple components are headless (“Language Technology Solutions: Enterprises”). Where do you need to be involved?
Yes, a headless global content flow can work – and work well. But it’s the result of an investment of time, expertise, design, and an awful lot of testing to make sure it all works as planned. Start small to validate your content model and how languages and locales fit within it. Remember that your source or HQ language – whether English or another tongue – is just another language, meaning that you want source content that is globally-generic, ready to be tweaked – if needed – for a variety of locales, rather than beginning with US-centric information that must always be modified, transcreated, or completely rewritten. Your global content environment can, with careful work, be headless – but don’t lose your head and expect it all to happen by magic!
Senior Analyst
Focuses on translation management systems, plus helping CSA Research’s clients gain insights into the technologies, pricing, and business processes key to executive buy-in
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