the industrialization of translation. causes, consequences and challenges

8/10/2019 The industrialization of translation. Causes, consequences and challenges

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/ - - John Benjamins Publishing Company

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e industrialization of translation

Causes, consequences and challenges

Keiran J. Dunne

Much has written by scholars on translation as product and as process, but

relatively little attention has been paid to translation as a commercial service,

business or industry. Tis article proposes a modest step in this direction by

using microeconomics as a window through which to examine the industrializa-

tion of translation, focusing on causes, consequences and challenges. It begins by

analyzing the outsourcing of translation and translation-related services. It then

considers consequences of large-scale outsourcing, including quality uncer-

tainty, information asymmetry, adverse selection, price pressure and perceived

commoditization. Finally, the article explores challenges posed by these develop-

ments, including signaling and screening, the productivity imperative and the

development of expertise. Te article concludes with an overview of potential

areas of research to be explored in this track in future issues.

Keywords: translation, industry, microeconomics, outsourcing, quality

uncertainty, information asymmetry, expertise, signaling, screening

You can ignore the market, but the market wont ignore you. Anonymous

Tere is no such thing as a commodity, only people who act and think likecommodities. Everything can be differentiated. Teodore Levitt (1991, 34)

Introduction

ranslation as a profession has historically been a solitary cra practiced by in-

dividuals. In recent decades, however, the globalization of markets (Levitt 1983),

the digital revolution, the advent of the information economy (Drucker 1988) and

the globalization of production (Ghemawat 2007) have transformed translationfrom a profession confined primarily to individuals, to a cottage industry mod-

el and finally to a full-fledged industrial sector (Shreve 1998, 2000). In recogni-

tion of the fast growth and increasing importance of professional translation and


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Keiran J. Dunne

translation-related services to national economies, the United States, Canada and

Mexico recognized translation as a distinct industrial sector in 1997 (US OMB

1997), followed by the European Union in 2008 (Eurostat 2008b, 81).1

oday, thesize of the language industry is estimated at USD 31.5 billion (Kelly and Stewart

2011, 6).

In 2012, the language industry is primarily digital, outsourced, and project-

driven. According to Common Sense Advisory, 87% of all translation buyers out-

source most or all of their translation projects (Beninatto 2006, 4). Nearly all

translation work is done on a computer, and most assignments are received and

submitted electronically. Tis enables translators to work from almost anywhere,

notes the United States Department of Labor (2010). Te role played by digitiza-

tion and projectization in the birth, growth and diversification of the language

industry have been discussed by Shreve (1998, 2000) and by Dunne and Dunne

(2011), respectively. Consequently, we will not dwell on them here. Instead, this

article will examine more closely the role played by outsourcing and other micro-

economic forces in the emergence of the industry, as well as certain consequences

and challenges posed by the industrialization of translation.2

Outsourcing

From a microeconomic perspective, outsourcing can be considered the primary

impetus for the advent of the language industry. In the 1980s and 1990s, soware

and hardware companies that entered international markets soon concluded that

translation and localization were not among their core competencies and that it

would be more efficient to outsource, or subcontract, the nuts-and-bolts work of

adapting soware products for international markets to external service providers

(Esselink 2000, 5). A new type of company arose in response to this demand the

language services provider (LSP) and rapidly established itself as the foundation

of a new outsourced services sector. In the predominant language industry out-

sourcing model, an organization requiring localization or translation subcontracts

the project to an LSP, which in turn subcontracts translation and other language-

related services to a secondary LSP that specializes in a single language and works

with in-house translators or with freelancer translators, or subcontracts transla-

tion and other language-related services directly to freelancers (see Figure 1).

It is worth pausing here to briefly discuss the variables that shape the out-

sourcing decision, namely fungibility, specialization, measurability and intercon-nectedness (Ungson and Wong 2008, 252260). Fungibility refers to the degree to

which a given commodity (i.e., a tradable product or service) can be replaced in

whole or in part by one of like nature or kind. Fungibility, or interchangeability,


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Te industrialization of translation

depends on the inherent uniqueness of the product or service, and thus of the

relative specialization of the work required to create it. All things being equal, the

more unique the product or service and the greater the specialization requiredto create it, the less likely it is that the work of producing that product or service

will be outsourced. Measurability refers to the fact that potential outsourced ac-

tivities are typically evaluated in terms of their cost and quality relative to their

production outside the company (Ungson and Wong 2008, 254). All things being

equal, costly activities that generate relatively little revenue are more likely to be

outsourced than activities whose revenue significantly exceeds their cost. Finally,

an activitys interconnectedness to the organizations core strategy also shapes the

perception of the relative benefits or dangers of outsourcing that activity. In sum,the widespread adoption of outsourcing as a business strategy with respect to

translation and translation-related services suggests that translation is perceived

as (a) tradable on an open market; (b) not particularly unique or specialized, and

thus interchangeable; (c) either unmeasurable or characterized by a weak cost/

benefit ratio; and/or (d) not closely tied to organizations core strategies.

Translation: A tangible and intangible product

Te choice of an outsourcing partner is shaped to a great extent by the relationship

between perceived quality and price. In the marketplace, quality is not viewed as

an absolute but rather is framed in terms of customer satisfaction. Tus, quality is

properly understood not as degree o excellence, but rather as an intrinsic character-

istic, property or attributethat influences the ability of a product to meet a buyers

requirements (identified needs) and expectations (unidentified needs). Te notion

that quality is whatever the customer says it is presents particular challenges in the

realm of services. Te intangible aspects of services make it difficult to identifythe characteristics of the outputs that shape perceptions of value and especially

to measure the adequacyof those outputs in a standardized, repeatable way with

respect to customer requirements and expectations.

Client LSP Freelancer

Figure 1. Te language industry subcontracting chain. Clients subcontract projects to

LSPs, which in turn subcontract work to freelancers and single-language vendors and/or

to specialized providers (not shown here).


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Keiran J. Dunne

Te outsourcing of translation magnifies these problems as translation is both

a product and a service. It follows that perceptions of translation quality are shaped

by both tangible and intangible characteristics and by the subjective assessment ofthose characteristics. In this respect, it is perhaps more useful when discussing the

market for outsourced translation to heed the advice of Teodore Levitt (1981)

and speak not ofproductsand servicesbut rather of tangiblesand intangibles:

Distinguishing between companies according to whether they market services or

goods has only limited utility. A more useful way to make the same distinction is

to change the words we use. Instead of speaking of services and goods, we should

speak of intangiblesand tangibles. Everybody sells intangibles in the marketplace,

no matter what is produced. (Levitt 1981, 94)

Although tangibility is typically associated with products and intangibility with

services, the sales appeal of both products and services is shaped to a very large

extent by intangibles. In practice even the most tangible of products cant be

reliably tested or experienced in advance, notes Levitt (1981, 96).

How do customers evaluate the quality of tangibles and intangibles? How can

these ideas help us to understand the factors that shape buyers perceptions of out-

sourced translation and translation-related services (i.e., perceptions of LSPs and

end clients, see Figure 1)? According to Nelson (1970), Darby and Karni (1973)and Zeithaml (1981), three sets of essential characteristics shape buyer percep-

tions of both tangibles and intangibles:

1. Search qualities: attributes that buyers can inspect and evaluate beorebuying.

Search qualities are typically associated with tangibles.

2. Experience qualities: attributes that buyers can evaluate only afer buying.

Evaluating canned tuna fish, for example, requires that the customer purchase

different brands for consumption and comparison (Nelson 1970, 312).

3. Credence qualities: attributes that buyers cannot evaluate, even aer purchaseand/or consumption, because they lack the knowledge or capacity to do so.

Tese attributes provide a framework enabling us to better understand when, and

even if, buyers can assess quality.

Te adequacy of translation and translation service is evaluated primarily on

the basis of experience and credence qualities. A translation cannot be touched,

seen, or evaluated prior to purchase. Sample translations offer a partial solution to

this problem by proposing limited search qualities for inspection, but the char-

acteristics of the target text may ultimately differ in significant ways from thoseof the sample. For instance, there is no guarantee that the person or team that

performed the sample translation will also perform the actual project work unless

this is formally stipulated as a contractual obligation. ranslation requires a level


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of proficiency in one or more foreign languages that most clients do not possess.

Indeed, this lack of knowledge is a major factor in many clients decision to out-

source the work in the first place. Consequently, translation is typically perceivedas a black box by clients. In other words, buyers of outsourced translation gener-

ally lack a fully informed basis on which to make purchasing decisions. Tus, buy-

ers of translation are essentially buying apromise: When prospective customers

cant experience the product in advance, they are asked to buy what are essentially

promises promises of satisfaction (Levitt 1981, 96). In the next section, we will

explore the ramifications of this observation for the outsourced translation ser-

vices market, and by extension, for the language industry as a whole.

Quality uncertainty, information asymmetry and adverse selection

In 1970, George Akerlof wrote a landmark article entitled Te market for lem-

ons: Quality uncertainty and the market mechanism. In this seminal article,

Akerlof explains how and why uncertainty about the quality of a product can have

a profoundly negative impact on the market for that product. Akerlof uses the

market for automobiles to illustrate his argument. For the sake of simplicity, he

posits that there are only four kinds of cars: new and used, as well as good and bad.Bad cars, which are referred to colloquially as lemons in North America, are to

be found among both new and used cars, and buyers cannot distinguish the good

from the bad. Because of this quality uncertainty, people who buy a new or used

car do not know whether they are purchasing a good car or a lemon. But they

do know that with probability qit is a good car and with probability (1 q) it is a

lemon; by assumption, qis the proportion of good cars produced and (1 q) is the

proportion of lemons (Akerlof 1970, 489).

Over time, owners gain more knowledge about the quality of their particular

car based on its performance and reliability. Firsthand knowledge enables owners

to estimate the probability qthat their car is a good one with greater accuracy. In

this way, an asymmetry in available information develops whereby sellers gener-

ally know more about the quality of cars than buyers (Akerlof 1970, 489), but since

buyers cannot tell good and bad cars apart, both types of cars must sell at the same

price. Buyers are unwilling to pay a premium because there is a significant chance

(1 q) that any given car is a lemon.

Since the owners of good used cars cannot receive a price that reflects their

cars true value, they have no incentive to sell. As owners of good used cars refrainfrom selling their vehicles, the average quality of used cars in the market drops,

which in turn causes buyers to lower the prices they are willing to pay. As sell-

ing prices drop, so too does the threshold of quality at which owners decide that


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Keiran J. Dunne

selling their car is not worthwhile. Te end result is a market in which most cars

traded will be the lemons, and good cars may not be traded at all. Te bad cars

tend to drive out the good. because they sell at the same price as good cars(Akerlof 1970, 489490). Te process whereby asymmetric information leads to

market failure is referred to in economics as adverse selection.3

Lets be clear about how dramatic and worrying this problem is. What Akerlof

described is not a market where some people get ripped off; its much more seri-

ous than that. He described a market that should exist and simply doesnt because

of the corrosive force of inside information. Akerlof showed that [no] value-

creating trades happen because the buyers will not buy without proof and the

sellers cannot offer proof. (Harford 2005, 111)

Akerlof demonstrated how quality uncertainty can lead to the development of

asymmetric information, which in turn can cause adverse selection: when buyers

have imperfect information and are unable to ascertain the quality of products on

offer, sellers of low-quality products may come to dominate the market, under-

mining the very possibility of mutually beneficial transactions. For this contribu-

tion to economic theory, Akerlof was awarded a share of the 2001 Nobel Prize in

economics.

It can be argued that Akerlofs market for lemons is analogous to the contem-porary market for outsourced professional translation services: both are charac-

terized by the fundamental problem of quality uncertainty, and in both cases this

problem is exacerbated by asymmetric information. Moreover, the magnitude of

the problem is presumably greater in the translation services market than in the

used car market. As we have seen above, experience and credence qualities play a

predominant role in shaping the perception of translation quality. Consequently,

buyers of translation cannot readily assess translation quality prior to purchase,

and oen cannot do so even aer purchase.

Let us first consider the market for translation services at the end of the sub-

contracting chain, where the buyers are LSPs and the sellers are freelance transla-

tors (see Figure 1). In the absence of personal experience (e.g., a prior business re-

lationship), LSPs as buyers of translation services cannot readily distinguish good

translations from bad ones, much like the buyers in Akerlofs used car market.4

Tis uncertainty about the quality of translation suggests that the prices LSPs are

willing to pay do not reflect the truequality of translation provided by a given

freelance translator but rather the LSPsprobabilistic estimatesabout the quality of

translation provided by individual freelance translators in the market as a whole(1 q). In other words, since LSPs cannot tell good and bad translations apart,

good and bad translations must sell at the same price. Barring personal experience

or some other form of inside information about the specific translation provider,


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buyers are unwilling to pay a premium because there is a probability (1 q) that

any given translation will be bad. In this way, quality uncertainty leads to a gap

between the theoretical true value of good translation services and actual prevail-ing rates offered by LSPs.

Te negative effects of quality uncertainty in the translation services markets

are exacerbated by the development of asymmetric information. Much like auto-

mobile owners in Akerlofs used car market, translators may gain a better under-

standing of the relative quality of their product over time in the form of repeat

business, informal feedback from project managers with whom they have worked,

etc. In this way, an information asymmetry develops whereby experienced free-

lancers know more about the quality of their services than generic buyers (i.e.,

LSPs with which the freelancers have not previously worked), but as noted above,

since LSPs cannot tell good and bad translations apart, good and bad translations

must sell at the same price. Te asymmetric information developed by freelance

translators can lead to adverse selection in much the same way as in Akerlofs used

car market. If good translators cannot receive a level of pay that reflects the true

value of their services due to the inability of LSPs to tell good and bad translators

apart, they may conclude that it is not worthwhile for them to continue to par-

ticipate in that market. As good translators leave the market, the average quality

of translators in the market drops, which in turn causes LSPs to further lower theprices they are willing to pay.5And so on.

Te ability to improve probabilistic estimates of quality over time is not con-

fined to freelance translators, of course. In similar fashion, LSPs understanding of

the relative quality provided by translators evolves as they discern patterns in sub-

contractors performance over time and the relative frequency and extent to which

subcontractors work requires remediation, for example. On a larger level, LSPs

understanding of the relative value of translators also evolves due to the LSPs

experience buying and selling translation services for projects involving various

language pairs in various domains. In other words, over time, an LSP that works

with a given freelance translator can gain a deeper understanding of the relative

quality (and thus the value) of the services offered by that freelancer, compared to

the market average, than that freelancer himself or herself. LSPs that possess asym-

metric information about the quality of individual freelancers services can use

this insider information to enhance their profit margin via arbitrage (assuming,

of course, that the LSPs can estimate the discrepancy between prevailing rates and

individual freelancers rates, and can exploit this difference when selling services

to end clients; see Figures 1 and 2). In sum, when quality uncertainty and infor-mation asymmetry obtain in a given market, buyers who know more than sellers

can use inside information to their advantage. Te converse is not true, however.

Sellers of good products cannot benefit from inside knowledge and command


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Keiran J. Dunne

premium prices unless they can offer proof, which by definition is not possible

in a market characterized by quality uncertainty (Harford 105). Te net effect is

downward price pressure (see Figure 2).6

Tese forces operate not only at the end of the subcontracting chain, but also

at the beginning of the chain, where the buyers are end clients and the sellers are

LSPs (see Figure 1). Just as LSPs are unable to distinguish between good and bad

translations in the absence of personal experience or other insider information,

so too clients cannot readily distinguish between good and bad LSPs. Since clients

cannot tell good and bad LSPs apart, good and bad LSPs services must sell at

the same price. Moreover, information asymmetries benefit buyers (clients) rather

than LSPs (see Figures 1 and 2). Tis dynamic does not appear to be a merely theo-retical problem. Indeed, quality uncertainty and information asymmetry emerge

as consistent themes in postings on professional networking sites such as LinkedIn

and on translator forums such as ProZ.com and ranslatorsCaf.com (although

the postings do not generally frame the problem using these terms from economic

theory).

Quantifying productivity

Outsourcing presupposes that the scope of the work effort can be quantified. In

other words, buyers and sellers must be able to accurately estimate the volume of

work in order to determine how long it will take and how much it will cost (i.e., to

create project schedules and budgets). In most industries, time and cost estimates

are derived using productivity and cost metrics. Productivity is typically estimated

or measured by dividing the volume of work by a baseline work output rate. Te

resulting ratio, or metric, is expressed in units of output of work per hour (e.g.,

number of widgets produced per hour). In similar fashion, cost metrics are ex-pressed in monetary units per unit of output of work (e.g., dollars or cents per

widget produced).

Price pressure

Information asymmetry

Information asymmetry

Price pressure

Less info

More info Less info

More info

Buyer Quality uncertainty Seller

Figure 2. Quality uncertainty and information asymmetry tend to drive down prices,

benefitting buyers more than sellers.


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Te establishment of translation productivity metrics, and by extension cost

metrics, presents particular problems. Human translation is not a mechanical pro-

cess, but rather an intelligent, knowledge-based activity (Wilss 1996a, 1996b). Teprocess by which translation input (source text) is transformed into output (target

text) is thus inherently subjective. A target text represents the synthesis of all of the

inferences and decisions made by the translator, and the inferences and decisions

made by one translator may be different from those that another would make. Te

subjective nature of human translation and the fact that translation productivity

is affected by a host of factors, not the least of which is the individual translator

himself or herself, raise fundamental questions about the very possibility of defin-

ing generic productivity rates.

Te challenges of estimating translation and localization work effort and ac-

tivity durations are compounded by the absence of empirically validated trans-

lation and localization productivity metrics.7Consequently, estimates are gener-

ally based on individual expert judgment or analogous estimates from previous

projects completed by a given company or organization. Mller (2007), Densmer

(2010) and Dunne (2011a) provide a high-level overview of the types of factors

taken into consideration by individual experts and organizations when estimating

work effort and duration, but much more work needs to be done. Tere is an ur-

gent need for large-scale studies and/or industry initiatives to develop and validateproductivity metrics, and to identify and assess the variables that can affect pro-

ductivity. Te development of validated metrics would help alleviate the lemon

effect of quality uncertainty discussed above.

e word as a proxy for work and cost

One of the more unfortunate consequences of the industrialization and outsourc-

ing of translation and localization, and the concomitant disaggregation of transla-

tion or localization project tasks, is the fact that the industry has adopted the word

as the base unit of work and cost estimates for translation and translation-related

services such as editing and proofreading.8Te use of the word as the base unit of

scope definition represents an attempt by the industry to standardize and normal-

ize the estimation of work effort, and by extension, the pricing of translation and

translation-related work. Indeed, in June 2005 the Localization Industry Standards

Association released the initial dra specification of GMX-V, a standard whose

stated goal is to provide a unified and verifiable standard of measurement ofwords and characters based on the characteristics of individual sentences. Te

aim is to provide sufficient detail to enable an accurate definition of the scale of the

translation task (Zydron 2004). Te fact that translation is undertaken to enable


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Keiran J. Dunne

multilingual and cross-cultural communication suggests that work, cost and price

should be estimated based on the intended function and desired effects of the com-

munication, not on surface characteristics of the message. Ironically, an excessivefocus on words at the expense of meaning is a critique that has been traditionally

leveled at machine translation, not human translation.

Te use of the word as the base unit for cost and productivity estimates and

measurements likely stems from the fact that perceived quality is shaped largely

by experience and credence attributes, as discussed above. Words are tangibles

insofar as they can be counted and analyzed. Consequently they are one of the few

search attributes available to buyers and sellers of translation input and output

(i.e., source text and target text). However, words are also intangibles as signifiers

of meanings, and this function of words places them squarely in the realm of ex-

perience and credence attributes.

Tese observations help us understand how and why the word has been ad-

opted as a proxy for work effort by the industry. Tey also underscore the fact that

although the word is used as a proxy for work, and thus of cost, it is not necessarily

a proxy for quality (i.e., adequacy) or value. Te relative richness of words as expe-

rienced and evaluated by a reader and by extension, their function and value, if

we are to speak of words in economic terms can vary dramatically depending

on the context of use. For example, a five-word tagline is generally far more valu-able than a five-word sentence from a 400-page technical manual. If the transla-

tion of the five-word tagline is worthmore, it should costmore. Tis implies the

use of price scales or tiers. However, absent a firm understanding of the character-

istics that shape the perception of value (e.g., function of the communication; cost

of communication failure; audience expectations and degree of scrutiny; etc.) and

that influence work effort (function of the communication; relative degree of con-

notation, denotation and ambiguity in the source text; ambiguity; newness of the

domain; the degree of overlap between source and target concept systems; etc.), it

is unclear how translation pricing scales or tiers could be established.

Te inability of buyers and sellers alike to reconcile the relationship between

translation tangibles and intangibles and express that relationship in terms of

work, cost, quality and value is arguably one of the most fundamental problems

facing the industry today. It is said that Einstein had a sign hanging on the wall

of his office that said, Not everything that counts can be counted, and not every-

thing that can be counted counts. Indeed, it could be argued that by focusing on

words and the mechanics of word counts, the industry has lost sight of the forest

for the trees and forgotten what really matters in translation, namely communica-tion and meaning.


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Price pressure

Te phenomena of quality uncertainty, asymmetric information and adverse se-lection may help explain the price pressure that has characterized the market for

outsourced translation services over the past two decades. Indeed, Rory Cowan,

CEO of Lionbridge echnologies, has observed that prices of translation dropped

30% in constant terms between 1992 and 2003:

In 1992, the price of a polished translation from U.S.-based multi-languageven-

dors (MLVs) was generally $0.22 to $0.27 per word for French, Italian, German

and Spanish (FIGS). oday [December, 2003] U.S.-based MLVs are still charging

US$ 0.22 to 0.27 per word for high-end FIGS, even though inflation has reduced

the buying power of U.S. dollars by 30% during that time ranslation consum-ers have experienced a 30% decrease in price per new word if the effects of infla-

tion are taken into account. (Cowan 2003; emphasis in the original)

Likewise, Donald Barab, Vice President of Professional Services at the ranslation

Bureau of the Government of Canada, has found that prices of translation services

dropped 30% in constant value from 1998 to 2008 (Barab 2008). (See also Chan

2005.) It is unlikely that translation prices have increased since the onset of the

worldwide economic slowdown, so it seems reasonable to hypothesize that this

trend has continued since 2008. Postings on the topic of falling rates on transla-tors forums provide strong suggestive evidence for this hypothesis. A discussion

thread on low rates created on Oct. 28, 2001 on ProZ.com continued to attract

postings until February, 2010 (Fernandez 2001). A similar discussion thread creat-

ed in February, 2003 on ranslatorsCaf.com remained active in March 2012 and

has attracted more than 2,600 responses (Patels 2003). Te fact that outsourced

translation prices have declined in constant value for two decades does not bode

well for the ability of the industry to attract and retain talented translators and

other types of specialized freelance service providers.

e perception of commoditization

Te stagnation of translation prices over the past two decades (and downward

trend in inflation-adjusted terms) is even more striking when one considers the

increasingly important role played by, and increasing valuation attributed to, in-

tangible assets (see Appendix), which presumably include the know-how required

to offer multilingual products and information. Te seemingly inverse relation-ship between the prices and value of translation raises questions as to how (and

even if) buyers assess the value of translation.


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Keiran J. Dunne

As we have seen, if clients have no firm basis on which to evaluate quality

prior to purchase (or even aer purchase) then it follows that they have no firm

basis on which to evaluate value. When clients cannot distinguish between quality,and thus value, price becomes the primary differentiating feature.9A product or

service whose primary differentiating feature is price is by definition a commod-

itized offering. Te implication is that translation is not perceived as a source of

value creation and of competitive advantage, but rather as a commodity factor of

production, that is, a cost of doing business that must be borne but provides no

competitive advantage.

Tis observation has serious implications for the current and future health for

the industry, and possibly even for the very survival of what Shreve has termed the

translation ecosystem (1998, 2000). But as Levitt points out:

Tere is no such thing as a commodity, only people who act and think like com-

modities. Everything can be differentiated and usually is. Tink only of soap,

beer, investment banking, credit cards, steel warehousing, temporary help servic-

es, education. Tere is no reason for any company to get stuck in the commodity

trap, confined to competing totally on price alone. Historically, companies that

have taken and stayed resolutely on the commodity path, even when they have

driven their costs deeply down, have gone extinct. (1991, 134)

It is imperative that industry stakeholders address the problems of quality confu-

sion and quality uncertainty, and the concomitant development of information

asymmetry, downward price pressure, and the perception of translation and trans-

lation services as commoditized offerings. As Levitts comments suggest, the very

survival of the industry may be at stake if these problems are not addressed.

Division of labor and economies of scale

Te (mis)perception of translation as an undifferentiated commoditized offering

fuels the illusion that practitioners can achieve economies of scale through the

division of labor and specialization:

Adam Smith identified the division of labor and specialization as the two key

means to achieve a larger return on production. Trough these two techniques,

employees would not only be able to concentrate on a specific task, but with time,

improve the skills necessary to perform their jobs. Te tasks could then be per-

formed better and faster. Hence through such efficiency, time and money could be

saved while production levels increased. (Heakal 2003)

Te unbundling of translation work calls into question this law of market eco-

nomics. Because translation is ultimately a decision-making process, dividing


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labor and increasing scale can actually increasethe work effort required of an in-

dividual translator or other project participant. For example, the disaggregation

of work and division of labor typically results in the separation of translatable textfrom the manner of its presentation. Tus, translators using translation memory

or working in a server- or cloud-based application are faced with the prospect

of translating textwithout context. Te presentation of disembodied text compli-

cates not only the translation decision-making process, but the very act of un-

derstanding the text as a whole and the communicative undertaking of which it

is an artifact. In understanding text, a reader must not only be able to integrate

information within sentences but also make connections across sentences to form

a coherent discourse representation, as Rayner and Sereno observe (1994, 73).

However, it is not always possible to make such connections while reading and

translating information objects or chunks of text from a content management

system (CMS). In this respect, translation of content or information objects is

technologically simpler than traditional localization because it does not require

translators to compile or build target files, but cognitively more complex because it

requires translators to construct a situation model of a text that does not yet exist.

Neubert and Shreve (1992) argue convincingly that the fundamental unit of

translation is the text. How do we reconcile this understanding of translation with

the reality of current practices in the industry, such as the focus on words overtexts and the translation of disembodied content chunks and soware strings,

which do not present a linear structure or narrative thread and thus cannot be

read in the same way as a traditional text? How do we address the translation

of texts that do not yet exist, such as individual information objects created by

structured authoring? How do we approach texts without beginning or end? What

skills are required to read, understand and translate such material, assess the ade-

quacy of the translations thereof, and teach students how to solve these problems?

e productivity imperative

Te unprecedented scope, scale and velocity of change in the early twenty-first

century are fueling the re-emergence of the macroeconomic productivity impera-

tive. Employees are expected to do more with less, quicker and better. Professional

translation and the language industry are not immune to these pressures. Although

the nature of human translation work precludes the exponential improvements in

productivity that have been achieved in heavily mechanized industries such asmanufacturing, improvements in productivity can and need to be pursued. Te

question facing the industry is how to do so effectively.


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Keiran J. Dunne

Generally speaking, productivity can be enhanced through increased capi-

tal per worker, improved technology, and economies of scale as output expands,

among other things. Increases in productivity are most easily achieved in indus-tries that make heavy use of technology and equipment. For example, it generally

took 108 men five days (i.e., 540 man-days) to unload a timber ship in London in

1970; thirty years later, thanks to containerization and automation, the same job

took eight men just one day (i.e., 8 man-days) (Peters 2003, 50). In other words,

improved technology enabled a 66,500% increase in productivity (and thus a

98.5% reduction in the manpower needed to complete the work).

Productivity also increases as a function of experience: the more oen workers

perform a given production process, the more efficiently they tend do so. In other

words, there is an inverse relationship between per-unit production costs and the

total number of units produced. Tis relationship is known as the experience curve.

Literally thousands of studies have shown that production costs usually decline

by 10% to 30% with each doubling of the cumulated output. For example, if the

thousandth unit of a product costs $100, the two thousandth unit will normally

cost $70 to $90. (Experience curve slopes generally fall in the 70% to 90% range.)

o a strategist, the experience curve suggests that the company with the high-

est share of an industrys cumulated output will also be the low-cost producer.

(Ghemawat 1985, 144)

Although improved technology and increased experience can lead to significant

productivity gains in manufacturing, such correlations tend to be far more modest

(or even non-existent) in labor-intensive service professions. Tis phenomenon

was noted by William J. Baumol and William G. Bowen in a seminal 1966 study

of the economics of the performing arts. Baumol and Bowen noted that the con-

ditions of production in the arts effectively preclude the possibility of significant

productivity improvements because the work of the performer is an end in itself,

not a means for the production of some good (1966, 164). Tus, it takes five musi-

cians approximately as long to play Mozarts String Quintet in G-minor today as it

did when Mozart composed the piece in 1787 (Surowiecki 2003).

ranslation is subject to similar constraints. ranslation memory can help

translators to work more quickly with less mental effort and to ensure greater con-

sistency in and across translations by enabling the reuse (or recycling) of previous-

ly translated material. In addition, the productivity of an individual translator can

improve over time when working on a large project or on repeat projects for a given

client. However, the conditions of production limit the scope of potential produc-

tivity improvements because the work of translation is ultimately a decision-mak-ing process (Lev 1967; Darwish 2008; Angelone 2010; Angelone and Shreve 2011).

Classical economic theory holds that wages are directly tied to productivity.

However, Baumol and Bowen showed that this is not the case in the performing


15/26


arts, and by analogy, in other labor-intensive professions such as education, nurs-

ing and law enforcement. In such professions, the potential for productivity growth

is inherently constrained by the nature of the work. Nevertheless, employers mustraise wages periodically to keep pace with inflation and the rise in the standard

of living, lest highly qualified staff abandon their jobs for more lucrative ones. In

economics, the phenomenon whereby salaries in certain professions rise in the

absence of productivity growth is called the Baumol effect.

Te productivity imperative and Baumol effect have medium- and long-term

implications for the translation profession, and by extension for the health of the

larger translation ecosystem. Because most translation work is outsourced, most

translators are freelancers, that is, they are sel-employed. Self-employed workers

cannot rely on guaranteed annual wage increases to keep pace with inflation. On

the contrary, their wages are directly tied to their productivity. It follows that if

the translation prices stagnate or drop, as they have in inflation-adjusted terms

since the early 1990s, then translators must work longer hours or cut corners just

to maintain a stable income. It seems reasonable to hypothesize that outsourcing

and the Baumol effect magnify the impact of quality uncertainty and information

asymmetry, increasing the chances that highly skilled translators will engage in ad-

verse selection and withdraw from the market. Tis begs the question: if the indus-

try is unable to attract and retain talented translators and other types of specializedfreelance service providers, where will the experts of tomorrow come from?

e experts of tomorrow

Te literature in expertise studies holds that deliberate practice is the single

best predictor of the development of expertise. As Gregory M. Shreve observes,

deliberate practice occurs only when (a) there is a well-defined task, (b) the task

is of appropriate difficulty for the individual, (c) there is informative feedback,

and (d) there are opportunities for repetition and the correction of errors (2002,

157158; see also Shreve 2006, 29). Performing the same task for a long period of

time may lead to improved efficiency (hence the experience curve, as discussed

above), but does not necessarily lead to the development of expertise. Tis conclu-

sion has profound implications for the industry. First, being aull-time proessional

translator for years or even decades is not necessarily synonymous with being an

experttranslator. From the perspective of deliberate practice, even the long-time

translator with twenty, thirty or more years translating may not develop expertiseand be capable of producing translations that exemplify superior performance

(Shreve 2002, 157).


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Keiran J. Dunne

As the preceding discussion clearly illustrates, conditions in the current trans-

lation services market, in which work is heavily outsourced and chunked into dis-

crete, individual tasks, mitigate against individuals ability to engage in deliberatepractice. Leaving aside the challenges of clearly defining translation- and localiza-

tion-related tasks, about which little consensus exists in the literature, controlling

the difficulty of tasks in an outsourced industry model is not always possible. ask

difficulty is typically a function of outsourced market demand at a given moment

in time and is not something that an individual can manage or control, as Shreve

points out (2002, 158). Magnifying this problem, feedback is rarely provided in

the current marketplace. For instance, the marketing manager of Berlin-based LSP

Milengo admits that We translate hundreds of thousands of words every day at

Milengo, for clients around the world. We receive files and deliver projects, and

once handed back thats oen the last we see of them (Davies 2012). Anecdotal

evidence and the scant treatment of this topic in the literature strongly suggest that

the throw-it-over-the-wall approach predominates in the industry (Shreve 1998,

2000; Aberdeen Group 2006; Byrne 2006, 3940; Dunne 2011b, 184).

Tese observations raise a number of questions about the industrys ability to

remain a viable ecosystem. How can those at the end of the subcontracting chain,

such as freelance translators, engage in deliberate practice and develop expertise

when the lack of two-way communication throughout the subcontracting chainoen precludes the possibility of receiving constructive feedback? Expertise does

not simply materialize in response to demand. As the literature in expertise studies

makes clear, the development of expertise requires a sustained, deliberate invest-

ment of effort. Who is responsible for developing the experts of tomorrow? How

will expertise develop in a market that tends to treat translation as a cost to be

controlled, rather than as a source of value creation and of competitive advantage?

Indeed, the current outsourcing model presents significant structural obstacles to

the development of expertise: aer all, why would a client or LSP want to invest

in the development of skills of non-employees? From the perspective of a client or

LSP, investing in subcontractors skills is akin to lowering the barriers to entry of

ones competitors.

Signaling and screening

Information economics suggests two potential solutions to the problems discussed

above: signaling and screening. Te idea of signaling was first proposed by MichaelSpence (1973), who uses the example of the job market to illustrate this concept.

Spence posits that hiring new employees amounts to an investment in the labor

market under conditions of uncertainty. Much like the buyer in Akerlofs used car


17/26


market who cannot know in advance whether a given vehicle is a good car or a

lemon, in most job markets the employer is not sure of the productive capabilities

of an individual at the time he hires him. o hire someone, then, is frequentlyto purchase a lottery (Spence 1973, 356). Employers perceptions of the quality

of job candidates are shaped largely, but not entirely, by experience attributes.

However, employers perceptions are also shaped by the observable characteristics

presented by job candidates, that is, their search attributes. Spence argues that

these observable attributes can be divided into two categories: those that are im-

mutably fixed, such as age, and those that individuals can alter, such as education.

He calls the former indicesand the latter signals. Spence demonstrates that hiring

and subsequent observation of the productive capabilities of employees relative to

signals creates a feedback loop, which enables a progressive refinement of the em-

ployers probabilistic estimates of job candidate adequacy over time (1973, 359).

Extrapolating Spences arguments to the language industry suggests that formal

education and certification are two signaling strategies available to sellers of trans-

lation and translation-related services, an avenue of inquiry explored by Chan

(2005, 2008, 20011a, 2011b).

Te theory of screening, which was developed by Joseph E. Stiglitz (1975;

Stiglitz and Weiss 1981), suggests that the problems of quality uncertainty and

information asymmetry in a given market can be addressed by sorting accordingto important attributes:

One of the most important kinds of information concerns the qualitiesof a factor

or a commodity. We know that there are important differences among individu-

als, among bonds, among equities, among brands of automobiles. Te identifica-

tion of these qualities we call screening, and devices that sort our commodities(in-

dividuals) according to their qualities we call screening devices. (Stiglitz 1975, 283)

In the Stiglitz model, parties who are better informed about the quality of their

product or service are induced to reveal that information to lesser informed par-

ties. Screening can be performed by third parties such as educational institutions

that sort individuals based on their performance and aptitudes (Stiglitz 1975), or

in some cases, by the individuals themselves. For instance, interest rates can serve

as a screening mechanism for distinguishing between good and bad credit risks:

those who are willing to pay high interest rates may, on average, be worse risks

As the interest rate rises, the average riskiness of those who borrow increases

(Stiglitz and Weiss 1981, 393). Te notion of screening in the language indus-

try is uncharted territory. Te problem is complicated by the fact that screeningmechanisms for services necessarily involve some assessment of performance,

and no consensus currently exists as to the tangible and intangible characteris-

tics that shape translation performance, nor how to measure the adequacy thereof


18/26

Keiran J. Dunne

(Dunne 2011b). One example of a screening mechanism in the language industry

is the Payment Practices list (www.paymentpractices.net/), which sorts translation

agencies and clients with respect to two qualities: reliability (on-time payment),and approval (translators willingness to work with them again).

In any event, the description and development of mechanisms to enable sig-

naling or screening of expertise would be one way to address the lemon effect

and associated problems discussed above. Signaling and screening mechanisms

would benefit not only LSPs and clients, but also individual translators. As Stiglitz

points out, the most able individuals have an economic interest in providing in-

formation about their capabilities (1975, 286). Creating signaling and/or screen-

ing mechanisms would require the development and validation of models of

translation performance and their use to empirically evaluate translators ability

to produce translations that exemplify superior performance. It would also be de-

sirable to map models of performance to project and task typologies within the

current subcontracting model to ensure that the types of expertise being assessed

are congruent with the types of expertise requiring signaling or screening. Te

development of such performance models would offer the additional advantage of

enabling empirical identification and validation of best practices.

A similar approach could and arguably should be taken with respect to the

project management expertise of LSPs. Te project management methodologyimplemented in a specific project can have a profound impact on translation and

localization team performance and output (Dunne 2011b), as can requirements

gathering and definition, decomposition, the creation of the work breakdown

structure (and scope management in general) and risk management, to cite but a

few important variables.10Existing capability maturity models, such as the Project

Management Institutes Organizational Project Management Maturity Model

(PMI 2008) could serve as a useful springboard for such efforts, but much more

work needs to be done to develop our embryonic understanding of translation and

localization project management and associated skills sets.

Conclusion

From a microeconomic perspective, the industrialization of translation has been

driven by the decisions of individual companies to outsource translation and trans-

lation-related services, and by the factors that influence the interactions between,

and choices made, by individual buyers and sellers. Critical factors include theassessment of quality, tangibility and intangibility, search, experience, and cre-

dence attributes, and quality uncertainty. Tis specific constellation of factors has

resulted in a number of consequences, of which we have examined information
http://www.paymentpractices.net/http://www.paymentpractices.net/


19/26


asymmetry, adverse selection, price pressure, the adoption of the word as the base-

line unit of productivity and cost estimates, and perceived commoditization of

translation. Finally these factors and consequences pose a number of challengesfor translation educators, trainers, students, scholars and professionals (and by

extension, their clients): addressing quality uncertainty and reducing information

asymmetry between buyers and sellers of translation and related services; reconcil-

ing the relationship between translation tangibles and intangibles and expressing

that relationship in terms of work, cost, quality and value; improving performance

and addressing the productivity imperative; and nurturing the new translators of

today so that they may become the experts of tomorrow. Signaling and screening

are two strategic approaches that may help effectively address these problems.

Another approach is suggested by microeconomics itself. As noted above, mi-

croeconomics is concerned with the interactions between, and choices made, by

individual buyers and sellers. In helping to elucidate the factors that shape the

decision-making processes of individual buyers and sellers, microeconomics can

also help translation educators, trainers, students, scholars and professionals (and

by extension, their clients) to improve their decision-making, one interaction at a

time. In this respect, further research is needed to identify the search, experience

and credence attributes that shape buyers perceptions of the adequacy of transla-

tion and translation services. Te existing literature on the outsourced business-to-business services market suggests five specific areas of inquiry:

1. Te precise levels of relevant expertise, capabilities and experience of the ser-

vice provider, which may not be apparent.

2. Te relative alignment of the service providers capabilities with the demands

of the project: clients are not generally able to assess the types or level of skills

required to complete technically complex projects in areas outside their spe-

cialization (e.g., translation and localization).

3. Product quality and content: the absence of measurable criteria can (and oendoes) lead to considerable qualitative variations in the definitions of products

and services. Perceived quality depends on all the other factors noted above

and below, of course, but the use of different processes, methodologies, etc.

should be weighed and taken into account.

4. Te exact quantities of work effort, time and human resources that the service

provider will deploy to complete the particular project: does the proposed de-

ployment offer a poor, fair, good, better or best solution to the project?

5. Random, exogenous factors that may, depending on circumstances, influencethe effectiveness of the service provided in such a way that it becomes impos-

sible to identify the service providers own responsibility (de Bandt 1995, sum-

marized in Gallouj 1997).


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Keiran J. Dunne

Te outputs of this research could inform education and training programs not

only in translation and translation-related fields, but also in fields that have need of

translation and translation-related services, including but not necessarily limitedto business (especially management, international business, sales and marketing),

graphic design, communication and technical writing.

Te foregoing discussion also suggests that microeconomics should be woven

into translation curricula without delay in order to educate translators about mar-

ket realities, and ideally, equip graduates with the skills necessary to address these

challenges, one interaction at a time. ranslators and LSPs need to do a better job

eliciting requirements and demonstrating that the translation, translation services,

tangibles and intangibles they provide are aligned with buyers requirements and

expectations. ranslators, and the supply side of the industry as a whole, ignore

these issues at their peril.

Future issues of this journal welcome submissions that address these questions

or other aspects of translation, commerce and the economy. Tere is no shortage

of potential topics and research questions. We look forward to many stimulating

and productive discussions!

Notes

. Before 2008 the Statistical Classification of Economic Activities in the European Community

classified translation in Section 74.8, Miscellaneous business activities n.e.c. [not elsewhere clas-

sified], in sub-category 74.85, Secretarial and translation activities (Eurostat 2008a, 47).

. Te vastness of the topic precludes a comprehensive treatment in this article. Also, because

the language industry is a complex and dynamic system, certain phenomena can be considered

both consequences and challenges, depending on the observers perspective. Te organizational

framework of this article thus represents but one possible approach.

. Te notion of adverse selection is oen (and erroneously) attributed to Akerlof, but was al-

ready understood and explicitly designated as adverse selection in the insurance industry in the

1870s (e.g., Whiting 1871, 131).

. Chan (2005, 2008, 2011a) calls attention to asymmetric information in the translation ser-

vices market, but does not address the mechanisms by which it develops. Instead, he posits a

causal relationship between quality uncertainty and asymmetric information: In a translation

service market, it is difficult for service buyers or clients to assess the skills of a translator before

they receive the translation. Terefore, the problem of asymmetric information exists in this

market (2005). Although quality uncertainty typically causes the development of asymmetric

information, the two concepts are not synonymous. Moreover, quality uncertainty can causemarket failure even in the absence of asymmetric information (Izquierdo et al. 2006).

. Work by Abdallah (2008) suggests that this form of adverse selection is in fact occurring.


21/26


. A lemon market provides an incentive to sellers to pass off bad products as good ones (the

stereotype of the used car salesman comes to mind), but this possibility is already accounted for

in Akerlofs model by buyers probabilistic estimates that any given car is a lemon (1 q).

. In early 2003 the Localization Institute announced the Localization Metrics Initiative (LMI),

whose stated goal was to define units of measurement primarily in the areas of time, cost, and

quality to allow participating companies not only to track changes internally, but also to com-

pare their numbers with industry averages (Localization Institute 2003). Te initiative was qui-

etly abandoned in 2005. In similar fashion, the Localization Industry Standards Association an-

nounced in November, 2004 that it would undertake work on GMX-C, a standard designed to

provide a notational mechanism for establishing the complexity level of a given task to enable

the quantification of relative work effort (Zydron 2004). Work on GMX-C had not progressed be-

yond the development of an initial specification when LISA declared insolvency in February, 2011.

. Te word is generally used as the base unit when estimating productivity of translation of

English to and from Romance languages. Other units are used, including characters in the case

of Asian languages, and lines of text in the case of agglutinative languages such as German and

urkish.

. Cowan (2003) estimates that the use of M across the supply chain can reduce the number

of new words needing translation by 30%, noting that [n]ot all customers achieve this level

of savings, but some achieve higher savings. Given that Cowan is the founder and CEO of

Lionbridge echnologies, the worlds fourth-largest LSP (Kelly and Stewart 2011), it is particu-

larly noteworthy that he emphasizes the role of M as a cost containment tool, rather than as a

productivity enhancement or value generation tool.

. For a detailed discussion of translation and localization project management, see Dunne

and Dunne 2011.

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Appendix: e importance of intangibles in the New Economy

In 2000, three Arthur Andersen consultants published the results of a study that compared the

book value and market value of more than 10,000 publicly traded companies from 1978 to 1998

(Boulton, Libert and Samek 2000). Teir research found that the book value of these companies

fell from 95% to 28% of market value over the course of this 20-year period. In other words, 95%

of company value was reflected in the traditional balance sheet in 1978, but by 1998 the pro-

portion had dropped to only 28%. Te authors concluded that this dramatic change in the wayequity markets value companies reflects a shi from tangible assetssuch as factories, equipment

and financial capital to intangible assetssuch as business models, people, relationships, knowl-

edge, brands and systems as the primary sources of value creation (see Figure 3).

Contribution of tangible vs. intangible assets to corporate value,

19781998

100%

90%80%

70%

60%

50%

40%

30%

20%

10%

0%1978

95%

5%

28%

72%

1998

Tangibles

Intangibles

Figure 3. angible and intangible assets as a proportion of market capitalization, 197898(Boulton, Libert and Samek 2000).
http://www.lisa.org/globalizationinsider/2004/11/gilt_metrics__s.htmlhttp://www.lisa.org/globalizationinsider/2004/11/gilt_metrics__s.htmlhttp://www.lisa.org/globalizationinsider/2004/11/gilt_metrics__s.htmlhttp://www.lisa.org/globalizationinsider/2004/11/gilt_metrics__s.html


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Tese findings were supported by a Brookings Institution study, which found that the book

value of non-financial companies dropped from 83% to 31% of market value from 1978 to 1998

(Blair and Kochan, 2000, 12). A larger follow-up study by the Brookings Institution confirmed

these findings and concluded that intangibles were becoming the primary source of economicvalue creation (Blair and Wallman, 2001). It is important to note that the increasing importance

of tangibles is a generalized trend and not confined to any one sector.

Authors address

Kent State University

Institute for Applied Linguistics

109 Satterfield Hall

Kent, OH 44242-0001

USA

the industrialization of translation. causes, consequences and challenges

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