Bring processes to create and maintain statistical standards within scope of GSBPM, as these processes consume and create GSIM objects and are core statistical processes of official statistics offices.
The HLG strategic vision demonstrates, in paragraphs 26 through 31, the pivotal relationship between GSIM and GSBPM, and how they contribute to the creation of common generic industrial statistics. It goes on to explain, in paragraphs 32 and 33, what the official statistics community needs to do with these models in the first instance:
To enable statistical organizations to arrive at standardised generic industrialised production of statistics, we first need to find one another at the conceptual level. We have to bring our concepts within the blue square under the umbrella of the GSBPM and the GSIM. This is a very high ambition which will take time. A first goal for the models is to act as a common language. We are lost if we cannot communicate properly.
It is obvious that the current version of the GSBPM is only a starting point which needs to evolve further, the same way common industrial standards evolve. This holds even stronger for GSIM for which a first version has yet to be established. The HLGBAS needs to actively promote development of and convergence on these conceptual standards.
The brochure describing GSIM provides the clearest articulation of how GSIM and GSBPM converge. On page 2 of the brochure, the diagram below shows how “GSIM models information that flows between these sub processes”.
This pivot point between GSBPM and GSIM is the point at which the models must converge. There should be conceptual equivalence between the two models at the point where they intersect. In other words, the domain of GSIM information objects should be equivalent to the domain of objects that GSBPM subprocesses consumes and produces. This, to me, is what “convergence” means.
Standards are statistical objects that are used in statistical processes. Creation of these standards is a core operation of statistical offices. Standards creation and maintenance processes often include similar steps to each other, such as looking at existing standards, looking at current practices, analyzing the statistical need, identifying or creating a proposed standard, and consulting with affected statistical stakeholders.
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