1. Paper No. 04/EECCA/2013 HIGH LEVEL SEMINAR FOR EASTERN EUROPE, CAUCASUS AND CENTRAL ASIA COUNTRIES (EECCA) ‘QUALITY IN STATISTICS: ADMINISTRATIVE DATA AND OFFICIAL STATISTICS‘ Vilnius, Lithuania 4-6 September2013 Session 1 Title: “The quality policy and quality framework at the Hungarian Central Statistical Office” Ms. Kornélia Mag Hungarian Central Statistical Office

2. The quality policy and quality framework at the Hungarian Central Statistical Office Kornélia Mag Hungarian Central Statistical Office High Level Seminar for Eastern Europe, Caucasus and Central Asia Countries (EECCA)

3. Contents: Introduction: Roots of quality in HCSO Necessity of a systematic approach Quality framework approach Quality policy Quality working program Quality framework Summary/The way forward Risks, problems, good tools 3

4. Roots of Quality in the HCSO Traditional commitment Methodological work on error measurement (Á.Marton: Reliability of sample surveys 1991) In-house methodological regulations on processes (survey design 1997, dissemination 1995, seasonal adjustment 2004) Conference on „Quality in Statistics” held by the Hungarian Statistical Association, Gyöngyös 2000 Efforts to improve field work in population surveys, standardisation of data collection and capturing in economic statistics Dissemination data warehouse (2001), metadata system External inputs Participation on the meetings „Working group on quality assessment in statistics” since 2002 Participations in European training courses in quality topics Pilot Project „Quality in Statistics” 2004-2005 4

5. Necessity of development, toward a systematic approach Internal commitment Mission of the HCSO, strategic plan 2005-2008; 2008-2012 Quality policy of HCSO, 2009 Need to provide „value for money” with less and less resources External commitment UN Fundamental Principles of Official Statistics (1994) Quality declaration of the ESS (2001) LEG recommendations (2001) Obligations regulated by law, EC 223/2009 Quality Reports required by Eurostat Code of Practice 2005; 2011 Sponsorship on Quality UN: Quality framework 5

6. Quality framework approach How to build a system? Top down – Quality management mainframes Total Quality Management (TQM) The EFQM Excellence Model (European Foundation for Quality Management) ISO 9000:2000 CAF Code of Practice Bottom up – Start with the core business: data production 6

7. First steps Organisation, learning, language: Methodology – central unit responsible Learning – WG, literature, practice of others Hungarian language – translation, vocabulary With the strategy 2005-2008 HCSO accepted: Definition of quality, concepts (April 2005) Working program on quality (June 2005) Project plans on product and process quality (October 2005) Quality policy (2009) 7

8. Quality policy of HCSO Mission – Quality Declaration – Quality commitment Mission: The mission of the Hungarian Central Statistical Office as part of the European Statistical System is to provide credible and good-quality statistical services – adequate for users’ needs – about the state and changes of society, economy and environment. http://www.ksh.hu/quality_policy_reports

9. Definition of quality 9 „Quality is defined as the totality of features and characteristics of a product or service that bear on its ability to satisfy stated or implied needs of the client or user.” (ISO 8402 – 1986, 3.1)

10. Quality criteria in HCSO 10  Relevance;  Accuracy;  Timeliness;  Punctuality;  Accessibility;  Clarity;  Comparability and coherence

11. Quality commitment HCSO is committed to get acquainted with the present and future needs of the users of statistical data measure the quality of statistical products and production processes regularly, assess the results of measurements and on the basis of the results execute the development of products and data production activities continuously utilize the latest achievements of the statistical profession during its operation, by applying the best national and international practices of other organizations make efforts to reduce the response burden develop quality culture in the offi ce and in other organizations of official statistics; in the frame of this, HCSO supports and initiates quality trainings and courses properly develop the professional knowledge and skills of the staff in line with requirements, and to improve the circumstances of work as much as possible

12. Quality framework 12 Quality requirements Assessment tools Measured quality features Measurement according to quality standards Reality Process variables Quality report Quality indicators Standards, regulations, User needs Internal/external audit Feedback talks Self-assessment Action plan Statistical data Production process

13. Elements of Quality working program 1.Development of an internal quality control system of statistical products 2.Development of an internal quality control system of statistical process 3.Setting up a quality management model 4.Training/Dissemination of quality culture 13

14. 1 st element: Development of an internal quality control system of statistical products 14  Product quality indicators (products, list of products with SZOR)  Glossary and inventory of quality indicators, scheme of quality report  Regulation of product quality measurement system (who does what, how often)  Relation between dissemination and indicators (minimum criteria)  Regulation of assessment scheme and procedure (use of quality report and indicator)

15. 12/12/2012 15 Decision, collection design Accessing administrative data Sampling design Questionnaire design Data collection, data capture, microvalidation, editing Weighting, estimation, sampling error computation Macrovalidation Index number construction Seasonal adjustment Further analysis Confidentiality and disclosure Dissemination Data archiving Statistical product Imputation

16. 2 nd element: Development of an internal quality control system of statistical process 16  Identification of the steps of statistical work process  Recommended methods and standards  Regulation of process documentation system  Quality guidelines and checklist  Quality measurement system  Assessment of quality: self-assessments, audits  Regulation of the feedback of results

17. 3 rd element: Setting up a quality management model 17 1.Customer/user focus – quality as perceived by customers 2.Relation between internal suppliers and customers 3.Data supplier is an element of statistical process 4.Continuous improvement 5.Involve people at all levels 6.Quality measurement methods, standards 7.Quality management policy and organization 8.Providing staff with training and recognition 9.Adequate communication Developments are in line with the principles but no formal certification

18. 18 Principle of quality management model Relation between internal suppliers and customer Data supplier is an element of statistical process Quality measure ment methods, standards Conti- nuous improve- ment Adequate communic ation Providing staff with training and recogniti- on Quality manage- ment policy and organiza- tion Involve people at all levels Customer /user focus

19. 4 th element: Training 19 Target groups  Middle and top manager in central and regions  Statisticians in subject matter departments  Experts from the regional competence centers Structure  Development of Quality management, historical overview  Quality concept, quality framework in official statistics  Product quality measurement and assessment  Statistical value chain, guidelines, process variables, measurement, assessment of process quality  Quality assurance in HCSO  Quality and development projects, relations + reference in methodological courses

20. Data quality framework 20 Quality requirements Assessment tools Measured quality features Measurement according to quality standards Reality Process variables Quality report Quality indicators Standards, regulations, User needs Internal/external audit Feedback talks Self-assessment Action plan Statistical data Production process

21. Vision on the working model Self assessment, feedback talks, audits Action plan/Feedback in PDCA cycle 21 Legal acts Standards Guidelines Agreements Internal rules Recommended practices Documentation Meta information Quality reports Quality indicators

22. Synergies Internal Tradition in standards (meta-driven systems) Methodology unit Strategy, planning and evaluation system Meta system (concepts, definitions, nomenclatures, documentation by statistical domains) New IT developments Other development projects External participation in Eurostat quality related grants and programs (DATQAM, process developments) monitor other international developments (i.e.UN) active participation in Q conferences 22

23. Summary/The way forward Tools Standard quality indicators Standard quality report Assessment scheme on product quality Statistical process model Quality guidelines Documentation schemes for process phases Process variables for certain process phases Self assessment checklist for survey process Transparency Intranet: quality page with related documents, quality reports HCSO webside: quality policy, quality guidelines, methodological documentation with information on quality Draft versions Quality audits, Feedback talks Operation of quality assurance system with responsibilities Future activities Planning and implementation of TQM Widening the scope beyond HCSO to official statistics Regular review and update of tools 23

24. Risks Maintain management support Provide quality information Measurable results – CoP implementation Gain experts’ support Involve them in the process Provide useful feedback Limit extra burden, avoid double work Build on existing systems, meta Automation of processes User friendly IT support Limited sources in methodology Involve experts in subject matter areas, academic people Make use of other countries experiences 24

25. Motivation of statisticians Make use of existing knowledge, practices Involve people in the development process Proceed step by step, keep cost-benefit balance To avoid formal implementation! 25

26. Forum for cross-cutting issues Involve staff in development of standards and rules and decision preparation Proposals for management only after consensus in the Board on Methodological Issues Today: Board on Methodology and IT 26

27. Competence building Transparency – available programs, documents Communication – keep quality on the agenda Training – widening scope, adaptation to current needs – from concepts toward concrete tasks 27

28. Good tools Project team Quality network – contact experts in departments Help-desk Training What failed: Providing tools without personal support, not public, not used, not controled 28

29. Sequence of development phases - aspects Follow logical order Requirements, measurement, assessment Take in use items developed Not just to archive Keep balance of cost-benefit Time used – benefit in information Avoid shocks and fears Workload, indicator with explanation, not to judge people 29

30. Keep in mind Quality problems are with processes not people Encourage initiative, push responsibility to lower level Communication and training are more important for improvement then control 30

31. Sequence of development phases - steps Complete terminology in Hungarian Set up conceptual framework: Quality concept, components Vision of quality assurance framework, Strategic plan Projects for statistical products and processes develop requirements, measurement and assessment tools Continuous training, communication 31

32. 32 Thank you for your attention!