A multi-market expansion strategy for any product is most effective if the various Globalization (i.e.Localization, Internationalization) activities are understood as a cycle that runs parallel to the multiple phases of software development; This cycle repeats during the various product upgrades. It is not an activity that is executed as if it were a process once the home market version (usually in English) is finalized. It is not a transaction that simply sends files to a professional localizer shortly before the global release. No; Globalization is not a process. Globalization is a cycle that runs multiple times. It is a cycle that runs in parallel with the product research, design, and development phases.

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.

Choosing a TMS is not an IT vs Localization decision. Localization understands the business problem and the workflow; IT understands the technical ecosystem. The best result comes when both work together, with clear roles, shared criteria and a selection process that looks beyond the vendor demo.

Words have the power to shape perceptions and influence actions, which is why reframing is such a powerful tool. In localization, we can reframe our role from simply translating to driving alignment across the company. By ensuring content is consistent, culturally relevant, and strategically aligned with business goals, localization professionals play a key role in helping businesses grow globally. This post explores how we create that alignment and why our work is much more than just translation.

AI is making it easier for teams to create multilingual content without going through Localization. That sounds very similar to a problem IT has been dealing with for years: shadow IT. In this post, I look at what Localization can learn from that experience and how we can keep visibility, quality and control without slowing the business down

What if asking AI the same question in English, Hindi, or Arabic leads to different levels of critical feedback? Anthropic’s latest research raises fascinating questions about culture, AI behavior, and why Localization expertise may become increasingly relevant beyond translation.

Localization Managers are often expected to keep many stakeholders happy: leadership, content teams, linguists, product teams, regional teams, finance, and procurement. But maybe happiness is not the real goal. In this post, I reflect on why stakeholder alignment matters more, and how Localization can make expectations, hidden work, ownership, and trade-offs more visible

AI can help create the first translation faster, but the work does not always disappear. Sometimes it simply moves to someone else’s calendar. In this post, I reflect on the hidden cost of asking bilingual employees to review AI output without a clear process, role, or quality ownership

When leaders push back on localization time, resources, or AI, the strongest answer is not to defend every step of the process. It is to reframe the conversation around risk.

In this post, I explore why explaining Localization from a quality perspective, with too many process details, may not always be the best strategy when speaking with senior stakeholders.

This post explores the key differences between working on the buyer versus the provider side of the localization industry. While there are some tasks common to both, others vary significantly in areas such as people management, operations, strategy, and metrics. The article breaks these tasks into four categories, providing examples for each to highlight these distinctions

LLMs don’t learn your brand style just because you use them more. They improve when someone guides them, feeds them with examples, corrects them, and owns the outcome. In this blog post I reflect on how we can create a strategy to do that

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.

In some RFPs today, it is no longer so clear what buyers really value from LSPs. This post explores why. Based on my experience on the buyer side, I share why the real need may be shifting from pure execution toward something harder to explain, but often more useful in practice.

What do you do when someone asks for the ROI of localization and you know the question is too narrow from the start? In this post, I reflect on why I stopped trying to prove isolated ownership and started talking more honestly about contribution.

Reading The Myths of Happiness reminded me of the arrival fallacy: the belief that once we reach a certain goal, everything will finally feel solved. In localization, that can look like waiting for the day when people will finally understand what we do. But organizations keep changing, so that moment may never fully come. And maybe accepting that is exactly what helps us stay grounded, avoid frustration, and keep moving forward.

In many companies, the localization budget does not sit with the localization team. At first, that may seem like a small detail. But over time, it changes how localization influences strategy

Defining localization metrics is relatively easy. In many cases, a team can write a reasonable list during a workshop, like the ones I mentioned above, or during a strategy session. The conceptual part of what to track and why rarely takes long. The real difficulty appears later: HOW you actually obtain those metrics.

AI will not eliminate (initially) localization roles, but it is reducing the time spent on certain tasks. What once took hours can now take minutes. That creates capacity.We can treat that time as a cost savings or reinvest it. If nothing meaningful replaces it, the value of the role will eventually be called into question.Jobs do not disappear because tasks are automated. They disappear when the value is not redefined.

So the real question is: what can you do now with the time AI gives you that wasn't possible before?