Localization teams collect tons of data, edit distance, LQA errors, fuzzy matches, deadlines met, but too often, that data doesn’t speak the language of business. This post explains how to change that. By linking each localization metric to one of the classic project management levers, quality, time, or cost, and showing its real-world impact, we can turn linguistic KPIs into insights that leaders understand, value, and act on.
Let’s be honest. Our industry has not done a great job explaining the cost behind a good translation. What does the translation cost? Is it by word, per page, per type of document? We've been opaque for years about this topic. There are many reasons behind the cost of translation. This post will help you understand what you should take into consideration when purchasing a localization job.
Many companies claim to be customer-centric, but too often that promise stops at English. Surveys and focus groups are run in the US or UK and treated as if they represent the entire customer base, leaving most global customers unheard. In this post, I share a practical framework 5 audit questions to help leaders test if their strategy is truly customer-centric or just a slogan.
Many companies claim to be customer-centric, but in practice their listening stops at English. Most research is based on customers in the US or UK and then applied everywhere else. The result is predictable: cultural blind spots, costly rework, and frustrated global customers. In this post, I explore why true global listening begins when localization insights are treated as part of the customer voice
Reorganizations are disruptive. For localization teams, they bring a double challenge: the fear of being affected and the pressure to keep global launches on track. While executives focus on restructuring, customers still expect consistent experiences across markets. That’s why reorgs can be an inflection point an opportunity for localization leaders to show resilience, protect business continuity, and earn a stronger seat at the table.
Usually, when we want to improve something in our Localization strategy, we first set an ambitious goal. From there, we design a strategy to reach it as quickly as possible. If we don't see rapid changes, we feel like we're not improving. To break this cycle, we can try changing the way we set goals—smaller, but consistent objectives that, when we look back, show us that we are indeed making progress. This progress can be the driving force for us every week, every month, every year.
Here are some ideas on how we could apply this Kaizen methodology in the Localization world.
"The Localization Accountability Ladder" explains how to go from avoiding responsibility to becoming a leader in localization. The blog covers seven simple steps, showing key behaviors, skills, and tasks to help teams improve.
I'm passionate about Localization metrics, but it can be frustrating. We live in a data-rich world, allowing us to measure our impact better. However, this data abundance brings challenges when building a Localization metrics system.
In my experience, two main pitfalls emerge (but they are not the only ones 😅). One is overemphasizing Localization ROI, which can lead to unproductive discussions. The other is tracking effort-related KPIs without translating their impact on company success into terms that matter to leadership and product owners.
Several factors affect the duration of localization for a digital product, including translators' availability and the technology setup level. This blog post explores the various elements that impact the amount of time needed for product localization.
Seven years ago, my twin Maria and I stood on the LocWorld stage in Warsaw and talked about Cultural Intelligence ….how culture shapes trust, feedback, leadership, and collaboration. Back then, the big question was: How can humans work better across cultures?
Today, that same question still matters but with a twist:
How can AI LLMs can work better across cultures?
In an AI-driven world, we’re seeing that language alone isn’t enough. Multilingual doesn’t mean multicultural. And as we rush to scale AI globally, cultural nuance is too often left behind.
Maybe it’s time to rethink how we build. Maybe it’s time for Cultural LLMs.
Localization teams collect tons of data, edit distance, LQA errors, fuzzy matches, deadlines met, but too often, that data doesn’t speak the language of business. This post explains how to change that. By linking each localization metric to one of the classic project management levers, quality, time, or cost, and showing its real-world impact, we can turn linguistic KPIs into insights that leaders understand, value, and act on.