Statistical quality by design: certification, rules and culture

Kuurstra, Douwe and Zeelenberg, Kees (2018): Statistical quality by design: certification, rules and culture.

Abstract

To achieve and to communicate quality of official statistics, it is essential that national statistical institutes adopt some system of quality by design, i.e. formal quality certification, e.g. ISO or EFQM. International law, international regulations, national law, specific statistical regulations, Code of Practice, Privacy, ISO 27001 (Information security) and ISO 9001 (Quality management systems). These are some of the ‘rules’ that National Statistical Institutes have to work with. In this paper we look at the why and how of these rules: why should we follow these rules, how to manage these rules and how to transform them into practice. Even if an NSI complies with all principles of the Code of Practice for European Statistics, it is still necessary to have external proof of commitment to process and product quality as well as to privacy and security. We argue that to achieve and to communicate quality of official statistics, it is essential that national statistical institutes adopt some system of quality by design, i.e. formal quality certification, e.g. ISO or EFQM. Such an external proof is necessary in order to maintain public trust in statistics. But quality does not come by itself. The statistics that are actually produced, must have sufficient quality. So we also need a quality culture that provides a production and work environment in which quality is embedded. In essence, the quality culture should be based on the principles that the staff of NSIs are professionals and are responsible for the quality of their products. But their main task is to produce statistics, not to understand all those rules mentioned before. Therefore the only way to make them involved is to make them the real owners of quality; this should be our goal for the years to come. It requires embodiment of the quality culture in work processes, management, and guidelines, based on Total Quality Management and plan-do-check-act cycles.

• Item Type: MPRA Paper
• Language: English
• Keywords: statistical quality, privacy, certification, ISO, EFQM, LOM, TQM, PDCA, Lean Six Sigma
• Subjects: C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; Data Access; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data ; Data Access

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