Jill Lepore is a professor of American history at Harvard University and chair of Harvard’s History and Literature Program. She is a staff writer at The New Yorker, and recently has written about Clayton Christensen’s ‘theory of change’ of disruptive innovation.
Although mannerly, Lepore’s dismissal of Christensen’s theory was a sharp attack on one of the most widely cited and celebrated ideas in modern business and since Lepore accused Christensen of poor scholarship, Drake Bennett of Bloomberg BusinessWeek reached Christensen by phone to ask him questions in response to Lepore’s takedown of his theory.
In the excerpts from the hour-long conversation, one or two things emerged clearly:
- Disruption doesn’t happen overnight;
- Disruptive innovation is not a theory about survivability;
- A single although sustaining innovation cannot be disruptive.
Talking about the innovation brought about by the iPhone, Christensen asked a key question: “Who are you disrupting?”
The translation industry is a good test field for Christensen’s theory.
In an article for the ATA Chronicle of May 2012, Jost Zetzsche ventured to predict the immediate future for translation technology that actually, in his own words, “is finally now, in 2014, becoming reality…”
He probably forgot the lesson from Watts Wacker and Jim Taylor in The Visionary’s Handbook saying that “The closer your vision gets to a provable truth, the more you are simply describing the present.” Maybe Jost also overlooked the fact that the translation industry is very conservative. It’s true that a lot has happened within the last two or three decades, but nothing really disruptive (at least from Christensen’s standpoint); not even translation memories have changed the century-old process. There is, though, an innovation that helped bring a disruptive innovation. I am talking about collaborative platforms that made crowdsourcing possible.
This is another outward sign that innovation seldom comes from isolation and rather often from collaboration, that it is always more the product of a collaborative process rather than the result of the intelligence of one individual, and that it is not any new piece of software, although astonishing.
At the TAUS European Summit in June 2012, Jack Boyce of Google ended his presentation describing an imaginary ‘TransDirect Inc.’:
- New MLV exclusively working with freelance translators (no SLVs);
- Built on a proprietary set of tools to connect creators directly to translators, and ensure reliability;
- Pay translators more, charge client less;
- Radical transparency from the client’s perspective;
- Vision: the eBay/Amazon marketplace of translation. The best place to work for a freelance translator.
This view entails an extensive use of technology, thus requiring heavy system integration capacity. System integration involves a broad range of skills including software and hardware engineering, as well as enterprise-level vision, business process management, and general problem solving skills. It is a challenge for LSPs that, in most cases, are brick and mortar translation companies, when not mom & pop shops. Even the largest MLVs do not have the necessary in-house capacity, not even to outsource a system integration project, and must trust their contractors.
The translation industry is an open market, with extremely aggressive competition. Like the translation industry, open market and extreme competition are also typical of the NYC cab system, with crappy cars and poor service, but very low fares. NYC cabs are much cheaper than London cabs, which work in a somewhat regulated market (although unquestionably not a monopoly) and generally offer a definitely better service. NYC cabs are really a public means of transport, and a fair alternative to subway and buses, while London cabs are convenient only when the Tube stops running, for a night ride back home, or to catch very early trains or planes: the Tube is generally more efficient, cheaper, and faster, although quite filthy and crowded.
Just like public transportation, price and speed are primary requirements for translation.
Uber is a mobile application that connects passengers with drivers of vehicles for hire and ridesharing services.
Initially, Uber drivers used luxury vehicles for hire, allowing users to be informed on the cars available closer to their present location, and helping drivers to cut downtimes.
In 2012, Uber expanded its basic service with a wider selection of cars to broaden its market to include also ridesharing in non-taxi vehicles.
Initially, Uber prices were about 50% to 75% higher than prices charged by conventional metered taxis, as a premium that customers would pay for a cab service that is not only reliable but also punctual and comfortable. Today Uber’s pricing is similar to metered taxis although all hiring and payment is handled exclusively through Uber and not directly with the driver.
Uber is a perfect example of disintermediation, and the allegations of illegality from taxi companies come from the attack Uber drivers carry to one of the most important niches in the market.
Uber is just another shining example of what happens when an old-fashioned service is transformed and renewed by using technologies that increase efficiency and effectiveness, not only for customers and end users, but the service as a whole.
Uber is definitely disruptive, but the question is “Who is it disrupting? Drivers or taxi companies?”
The typical translation service bundle consists also of vendor and project management, which are actually the two main processes of a mainstream LSP and can be sold as discrete added-value services. This is especially true for crowdsourcing.
As a business model, crowdsourcing makes it possible to blend efficiency with highly skilled professionals by recruiting specially selected communities of paid translators. Yet, a specialized back-end technological infrastructure is needed.
Again, do LSPs have the necessary skillset to face this challenge?
For a few years now, the trend is constantly growing to reduce the size of single projects. It is a model change still resting on the now traditional use of email to support a continuous flow of strings or small files to be processed in a very short time. This change is largely due to the adoption of content and workflow management systems by an increasing number of translations buyers.
At the end of the supply chain, most translators are clearly and understandably annoyed with this model because of the overhead it involves and the financial instability it entails. On the contrary, in an increasingly crowded arena, LSPs try to leverage continuity to retain customers, driving them to their TMSs — that possibly they can hardly run — and pushing them to sign SLAs.
And yet, this model could prove effective even to translators, when a special app will eventually be available. The app could alert the translators that a new ‘drip’ is waiting for translation, and the translators could simply access it on the TMS without even logging in; the app would require the translator to register and store the different credentials for each customer using the system in a virtual safe. Payments could be made on a PayPal or even Bitcoin account. Is it that hard to develop? Probably yes for an ordinary LSP.
This could be easier with reverse and forward proxy servers that, according to Sajan, are raising the interest of an increasing number of translation buyers. Again, are LSPs ready to meet the challenge?
In conclusion, there is no reason to be scared of technology, even or mainly machine translation. Every day most LSPs show they are not ready to make proper use of technology, especially machine translation. This is the reason for the continuous, relentless, and increasing demand for experienced and tech savvy professionals. This is the reason behind the increasing attempts of brazenly incompetent LSPs to resort to machine translation to reduce compensations and keep their margins afloat.
Therefore, it is miserable and distressing to know, hear, and read about neo-luddite translators raging against machine translation and even translation technology at large, when most of them probably only know about Google Translate or use basic translation tools.
Technology may bring about salvation or threaten livelihoods. Or it may do both. Massive technological innovations have radically reshaped our world. We need to develop new business models, new technologies, and new policies to stay economically viable in an age of increasing automation. Those who embrace the new technologies will be the ones who benefit most. The others will drift apart.
The real change then, if any, for translators could be in racing with the machines, not against them.