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Quality reports

21-03-2014 The Quality Guidelines 2014 sets out the guidelines applicable to the statistical processes of Statistics Netherlands. The guidelines form the basis for audits and self-assessments of statistical processes. The report may also serve as input for redesign processes of statistics. The Quality Guidelines integrates international and national frameworks as well as Statistics Netherlands’ guidelines and Board resolutions.

10-04-2013 It is the challenge of statistical offices to use their knowledge and innovation power to the optimal extent in order to remain able to respond pro-actively and in a creative way to these developments. This paper describes how Statistics Netherlands has developed an Innovation programme. A three-stage funnel approach plays a key role in this programme. This approach gives maximum room for bottom-up development of ideas, while its focuses at the same time on maximum contribution to the goals of the organization. The Innovation Lab is an important instrument for the Innovation programme. It offers a suitable environment to support the generation of ideas and test their feasibility.

10-04-2013 The paper describes how Statistics Netherlands has developed a Knowledge and Innovation programme. The Knowledge part of the Programme has three goals: (i) to preserve knowledge with regard to the expected retirement wave (ii) to develop and share knowledge in order to be prepared for the future, and (iii) to provide adequate tooling for knowledge sharing. Mobility of employees is an important vehicle for knowledge sharing. Besides job rotation there are other instruments that can be used to create more flexibility in the organisation and stimulate knowledge sharing. The paper presents the first experiences of Statistics Netherlands with instruments like working in flexible, multidisciplinary teams and internal network communities in order to stimulate knowledge sharing and developing and to make use of best practices.

06-11-2012 Data quality is important for statistical institutes, not only in relation to the data they produce, but also because they use more and more secondary data sources to produce statistics. Examples of secondary data sources, data produced by others, are administrative data, transactional data and data from the Internet.

24-07-2012 The objective of this document is to describe a Standard for objects that are relevant for statistical processes and products. It is a Standard that can be applied to individual statistical processes.

19-05-2011 The objective of this document is to describe a Standard for objects that are relevant for statistical processes and products. It is a Standard that can be applied to individual statistical processes.

26-08-2010 This paper explains the OQM model developed by SN, and describes nine applications of the model. The applications vary from large-scale (TQM and process assurance) to small-scale. They demonstrate that the concept of quality areas is both powerful and flexible, and can be used in any domain.

23-09-2009 This paper gives introduction to the OQM model, discusses its characteristics and advantages, and describes the applications of the model up to now.

29-04-2009 CBS is looking for a suitable model for quality management. One reason is that CBS wants to manage quality in a systematic way to meet the European Statistics Code of Practice and the Quality Declaration of the European Statistical System. Existing quality systems do not fully meet CBS requirements, so a model was developed that would comply. One of the requirements is that the new model should combine with the EFQM Excellence Model. The OQM model is composed of components of well-known quality management models. This model is applicable to all areas of quality assurance and all types of organizations. It is called an object-oriented model, because objects play a central role in it.

10-04-2009 This report describes the results of the project Quality of Statistics Relevant to Statistics Netherlands’Corporate Image (KIS) as reported to Eurostat. In the project KIS three tools are developed that can be used to manage the quality of statistical output: a checlist, a questionnaire quick scan and a questionnaire deep scan.

09-02-2009 This report describes nineteen characteristics of statistical output. Each characteristic – also called dimension - is elaborated according to a certain structure starting with the definition of the characteristic. For each characteristic possible indicators and measures are formulated and summerized as a checklist in an annex. This report has several purposes. Seven purposes of the report are identified like serve as a knowledge base while making an agreement with customers about quality of statistical output. The report does not contain guidelines for the CBS organization and has no mandatory character. Although it can serve as a starting point for developing guidelines.