2017 Translation and Localization Trends
Acceleration of mergers and acquisitions. Neural Machine translation and deep learning. Focus on Marketing and Big Data. Industry 4.0. These areas gathered a lot of steam and interest in 2016 and are here to stay.
In 2017, many of these developments will evolve from “early adopter” to mainstream. To keep our finger on the pulse, let’s explore 2017 trends!
Customer Experience is Changing
Not only is connectivity increasing, there is also a shift in consumption of content. With mass-market devices becoming available, Virtual Reality (VR) is expanding its reach. Augmented Reality (AR) is embedding content in our world view. Applications such as Enhanced GPS systems, sightseeing and tours, practice surgery, maintenance and training in complex manufacturing and of course finding Pokémon are mainstreaming.
These interactive environments need a new level of dynamism in global language; verbally, orally and visually.
A good example can be seen with Chatbots. There is an important area in IOT (Internet of Things) interfaces and hard to get right from a translation perspective. How can you localize chat apps that speak to you semi-naturally (using text or audio)? Here the language challenge will be that you need part translation and part adaptation to really succeed.
Continuous Delivery: How Agile Are You?
18 month release cycles are a thing of the past. Speed is the name of the game. To make speed a reality, businesses have responded by incorporating agile methodologies for content and product development across all sectors. This concretely means tackling three main areas: technology-led automation, mindset shift, and adaptable quality.
Automation will “attack” every remaining inefficiency in file management and enable a continuous flow. As a provider of languages services, a robust translation management platform is a must. Content owners should have the flexibility to pick the flow according to content type and importantly content purpose and usage. Next stage evolution means localization moves further “left” in the “global content lifecycle”. We predict this will open the door to more asynchronous translation models.
The mindset shift is also necessary to make continuous delivery a success and is about aligning teams to think differently (see: Continuous Delivery: Adapt the Thinking, Adopt the Mindset)
Defining the level of quality is about understanding the goal of customers for how the translated content will be consumed. Each piece of content has a specific job to do. For “just to know” content, the message can be rudimentary, so long as a content user receives it in the right place, at the right time.
Many industries are now employing the power of live telemetry to make informed global content decisions. This enables test content to infer interest in a market. Do you have a market approach which tells you how good your content is performing?
In a world where everything is ultra-connected and complex, there is a shift to simplicity. It is visible in everyday life: self-driving cars, shift from typing to speaking, easy pay solutions such as “Amazon Go”, disruptive systems like Uber and Airbnb, simplified User Interfaces. The focus is on “easy”.
The translation industry is no exception. Mature buyers of localization services have either turned to single-sourcing for all their translation needs or are currently streamlining translation. Consolidating the translation supply chain brings measurable cost savings but, and perhaps more importantly, saves a lot of time. Getting translation “done” should be simple and seamless.
As a supplier, make it easy to buy! In our opinion, there are 3 areas to focus on: user-friendly technology (for example to order projects or perform in-country review), fast service and a car-wash approach (select among services ranging from machine translation to transcreation depending on content type).
If you connect your audience simply and faster with what they need, they will buy.
Further Evolution of Data Management
Analysts at Gartner have estimated that total IT spending will reach $3.5 trillion next year. Many organizations aim to reach maturity in data management. We will witness more and more corporations embark on programs to consolidate their systems: Content Management Systems (CMS), Product Information Management (PIM), Marketing Automation, Digital Asset Management (DAM), Enterprise Resource Planning (ERP). It will be about connecting easily to those systems and to get the content for translation in and out automatically. The global-readiness of the systems is critical for success. A good example is Sitecore which has evolved its products to make them ready for global usage.
Another important aspect in data management will be the move from searching into structured content to mining unstructured content and its effects on translation.
If you are based in Europe or in in the Americas, perhaps you tend to be rather focused on these geographies? A look at tech news will probably give you more information about the latest Silicon Valley start-up rather than a feature on Alibaba.com. The reality however is that Asian power players such as China, India, Korea or Vietnam are growing far beyond their region and going West. How ready are you to embrace this trend?
Neural MT and Deep Learning: Continuing Trends
Some of you may wonder why we did not dwell on neural machine translation and machine learning. We felt this is a trend which is there to stay and that MT has been around for decades but that we now have the processing power to make it work. An exciting area worth its own post. Stay tuned!
Will these trends ring true? We’ll be there to revisit in 2018!