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Introducing a robust system to ensure the quality, integrity, and coherence of statistical data, aligning with national and international standards. Analyzing interrelations with metadata management and business processes.
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Quality Assurance System of theStatisticalInformation October, 2011
Background • Quality is a therefore multi-faceted, user-driven concept. The dimensions of quality that are considered most important depend on user perspectives, needs and priorities, which vary between processes and across groups of users.
Background Questionnaire General and Specific Standards and Frameworks QUALITY STATISTICAL INFORMATION • Ejemplos • Guide to Drafting a Roadmap for Designing the National Strategy for the Development of Stadistics NSDS (París 21). • Management Oriented to Ensure the Quality of the Data at the National Institutes of Statistics (EUROSTAT). • Statistics Canada Quality Guidelines (Of. Est. Canadá). • Ejemplos • Data Quality Assessment Framework( IMF-WB). • European Stadistics Code of Practice, Self Assessment Questionaire (eurostat). • European Self-Assessment Questionnaire for those Surveys Responsible (EUROSTAT).
Purposes Present the General Quality Assurance System for statistical information that allows warranteeing the proper implementation of the national and international policy frameworks, of the established methodological basis, the compliance of the determined policies, the objectives, principles and values, as well as the proper and transparent use of resources allocated. Generally analyze the interrelations and coordination of the Quality Assurance System with the Generic Statistical Business Process Model and finally with the Metadata Management.
Statistical Information Process Elements and components Metadata Management Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate 1 Statistical Information Process Census Surveys Administrative Records Statistics Derived / Secondary Stadistics Integrate
Elements and components Legal framework Legal Framework Laws and Regulations 2 Metadata Management Monitoring Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Statistical Information Process 1
Laws and Regulations C1. Instituto Nacional de Estadística y Geografía: Functions: • Regulate and coordinate the system. • Regulate and coordinate the activities to carry out units, taking into account national and international standards. • Request the units information concerning its activities for the integration of the drafts of the programmers. • Request the information they have obtained in the field of its competence unitsSolicitar a las Unidades la información que éstas hayan obtenido en el ámbito de su competencia. Exclusive powers: Regulation: General provisions on collection, processing and publication. National Census INEGI Monitor compliance with the provisions of a general nature. National Accounts System Authorization procedures for standards. National CPIs Provide and promote the use of definitions, classifications, Nomenclatures, directories, symbols, geographical boundaries. Other analogous concepts Produce any other information of national interest. Governing Board
Elements and componentsStandards / Recommendations / Agreements / Conventions Legal Framework Laws and Regulations Standards / Recommendations / Agreements / Conventions 2 National and International Agencies Metadata Management Monitoring 3 Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Observation Statistical Information Process 1
International agencies UN EUROSTAT OCDE IEA UNESCO OMS OPS FAO GSDI DGFI ITRF WGS IERS WEF UNECE ILO FMI BM ISO STATISTICS STANDARDS DEMOGRAPHIC RECOMENDATIONS ECONOMICS AGREEMENTS SCIENCE AND TECHNOLOGY CONVENTIONS ENVIRONMENT GENERAL FRAMEWORKS TECHNICAL STANDARDS
Elements and componentsMETHODOLOGICAL BASES Legal Framework Laws and Regulations Standards / Recommendations / Agreements / Conventions 2 National and International Agencies Metadata Management Monitoring 3 Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Observation Statistical Information Process 1 Application Methodological Bases 4 Criteria / Parameters Procedures
METHODOLOGICAL BASES Methodologica Bases Stadistic Information Examples Collect Home Surveys • Census. • Surveys. • Administrative Records. • Derived Statistics • Integrate Statistics. Collect Industries and Commerce Surveys Design data collection methodology Classify and code
Elements and components RESOURCE MANAGEMENT Legal Framework Laws and Regulations Standards / Recommendations / Agreements / Conventions 2 National and International Agencies Metadata Management Follow-up 3 Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Observed Statistical Information Process 1 Management Application Resources 5 Methodological Bases Controls 4 Criteria / Parameters Procedures
Elements and components RESOURCE MANAGEMENT Material Financial Human • Budget Management: • Allocation. • Control and Monitoring. • Costs Management: • Direct: • Contracts. • Human. • Equipmen. • Materials. • Indirectos: • Infraestructure. • Human. • Accounting Management. • Human Management: • Job Profiles. • Selection. • Recruitment. • Training • Evaluation. • Certification. • Control and Monitoring. • Human Capital. • Payroll. • Management Material: • Information Technologies. • Hardware. • Software. • Datawere. • Infrestructure. • Furniture and Equipment. • Materials • Maintenance.
Elements and componentsPROCESs Legal Framework Laws and Regulations Standards / Recommendations / Agreements / Conventions 2 National and International Agencies Metadata Management Monitoring 3 Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Observation Statistical Information Process PROCESS 1 Management Application Resources 5 Methodological Bases Controls 4 Criteria / Parameters Procedures
Elements and components PRODUCT Legal Framework Laws and Regulations Standards / Recommendations / Agreements / Conventions 2 National and International Agencies PRODUCT Metadata Management Monitoring 3 Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Observation CUSTOMER Statistical Information Process 6 1 Attributes or Characteristics Result USER Management Application Resources 5 Methodological Bases Controls 4 Feedback / Improvement Criteria / Parameters Procedures
attributes or characteristics Statistical Information Relevance Coherence Accuracy Statistical Information Opportunity Interpretability Accessibility
Elements and components Quality Assurance System of the Statistical Information Legal Framework Standards / Recommendations / Agreements / Conventions Laws and Regulations 2 National and International Agencies 3 CUSTOMER Metadata Management Monitoring Attributes or Characteristics Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate 6 Observation Testing/ Briefing Statistical Information Process Monitoring and Evaluation Result 1 Verification Report USER Management Application Resources 5 Methodological Bases Controls 4 Criteria / Parameters Procedures Feedback / Improvement
Elements and components INTERACtion of GSBPM and qas Standards / Recommendations / Agreements / Conventions 3 GSBPM Metadata Management 1 Specify Needs Design Build Collect Process Analyse Disseminate Archive Evaluate Observation Verification Quality Monitoring and Evaluation Statistical Information Process Report Stadistics Integration Censs Statistics Derived / Secondary Surveys Administrative Records Preventive, corrective actions and improvements
Elements and components QUALITY EVALUATION Tools Elements Guides Indicators Tables Standards Guidelines Recommendations Controls Parameters Bases Requirements Methods Procedures Documents Records Compliance Questionnaires Reviews Insterviews Inspections Audits Quality Monitoring and Evaluation Level 0, statistical business process Level 3, elements of sub-processes Level 1, the nine phases of the statistical business process Level 2, the sub-processes within each phase
Elements and components INTERACtion of metadata management and qas Relationship toStatistical Cycle/ Processes Integrity. Matching metadata. Describe flow . Capture at source Exchange and use Metadata handling Statistical Business Process Model. Active not passive. Reuse. Versions. Quality Monitoring and Evaluation Metadata Authority Registration. Single source. One entry/update. Standards variations. Users Identify users. Different formats. Availability.