Renat Bikmatov gave a presentation on translation automation tools at the TAUS Roundtable 2014 in Moscow, Russia. He discussed how localization service providers (LSPs) can minimize costs by adjusting license configurations and calculating the optimal number of licenses needed. He demonstrated live calculations to determine the number of translator licenses and annual costs under different licensing schemas. The conclusion was that rental terms longer than 30 days are not cost-saving, and the minimum number of licenses in a rental package is an inessential factor. Bikmatov also discussed how LSPs could use business intelligence tools and big data to further enhance their business through analysis of translation projects, CAT tool usage, license utilization, translator productivity and skills, and ensuring

1. TAUS ROUNDTABLE 2014
22 May/ Moscow (Russia)

2. THURSDAY, 22 May /14:30 – 15:00
CAT or TMS Implementation:
Calculation of the Number of Licenses and the Total
Cost of Ownership
Renat Bikmatov, Logrus International
TAUS ROUNDTABLE 2014
22 May/ Moscow (Russia)

3. Translation Automation Tools: The Use Case
Big Data Analytics in Localization Industry
The Presentation Topics:
• How LSPs could minimize the cost of ownership of the tools
• Live demo: the calculation of number of CAT licenses
• Which Big Data and business intelligence features LSPs might need

4. Translation Automation Tools: The Cost Factors
How LSPs Could Minimize the Cost of Ownership of the Tools
• Different types of licenses for different workflow roles:
o project manager
o linguist (translator, editor, proofreader)
• Flexible licensing schemas:
o fixed license bound to PC or user without expiration date
o mobile license transferable between users
o temporary license purchased on demand for limited period of time
o license for online connection to the translation server
o etc.
• Opportunities for LSP:
o adjusting the configuration of the pool of licenses
o minimizing the total cost of licenses

5. Translation Automation Tools: The Live Demo
Calculation of Number of CAT Licenses
• The Task: to minimize the annual cost of ownership of translator licenses
• The Method: to play around with modifying parameters of licensing
schema and calculate the number of translator licenses needed and their
annual cost in each case
• The Source Data: daily statistics of translation tasks handed off to
translators and delivered back for all translation projects got from
selected client(s) during the past year(s)

6. Translation Automation Tools: The Live Demo
Calculation of Number of CAT Licenses

7. Translation Automation Tools: The Live Demo
The Summary of the Live Demo
The conclusions:
• The rental longer than 30 days is not cost saving (the optimal term of lease would be 5
days with 30% savings in total cost)
• The minimal number of licenses in the rental package (5) is unessential factor

8. Translation Automation Tools: More Use Cases
Big Data and Business Intelligence That LSPs Might Need
Big Data and Business Intelligence (BI) clear the way to further
enhancements in LSP’s business. Let’s consider just a few possible benefits
using the following template:
• The translation project/task parameters to be used as input data for
BI tools
• The BI reports generated from the source data using business
analytic methods
• The business decisions that can be made using the generated BI
reports

9. Translation Automation Tools: More Use Cases (Cont.)
Comparison of Different CAT or TMS Products
Input data:
• CAT tool: The name of CAT tool used by translators on given translation
project
• Project cost: The invoiced price of the translation project
BI reports:
• Distribution of company revenue by CAT tools in use:
o % of total revenue provided by each CAT tool
o The volume of revenue provided by each CAT tool
The business questions to be answered:
• Which of CAT tools in use could be replaced by competitors (if any) to
reduce the cost of the tool ownership?
• Which of Translation Memory Server products would be the cheapest
solution to support the given pool of CAT clients already in use?

10. Translation Automation Tools: More Use Cases (Cont.)
Utilization of Available Pool of Licenses
Input data:
• CAT license ID: The unique identifier of each CAT license (if
supported by the license server)
BI reports:
• Distribution of utilization percentages by CAT license IDs
The business questions to be answered:
• For how many licenses is the utilization below a predicted threshold
value?
• Does it make sense to adjust the licensing schema settings so as to fit
it to the usage scenario?

11. Translation Automation Tools: More Use Cases (Cont.)
Identifying Bottlenecks in Localization Workflow
Input data:
• Translator’s/Editor’s Productivity Measurement Log records
BI reports:
• Distribution of time spent by the translator or editor on different subtasks:
translation of content; searching glossaries for term translations; reading
style guides; reading other reference materials provided for particular
project; searching Internet for additional reference information; filling in
feedback or Issue Tracking forms; etc.
The business questions to be answered:
• Which activities other than translating or editing as primary job take most of
translator’s/editor’s time?
• How much time is spent on supporting activities if compared to translating
or editing?
• Are there any supporting activities that might be further/better automated
to save more time?

12. Translation Automation Tools: More Use Cases (Cont.)
Measuring Machine Translation Quality and Post-editor’s Productivity
Input data:
• Translator’s/Editor’s Productivity Measurement Log records
BI reports:
• Distribution of time spent by the post-editor on different Translation Units
containing machine translations
The business questions to be answered:
• What is the average personal productivity of each of post-editors? This
information needed for planning resources for translation projects and
calculating personal rates.
• Which pieces of MT output are worse and which are the best? The feedback
on both data categories would help to enhance the MT engine.
• The average post-editing time normalized by personal productivity could be
used as indirect measure of MT quality.
• If any enhancements have been implemented in localization workflow, is
there any impact on the overall translator’s or editor’s productivity?

13. Translation Automation Tools: More Use Cases (Cont.)
Measuring Translator’s Skill Level and Domain of Expertise
Input data:
• Translator’s/Editor’s/Proofreader’s ID or Name
• Reviewer’s feedback report as a set of quality metrics of output content
BI reports:
• Distribution of quality rating of given translator by the domains of translated
content
The business questions to be answered:
• In which domains the translator produce translations with a quality score of
“good” or above?
o This information would allow to implement generally accepted translator’s
certificate of quality and domain of expertise.
o The list of domains of expertise can be used for automated selection of
translators for incoming translation projects in Translation Management
System.
o The list of domains of insufficient expertise can be used as a guide for
translator’s self-education

14. Translation Automation Tools: More Use Cases (Cont.)
Utilization of Pool of Freelance Translators and Editors
Input data:
• Translator’s/Editor’s/Proofreader’s ID or Name
BI reports:
• % of utilization of given translator/editor in translation projects within
his/her domain of expertise
The business questions to be answered:
• Are there any freelancers who are underused?
o Underused freelancers usually tend to cease cooperation with the
employer. As a result, LSP might loose the money spent on selection
and training of the translators and have to spend more to replace
the leakage of employees

15. Translation Automation Tools: More Use Cases (Cont.)
Automated Control of Quality of Service: NDA Agreements
Input data:
• Client’s instruction not to transfer the content to any Cloud locations
(TMS, file sharing services, etc.)
- OR -
• Client’s instruction not to transfer the content to specific online machine
translation service
BI reports:
• An alert to be issued in case of improper configuration of any translation
project received from that client
The business questions to be answered:
• Are the requirements of client’s NDA met in each translation project?

16. Translation Automation Tools: More Use Cases (Cont.)
Automated Control of Quality of Service: Connecting Proper
Style Guides and Glossaries
Input data:
• Style Guide ID or Name: The client might have different style guides and
glossaries for different content domains
BI reports:
• An alert to be issued in case of improper configuration of any translation
project received from that client. Typically, clients do not duplicate all the
instruction in each handoff, so the project manager at LSP should keep
an eye on projects settings. The domain of the handoff might be
specified in email or encrypted in project package name.
The business questions to be answered:
• Are the requirements of client’s translation instructions met in each
translation project?

17. Translation Automation Tools
Calculation of the Number of Licenses,
Evaluation of the Total Cost of Ownership,
and Other Applications of Business Intelligence
THANK YOU!
Questions?