In countries with low government centralization, the market tends to be messy, for both the provider and the buyer. There are lots of small players and individual interpreters that compete for a myriad of small contracts and individual assignments. For both the buyer and the provider this usually means that a lot of time is wasted on the procurement process and there is usually an overload of bureaucracy. In these markets, we won’t see many large players because it is much harder for an LSP to make significant profits. Examples of this are countries like Germany, France, Italy, and Belgium.
In countries with high government centralization, usually one or two large players occupy the majority of the market. While this significantly reduces the time spent on procurement, it also means that these one or two large players are in a monopoly position. This poses a number of risks that can have a negative knock-on effect:
A medium level of centralization is the Goldilocks Zone countries should aim for.
Examples of this can be found in Australia, the US, Canada, and the UK.
We all know that human input is still invaluable when reviewing localized content. But with ever-improving localization technologies, where does a manual approach to auditing matter most?
Do you remember the last time when people were NOT talking about machine translation (MT)? We don't. Wherever you go, there’s someone talking about MT. With few exceptions, it seems like the only major disruptors in our industry over the past few decades have been breakthroughs in language technology.
Some machine translation providers are holding out hope for MT systems that adapt to document context. Could this development eliminate the need for custom MT engines? Will context-enabled MT help MT achieve human parity? Will we still need to customize a few years from now? Let’s discuss further.