This paper aims to elicit a discussion of the existence of a paradigm shift in official statistics through the emergence of new (unstructured) data sources and methods that may not adhere to established and existing statistical practices and quality frameworks. The paper discusses strengths and weaknesses of several data sources. Furthermore, it discusses methodological, technical and cultural barriers in dealing with new data and methods in data science; cultural as in the culture that reigns in an area of expertise or approach. The paper concludes with suggestions of updating the existing quality frameworks. We take the position that there is no paradigm shift but that the existing production processes should be adjusted and that existing quality frameworks should be updated in order for official statistics to benefit from the fusion of data, knowledge and skills among survey methodologists and data scientists.

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This paper discusses how Statistics Netherlands managed to respond quickly with a range of new outputs to the sudden increase in the need for statistical information following the outbreak of the COVID-19 pandemic. It describes the innovation process already in place, as well as the innovations in response to the pandemic. This is followed by a discussion of what made speedy innovation and implementation possible, after which lessons are drawn in order to maintain the ability to react quickly to future policy questions. One important success factor is the combination of new data sources with already existing statistics for calibration. The developments at Statistics Netherlands can be seen as a case study. Several other NSIs also accelerated innovation after the outbreak of the pandemic, such as the Australian Bureau of Statistics and the British Office for National Statistics.

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