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Quality assessment ESTP Training Course “Quality Management and survey Quality Measurement” Rome, 24 – 27 September 2013 Giorgia Simeoni Researcher Unit “Auditing, Quality and Harmonisation“ Istat Marina Signore Director of Research Chief, Division "Metadata, Quality and R&D Projects“ Istat
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Content Data quality assessment map Quality reporting Self-assessment, auditing, peer review Labelling and certification
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Elements of a quality management system*
Quality assessment Assessment Institution Statistical products and processes Elements of a quality management system* User needs Institutional environment Production processes Statistical products Management systems & leadership Support processes *Bergdahl et al. (2007) Handbook on DatQAM
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Data quality assessment map*
External Environment Users Requirements Standards Assessment methods and tools Labelling Certification (ISO 20252) Self-Assessment Audits Process Variables Quality indicators Quality Reports User Surveys Preconditions Measurements of processes and products *Bergdahl et al. (2007) Handbook on DatQAM
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Main features of a quality report:
Quality reporting A quality report provides information on the main quality characteristics of a product so that the user should be able to assess product quality. In the optimal case quality reports are based on quality indicators (Bergdahl et al., 2007) Main features of a quality report: Object: a statistical product or statistical process Target recipients: users or producers of official statistics Purposes: to accompany official statistics dissemination, to support quality assessment Contents: quality dimensions, quality indicators Further characteristics: standard structure, different levels of detail tailored on recipient and purpose
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ESS standard structures for metadata and quality reporting
Euro SDMX Metadata Structure (ESMS) Development of the technical standard «Statistical Data and Metadata eXchange (SDMX)» Commission Recommendation of 23 June 2009 on reference metadata for the European Statistical System: ESMS is to be used by NSIs when compiling reference metadata in the different statistical areas and exchanging them within the European Statistical System or beyond. Definition of reference metadata: Metadata describing the contents and the quality of the statistical data. Preferably, reference metadata should include all of the following: a) "conceptual" metadata, describing the concepts used and their practical implementation, allowing users to understand what the statistics are measuring and, thus, their fitness for use; b) "methodological" metadata, describing methods used for the generation of the data (e.g. sampling, collection methods, editing processes); c) "quality" metadata, describing the different quality dimensions of the resulting statistics (e.g. timeliness, accuracy).
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Euro SDMX Metadata Structure (ESMS)
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Type of statistical processes: Main section headings:
ESS standard structures for metadata and quality reporting ESS Handbook and Standard for Quality Reports Guidelines for preparation of comprehensive producer oriented quality reports for different types of statistical process. Type of statistical processes: Main section headings: Introduction Relevance Accuracy Timeliness and Punctuality Accessibility and Clarity Coherence and Comparability Sample survey Census Statistical process using administrative source(s) Statistical process involving multiple data sources Price or other economic index process Statistical compilation Trade-offs Assessment of user needs and perceptions Performance, cost and respondent burden Confidentiality, trasparency and security Conclusions
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ESS Standard for Quality Reports Structure (ESQRS)
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Self-assessment Comprehensive, systematic and regular review of an organisation’s activities and results against a reference model/framework «Do it yourself» evaluation, subjective More general, not based on quantitative measures It does not require extensive production of ad hoc documentation Based on the compilation of check-list or questionnaires It stimulates the quality awareness and continuous improvement Self-assessment can be applied also at program/process level
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Self Assessment Checklist for Survey Managers (DESAP)
generic checklist for a systematic quality assessment of surveys in the European Statistical System (ESS) tool to support survey managers in assessing the quality of their statistics and in identifying improvement measures fully compliant with the ESS quality criteria comprises the main aspects relevant to the quality of statistical data two versions: long and condensed
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Statistical auditing Systematic, independent and documented process for obtaining verifiable evidence and evaluating it objectively to determine the extent to which the audit criteria (policies, procedures or requirements) are fulfilled External or internal auditors (external to the audited process) It may require the compilation of reports, computation of quality indicators, preparation of ad hoc documentation It may use supporting questionnaires It results in the identification of strength and weaknesses of the process, and definition of improvement actions with a time scheduling for their implementation
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Main tools for data quality assessment
Statistical auditing experiences In October 2006, Istat interviewed some European Statistical Institutes and some overseas Statistical Offices on Statistical and IT Auditing activities. At that time almost more than 1/3 of the institutions had started statistical auditing activities and the same amount of institutions were planning to adopt it. Auditing is generally performed with reference to: Standards and Guidelines for Statistical Surveys Standard Quality Reports ISO norms and Statistical production procedures manuals Tools Auditing questionnaire, Quality reports, … Assessment report Improvement actions report Monitoring systems are built
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Main tools for quality assessment
Peer reviews Systematic examination and assessment of the performance of a statistical agency by other statistical agencies, with the objective of helping the reviewed institution to improve its quality policy, adopt best practices and comply with given standards and principles More informal and less structured respect to auditing May require to have extensive documentation at hand Generally oriented to assess at high level of the institution Generally they are not aimed at controlling conformity towards detailed checklist Usually they produce recommendations and an implementation programme
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Eurostat peer reviews In Eurostat and all National Statistical Institutes were subject to a peer review to evaluate the compliance with the areas related to the institutional environment and dissemination of statistics (principles 1-6 and 15 of the Code of Practice The exercise was complementary to a prior self-assessment evaluation A general report and country-specific reports with the evidence of the results of the review process and a Summary of the good practices are publicly available on Eurostat website Country specific reports included: - Good practices to be highlighted - Recommendations of the peer review team - List of improvement actions by principle of the Code of Practice Implementation of the action was monitored by means of a questionnaire in the next years Eurostat is planning a new round of reviews (methodology not yet publicly available)
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Labelling It consists on the assignment of an attribute (short message) conferring a quality connotation to the product/service, based on a procedure to evaluate compliance to ex-ante (before statistics are produced) or ex-post (after statistics are produced) standards or requirements. In official statistics field, the message is usually referred to the product or to the producer Need for careful selection of the message Need for existence of a procedure to guarantee the message is appropriate It provides guarantees on the product/service It increases the producer’s authoritativeness Example of labels “Official statistics”; “European statistics”
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Certification Method aimed at certifying the compliance to a international standard combining the external audit approach with the labelling one ISO 20252:2006 Market, opinion and social research is an international standard on quality of data in the sector of the marketing, opinion and social research studies It requires the adoption of a quality management system It is a very transparent system It may increase the Institution credibility Usually, it requires the production of extensive documentation It increases the awareness on process quality and it stimulates the quality improvement
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References Brancato G. (2007). Review on IT and Statistical Auditing Procedures, Istat, Italy Eurostat ( ). Code of Practice Peer review reports by country Handbook on Data Quality Assessment Methods and Tools (2007), ESS Standard for Quality Reports Structure (release 1, October 2010) Euro SDMX Metadata Structure (release3, March 2009) Eurostat (2010), ESS guidelines for the implementation of the ESS quality and performance indicators Eurostat (2009). Eurostat Methodologies and Working papers “ESS Standards for Quality Reports”. Eurostat (2003a), Definition of Quality in Statistics. Eurostat Working Group on Assessment of Quality in Statistics, Luxembourg, October 2-3. Eurostat (2003b), Glossary. Eurostat Working Group on Assessment of Quality in Statistics, Luxembourg, October 2-3. Eurostat (2003). Checklist for Survey Managers (DESAP) D’Orazio M, Carbini R, Signore M. (2012) Quality assessment in ISTAT: The combined use of standard quality indicator analysis and audit procedures. European conference on Quality in Official Statistics (Q2012) Athens, 29 May – 1 June Götzfried A., Linden H., and Clement E. (2011) Standards and processes for integrating metadata in the European Statistical System. UNECE, Workshop on Statistical Metadata (METIS), Geneva, Switzerland 5-7 October 2011 International Organisation for Standardisation (ISO) (2006). Market, opinion and social research – Vocabulary and service requirements (ISO 20256:2005)
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