Australian Bureau of Statistics: use of GSBPM

Since GSBPM (Generic Statistical Business Process Model) reached full maturity with the release of V4.0 agreed in April 2009 it has been regarded as the preferred reference model for the statistical business process within the ABS. This status for the GSBPM was confirmed with the area leading the enterprise architecture initiative within the ABS at that time. The IMT Program launched in February 2010 also confirmed this status for the GSBPM. 

A number of reference models for the statistical business process existed, and were harnessed, within the ABS prior to the development of the GSBPM. 

A particularly broadly applied model was affectionately known as "The Caterpillar" within the ABS. The Caterpillar was developed by the ABS as a reference model to support the Business Statistics Innovation Program (BSIP) launched in 2002.. It allowed a disparate range of surveys and other statistical activities whose processes were (especially prior to BSIP) very different in detail to describe what they did, why and how (eg what systems and data stores were used) in terms of a common high level reference point for the statistical life cycle. It later allowed "leading practice" to be identified in different parts of the statistical cycle. 

The broad relationship between the Caterpillar and GSBPM, documented previously in this section of the case study, has been moved to a supporting page. 

Extensive process documentation, together with categorisations of information and even software interfaces, was developed during the course of initiatives such as BSIP and ISHS (both described in BHM). This activity was undertaken based on the "pre GSBPM" reference models for the statistical business process associated with those initiatives. It has been agreed existing process documentation within the ABS will not be rewritten for the sole purpose of referring to the GSBPM. Formalising, and making readily available, mappings between the GSBPM and the local reference models has been particularly important. 

The paper Applying the GSBPM within an NSI : Experiences and examples from Australia, prepared for the METIS Work Session in March 2010, provides more information in regard to ABS utilisation of GSBPM as well as in regard to statistical business process models that preceded GSBPM. Annex 1 of that paper provides a full description of the Caterpillar. 

Key points include 

• GSBPM is harnessed, within the business domain of ABS Enterprise Architecture, as the primary reference model for the for the statistical business process.
• Recognition within business architecture allows GSBPM to serve (among many other roles) the purpose for which it was originally commissioned internationally, namely linking metadata management (and statistical information management more generally within the data/information domain of Enterprise Architecture) to the statistical business process.
• GSBPM is seen as a vital enabler of practical, purposeful and collaborative external engagement at the international level, national level and sub-national level.
• GSBPM is harnessed as a reference model for the statistical business process for corporate planning and management purposes. A number of specific ABS applications of the GSBPM in this regard are listed in Section VI of the paper for the METIS work session.
• Experience with BSIP and ISHS highlighted the practical value of common (within each initiative) reference model for the statistical business process prior to GSBPM maturing to fulfil this role across the ABS as a whole, as well as internationally. .(See Annex 2 in the paper for the METIS work session)
• While ABS waited until GSBPM achieved the level of maturity, and breadth of international recognition, associated with V4.0 prior to adopting it formally, it has had an active interest in GSBPM since the inception of its development. (See Annex 3 in the paper for the METIS work session)

IMT has a focus on statistical information management rather than, eg, financial and human resource information within the ABS. 

That said, information about costs, information about organisational structures, people and their roles are examples of information that can be relevant to managing and performing statistical business processes. More generally Statistical Information, Corporate Information and Business Information can be visualised as intersecting circles, and the intersections with Statistical Information are certainly in scope for IMT. 

Also, as long as it does not distract from the focus on the statistical information used and/or produced in the course of various sub processes within a statistical business process, there is no reason why elements of the Statistical Information Management Framework associated with IMT could not be applied to these other information domains. 

A further connection is that a range of high level key performance indicators in relation to the core business of the ABS are expected to be able to be sourced via the MRR in future. These will assist in high level corporate monitoring and reporting, on a more consistent and informed basis, of efficiency, productivity, return on investments etc. 

One reason IMT does not have a primary focus on corporate information and business information is that well recognised standards and frameworks (not specific to producers of official statistics) already exist for these domains of information. A more natural alignment in this case might be with Australian Government Architecture rather than the common reference architecture for producers of official statistics internationally. 

These other domains of information are recognised within ABS Enterprise Architecture (eg in terms of data/information architecture). The redevelopment of information systems related to human resource management is an example of an "architecturally significant" project in this regard. 

In this regard, the IMT approach parallels the 2003 metadata strategy which defined its scope as relating to "statistical" metadata (rather than all the metadata potentially relevant to any aspect of ABS operations).