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Nilgün DORSAN Turkish Statistical Institute

International Seminar on Modernizing Official Statistics: Meeting Productivity and New Data Challenges, 24-25 October 2013. How the standards based modernization of statistical production serves dissemination?. Nilgün DORSAN Turkish Statistical Institute.

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Nilgün DORSAN Turkish Statistical Institute

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  1. International Seminar on Modernizing Official Statistics: Meeting Productivity and New Data Challenges, 24-25 October 2013 How the standards based modernization of statistical production serves dissemination? Nilgün DORSAN Turkish Statistical Institute

  2. What makes a statistical organisation efficient? 1 • Use of administrative records • Optimization of data collection • Standardization of business processes • Management of human resources • Decisions at each stage of statistical processing cycle 1 From the presentation made by Lidia Bratanova, UNECE

  3. Turkish StatisticalInstitute • Main data provider in Turkish Statistical System • Coordination role in Official Statistical Programme (63 organization, 287 subjects) • Central and 26regional offices, 1672 permanent and 1920 temporary: total 3592 staff • The vision for 2012-2016 is “to establish a user focused and sustainable statistical system based on international standards”

  4. Principles of officialstatistics and Turkish Statistical Law Trust in statistical organizations Trust in statistics

  5. To define the production line • To establish comparable, harmonized and integrated systems • To portray the statistical studies • To define which outputs of the surveys are inputs of which surveys • To consolidate the concepts within the institution • Transfer of institutional culture to future generations Why standardization is important? • Effective organizational structure • Base for the statistical metadata system • Benchmark or peer review processes with other organizations within the statististical system

  6. Some of the objectives and strategies on standardization • TurkStat 2012-2016 Strategic Plan: • Development of strategic management approach and management of the knowledge • Creation and development of process management • Establishing metadata system • Use of international standards (NACE, ISCED, PRODCOM, etc.)

  7. Statistics Production Process TurkStat Draft Model for GSBPM (Level 1 and 2) 1 Specify needs 2 Design 3 Build 4 Collect 5 Process 6 Anaylse 7 Dissemination 6.1 Evaluate the information for İts effect 7.1 Update dissemination systems 4.1 Establish frame and registers, select sample 1.1 Determine need for information Design statistcal Products and outputs 3.1 Build and enhance production system components 5.1 Classify and code 4.2 Set up collection 6.2 Produce statistics 7.2 Produce dissemination product 1.2 Consult and confirm need 2.2 Design frame, register and sample methodology 3.2 Integrate production System with other systems 5.2 Micro-edit 3.3 Test production system 4.3 Run collection 6.3 Quality assure statistics 7.3 Manage publishing for dissemination product 1.3 Establish output objectives 2.3 Design data collection methodology 5.3 Macro-control 4.4 Finalise collection 6.4 Examine and evaluate statistics 7.4 Manage user demands 1.4 Check data availability 2.4 Design process and analysis methodology 3.4 Finalise production system 5.4 Imputation Determine business plan 5.5 Calculate weights and derive variables 2.5 Design production system and work flows 6.5 Prepare statistics for dissemination 6.6 Finalise content Methodology and Information Systems Data Collection Thematic Units Dissemination

  8. Actions for streamlining the statisticalproduction • Process modeling and standardization studies launched in 2010 • TurkStat Draft Statistical Businesss Process Model in 2011 • Bilateral negotiations with the technical units • Processes for 273 products and services • Standardization plan for metadata and processes in 2011 • Under 7 main processes,33 processes in 2nd level, 106 sub processes in 3rd level and thousands of activities under these levels.

  9. ReferenceandStructuralMetadata • Metada template prepared in DDI format • Training of technical units • Code lists used in the surveys were standardized across all business surveys and all household surveys, wherever possible. • 125 projects in DDI format • 103 standard code lists • 143 codes in global repository

  10. Where dissemination begins? Main statistical processes and systems Collect Process Analyse Disseminate Input Micro data Statistical data Raw data Raw data Micro data Statistical data (Macro data) Output Production Database Production Database Institutional Database Dissemination Database

  11. Outputs • News bulletins • Dissemination databases • Statistical tables • Anonymized micro data • Printed / electronic publications Disseminated through web page, teletext, micro data research center, paper, CD, Social media

  12. Maindisseminationchannel : www.tuik.gov.tr • In 2012, 267 news bulletin in 80 subjects • Dissemination databases in 58 subjects including detailed time series data • 1 336 statistical tables • Metadata

  13. Challenge facing statistical producers

  14. Challenges of the data • New data needs in statistical domains • Abundance of data sources and data flows from different registers • Management of the data and data sources • Non standardised codes • Data integration • Micro data exchange and transperancy • Data confidentiality • Effective use of the data and its quality

  15. Without a good description of the needs and effective design of the processes, you can not get quality outputs.

  16. Statistics Production Process TurkStat Draft Model for GSBPM (Level 1 and 2) 1 Specify needs 2 Design 3 Build 4 Collect 5 Process 6 Anaylse 7 Dissemination 6.1 Evaluate the information for İts effect 7.1 Update dissemination systems 4.1 Establish frame and registers, select sample 1.1 Determine need for information Design statistcal Products and outputs 3.1 Build and enhance production system components 5.1 Classify and code 4.2 Set up collection 6.2 Produce statistics 7.2 Produce dissemination product 1.2 Consult and confirm need 2.2 Design frame, register and sample methodology 3.2 Integrate production System with other systems 5.2 Micro-edit 3.3 Test production system 4.3 Run collection 6.3 Quality assure statistics 7.3 Manage publishing for dissemination product 1.3 Establish output objectives 2.3 Design data collection methodology 5.3 Macro-control 4.4 Finalise collection 6.4 Examine and evaluate statistics 7.4 Manage user demands 1.4 Check data availability 2.4 Design process and analysis methodology 3.4 Finalise production system 5.4 Imputation Determine business plan 5.5 Calculate weights and derive variables 2.5 Design production system and work flows 6.5 Prepare statistics for dissemination 6.6 Finalise content Methodology and Information Systems Data Collection Thematic Units Dissemination

  17. Specify needs • For an efficient data production and meeting the user needs some questions arise… • What users wants? • What is our sources? • Do we need extra data source? • Which data source best meets the needs? • How we manage the big data?

  18. Design • Data integrationfrommultiplesources • Data structure • Management of metadataand meta information • Statisticaloutputs • Variables • Conceptsanddefinitions • Classifications, codelists • Questionnairedesign • Design of architecture

  19. Structural Metadata Components MetadataEditor Production database Institutional Database Disseminationdatabases

  20. Build Necessary for an efficientproductionsystem. Withoutthisprocessyou can not manageandintegratethe data.

  21. Analyse • Production of statistics / indexes • Evaluation of data quality • Seasonaladjustments • Evaluation of responserates • Benchmarksforotherperiodsand data sources • Application of data confidentialityrules • Decision of thedissemination of data level • Metadatapreparationforoutputs • Preparation of the data forthedissemination

  22. Disseminate • Feedback of the users and update of the specifying needs • Update dissemination system for relevant, timely and accesible data • Development of the dissemination channels

  23. TurkStat’smainprinciplesfordissemination • Maximum data:open and free access • Transperancy, clarity • Timeliness and punctuality • Comparability

  24. Data Confidentiality • Confidentiality rules determined in Law No.5429 (Articles 4, 12, 13 and 14) and related regulation • Data Confidentiality Board • Decisions on conflicts • Confidentiality Commitment Document is signed by every staff

  25. Productionprocess: Continuousimprovement, monitoring, evaluation (qualitymanagement) Missingcoverage I have to rotate this wheel Plan Act InternationalComparability Incompleteadministrativerecords Do Check Uptodateandtrusted data Data incompatiblewithclassificationsandstandards Respondentserrors ……..

  26. Future plans for streamlining • Finalize the statistical business process model integrated with a strong statistical metadata system. • Provide a strong infrastructure for quality management system. • A leading model for other producers of official statistics. • Develop metadata infrastructure

  27. Thankyouforyourattention. Anyquestion?

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