The availability of quality official statistics has become an increasingly important need, both because they allow the quality of services provided by public institutions to be correctly assessed, and because of the relevance that the indicators derived from these statistics play to support policy evaluations in the economic and social, health and development fields of a country.
Consider the today importance of the “Benessere Equo e Sostenibile” statistical indicators produced by ISTAT and those used in many countries starting from 2016 for monitoring the Sustainable Development Goals of the UN 2030 Agenda. Moreover, the Next Generation EU Plan and the “Piano Nazionale di Ripresa e Resilienza” (PNRR) adopted respectively in Europe and Italy in 2021 will have a significant impact in the next years on the requests for quality official statistics regarding services, not only public but also private. In Italy, ISTAT has recently responded to this need for quality official statistics adopting the ” Codice italiano per la qualità delle statistiche ufficiali” in 2022 (replacing the previous edition of 2010 and analogous to the European Statistics Code of Practice) dedicated to the “Sistema Statistico Nazionale” (SISTAN), made up of entities with different levels and territorial dimensions, and therefore characterized by rather heterogeneous economic and social contexts.
The increasingly strong impact of new technologies on the quality of official statistics should certainly not be underestimated. The rapid evolution of data sources and statistical-informatic techniques for the construction of multidimensional and composite indicators open further challenges for the evaluation of the quality of official statistics concerning public and private services. The need for timeliness and compliance with the legislation on the protection of personal data (privacy) requested by stakeholders is ever greater; furthermore, the need for integration, interoperability and reuse of various databases (linked data), in open contexts (open data) with large volumes, complexity and heterogeneity of sources (big data), are increasingly strong.