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Industrialisation of Statistical Processes, Methods, and Technologies
In the official statistical context, it is important to understand that industrialisation does not represent the robotic automation of standardised statistical activity. Rather, it offers improved capacity to replicate basic processes, freeing up analyst resources so they can add value where needed, with the support of knowledge-based decision-making tools.
There are many different statistical processes within the ABS that are amenable to greater industrialisation, including the seasonal analysis of time series, microdata confidentialisation and the compilation of price indexes. Standardised metadata can be used to drive business processes and capture data relationships to promote greater harmony between similar or dependent activities. Since at their core all of the production processes for official statistics are about manipulating and quality assuring information, information management must be a strategic focus to achieve greater harmonisation and "industrialisation".
Anyone who has been involved in the process of developing an international statistical framework will be aware that it can be a slow and tedious process. Reducing the rate of innovation in the production methods of official statistics is a genuine risk to the "industrialisation" philosophy. It need not necessarily be so, as the experience of the growth of the internet has shown. The internet has created an environment within which enormous bursts of technological creativity and innovation occur - and yet at its heart it is reliant upon some basic standards which have been widely adopted. The task for methodologists working in the production of (official) statistics therefore becomes one of establishing which methods can and should be standardised, and which should not.
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