Why You Should Be Measuring Localization Data
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Why You Should Be Measuring Localization Data

Why You Should Be Measuring Localization Data

Why You Should Be Measuring Localization Data

Localization data is at the very heart of making smoother entries into new markets, asking for a bigger budget, and raising company-wide awareness. If you’re a localization data junkie, you already know this. But if you aren’t yet measuring how much you translate, how you translate, the time it takes, and so on, this post arms you with four solid reasons why you should have started on it yesterday.

1. (Tons of) Data is there for the taking

A typical localization program can easily include over 100,000 data points — and that’s just from some simple math, such as translating over 100 projects into 30 languages with six different fuzzy match categories. You could be tracking translation for online help differently than for software, which could be different from how marketing material is measured. They each might have different metrics and quality goals associated with them, as well as turnaround time expectations.

And while you have to pick and choose what you want to track, it does seem like an utter waste of information if you are tracking none of it. Data is also cheap and easy to use. Just about any spreadsheet tool today has built-in analytical tools. It only takes a few seconds to do the number-crunching, so it’s a lot easier for people who aren’t hard-core mathematicians to be able to process and use data.

2. Learn from mistakes as well as successes

A data-driven approach can help you look at the risks and opportunities associated with different paths you might take as a manager. You could be responsible for delivering something on time, monitoring linguistic quality, or managing localization budget. In all of these cases, you can use analytics to save thousands of dollars by applying the data to evolve best practices. Don’t repeat the same mistakes or pass up chances to replicate successes.

3. It’s good for your career

No matter where you are in the hierarchy of an organization, being able to show that you have numbers to support your decisions places you in a strong position. And, the senior management team typically loves to see numbers. Of course, things can still go wrong with data-driven decisions. Even then, at least there is evidence to show it was not a random decision, but that there was some quantitative thought to it.

Business analytics leaders Thomas Davenport and Jinho Kim identified three stages of analytical thinking: framing the problem, solving it, and communicating the result. Data is the critical element in all three phases. For our purposes here, the third phase is especially important in communicating to the company how localization was effective in solving problems related to international business.

4. Lastly, it’s good for the localization cause

Yes, couldn’t help getting that in. Too many localization managers are asked all too often about the localization return on investment. Yet this data is frequently missing; not because it doesn’t exist or is hard to track, but simply because no one has sat down and put measures in place to start tracking it. This needs to change, and the faster the better.

Intuition and personal experience have a place, but when decisions are driven by data, localization is elevated to being a measurable, scalable, and repeatable process.

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