Thursday, March 1, 2018

Machine Translation Maturity Model (MTMM)

This is a guest post by Valeria Cannavina, Project Coordinator at Donnelley Language Solutions, adopting the Common Sense Advisory’s Localization Maturity Model (LMM) which is itself an adaptation of the software industry’s Capability Maturity Model (CMM). The resulting Machine Translation Maturity Model (MTMM) is a way of assessing the users’ understanding of the technology, and whether they are using it in an efficient and effective manner, properly linking it to other organizational processes. Valeria provides a framework for businesses to “identify where they are and what they can do to either significantly or modestly improve their existing production model to maximize the value that MT can provide to their organizations.” 

This is, however, a perspective that is quite localization-centric, and process alignment for a global Enterprise MT service that might be used by thousands of users, across an enterprise to translate hundreds of millions of words could be quite different.

As we head into 2018, we continue to see excitement and hype around Neural MT (Machine Translation), which is a breakthrough approach on the verge of providing a wealth of possibilities for the creation and management of business content. But, because the technology is relatively new, many players in the translation industry are overlooking the importance of implementing aligned procedures to guide the use of MT.

Neural MT, or any other kind of MT on its own, is not a magic wand that can solve any and every translation problem. Production and work procedures need to be aligned in an informed and competent way to enable the technology to provide maximum benefits and also minimize risks and data security issues.

It is useful to always ask fundamental questions before embarking on new technology deployment initiatives. The most fundamental question for businesses looking to invest in MT may be:

Why do we want to translate the content at all? 

Content translation only makes sense if it furthers overall business objectives and improves the global customer experience in some way. Today’s markets are massively global and that means communication and collaboration need to happen at scale and in volumes that were inconceivable just a decade ago. Today, any business that seeks to have even a moderately global footprint must understand how MT can provide increasing volumes of relevant content to their customer base.

Customers all over the world expect relevant information at their fingertips as quickly as possible, and this information is increasingly more dynamic and also short-lived. Business information is very important for a brief instant and of very limited value after that. This ability to deliver the right content quickly and effectively is often critical to the impression the customer forms of the business and its product offerings.

In addition, businesses are rightly concerned about data security and privacy. Improperly implemented MT deployments, where key processes and systems are not properly aligned, can expose private and confidential data. As the sheer volume of information continues to increase, businesses need to ensure that security is not compromised when content flows through these new translation processes. This may be especially critical with new product/service developments, sensitive employment, credit-related, medical, and financial data.

As MT becomes much more pervasive, it is wise for us to understand the bigger picture. In this paper, Valeria provides a unique and valuable perspective on assessing organizational alignment with new technology deployments. I hope you find it a useful guide for assessing your business needs around MT.

This post was originally published last month and then removed so that Donnelly could prepare the more complete document that is referenced at the bottom. 


5 different approaches to succeed with machine translation


With the ever-increasing volume and pace of global trade, the need to communicate to multiple markets simultaneously has never been greater. Add to this the huge technological advances of recent years, and it’s easy to see why machine translation (MT) has emerged as a translation tool of choice for high volume, high-speed translations, with ever-improving quality.

MT delivers big time-saving and money-saving benefits, plus big gains in productivity. But as is often the case when technology moves at speed, many businesses are lagging behind. While the demand for MT is growing very fast, there are still some basic challenges that clients are not aware of. For example, not all language combinations, documents, and formats types are ideal for MT. In fact, the quality of the output can change considerably based on these criteria which could affect your workflow, the time to market, quality and business targets.

This is where partnering with a specialized Language Service Provider (LSP) can give you the upper hand. A professional LSP will not only help you understand the MT landscape together with the latest developments but also advise on how it can be best used to optimize your processes, productivity and profits.

MT engines, its output, and training require skilled professionals and solid technologies to support automated workflows. Simply put, MT is currently far from being just a plug-and-play technology.

This approach is paramount, especially when confidentiality is key to the process. Assessing the risks of publishing data and securing processes is not a standard practice for all language service providers, so while clients and regulators are setting up very strict measures for data breaches, vendors are struggling to create processes to ensure top quality processes and services for MT.

Whether you are a large or a small business; whether you have a little or a lot of knowledge of MT, this paper will show you how to take full advantage of it. We follow a Machine Translation Maturity Model (MTMM) which is based on the Localization Maturity Model[1] created by Common Sense Advisory, an independent market research company for the language services industry. This paper is a guide to help businesses identify where they are and what they can do to either significantly or modestly improve their existing model to maximize the value that MT can provide to their organizations.

[1] The Localization Maturity Model was created by Common Sense Advisory, an independent Massachusetts-based market research company for the language services industry. It is based on the Capability Maturity Model (CMM), a development model informed by a study of data collected from organizations contracted with the US Department of Defense, who funded the research. The term "maturity" relates to the degree of formality and optimization of processes – from ad hoc practices, to formally defined steps, to managed result metrics, to active optimization of the processes. The model's aim is to improve existing software development processes, but it can also be applied to other processes.

Machine Translation Maturity Model (MTMM)

The model has five maturity levels, each divided into different areas which we encourage companies to evaluate individually on their own merits, allowing you to freely move from one level to another, not necessarily in successive steps, although an ideal path is shown below.

We will now walk through them so you can identify where you are and what you need to do to move to a different level  - and enjoy the associated benefits.

Level 1: Initial

If you're at this level, you are requesting MT only when absolutely necessary. This could be due to time or budget constraints, or because your communication is internal only. It may be that you are not satisfied with the service that you are getting. Or it could be that you have no MT investment, resources or best practices in place. This may be because you don't have a localization department in place, or because it is not directly affecting a core activity within your organization.

This model may work for some organizations with a very limited usage of MT, but who may benefit from taking the following steps to increase its value within their organization:

  • Governance: make a case to management for investment in the maturity process.
  • Organization: appoint a dedicated MT resource in the localization/translation/marketing department who will set the basis for the process investigation.
  • Process: document the main tasks of the outsourcing process so you can track those that can be repeated and those that can be deleted because they don't generate any added value. For example, to track which department translation requests come from, the type of content you receive, and the turnaround times. This will help you start setting best practice for your process.

Level 2: Repeatable

The first step to maturity through process improvement is two-fold: describing what you do, and doing what you've described. If you are at this level, you have started documenting some tasks of the process which are repeatable - for example, your criteria for identifying texts that can be sent out to MT and how to store them by category. You view terminology management as a relatively low priority, whereas in reality, it's an investment that will pay dividends by ensuring consistency.
This is where most organizations may be at and would benefit from taking the following steps to evolve their existing processes:

  • Organization: define an internal process to track feedback on the source text from your LSP. For example, you might have received a comment saying that the text wasn't suitable for MT because it was too creative or overly complex in structure. Make a note of this in the process documentation.
  • Process:
    • analyze your existing content in order to understand exactly which documents can be translated with MT and how the source text is structured.
    • organize linguistic reviews on the translated material involving internal country reviewers, so that terminology management starts to become part of your internal process.
  • Governance:
    • track the costs of the process improvements you are implementing (expectations/forecasts vs. reality).
    • define KPIs for this process to track the ROI of activities involved at this level
  • Automation: investigate available tools for automating some tasks. For example, look for tools to help you build a repository of texts that have already been sent to MT and decide a naming convention. You will then be able to identify similar content and remove text that's not suitable for MT. The automation will be run parallel to the process of analyzing the texts.


Level 3: Defined

At this level, you will have clear goals around integrating MT into your business, in the form of a roadmap of tasks aimed at continuous improvement through collaboration with your LSP.
Your processes will be documented and fully executed. The internal process of outsourcing MT is defined, repeatable and managed. You have best practices in place - a process to identify the MT content, a process to collect and implement feedback, a process for internal translation review, a process to track costs etc.. and can now measure your process.

For example, to track productivity you might want to measure word output per hour. Before a process improvement is introduced, a baseline measurement is taken. At the end of the project, the process is measured again to show whether the change resulted in more words produced per hour.

Terminology management is no longer seen as a secondary task, but as a fundamental step which adds value to your business and your brand. The benefits are now showing in your ROI. For example, you can identify which content has already been sent to MT, which means fewer words to process, fewer man-hours for both you and your LSP, reduced time to market and reduced costs.
This is the stage where most organizations should aim to reach in order to optimize their supplier relationship with their language service provider and maximize return on investment. That said, some organizations take additional steps to further mature their MT procurement strategy as follows:
  • Organization: supported by your LSP, hire specialized terminology management staff who will work closely with other departments to:
    • organize feedback received on source text for fields of application
    • pass the feedback to internal technical writers
    • check the feedback has been implemented
    • incorporate the feedback into your CMS or whichever tool you're using to store the source and target documents.
  • Process:
    • define the internal process to combat source linguistic inconsistency. For example, give clear guidelines on what to do if a word has more than one meaning, who is the decision maker, how many review cycles the work will go through, and how this will be implemented in the CMS
    • plan internal review cycles so you can send feedback to your LSP and implement it in the CMS.
  • Governance:
    • establish the budget for multilingual projects based on the forecast for previous MT projects in terms of volumes and languages
    • establish decision making to prioritize languages and markets.
  • Automation: identify a tool to automatically apply correct terminology to source content in the CMS.

Level 4: Managed

MT is now tied to your corporate goals and part of your production process. The different departments rely on the MT department to prepare documents before sending the files to translate. The idea of 'department' here is fluid; for example, it could take the form of resources performing MT tasks alongside non-MT tasks. Alternatively, if you don't have your own MT department you can contact your trusted LSP to help you manage this internally or serve as the department itself.

The size of your business will dictate its scope.

The MT department has its own budget and schedule for incoming projects during the year, with automated checks in place for managing terminology and producing the source documents. The focus at this level is on automation; you will be working closely with the technology department to improve the source i.e., a style guide for writing source text to ensure consistency.

If your organization is in this camp, consider taking the following steps to improve the maturity of your sourcing model:
  • Organization: define roles within the process; for example, a project manager (PM) to handle requests from different departments, dedicated engineers for automation, and internal reviewers.
  • Processes:
    • define delivery parameters around new products/documents. For example, you're issuing a new set of letters to shareholders and, based on previous experience, you know they will need to go through X reviews. This knowledge enables you to set realistic deadlines, review cycles, and delivery volumes
    • define text structure rules (short sentences typically translate much better than long, complicated sentences).
  • Governance: measure business benefits vis-a-vis strategic use of MT budgets.
  • Automation: technology resources work on a roadmap to automation which integrates all the previous stages: from terminology management to check that the source text follows the defined rules.

Level 5: Optimized

At level 5 you have a team of engineers, terminologists, internal reviewers and project managers running the content creation process for MT on a daily basis. You have rules in place for content editors writing source text, ad hoc terminology and an internal tool to check and select the right kind of source text for MT, extracting only the new parts to be translated. You are now looking at new ways to get the same quality output while trying to keep costs and content creation time to a minimum.

What to do to achieve continuous improvement beyond level 5?
  • Organization:
    • prepare training material for staff and build a career path in the MT office
    • plan to offer a global service 24/7/365.
  • Process
    • content creators work to minimize content sent to MT: less content = lower costs
    • customize writing rules based on target language to minimize linguistic disparity between source and target. You will already have writing rules for new content creation, but with your accrued experience, constant LSP feedback, and the help of internal reviewers with in-depth knowledge of the target languages, the rules can be customized further to optimize MT for each target market
    • allocate LSP resources strategically, based on the language combination that best fits your quality expectations.
  • Governance: based on your long-term business goals plan how to support everyone involved in the roadmap to continuous improvement.
  • Automation: connect your CMS with your LSP's Translation Management System (TMS) to:
    • speed up the process
    • send requests and import the MT content automatically
    • centralize review cycles in a familiar environment
    • ensure consistency across content with a shared repository of linguistic assets.


Even if localization is not central to your organization, it can and does have an impact on your business. To reap the maximum rewards from MT, working with a trusted LSP is key to strengthening your supply chain, improving ROI and protecting your brand and reputation.

The MTMM was designed for any size or type of organization to use to make the most of MT. It is an ideal path to maturity because it has built-in flexibility – each activity can be performed as a stand-alone step as well as in a sequential way.

We believe that MT is not just about getting the technology right. It’s also about having a strong relationship with your LSP; a partnership that is characterized by collaboration and constant feedback between the whole team. Only by analyzing your process and implementing some of the suggested tasks will you arrive at an MT roadmap which delivers against your expectations.

It is also possible to get a more complete  version of this post directly from  the RRD website at this  link:


Valeria Cannavina holds a degree in language and culture mediation, and a master's degree in technical and scientific translation from Libera Universit√† degli Studi “San Pio V” in Rome. She has spent 10 year in the GILT industry as Project Manager and while working for companies like SAP and Xerox she was involved in quite a few research projects on new processes implementation and Machine Translation. At present she works for Donnelley Language Solutions a Project Manager.

No comments:

Post a Comment