Localization 2.0 Part II: Leveraging Tomorrows Tools And Technologies For Success Today

LOCALIZATION 2.0 Part II:Leveraging tomorrow’s tools and technologiesLeveraging tomorrow s tools and technologies for success todayPlease note that the audio for this webcast will be streamed.

Presented by Nicholas McMahon and Marcus CasalModerated by Paula ShannonMarch 17, 2009

About Lionbridge

Global ScaleGlobal Scale Market LeadershipMarket LeadershipGlobal ScaleGlobal Scale4,600 employees 26 countries

• Global network of 25,000 translators

Market LeadershipMarket LeadershipLeader in $12B services industry• Translation and adaptation of products

and content for international markets

Global ClientsGlobal ClientsRecurring relationships with 500+

Hosted TechnologyHosted TechnologyW b b d l t h l Recurring relationships with 500+

global clients• 80% of revenue comes from recurring clients• 12 of the Fortune 20 companies are client

Web-based language technology platform• Enhances competitive advantage• Drives efficiency

Company confidential – distribution prohibited without permission

Localization 2.0 Emerging

New customers New communities New content


New customers New communities New content


SaaS Delivery Live Language Open Integration


Mechanisms Assets


SaaS Delivery Live Language Open Integration


Mechanisms Assets


Focus on business enablement

Focus on live, direct dynamic interactions between demand and

Focus on mechanism as an enabler over translation services


supply

Localization 2.0: Bridging the Human Communication Gap

Set of Core Centralized Tools

MT, Glossary, Chat, TM’s, Authoring, QA CheckersCheckers

SaaS delivery mechanisms

Instant, scalable, upgradable and globally accessible

Web 2.0 and AJAX capable for real time customization and complete connectivity

OPENAny vendor (based on quality of service)Any resource type (independent, amateur, MT or hybrid)Any partner – new technologies, systems and resourcesAny partner new technologies, systems and resources

MT and Human Hybrid Types:Rules Based MT


MT and Human Hybrid Types:Statistical MT


MT and Human Hybrid Types:Human Hybrid


Based on your experience is MT better as a method of translating things ‘non translatable in a traditional g gmodel’ or as an efficiency drive for human translation?

MT is better as a human translation efficiency driverMT is best used to tackle currently un translated contentMT is still not a viable solution for anything other than instant communication


MT has Potential!

Business enablement for ‘un‐translatable’ content

Business enablement forinstant communication

Efficiency driver for human quality output


MT has Challenges

Training linguisticTraining linguistic resource for MT output

Setting expectations for variable quality

Budgetary readiness for upfront

customization or


source content

Case Study – MT FAQs

Volume of content made human

Fortune 500 Enterprise IT Organization

Volume of content made human translation unrealistic

Users showing clear interest in translated versions of US materials

Significant cost of support via telephone and emailtelephone and email

Community and brand challenges for commitment to local markets



Cost and time of core engine MT training

f fWorkflow integration of MT and TM quality loop

Expectation setting for usersExpectation setting for users

Expectation setting for internal customers

Partner mix and interaction



100% availability of content in three

AchievementsAchievementsy

core languages

Mixed quality response based on ki f hi f iranking of hits for support issues

15 – 20% Reduction in support enquires based on ‘resolutionenquires based on resolution confirmation’

Quality improvement request to feed into demand data (basis for HT)

Improved user access to instant


Improved user access to instant support

Communities within Loc 2.0 environment

Cost Quality Balancing Localization CommunitiesQuality

Q

Raw MT

Cost

Cost Quality Balancing Localization CommunitiesQuality

User generated content: blog and social translation

Q

Raw MT

Cost

Cost Quality Balancing Localization Communities

Small/medium loc. buyers:Small/medium loc. buyers: SMB and fragmented enterprises

Quality


Q

Raw MT

Cost


TAUS 200: enterprise MLVs

Small/medium loc. buyers:


Small/medium loc. buyers: SMB and fragmented enterprises

Quality


Q

Raw MT

Cost



Small/medium loc. buyers:


Small/medium loc. buyers: SMB and fragmented enterprises

Quality


Q

Raw MT

Cost

Loc 2.0 Community Value

Content expanders

Passionate content generators

expanders –new content types to extend reach

Global brand enhancement through

iti

Business enabler for ‘long tail’ of

positive community networks


long tail of languages

Challenges of global community Utilization

Maintaining consistency across huge base of ‘untrained users’

Delivering to specific milestones

Establishing and maintaining effective motivation and return

Maintaining investment into the relationship

Providing interface and ability to interact with content


interact with content

Facebook Case Study

Facebook –C t t b d h t f bli h d d t it i till thContent based on huge amount of published data – it is still the best example of communities in action


Facebook Case Study

l l b l h hScale to global growth within a very community centric market


Facebook Case Study


Limited funds and resourcesLimited funds and resources


Facebook Case Study


Limited funds and resourcesLimited funds and resources

Very competitive and fast paced environment where time toenvironment where time to market is critical


Facebook case study

Untrained and disparate users

Traditional quality controlTraditional quality control process and expectations

Community activity = strongerCommunity activity stronger community

Infrastructure to support massive scalable live translation


Facebook Case study

Sector leading adoption in most languages

Outperformed existing ff iofferings

Community driven qualityCommunity driven quality control

‘Fame’ based incentive model


Source : TechCrunch/iSearchlight

Platforms: Server Based

Can be hosted or not

Upfront license fee’s or ongoing hosting costs

Customization at specific server level


Platforms: SaaS Based

Always on

Live (not just centralized) assets

Subscription based charges (no tie in)

Best practice sharing


Platforms

Creates more time for localization management by removing administrative burden of Loc processadministrative burden of Loc process

Creates statistical reporting as a basis for strategic ROI calculationsstrategic ROI calculations

Facilitates greater productivity per resource

Facilitates application of centralized resources and other technologies


Platforms

l b l b l f dFlexibility balance of systems and process

Long term cost of ownershipLong term cost of ownership versus return

Extended integration into otherExtended integration into other enterprise systems

Support for translator community

Strategic value versus tactical costs


Big Box Retailer Case Study

Providing global communication support for hundreds of smallish jobs from hundreds of individual requesters

B i d d f ffi i fBusiness demand for efficiency of process



Number of users and translators within the system (over 1000 jobs a month)month)

Very little consistency of process or file typesfile types

Cost allocation and control expectations

No language asset value embedded



AchievementsAchievements

SaaS based Live dynamic centralized asset supporting 100s of concurrent users

Integrated auto and manual file handling triage

Very limited administration time for both teams – focus on foverall operation and delivery of mechanism

Full global support and billing integration to facilitate global communicationcommunication


Loc 2.0 Best Practices Summary

Value of individual components increased through unifying platform

Increased awareness of function and value of each Loc 2.0 component improves adoption and viabilityimproves adoption and viability

Multi component/ multi resource solutions return best value andsolutions return best value and flexibility

Re-setting current expectations is aRe setting current expectations is a critical component of successful Loc2.0 adoption


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