Freelance translators, agencies, in-house linguists, global content creators — there are so many different ways you can structure your team in order to get your content translated most effectively. And, although looking at what other companies do can certainly be useful, it doesn’t mean that what’s working for your competitors or other businesses will work best for you.
As a client-side localization manager, how do you ensure you have the right structure in place to support your company’s global expansion strategy? Here are some guidelines to help you figure out what team structure will best suit your needs.
Having a clear picture of your current state of affairs, what issues you are trying to solve and your company’s overarching goals will make it easier for you to choose the best path for you moving forward.
For example, is budget the main concern or are you trying to sustain ever-increasing volumes of translatable content? Is your company focusing on a few specific markets or is it rapidly expanding and needs support to quickly reach new audiences? Are you mainly concerned by quality or are you trying to make processes more efficient?
It’s likely you’ll be facing more than one challenge at the same time. However, some solutions may be more impactful in the short term than others, so find out which areas need prioritization.
Now that you know what your priorities are, you might want to proceed with an evaluation exercise. Use the following questions to assess the different models:
This list is quite standard, and you can adapt it to your needs by adding or removing any of the elements.
An easy way to look at this as a whole is to create a table with the models you want to evaluate on one side and the above-mentioned elements on the other. You can then assign each of them a value and, if you like, a score.
By way of example, your table might look something like this:
You can go more granular (for example, adding very high to very low values). For the score, you can set up a simple calculation assigning a numerical value to each of the different levels.
At the end of this exercise, you’ll have an objective view of which model is more useful for your organization, while taking into account your priorities. You can then use it to show your management the reasoning behind your chosen localization program setup.
Last, but not least, remember there’s no single one-size-fits-all approach when it comes to setting up a language team and supply chain, and you may find that none of the options listed above quite suit your needs. In that case, don’t be afraid to mix and match. Often, a hybrid model is the best approach for you to take for your company if it ticks all your boxes.
Simultaneously the smallest continent and one of the largest countries in the world, Australia is a country like no other, as is its language services industry. On the one hand, Australia has one of the highest proportions of immigrants in the world, with more than a quarter of all Australians having been born overseas.
Since ChatGPT’s launch in November 2022, media outlets have been churning out article after article about how generative artificial intelligence (AI) is coming for our jobs. Nearly every week, a new piece comes out in publications like The Atlantic or Business Insider about how ChatGPT will “destabilize” the job market, making certain workers redundant.
oday, machine translation (MT) is so pervasive that — for many young or early-career localization professionals, at least — it’s hard to imagine a time without it. But such a time did exist. Those with a decade or two of language industry experience under their belt have, no doubt, witnessed firsthand MT’s evolution into the nearly omnipresent entity that it is today.
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