Building Equity In The Translation Workflow With Blockchain

This is a guest post by Bob Kuhns on the subject of blockchain use in the translation industry. He presents a very "simple" model where he shows how a blockchain could enable an ongoing,  robust, and trusted Buyer to Translator business connection that could quite possibly reduce the role of LSP middlemen whose primary value-add in business translation work today is project management services and coordination. Though this is a valuable service, it often significantly increases the cost of translation, and also sometimes creates discord, disgruntlement, and enmity amongst the freelance translation-service suppliers who ultimately do the work. 

A blockchain solution is not just about technology, it’s about solving business problems that have been insolvable before due to the inability of the ecosystem to share information in a transparent, immutable, and trusted manner.  

 LSPs continue to struggle in their communications on translation quality and the value of ongoing project services and thus it theoretically seems that a blockchain that did in fact deliver direct-to-buyer translation services that are trusted, reliable and predictable would indeed be a great step forward for the business translation industry. This is also exactly the primary reason why some in the LSP sector would not want blockchain to succeed. However, there is also a role for a more enlightened LSP in a functioning translation blockchain, one committed to transparency, equitable sharing of business value and benefits, and ultimate customer success in all their globalization initiatives.    

Blockchains show potential to address key concerns of our digitally-driven lives, such as a lack of transparency, accountability, verifiable identity, and control of data. Blockchain has the potential to enable defined quality to be delivered at a defined price in a defined timeframe with minimal administration overhead. The extent that it is able to do this in a clean and trusted way will likely drive its adoption. Blockchains are poised to catalyze new business models by cutting the costs of verifying the truth.  

Explanations of blockchains tend to get complicated quickly. However, in very basic language, blockchains help us certify that something is true, without someone in the middle doing checks and balances.  But recent translation market activity perhaps points to some of the vital building blocks to making blockchain more real in the translation industry.     

What might some of the elements to make a functional blockchain in the translation industry possible be? 

• A robust TMS platform that could enable ANY buyer (not just localization buyers) to engage ANY translator to perform a necessary translation task.
• Assistive translation technology that can be easily connected into a blockchain workflow (MT, TM, NLP Tools)
• The ability to create self-sovereign data that would allow more equitable sharing of data. In the vision of many pioneers in the blockchain space, the “ownership” of data would switch from the organization that gathers it to the individual or organization that contributed it.
• An Independent Translator rating, certification, ranking, identification database to enable competent resources to be identified and selected. 
• Smart Contracts
• And....

For those who think blockchain is still a distant dream, there is evidence that it is making meaningful headway in improving efficiency, accuracy, and transparency in some areas that have historically been project-management nightmares. The members of Tradelens, a blockchain joint venture between IBM and the shipper Maersk, control more than 60% of the world’s containership capacity. Seriously, do we really believe that a translation task has more variance and unplanned changes than these goods and trade flows? Watch the short movie clip at the link above to see it at work. Having trusted food quality from all over the world is perhaps an even more challenging scenario. Food Trust is a blockchain ecosystem that covers more than 100 organizations, including Carrefour and the top four grocery retailers in the U.S.     

It is quite likely that the old guard (executives, managers, and localization teams) will not be at the forefront of translation blockchain if it ever does become a reality. Mostly because they are "just too old, too tired, and too blind " as the movie says. Change is most often driven by the young who see the new potential and have the motivation in solving old enduring problems. 

"Disruption could also be spurred by an even younger generation. New York Times writer David Brooks traveled to college campuses to understand how students see the world. In a story, he wrote after the experience, starkly titled “A Generation Emerging from the Wreckage,” Brooks describes a cohort with diminished expectations. Their lived experience includes the Iraq war, the financial crisis, police brutality, political fragmentation, and the advent of fake news as a social force. In short, an entire series of important moments in which “big institutions failed to provide basic security, competence, and accountability.” To this cohort, in particular, blockchains’ promise of decentralization, with its built-in ability to ensure trust, is tantalizing. To circumvent and disintermediate institutions that have failed them is a ray of hope—as is establishing trust, accountability, and veracity through technology, or even the potential to forge new connections across fragmented societies.

This latent demand is well aligned with the promise of blockchains. While it’s a long road to maturity, these social forces provide a receptive environment, primed and ready for the moment entrepreneurs strike the right formula. "             

Alison McCauley, author of Unblocked 

===============

News recently has shed light on unfair work arrangements for freelancers or “gig workers” with Uber being a prominent example, and now more industries have begun to examine their relationships with freelancers. Though on a modest scale, this self-examination has come to the translation industry as well. The proposed translation model is grounded on the idea that blockchain can bring equity to translators while streamlining the translation workflow.

The Realization For Change

Even before the pandemic, the translation industry was changing and self-reflecting. NMT took center stage and the less-than-equitable working relationships for translators gained notice ^[1]. In “The State of the Linguist Supply Chain,” Common Sense Advisory examined the translation supply chain from the perspective of over 7,000 linguists, 75% of whom are freelancers representing 178 countries and 155 language pairs ^[2]. This data-rich survey identified many discrepancies between translators/linguists and their clients - the Buyers of translations and LSPs.

Several illustrative takeaways are:

• Over half (54%) of the respondents could not live solely on their translation income.

• Linguists are attracted to the translation profession because of flexible hours (91%) and the diversity of projects (75%). Only 33% rated their pay as being a plus.

• The frustrations of linguists include fluctuating income (65%), irregularity of work (57%), and lack of respect (25%).

• There is a preference for working for clients (65%) because translators (80%) earn more, have more job flexibility (56%), and quicker payments. Clients (76%) pay in less than 30 days compared with only 32% with LSPs.

• The largest benefit of working for LSPs is more work (71%).

• Translators perceived that cost (40%) and speed (33%) are more important than

Some of the largest challenges facing translators are finding clients (55%), negotiating prices (50%), dealing with tight deadlines (35%). Just before the pandemic, linguists felt the market changing to lower prices (64%) and faster turnaround times (56%).

Though not included here, linguists’ comments found in the report provide a more human context of their jobs than the raw percentages.

The Standard Model and Its Beneficiaries

The current translation workflow is one where translation Buyers hire LSPs to provide translators and manage the translation process including day-to-day project management, translation reviews, source-target file transfers, and handling of invoicing/payments between Buyers and translators. Even with translation management systems (TMSs), the tasks of LSPs are still mostly manual with continual updates to project status and translation reviews. In short, LSPs orchestrate the translation process and relieve Buyers from needing dedicated localization departments.

Who Benefits From the Standard Model

The primary beneficiaries of the Standard Model are Buyers which can have their content translated without investing heavily in a localization team and the LSPs. While LSPs do provide a much-needed project management function, they are in control of the purse strings and, like other businesses, they exist to maximize their share of the purse.

Weaknesses of the Standard Model

Inadequacies range from workflow issues to fairness.

Project management overhead is a glaring inefficiency. Despite the use of TMSs, there is simply too much human administration and intervention throughout a project.

Translation delays can result from time differences between LSPs and their geographically-dispersed pool of translators especially when issues can not be resolved promptly.

Security is a major problem for the Standard Model. LSPs do not know who is actually doing the translating. Online MT engines have been used to translate texts risking exposure of propriety material. ^[3]

The inequity of the Standard Model, where the Buyer wants to minimize translation costs and the LSPs want to maximize their profits, leaves [especially freelance] translators at the bottom of the food chain.

A Blockchain-based Translation Workflow

Breaking with the Standard Model, the proposed translation workflow reduces human administration and improves translation workflows with blockchain as the backbone ^[4]

Blockchain, smart contracts and oracles are the key pieces of the proposed workflow. A blockchain is a decentralized ledger of immutable, encrypted records (blocks) securely denoting asset transfers such as source/target files. Since each block on a blockchain contains the identifiers of a provider and recipient of an asset, the provenance of an asset is traceable.

A smart contract is a computer protocol that is intended to enforce the execution of a contract without a third party. Smart contracts could facilitate direct source-target file transfers between Buyers and translators and quicker payment for translators when projects are completed. These transactions are trackable and irreversible.

For a wide set of applications, a blockchain, actually, a smart contract, might require real-world information. Fulfilling that need, a blockchain oracle is an entity providing network-external data through an external transaction. Linguists and MT engines are examples of oracles receiving data (source files) and sending data (target files) to a translation blockchain workflow.

Figure 1: Blockchain Translation Schematic

A skip through the workflow

While the SkipThrough of the blockchain translation schematic (Figure 1.) glosses over many details of the translation process, it points to where the human workflow administration performed by LSPs is completed by smart contracts with a blockchain recording the handoffs of files and payments.

1. As with the Standard model, a Buyer assembles source documents and project requirements including target languages, linguistic assets (terminologies and TMs), budgets, and schedules.

2. The source content, linguistic assets, and requirements are recorded on a blockchain.

3. Smart contracts execute throughout the workflow directing texts to TMs, then to MT engines, or directly to MT engines or translators. Each file transfer is recorded on the blockchain.

4. Based on MT review acceptability, smart contracts initiate transfers of translations to Translators/MTPEs for review. The blockchain records the translation transfers.

5. Once a reviewer approves the translations, a smart contract executes, thereby sending translated material to the Buyer. The blockchain is updated.

6. The buyer’s acceptance of the completed translations invokes a smart contract that sends payment to the Translators/MTPEs. The blockchain records the details of payments.

Who Benefits from the Blockchain Model?

The Buyers and Linguists are the primary beneficiaries. That is not to say that there is no role for LSPs in the translation industry. Until there is widespread adoption of a blockchain or some other nearly fully-automated model of translation, LSPs will co-exist with automation. Also, Buyers may turn to LSPs for projects when they lack the availability of PMs.

Buyers

Buyers want quality translations with tight deadlines and a limited budget.

The streamlining of the translation workflow with blockchain replacing much of the managerial overhead will reduce costs. The savings could be used for other localization projects and ideally for fairly compensating the translators.

Because every file transfer or handoff is recorded on the blockchain, the Buyer is fully aware of the state of the project at any time. They now have access to real-time project management.

The Buyer’s material is secure. Inherent features of blockchains in recording asset transfers are transparency, traceability, and security. With the appropriate service agreements with any of the oracles involved, security weak points can be tightened.

Increased automation leads to faster translations. Since files are transferred and tracked upon execution of smart contracts, time differences are eliminated and translations can be produced 365/24/7.

Linguists

As noted, linguists prefer to work directly for clients with better pay, less time pressure, and recognition.

In the proposed workflow, the work of translators can be tracked. Those producing quality translations would gain recognition and could be compensated in a fair, transparent, and consistent way. There is another side effect of traceability as well. Consistent errors either by humans or an MT engine could be identified and corrections made to improve quality on future projects.

Without the intermediate LSPs, linguists will be working and communicating directly with the Buyer. Yes, the workflow will be automated, but there would be no obstacles to human communication between the Buyer and the translators.

Elimination of time-difference delays and the human management level could allow for more time for actual translation and should lessen the time pressure felt by translators today.

Obstacles to the Blockchain Workflow

While there is much to be gained from the blockchain workflow, there are three broad hurdles for its success. One is technical and the others are due to industry resistance.

• The technical obstacles are huge. Despite all the hype and predictions, blockchain technology is in its infancy and its future remains uncertain. Nevertheless, blockchain technology is viable and scales with Bitcoin as the most visible example. So the utility of blockchain cannot be dismissed a priori.

• Industries do not usually embrace change, especially when it changes their business models. The Standard Model represents business as usual and it has taken time and effort to put the infrastructure into place. LSPs, who play a valuable role in today’s translation process, would be most resistant to change. However, the overhead of LSPs drives up translation costs, perhaps at the expense of the translators at the far end of the supply chain.

• Another major barrier is the human one. With the diminished roles of LSPs, localization managers would need to adapt to a new work environment, undoubtedly a stressful situation. Translators, especially those who have well-established relationships with LSPs, would lose a conduit for work and would also have to adapt. However, there could be monetary rewards as their work and expertise are recognized via blockchain.

Change is not easy!

A Few Final Remarks

Blockchain can provide the backbone for a supply chain that brings equity, improved work arrangements, and recognition to translators. At the same time, blockchain with smart contracts streamlines the workflow by automating much of the current managerial tasks. Granted, the blockchain model is a heavy lift and faces opposition from stakeholders that control much of the workflow today. In any case, whether technical, legal, or social pressures bring about change to the supply chain, solutions for a more equitable translation environment are being discussed and concrete solutions are being proposed. Change seems inevitable.

^[1] See TAUS Webinar “Blockchain: When the Token Economy Meets the Translation Industry” - https://blog.taus.net/blockchain-when-the-token-economy-meets-the-translation-industry; For fair pay, see: TAUS blog “Fair Pay for the translators and data-keepers!” - https://blog.taus.net/2021-according-to-taus

^[2] Pielmeier, Hélène, and Paul O’Mara, “The State of the Linguist Supply Chain,” CSA Research, January 2020.

^[3] See: https://slator.com/technology/translate-com-exposes-highly-sensitive-information-massive-privacy-breach/ and https://www.nrk.no/urix/warning-about-translation-web-site_-passwords-and-contracts-accessible-on-the-internet-1.13670874

^[4] For other blockchain architectures, see: Exfluency - https://www.exfluency.com and Kuhns, Bob, “The Pros and Cons of Blockchains and L10N Workflows,” TAUS White Paper, March 2019 - https://www.taus.net/insights/reports/the-pros-and-cons-of-blockchains-and-l10n-workflows-white-paper

Bob Kuhns is an independent consultant specializing in language technologies. His clients have included the Knowledge Technology Group in the Sun Microsystems Labs and Sun’s Globalization group. In the Labs, Bob was part of a team developing a conceptual indexing system and for the Globalization group, he was the project manager and lead translation technology designer for a controlled language checker, a terminology management system, and a hybrid MT system. He was also responsible for developing translation metrics and leading a competitive MT evaluation. Bob has also conducted research and published reports with Common Sense Advisory, TAUS, and MediaLocate on a variety of topics including managed authoring, advanced leveraging, MT, blockchain, and L10n workflows, and global social media.

Bob’s email is: kuhns@rcn.com

Why MT Matters and its Role in Digital Transformation

We live in an era where there is more information available to a digitally savvy human than has ever been possible in the history of mankind as we know it. The volume growth implications are so significant and substantial that it is worth considering some contextual facts to get a proper understanding of this fact.

The Encyclopedia Britannica announced in 2012 that after 244 years, dozens of editions, and more than 7M sets sold, no new editions would be printed. The 32 volumes of the 2010 installment, it turns out, were the last edition of this great publication. The primary cause for this was the increasing use and relevance of the Wikipedia (and other digital alternatives) which would cover 2,670+ Encyclopedia Britannica sized volumes if it were to be actually printed. While some may argue that the Wikipedia is less reliable, this contrast is quite astonishing and clearly, there is more information.

This explosion of content is even more astounding if we survey the larger information landscape which reveals the following fact described in the graphic below.

This explosion, however, presents special challenges to the modern enterprise which now needs to assimilate, digest and determine what is relevant and what is not. In this age of digital disruption, those who fail in doing this becoming increasingly irrelevant, as we have seen in the retail industry in particular. Once iconic brands now fall by the wayside, and will quietly disappear e.g. Sears, Toys R Us, and many more. Studies by experts suggest that many more companies, across many industries, will disappear because they fail to understand the changes in values and priorities inherent in this content explosion and the related digital disruption it causes.

The behavior of the modern customer has changed and is now much more affected by freely flowing content. In fact in many B2C and even B2B scenarios we see that the modern customer may conduct the whole customer journey without ever talking to a salesperson. Studies show that as much as 67% of the buyer’s journey is conducted digitally (though some put a different spin on that statistic), and customer behavior driven by content that they discover. It can be said that in the modern era, companies that provide relevant, high-quality content succeed, and those that don’t, become irrelevant. The following graphic shows the many stages at which relevant customer content is required to persuade and develop a deeper engagement with a potential customer, and then maintain an ongoing relationship with an enterprise or a brand after a customer relationship has been established.

Now, consider doing this across the many languages that are needed to engage and connect with the global customer, and we see the crying need for not just translation of mandated packaging materials, but translation capabilities that can support the constant and always updating content that may influence a buyer in their evaluation and decision-making process. And, also provide adequate information support in the post-purchase phase of the relationship.

While historically corporate marketing had a great degree of control, today most consumers distrust or at least prefer additional sources of this kind of product messaging, and many would rather trust the shared customer experience of fellow consumers. The value of business content increasingly has a very short shelf-life and thus traditional (slow and expensive) translation approaches are increasingly questioned for information that may have little or no value after six months.  In actual fact, the fastest growing type of content is actually user-generated content (UGC) that is found in blogs, FB, YouTube, Twitter and community forums. It is estimated by IDC that 70% of the content on the web is UGC and much of that is very pertinent and useful to enterprises to understand trends and customers better. This content is now influencing consumer behavior all over the world and is often referred to as word-of-mouth marketing (WOMM). Consumer reviews are often more trusted than “corporate marketing-speak” and even “expert” reviews which are often funded by the same corporations. We all have experienced Amazon, travel sites, C-Net and other user rating sites. It is useful for both global consumers and global enterprises to make this multilingual.

 It is estimated that as many as 600 billion words a day are translated by computers today, across the various MT (machine translation) portals. This dwarfs what the localization and professional business translation industry does by a factor of more than 99X! Recent reports suggest that a new MT developer, Alibaba, does as much as 200 billion words a day alone on their various eCommerce platforms. This brings the total MT word tally up to almost 800 billion words a day. Clearly, global customers need specific information that may not be available in their native tongues, and they will use MT to get at least a gist of what they need to understand. While many continue to moan about the imperfection of MT quality at a human linguistic quality assessment level, we have already reached a point in human history where the substantial bulk of language translation being consumed on the planet today is being done by computers.

 Global customers who research products and services, can and will get many disparate sources of information, that is not controlled by an enterprise to make their evaluations on whether to buy a product or not. MT will allow them to get access to non-native language content, and instantly obtain a translation that is “good enough” to support a personal evaluation process.

In our modern times, we’re experiencing a state of unprecedented connectivity thanks to technology. However, we’re still living under the shadow of the Tower of Babel in terms of global human communication ease. Language remains a barrier to business and marketing. Even though technological devices can quickly and easily connect, humans from different parts of the world often can’t. And traditional translation service offerings simply cannot scale to the real translation needs of the modern enterprise without leveraging technology in a substantial and competent way.

There are many kinds of business translation applications where MT just makes sense, and it would be foolish to even attempt these kinds of projects without competent MT technology as a foundation. Usually, this is because these applications have some combination of the following factors:

• Very large volume of source content that simply could NOT be translated without MT in any useful time frame
• Rapid turnaround requirement (days, hours or minutes) for the content to have any value to the content consumers
• A user tolerance for lower quality translations, at least in early stages of information review
• To enable information and document triage when dealing with large document collections and help to identify highest priority content from a large mass of undifferentiated content. This process also helps to identify the most important and relevant documents to send to higher quality human translation processes.
• Translation Cost prohibitions (usually related to volume)

One can find this combination of requirements in several customer communications oriented functions like providing technical support knowledge-base, eCommerce product listings, customer service/support, and customer experience reviews for all kinds of products and service experiences. However, in an increasingly digital world, we see that the need to be able to process large volumes of business content will only grow, and the need to identify what is most relevant and valuable for ongoing international business mission needs is becoming a critical success-enabling technology requirement.

Competently deployed machine translation technology, that is properly integrated with relevant content flows to enhance customer experience, solves high-value business problems that further and enhance any and all global business initiatives.

So if we are to summarize these key trends we see the following:

• A content explosion that makes huge amounts of information available to global customers to help them understand products and services on a scale that has never been seen before. Much of this content is out of the control of the modern enterprise but yet it can deeply influence the behavior of potential and existing customers of the enterprise. Understanding what is most relevant and important is also becoming an increasingly more valuable skill.
• An era where content is increasingly your best salesperson and customers everywhere will use digital content to make purchase decisions. For an enterprise to be relevant in the modern era they will need to be present at every stage of the buyer and customer journey with relevant and high-value content. Those that provide the best digital experience (DX) with relevant content will thrive and prosper, and those that do not will struggle and fail.
• The modern global customer expects to get as much content and information in his language as his counterparts across the world. MT technology use will continue to accelerate to support these needs to make relevant content visible in a timely and efficient manner. MT technology will continue to improve as the smartest researchers in the world continue to focus on it.

"Mass machine translation is not a translation of a work, per se, but it is rather, a liberation of the constraints of language in the discovery of knowledge."  

                                                                                      Peter Brantley

Thus, in this era of digital disruption, content-driven customer engagement, and B2C relationship building, where global customers want access to the same content that their English speaking counterparts have, what is the leadership at a modern enterprise to do?

In reviewing the needs for the day and the skills that really matter for the future increasingly point to three things:

1. An understanding of what is relevant content within the deluge that every enterprise today faces. The need is to increase relevant communication not just make any random content more available.
2. An alignment of the content development and management strategies, with efficient and optimized translation processes that enable the enterprise to quickly reach a global audience. Content creation needs to be aligned with content transformation (translation) and delivery strategies.
3. An understanding of the new AI-based emerging technologies that will help the enterprise to rapidly evolve to producing relevant content and establish a global digital presence so that the relevant content is delivered to the right customers at the right time.

 In a respected paper published in the Harvard Business Review, the authors point out three building blocks that can help drive a modern enterprise into building a market leadership position in this age of digital disruption. The building blocks are summarized in the graphic below.

And for those who look carefully, we can see that MT has now reached a point of being a critical and strategic technology to assist in this digital transformation.  MT enables the communication that enables and underlies product innovation from global teams, helps an enterprise to understand and communicate more effectively with customers across the world, and, also enables efficient delivery of highly relevant multilingual content across the world to build market leadership.

The Future of Translation in a Gig Economy

 This is a guest post by Luigi Muzii based on a presentation he made recently on the coming industry disruption. Digital disruption is all around us today, and one characteristic of how it manifests is how it sneaks up and is in control before the incumbents even realize what has happened. Sears and other retailers barely saw Amazon coming, taxi companies did not see Uber coming, the hotel industry was caught unaware by Airbnb and so it goes.  

A recent Cisco/IDC suggests that 40% of all companies today will be affected (disappear) by the digital disruption. 

 It is quite possible that a new player could emerge in the translation industry that produces a platform that allows buyers and sellers to congregate and conduct efficient transactions with minimal broker (LSP) support (or just platform support). The translation industry is one that still struggles to talk about quality in a way that is clear and meaningful to customers. A platform that provides CAT tools, properly integrated MT, and a straightforward means to discuss quality and the deliverable, could be a force of disintermediation. Several have tried and failed recently but the platform technology is getting better all the time. It could happen. Soon. There are too many people involved in performing repetitive, mundane tasks in a translation project, and some say it is ripe for change. 

• Platforms ensure consistency, quality, and a good customer experience through the whole buyer journey
• Platforms enable new people to enter the marketplace, both buyers, and sellers and often expand the traditional view of the market place
• Platforms are especially powerful means to create transformation around service offerings 
• TM and MT are not disruptive in themselves, but properly organized into intelligent  AI workflow solutions they can indeed be used to deliver disruptive services
• Mostly, platforms deliver new, no-hassle, customer experiences to industries where people have gotten used to less than satisfactory CX.

 This article suggests that getting legal advice for "standard" legal work is a service that is ripe for disruption. If this is indeed true, then how long before "standard" translation work will also follow?

 Don't be surprised if soon you might be able to ask a chatbot for specific legal advice.

 

 =====

Preparing for disintermediation: Or what will the future look like in a global gig economy?

The following are a few basic questions about the gig economy using the classic “Five Ws (and One H)” rule of rhetoric:

1. What is the gig economy?
2. Who benefits from it?
3. Where does it apply?
4. When is it going to prevail?
5. Why is the translation industry affected?
6. How is disintermediation relevant?

The answers to these questions raise a few more ones that will hopefully be given a tentative answer.
Let’s start with a brief recap first.

Hic et Nunc from Luigi Muzii

The translation industry

While the translation profession as we know it today was born in between the two world wars, with the development of world trade, the so-called translation industry was born between the late 1980’s and the early 1990’s, with the spread of personal computing.
In practice, with the burst of technology, in a few decades, a century-old single practice rapidly evolved into shops and then into an industry.

Industry 4.0 & Translation

The same irruption of technology has led to two new industrial revolutions.
In fact, in 2011, the German government coined the term “Industry 4.0” to indicate the “fourth industrial revolution” with smart machines capable of autonomously exchange information, triggering actions and control each other independently via the Internet, big data analytics, and AI.
Does the translation industry fit “4.0”? With some effort and a little imagination, the translation industry could be halfway between “2.0” and “3.0.”

The Gig economy

Let’s now address the six fundamental questions. The first one is, what is the gig economy?
The term gig was coined in the 1920s by jazz musicians to mean “engagement.” The concept of gig economy was introduced in 2009, when the effects of the financial crisis began to bite badly, to describe the economic activity of people using digital platforms for short-term engagements to make a living.

Where does the gig economy apply?

A gig economy typically develops after the disruption of markets following the establishment of technological platforms connecting businesses and independent professionals. In this respect, any market is exposed to the gig economy if its players can be digitally connected to customers regardless of their size and position.
The use of self-employed workers is not a peculiarity of post-crisis years. Businesses have been trying for decades to replace the traditional employment model to escape taxes and labor laws. Previously, intermediaries were used instead of digital platforms.

When does the gig economy prevail?

It has been happening, from consumption and leisure to services and manufacturing. Companies like Airbnb, Amazon, Foodora, Netflix, Uber, Upworks have been disrupting their sectors and nothing can apparently stop them, not even the class actions of drivers and riders or the efforts to have them pay their dues to the communities they thrive on.

Why is the translation industry affected?

The business model is roughly the same as that of the gig economy. The parcellation of jobs, the infinite quest for the lowest remuneration, the way jobs are dispatched, and how people are hired and remunerated in the gig economy is no news in the translation industry.

So even the most celebrated companies of the gig economy have little to teach to their translation industry counterparts except, maybe, for the tech element and the sophistication in tax evasion.

Who benefits from the gig economy?

The promises about the gig economy may sound appealing. Digital technologies let workers become entrepreneurs, free from the drudgery of traditional jobs while making extra cash in their free time.
Indeed, workers in the gig economy are often manipulated into working long hours for low wages and continually chasing the next gig, while companies exploit the many loopholes in the tax and labor laws.

The surge of the digital economy has led to a new feudalism and those who own the platforms are the new vassals.

How is disintermediation relevant?

The gig economy with its new landlords is reaching into all other industries, and localization is no exception.
Digital platforms are disrupting old-fashion markets by parceling out jobs in discrete tasks and matching customers and workers, with pay being determined by demand only.
From the customer’s perspective, disintermediation is the answer to their quest for convenience and for cutting out the additional costs charged by intermediaries.
Parcellation of jobs has been happening for a few years now in the localization industry. A major difference with the companies of the platform economy is the use of platforms.

The great decoupling

The wild side of the sharing economy and the gig economy is that convenience and affordability also come at a price, usually from eluding taxes and laws, thus, eventually, damaging the society.

Also, the sharing economy has created a new monstrous type of customer who expects the service level of the Ritz Carlton at McDonald’s prices.

And what about the promise of the sharing economy of freedom and additional substantial income? It couldn’t be farther from the truth. In fact, the growth of the sharing economy presents an economic paradox: Productivity is rising, while median income is flatting out.

Finally, the on-demand economy was supposed to unleash innovation. Can you see any real innovation coming? Or only a typical Schumpeterian “creative destruction”?

The future

The future is not what it used to be. With computers performing already 99% of translation jobs, a totally new approach should be devised to curb threats and take advantage of any opportunities brought by innovations.

Some questions arise then, that should be answered however challenging: Will the translation industry survive? How long? What will the translation business look like in five years? Is a career in translation still advisable? What are the options and the strengths to explore? What are the threats and the weaknesses?

How long will the translation industry survive?

Some people claim that the demand for translation is growing and that it will keep growing in the coming years, but the measurement approach followed so far is questionable. As a matter of fact, any growth in revenues may correspond to a growth in volumes, but it may also hide a stagnation if not really a decline in prices, and, possibly, in profits.

Looking at production life cycle stages, translation revenues might already have peaked, while profits have possibly been decreasing for a few years now. This would explain the revival of the M&A frenzy: Organic growth is getting harder and harder, more and more investments are required to keep businesses profitable, and consolidation is the easiest way to grow and the most profitable exit strategy.

What will translation look like in five years?

In five years, the platform war will be over and a bunch of wealthy few will most probably rule the business world.

However young, the translation industry is fast drawing near the end of a cycle and desperately needs to be renovated. Especially in the last few years, translation industry players have been desperately struggling to meet the demands of translation buyers craving to process ever-growing content volumes into more language pairs. Unfortunately, talents don’t combine with the abundance of tools, technology, and data because a varied bouquet of skills is increasingly required, while education initiatives are dramatically lagging. And while MT will keep proliferating, the shortage of talent will be much more serious.

In fact, the emphasis on language knowledge is still overstated when expectations are growing every day that Internet giants are going to solve the pesky language problem once and for all, without any intricacies and possibly at almost no cost.

LSPs should then be utterly concerned about the sustainability of their business models. Scrambling for scale might not be enough even for the largest providers: Translation will still be here in five years, it will be here also in twenty years, but the translation industry may not.

Is a career in translation still advisable?

Translation education still looks less demanding, thus faster, than scientific and technical education. The lower return is perceived as the result of high costs rather than of low benefits. Yet, however friendly technology may look today, skills other than languages are more and more needed to cope with the growing complexity of the business world.

In this respect, with the almost total absence of any real specialization from translation education, newbies and even practitioners will be needing intense continuous training all the time more to specialize and try to keep up with the growing expectations.

Unfortunately, with LSPs struggling to keep profiting despite obsolete, inefficient, and costly processes while resisting their customers’ pressures on prices, pays will keep lowering, thus forcing the best resources out of business. At the same time, the harshness of the gig economy will force more and more people with technical and science skills to look for additional incomes in translation. No specialization in medicine, biology, law, engineering, etc. would make a translator any better at translation than a physician, a biologist, an attorney, an engineer with the same language pair and the access to the same tools and resources.

What are the options and the strengths to explore?

Three areas should then be explored, technology, knowledge, and data. Machine translation is now a general-purpose technology and will be a game changer even more than it has been so far. Indeed, MT is going to be so pervasive as to be embedded practically in every tool and application. Don’t forget that the washing machine has changed the world more than the Internet, and yet many would hardly be able to tell how and how much.

Knowledge will be as important as technology. Language is a technology too, but it is useless without the necessary ability to exploit it. Just like language, any other technology is no magic wand. Technology does not solve problems, people do with their practical intelligence. The same practical intelligence allows them to devise the processes that enable technology to maximize benefits and minimize risks.

Finally, the human brain is still the most powerful processing tool when it comes to reasoning. And knowledge allows people to pick the best data to have the machine make inferences and reliable predictions.

What are the threats and the weaknesses?

The major threat comes from the business model that is common to most translation business players. Not only is this model obsolete and largely wasteful, it is a major reason for disintermediation. And, in fact, industries remaining too long as such with large inefficiencies are ideal candidates for disruption.

A major weakness comes from what is conversely often perceived and brandished as a weapon: Information Asymmetry. Only distrust and discontent come from the imbalance in transactions due to the inability of buyers to assess the value of service before sale.

Another significant weakness is the growing skill shortage. This is due to a killing combination of increasingly lower pays driving best resources out with inadequate educational programs producing poorly-skilled would-be translators.

Finally, the constant tide of new entrants and substitutes will help further undifferentiation and minimize any network effect.

New entrants

The many affordable technologies and the very low financial, commercial, and legal barriers will result in new entrants being more and more often outsiders. But raising barriers is not the solution.

On the eve of disruption

Decreased transaction costs are expunging intermediaries from electronic value chains.

This means that also a buyer-seller matching platform for translation could be hard to develop, setup and run profitably. A so-called marketplace is not enough. For real disintermediation, best-matching algorithms are required to shorten the traditional translation supply chain. However, project management can hardly be totally automated especially for large and complex jobs involving several language pairs. The same goes for vendor management.

However, for small, single-pair jobs there will be more and more customers searching for translators through portals, willing to use them as virtual one-stop shops. Also, these customers will most probably be more and more expecting to have their content translated nearly for free if not for free. On the other hand, this is a typical sharing economy effect.

Will you be still willing to fight for any customer and any job, even for those going for the cheapest price? There will be more and more of them even among the once premium customers in the legendary premium segment.

So what?

If your competitors are getting stronger and stronger and you are unable to outdo them, you might band together with them and possibly gain some advantage rather than just giving up.

Side with evil

In other words, you can embrace the sharing economy and try to replicate the success of the companies in the gig economy.

The other dude

In this case, be ready to embrace Uber’s co-founder Travis Kalanick’s philosophy and get rid of the other dude, i.e. go for complete automation.

Reputation

Be also aware that high-attrition rates may not be a feasible long-term strategy. Unfortunately, and yet unsurprisingly, when getting bigger and bigger, rather than investing more money and more ability in the employee experience, companies usually become worse places to work. And in this case, things can get very bad if the tide of side-giggers withdraws.

Reputation is a unique asset, that is hard to gain and much too easy to spoil, with both customers and vendors.

So, the next time you find yourself thinking about cutting costs to raise profits or protect your margins, remember that someone might pay your savings and your reputation will eventually be affected.

Re-intermediation

There is no reason to fear disintermediation. Technology allows mindful players to develop and provide new service bouquets, but this requires a strong brand, the ability to differentiate from competitors, and deep diversification of services.

Digital transformation is no child’s play, though, and every business has its own intricacies. When seeking business opportunities in foreign markets, companies are challenged with functions they are not expert at and must adapt fast. Most of these companies embraced automation and digital transformation way earlier, but they still have issues in handling their digital content.

Focus on the "S" in LSP

There are many good opportunities for LSPs there, provided they can re-shape their business models and start adding real value. In times of industry 4.0 companies are no longer willing to partner with old-fashioned organizations with virtually no real tech savvy.

Mindful LSPs may start by refining their service offering by including consulting services in their bouquets for companies that are trying to do business abroad.

Exploit technology

In this respect, the approach to technology should go well beyond CAT, TMS, and MT and extend to modern content processing technologies and techniques like machine learning, AI and natural language processing, to make content more useful to humans and computers.

Turn data into assets

To this end, LSPs should turn their data into assets and make the most of it. Machine learning algorithms are rapidly becoming a commodity, and the cost of even the most advanced of them will soon plummet. The value will not be in algorithms, then, but in data, that is indeed the oil of the digital era.

Measure

As a first step, start measuring. Through measurement, you’ll know more, reduce uncertainty, and thus risks. Anyway, for correct measuring you must perfectly know your data, master metrics, identify key measurements and the right tools to use, and, above all, develop and continuously refine your methods of measurement.

Once you have made your measurements and collected the results, convey this information to customers so that they can positively correlate it with your capabilities.

Knowledge

“Lunch atop a skyscraper” is a very famous picture, but few probably know its title, history, and, above all, who shot it. Even fewer would know who shot the “shooter”.

This is the kind of knowledge that might be considered specialized and yet it’s available to all, but you must have the practical intelligence to acquire it.

Today a computer system can play Go or drive a car, but still, no Go-playing computer can also drive a car. Machines may perform specific tasks, but they lack understanding of the world—sentience—and cannot transfer knowledge laterally between domains.

Translation will be more and more an engineering thing, but machines will remain dependent on humans for building their “knowledge” from training data for the foreseeable future.

Embrace the future

The future has already begun, tempus fugit, time is running out and it is always less than you expected. So, if the question is when, the answer is now, hic et nunc, before it’s too late.

=======================

Luigi Muzii has been in the "translation business" since 1982 and has been a business consultant since 2002, in the translation and localization industry through his firm. He focuses on helping customers choose and implement best-suited technologies and redesign their business processes for the greatest effectiveness of translation and localization-related work.

This link provides access to his other blog posts.