#AskTheExperts - Automation and Business Model

Automation workflow

A new instalment of #AskTheExperts, a GALA blog series where we ask translation industry experts inside and outside the GALA community for their insights and advice on managing business processes and digital transformation. Do you have a burning or knotty question? Send it to us and we’ll ask our experts.

Today we ask our experts to answer the following question:

With the ever-increasing push to automation, how is the business model for the language industry set to change?
Requirement-compliant workflow and transparent time-based business models

There are three different types of automation in our industry: linguistic automation, process automation and transaction automation. Linguistic automation includes everything related to machine translation, pattern detection, quality assurance, and speeds up the work of the linguist (hopefully). Process automation cuts the slack in company-internal processes, and speeds up the work of the project managers. Transaction automation connects different systems and enables seamless cooperation between two players, increasing transparency and standardization for everyone involved. Through automation the integrity of the workflow can be regained, points of importance harmonized, and this enables a more seamless workflow between end-customer and linguists, without damaging the interests of the LSPs. Web-based systems also lend themselves better to measuring the time spent on a task than desktop-based systems. Technology improvements enable a more requirement-compliant workflow for the end users, and honest time reporting fosters time-based models, where everyone is compensated according to the real effort, and it's also in the interest of the end-customer to provide a better experience for the linguists.

-- István Lengyel, Founder at BeLazy
Efficiency through evaluation and standardization

With automation, we are making processes and people more efficient. Yet successful automation relies on establishing pre-defined sets of rules that produce consistent, repeatable processes. This requires evaluation and standardization of processes to ensure that automation can be leveraged to optimal effect. Over time we expect that AI will help us determine the rules based on data trends and patterns of behavior to speed up implementation and also improve success rates. The other big area for change is around linguist expectations. How do they fit into the business model and what do they have to gain? Automation improves efficiency within services management (i.e., giving more time back to the linguists to complete the work), and AI-driven products can improve translator productivity so they have more time on their hands. However, these improvements shouldn’t be seen as a ‘pay cut’ - instead, they leave room for translators to do higher value tasks, like more robust QA checks, constructive feedback loops for continuous improvement, improving language assets, and more. As well, they’ll then have more opportunities for work moving forward.

-- Samantha Reiss, Director of Services at Lilt
Integration of language services into production processes

To me, it all begins with the client’s needs—how they think of making their business or activity global or international or multilingual or multicultural. Any “push for automation” or “change in the business model” will be the result of the process that the client uses to achieve this. Language operations never exist in a vacuum; they are always part of how a product or service is made. Language operations are also never the end: multilingual or multicultural products/services are. To quote the late Theodore Levitt, “Customers don’t want a quarter-inch drill. They want a quarter-inch hole.” In the life of many clients, language operations (translation, localization) are an afterthought; they try to “globalize” the already finished product. Others, however, have begun to recognize that their products or services will need to be multilingual or multicultural by design, and they need to deal with language and culture as early in the product life cycle as possible.
The more language operations become integrated into production processes, the less it will be possible to just sell translations by the word. Language services will become more complex because they require an understanding of the production process—and not because of the push for automation. In this constellation, automation is a by-product, a consequence, and not the trend itself. 

-- Balázs Kis, Co-founder and Co-CEO at memoQ
Higher translation quality, lower prices, and focus on integration

With the numerous benefits automation brings, it’s no surprise that companies are adopting automation at an accelerated rate. In the language industry, machine translation (MT) is already at the forefront of automated translation production. Our 2020 data shows that 56% of translation jobs had MT enabled which means that machine translation post-editing has become the dominant translation method in enterprise localization. Businesses, from tech providers to translation buyers, are investing in this technology. But how will this change language industry business models? MT will bring higher translation quality for a lower price which will open up new use cases for companies to introduce MT-based localization to new content types. For the TMS market, we could see a stronger focus on integrability to address the needs in specific verticals, a deeper MT integration, and a focus on MT post-editing instead of traditional translation feature development.

-- David Canek, Memsource
Data-driven business efficiency

Thanks to automation, translation services are becoming an always ready utility that can be easily integrated into existing operating models. New technologies available in the language industry enable companies to better integrate their existing content systems with translation management systems to automate their entire localization process, saving everyone in the supply chain time and effort, transforming the way businesses operate. Clients, for example, will start to see translation costs reduce as project management overheads decrease, and translators’ work days will be less labor intensive and less unpredictable as many of their administrative tasks (such as quoting and invoicing, submitting translated files back etc.) will automatically take place. For example, new cloud-based platforms combine Linguistic AI with advanced workflows to automatically route tasks to the most suitable translators. The content is then instantly available within their CAT tool and invoices are automatically generated once the work is complete. The whole process is streamlined from start to finish, decisions are data-driven and manual steps are minimized, freeing up time to ensure translations are completed and delivered on-time. Ultimately, it’s fair to say the push to automation will increase business efficiency and decrease operating costs for the language industry.

-- Andrew Thomas, Senior Director of Product Marketing, Language Technologies, SDL
Zeroing project management costs

Brands are powered by words. From advertisements and marketing websites to application user experiences on your phone or browser, the sheer scale of content is increasing, and the specific words that are used establish differentiation from one brand to the next. For the past decade, automation has already disrupted the business model for the language translation industry because it has eliminated the need for costly project management throughout the content lifecycle for both translation buyers and suppliers. The result is that translation buyers can launch their content faster with fewer resources.
While automation makes scaling content a bit more palatable by eliminating the human effort surrounding the translation process, the industry is poised for change once again. There will always be a place for human translators, however machine learning systems including neural machine translation will play a bigger role; and, over time they will learn from their mistakes and improve. Pricing models will evolve and brands will be looking for ways to optimize their translation spend while maintaining a high-quality output. Having the right technology in place to produce words and monitor the effectiveness of the supply chain is key to how this future will be realized.

-- Jack Welde, CEO at Smartling
More, faster and cheaper

Automation is a way to respond to new market needs. And they are: deliver more, faster and at lower unit cost. It does not mean that automation will eliminate humans! Well the contrary. In order to deliver more, faster and cheaper we need both - humans and machines/automation mechanisms. What changes is the role of humans and their position in the process. Since the market requires fast delivery - counting from the start of the process - a lot of preparation needs to be done upfront, by humans, in order to prepare the automated process well before the project starts. That means we need more experts who can configure processes and workflows and define possible automations in the flow of the process as well as in the execution of particular steps. To give an example: automating a workflow requires setting up the rules according to which the workflow automation system triggers the acceptance of one step and launches the execution of the next one, when moving the content along the whole “production chain”. On the other hand, automating a particular step, like translation as an example, requires training of machine translation engines, so that they can be applied within a predefined process.

-- Andrzej Nedoma, CEO at XTRF Management Systems

For more on automation, please visit GALA's Knowledge Center.