Quality management in a changing environment: Eurostat's perspective Marie Bohatá and Martina Hahn Eurostat

Changes in the production pattern of European statistics…. Exploitation of additional sources, incl. private sources Increased mix of primary and secondary sources (administrative data, Enterprise Reporting Systems, private sources) Re-/combination of data to obtain ad hoc output (data warehousing) according to ex-post user demands

Screening of institutional environment (independence, objectivity, impartiality) Data access conditions (security, sustainability, costs, property rights) Confidentiality (more combinations, decentralised systems) Accuracy to be established ex-post (control surveys) Comparability (existence of European market, definitions) New role(s) of official statisticians (contracting, warehouse design, legislation, inter-disciplinary, market player, cross-border co-operations, ownership) …impact on ESS quality assurance….

Quality to be determined ex-post, different quality levels Importance of paradata Relevance changes with use Multi-domain quality determinants, “net quality”, risk-based approach Lack of information / too complex information / limitations of use …and impact on ESS quality reporting….

Changing user role and implications for communication on quality and quality management Users’ needs become complex and cross-cutting Users and their needs are not homogenous –General statistics –Market sensitive statistics –Political statistics

Due to changes in the production systems users exercise more influence Quality becomes a relative concept led by the purpose (multi-purpose) of usage Quality management of “traditional” statistics covered by the Code Quality management of political statistics? Changing user role and implications for communication on quality and quality management

Conclusions ESS to work towards standardised approach for quality assurance of secondary data sources Data warehousing requires that statisticians negotiate with data owners shifting their role from production to consultancy Data warehousing requires to better communicate limitations of use Quality management for multipurpose statistics and data warehousing lead to varying pertinence of individual quality dimensions and trade-offs. The underlying philosophy of labelling has to be developed (involvement of ESAC). Quality management for political statistics means to assure their political adequacy (involvement of ESGAB)