The Generic Statistical Business Process Model (GSBPM) describes and defines the set of business processes needed to produce official statistics. It provides a standard framework and harmonised terminology to help statistical organisations to modernise their statistical production processes, as well as to share methods and components.
Generic Statistical Business Process Model (GSBPM)

The Generic Activity Model for Statistical Organizations (GAMSO) adds additional activities needed to support statistical production. The GAMSO describes activities – that is, what statistical organisations do – while the GSBPM describes the process – that is, how statistical organisations undertake the activity of statistical production.

GSBPM is an elaborate example of a (Business) process model.

In the model on this page the ArchiMate Framework's Business Function model elements are used to depict the GSBPM top level concepts.

The overarching processes included in the list below are also included in the GAMSO:

  • Quality management - This process includes quality assessment and control mechanisms. It recognises the importance of evaluation and feedback throughout the statistical business process;
  • Metadata management - Metadata are created/reused and processed within each phase, there is, therefore, a strong requirement for a metadata management system to ensure the appropriate metadata retain their links with data throughout the GSBPM. This includes process-independent considerations such as metadata custodianship and ownership, quality, archiving rules, preservation, retention and disposal;
  • Data management - This includes process-independent considerations such as general data security, custodianship and ownership, data quality, archiving rules, preservation, retention and disposal;
  • Process data management - This includes activities of registering, systematising and using data about the implementation of the statistical business process. Process data can aid in detecting and understanding patterns in the data collected, as well as in evaluating the execution of the statistical business process as such;
  • Knowledge management - This ensures that statistical business processes are repeatable, mainly through the maintenance of process documentation;
  • Provider management - This includes cross-process burden management, as well as topics such as profiling and management of contact information (and thus has particularly close links with statistical business processes that maintain registers).

There is an easy to navigate "clickable" version of the model: Clickable GSBPM v5.1.