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Dynamic Quality Framework
Dace Dzeguze
TAUS Global Content Summit
Fixing the operational gap
©Performance Management Company
Inclusive
Industry-
shared
Data-
informed
Dynamic
DQF Principles
• Quality is not static, but well defined
• Choice of methodology is based on content type, process, communication
channel and target audience
• Industry-wide agreement on measurements and benchmarks
• Quality management is data-informed
Connectivity
Open API & Plugins
Integration
Most common
CAT tools & TMS
Data collection
Translation & review
processes
Visualization
Interactive
dashboard
Performance
tracking
Project-level and
benchmark reports
How it works
DQF Integrations
Harmonized DQF-MQM error typology
Perform project level analysis
• Average productivity rate
• Edit distance
• Ratio of edited segments
• Time spent
• Corrections density
• Error density
Analyze trends in your own organization
Benchmark your results against the industry
Compare the averages per language pair, content type, process, etc.
Measuring the sweet spot TM vs. MT
Less edits in post-edited MT than in fuzzy TM
DQF Roadmap 2019
• BI Bulletins
• My DQF Toolbox
• DQF Confidence Score
• More integrations
Thank you

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