TAUS Roundtable Moscow, CAT or TMS Implementation-Calculation of the Number of Licenses and the Total Cost of Ownership, Renat Bikmatov, Logrus International
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TAUS Roundtable Moscow, CAT or TMS Implementation-Calculation of the Number of Licenses and the Total Cost of Ownership, Renat Bikmatov, Logrus International

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TAUS Roundtable Moscow, CAT or TMS Implementation-Calculation of the Number of Licenses and the Total Cost of Ownership, Renat Bikmatov, Logrus International TAUS Roundtable Moscow, CAT or TMS Implementation-Calculation of the Number of Licenses and the Total Cost of Ownership, Renat Bikmatov, Logrus International Presentation Transcript

  • THURSDAY,  22  May  /14:30  –  15:00     CAT  or  TMS  ImplementaAon:     CalculaAon  of  the  Number  of  Licenses  and  the  Total   Cost  of  Ownership   Renat  Bikmatov,  Logrus  Interna4onal     TAUS  ROUNDTABLE  2014    22  May/  Moscow  (Russia)  
  • TranslaAon  AutomaAon  Tools:  The  Use  Case   Big  Data  AnalyAcs  in  LocalizaAon  Industry   The  Presenta+on  Topics:   •  How  LSPs  could  minimize  the  cost  of  ownership  of  the  tools   •  Live  demo:  the  calculaAon  of  number  of  CAT  licenses   •  Which  Big  Data  and  business  intelligence  features  LSPs  might  need    
  • TranslaAon  AutomaAon  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  expiraAon  date   o  mobile  license  transferable  between  users   o  temporary  license  purchased  on  demand  for  limited  period  of  Ame   o  license  for  online  connecAon  to  the  translaAon  server   o  etc.   •  OpportuniAes  for  LSP:   o  adjusAng  the  configuraAon  of  the  pool  of  licenses   o  minimizing  the  total  cost  of  licenses   View slide
  • TranslaAon  AutomaAon  Tools:  The  Live  Demo   CalculaAon  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  staAsAcs  of  translaAon  tasks  handed  off  to   translators  and  delivered  back  for  all  translaAon  projects  got  from   selected  client(s)  during  the  past  year(s)   View slide
  • TranslaAon  AutomaAon  Tools:  The  Live  Demo   CalculaAon  of  Number  of  CAT  Licenses  
  • TranslaAon  AutomaAon  Tools:  The  Live  Demo   The  Summary  of  the  Live  Demo   The  conclusions:   •  The  rental  longer  than  30  days  is  not  cost  saving  (the  opAmal  term  of  lease  would  be   5  days  with  30%  savings  in  total  cost)   •  The  minimal  number  of  licenses  in  the  rental  package  (5)  is  unessenAal  factor  
  • TranslaAon  AutomaAon  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  translaAon  project/task  parameters  to  be  used  as  input  data  for   BI  tools   •  The  BI  reports  generated  from  the  source  data  using  business   analyAc  methods   •  The  business  decisions  that  can  be  made  using  the  generated  BI   reports  
  • TranslaAon  AutomaAon  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  translaAon   project   •  Project  cost:  The  invoiced  price  of  the  translaAon  project     BI  reports:   •  DistribuAon  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  quesAons  to  be  answered:   •  Which  of  CAT  tools  in  use  could  be  replaced  by  compeAtors  (if  any)  to   reduce  the  cost  of  the  tool  ownership?   •  Which  of  TranslaAon  Memory  Server  products  would  be  the  cheapest   soluAon  to  support  the  given  pool  of  CAT  clients  already  in  use?  
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   UAlizaAon  of  Available  Pool  of  Licenses   Input  data:   •  CAT  license  ID:  The  unique  idenAfier  of  each  CAT  license  (if   supported  by  the  license  server)     BI  reports:   •  DistribuAon  of  uAlizaAon  percentages  by  CAT  license  IDs     The  business  quesAons  to  be  answered:   •  For  how  many  licenses  is  the  uAlizaAon  below  a  predicted  threshold   value?     •  Does  it  make  sense  to  adjust  the  licensing  schema  secngs  so  as  to  fit   it  to  the  usage  scenario?    
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   IdenAfying  Bodlenecks  in  LocalizaAon  Workflow   Input  data:   •  Translator’s/Editor’s  ProducAvity  Measurement  Log  records     BI  reports:   •  DistribuAon  of  Ame  spent  by  the  translator  or  editor  on  different  subtasks:   translaAon  of  content;  searching  glossaries  for  term  translaAons;  reading   style  guides;  reading  other  reference  materials  provided  for  parAcular   project;  searching  Internet  for  addiAonal  reference  informaAon;  filling  in   feedback  or  Issue  Tracking  forms;  etc.     The  business  quesAons  to  be  answered:   •  Which  acAviAes  other  than  translaAng  or  ediAng  as  primary  job  take  most  of   translator’s/editor’s  Ame?   •  How  much  Ame  is  spent  on  supporAng  acAviAes  if  compared  to  translaAng   or  ediAng?   •  Are  there  any  supporAng  acAviAes  that  might  be  further/beder  automated   to  save  more  Ame?  
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   Measuring  Machine  TranslaAon  Quality  and  Post-­‐editor’s  ProducAvity   Input  data:   •  Translator’s/Editor’s  ProducAvity  Measurement  Log  records     BI  reports:   •  DistribuAon  of  Ame  spent  by  the  post-­‐editor  on  different  TranslaAon  Units   containing  machine  translaAons     The  business  quesAons  to  be  answered:   •  What  is  the  average  personal  producAvity  of  each  of  post-­‐editors?  This   informaAon  needed  for  planning  resources  for  translaAon  projects  and   calculaAng  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-­‐ediAng  Ame  normalized  by  personal  producAvity  could  be   used  as  indirect  measure  of  MT  quality.   •  If  any  enhancements  have  been  implemented  in  localizaAon  workflow,  is   there  any  impact  on  the  overall  translator’s  or  editor’s  producAvity?  
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   Measuring  Translator’s  Skill  Level  and  Domain  of  ExperAse   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:   •  DistribuAon  of  quality  raAng  of  given  translator  by  the  domains  of  translated   content   The  business  quesAons  to  be  answered:   •  In  which  domains  the  translator  produce  translaAons  with  a  quality  score  of   “good”  or  above?   o  This  informaAon  would  allow  to  implement  generally  accepted  translator’s   cerAficate  of  quality  and  domain  of  experAse.   o  The  list  of  domains  of  experAse  can  be  used  for  automated  selecAon  of   translators  for  incoming  translaAon  projects  in  TranslaAon  Management   System.   o  The  list  of  domains  of  insufficient  experAse  can  be  used  as  a  guide  for   translator’s  self-­‐educaAon  
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   UAlizaAon  of  Pool  of  Freelance  Translators  and  Editors   Input  data:   •  Translator’s/Editor’s/Proofreader’s  ID  or  Name     BI  reports:   •  %  of  uAlizaAon  of  given  translator/editor  in  translaAon  projects  within   his/her  domain  of  experAse   The  business  quesAons  to  be  answered:   •  Are  there  any  freelancers  who  are  underused?   o  Underused  freelancers  usually  tend  to  cease  cooperaAon  with  the   employer.  As  a  result,  LSP  might  loose  the  money  spent  on  selecAon   and  training  of  the  translators  and  have  to  spend  more  to  replace   the  leakage  of  employees  
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   Automated  Control  of  Quality  of  Service:  NDA  Agreements   Input  data:   •  Client’s  instrucAon  not  to  transfer  the  content  to  any  Cloud  locaAons   (TMS,  file  sharing  services,  etc.)   -­‐  OR  -­‐     •  Client’s  instrucAon  not  to  transfer  the  content  to  specific  online  machine   translaAon  service   BI  reports:   •  An  alert  to  be  issued  in  case  of  improper  configuraAon  of  any  translaAon   project  received  from  that  client     The  business  quesAons  to  be  answered:   •  Are  the  requirements  of  client’s  NDA  met  in  each  translaAon  project?  
  • TranslaAon  AutomaAon  Tools:  More  Use  Cases  (Cont.)   Automated  Control  of  Quality  of  Service:  ConnecAng  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  configuraAon  of  any  translaAon   project  received  from  that  client.  Typically,  clients  do  not  duplicate  all   the  instrucAon  in  each  handoff,  so  the  project  manager  at  LSP  should   keep  an  eye  on  projects  secngs.  The  domain  of  the  handoff  might  be   specified  in  email  or  encrypted  in  project  package  name.     The  business  quesAons  to  be  answered:   •  Are  the  requirements  of  client’s  translaAon  instrucAons  met  in  each   translaAon  project?  
  • TranslaAon  AutomaAon  Tools   CalculaAon  of  the  Number  of  Licenses,     EvaluaAon  of  the  Total  Cost  of  Ownership,     and  Other  ApplicaAons  of  Business  Intelligence   THANK  YOU!   QuesAons?