Unlocking Language Quality Management: Insider Insights from Beyont’s Expert Panel [Video]
Enhancing language quality is the most reliable way to boost your localization outcomes. However, even seasoned localization managers may need guidance through the complex terrain of language quality management.
To clarify your path, we assembled a group of experts to share their experiences and their opinions on the field’s most difficult challenges:
- Esther Curiel, globalization manager at Zoetis, the world’s largest animal pharmaceutical producer.
- Valeria Fuma, senior language quality manager at Centific, a global IT services company.
- Eveline Jebaili, head of translation quality at Acclaro.
Beyont program manager Satu Suomalainen led the wide-ranging conversation, exploring the intricacies of language quality review and assurance. Watch the 4th Beyont Panel Discussion
So, what are the most pressing challenges for today’s language quality managers? Here’s a look at what our expert panelists had to say.
- Using metrics with care
While metrics are useful, it’s vital to keep their limitations in perspective. When managers only focus on metrics, it’s easy to lose sight of the big picture. For instance, your language quality program may report strong results for all languages and content types. But if end users in some regions complain or reject the content, that’s a sign that you’re still missing key information.
The kind of metrics we use can also skew our language quality evaluations. We often focus on metrics that are easy to collect, measure, and apply. However, we also need to consider metrics that are harder to control or access, or we risk excluding crucial variables from our analysis.
Finally, it can be extremely challenging to grasp how all the metrics fit together, so you aren’t just looking at them piecemeal. How do you achieve a comprehensive view that includes linguistic quality, usage, engagement, and more? Language quality managers need to figure out how to consolidate all this information and spot misalignments.
- Assessing the end-user experience
User experience is the ultimate test of localization quality: Even the best-written content will fail if it doesn’t serve users and their goals. Nonetheless, the user experience can be tricky to evaluate. To tackle this challenge, we need to include methods that assess user interactions through a cross-linguistic and cross-cultural lens.
For example, a group of linguists can be assigned to browse a localized website and report any issues they find. These may include both linguistic errors and practical UX problems such as unclear information, too many options, or complicated navigation.
In addition, the reviewers could also answer broader prompts about their experiences. Do they find certain features useful or appealing? Do these features seem relevant for their market, and if not, what alternatives can they suggest? By asking such questions, we can gain a broader overall view of how localized content is performing and how to improve it.
- Drawing accurate conclusions from data
In language quality management, you can easily make mistakes if you jump into decisions without enough data, or with data that’s out of context.
While basic pass-fail metrics like on-time deliveries can serve some needs, quality data only becomes valuable when analyzed in context over time. Language quality managers need to consider a wide range of variables and avoid getting trapped in a static perspective.
All quality data has a story behind it. For example, was the translator new or dealing with a challenging project? It’s critical to take such variables into account. To ensure your language quality program succeeds, you need experts who know how to interpret and explain the data, rather than taking it at face value.
- Communicating with stakeholders
Communication can pose another barrier to sound language quality management. Many clients know relatively little about localization, which makes it hard for them to understand what’s needed and provide useful guidance to linguists. Managers need the ability to take what clients tell them and translate it into the clear requirements that language specialists need to produce high-quality work.
Meanwhile, the level of stakeholder involvement can vary from one company to another. Some stakeholders take an active role in conversations about language quality, but others are too busy with other tasks and have other jobs besides localization. Communication can become even tricker when localization teams and quality reviewers are dealing with multiple languages.
To avoid these and other problems, managers need to factor language quality into the localization process from the start. You can’t wait to tackle quality issues until the translation is done. Instead, you need a proactive strategy that aims to prevent such issues in the first place.
Watch the Video to Learn More
To sum up, data and metrics are indispensable tools. But they’re far from the only factors in successful language quality management. Managers need to consider the human element, from the user experience to stakeholder communication. Just as important, they need to stay aware of variables that the numbers don’t always capture.
In the rest of the discussion, our expert guests delved deeper into strategies for dealing with these challenges. They also touched on AI, the role of technology, and other topics of interest. Watch the video for more insight into how to improve the quality and effectiveness of your business’s localization program.