1. GSBPM Giorgia Simeoni, Istat, simeoni@istat.it
“Methods and tools for reference metadata documentation and communication” Project
“Methods, quality and metadata” Division
ESTP Training Course
“Information standards and technologies for describing, exchanging and disseminating data and metadata”
Rome, June 2018
THE CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION

2. What is GSBPM?
The Generic Statistical Business Process Model (GSBPM) is a international standard model that “describes and defines the set of business processes needed to produce official statistics”

3. GSBPM Background
Developed by the Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS)
Born as a documentation model, with the aim of standardising terminology
First version released on April 2009 (4.0)
Widely adopted by the global official statistics community
Revised in 2013:
to incorporate feedback based on practical implementation
to improve consistency with Generic Statistical Information Model (GSIM), released in December 2012

4. GSBPM 5.0 GSBPM 5.0 released in December 2013
A cornerstone of the High-Level Group for the Modernisation of Statistical Production and Services (HLG) vision and strategy for standards-based modernisation
Managed by the “Supporting Standards Group”, under the HLG
Fully aligned with version 1.1 of the GSIM

5. GSBPM has been approved as ESS Standard by the ESSC in February 2017.
GSBPM as ESS Standard
GSBPM has been approved as ESS Standard by the ESSC in February 2017.
Definition of ESS standard: A normative document, established by consensus among ESS members and approved by a recognised body according to the procedure of ESS standardisation, that provides for common and repeated use by several actors in the ESS, rules, guidelines or characteristics for the development, production and dissemination of European Statistics, aimed at the achievement of the optimum degree of order in the context of the implementation of the mission and vision of the ESS.

6. Overarching processes
The Generic Statistical Business Process Model
Level 0
Overarching processes
Level 1
Level 2
5.2. Classify and code - This sub-process classifies and codes the input data. For example automatic (or clerical) coding routines may assign numeric codes to text responses according to a pre-determined classification scheme.

7. Main characteristics
Organised in 3 levels with increasing level of detail
Detailed description of what is included in each sub-process
Several overarching processes broadly classified in 2 categories:
- With statistical component
More general
It is «Generic»
National, domain-specific or other implementations (e.g. Checklist for SDMX Design Projects) are possible
It is extremely flexible:
Not all the subprocesses should be performed
The order of subprocesses can be different from the one presented
It is possible to repeat some steps more than once

9. Applicability
“The GSBPM is intended to apply to all activities undertaken by producers of official statistics, at both the national and international levels, which result in data outputs”
Surveys
Censuses
Processes based on administrative records
Processes based on other non-statistical sources
Processes based on mixed sources
Revision of existing data
Re-calculation of time-series
Compilation of National Accounts
Processes of international statistical organisations
Development and maintenance of statistical registers

10. Overarching processes
With statistical component
General
Quality management
Human resource management
Metadata management
Financial management
Data management
Project management
Process data management
Legal framework management
Knowledge management
Organisational framework management
Provider management
Strategic planning
Statistical program management
Statistical framework management
Customer management
GAMSO

11. GAMSO v.1.1
The Generic Activity Model for Statistical Organisations

12. The Generic Statistical Business Process Model
Planning
Realisation

13. The planning sub-processes
Dialog with users, Identification of needs (new or additional), Definition of high level solution, Get approval from senior management
Definition of all methods and tools that will be used in the realisation of the statistical process
Set up and test of all methods and tools defined in the design stage

14. The realisation sub-processes (1)
The actual data acquisition, whatever the source or the method used, including data entry
The traditional phases of data treatment till the macrodata estimates are produced
It includes the production of complex statistics (e.g. indices), macrodata validation, confidentiality treatment

15. The realisation sub-processes (2)
The release of statistical outputs to users
The quality evaluation done at the end of a specific edition of a statistical business process
Quality Management
The overarching process on Quality represents quality assurance system implemented
across the business process

16. Uses of GSBPM Standardisation of terminology in international context
Support to statistical process documentation
Analyse processes in order to identify common subprocesses
Make inventory of available IT tools and application to rationalise and identify gaps
Make inventory of available methodological tools to rationalise and identify gaps
Reference model to support audit and self assessment procedures …

17. Example 1. Business Process Model at Statistics Sweden

18. Example 2. Spreadsheet for process documentation (v4.0)

19. Example 3. ABS Prices processes mapped to GSBPM (V4.0)

20. Example 4. Istat repository of methods and tools organised by GSBPM phases

21. Quality indicators for GSBPM
A wide set of quality indicators (partly qualitative and partly quantitative) has been mapped to each subprocess of GSBPM version 5.0 with the aim of expanding the quality management layer for the GSBPM
UNECE (2017) Quality Indicators for the Generic Statistical Business Process Model (GSBPM) - For Statistics derived from Surveys and Administrative Data Sources. Version 2.0 October 2017

22. Principles used in mapping the QIs to the GSBPM
Generic indicators as GSBPM is;
Consistent with existing quality assurance frameworks;
No formulas, only descriptions or explanations;
Quantitative indicators whenever possible;
Qualitative indicators in the form of yes/no or large/medium/low when appropriate;
Map indicators to the phase they measure even if they might be calculated at a later stage;
Allow for a certain degree of redundancy by mentioning the same indicators in different phases or sub-processes
Personalisation of the indicators left to NSIs

23. Example Quality Dimension Indicator Notes Soundness of implementation
Has the questionnaire been tested using appropriate methods (e.g. questionnaire pre-test, pilot in real situation, in depth - interviews, focus groups, interviewer support,…)?
Corresponds to the appropriate statistical procedures principle in the ES Code of Practice
Have the test results been taken into account in the process of implementing the final questionnaire, and documented in a report?
Corresponds to…
Has the data collection tool/instrument (electronic questionnaire, acquisition web site, SDMX hub) been tested and how?
This indicator refers to the tests of the IT instruments used for data collection (e.g. functionality test, stress test…)
Corresponds to …
To what extent have the test results been taken into account in the process of implementing the final data collection tools
Corresponds to…..

24. Example Quality Dimension Indicator Notes Accuracy and reliability
Edit failure rates can be calculated for key variables and by domains of interest. A sub-class of edits could be those designed to detect outlier observations.
A high/very high edit failure rate for a given variable would be suggest possible errors in previous phases (e.g. in the questionnaire or in data collection).
……….
………..
Accessibility and clarity
Percentage of metadata adequately archived (easily retrievable; properly labelled; retention period indicated)

25. On-going activities on GSBPM
Further revision of GSBPM: a consultation is ongoing on the UNECE wiki.
Relationships between GSBPM and other standards are being discussed
Improvement to specific phases and sub-processes description

26. The Istat experience on business process documentation: SIDI/SIQual
Istat official information system for documenting quality and reference metadata of the statistical production processes
SIDI «input» system, SIQual for consultation
SIDI first implementation in 2001, later converted in a web-based architecture
SIQual first release in 2005, English version released in 2008
SIDI/SIQual approach to documentation is highly structured and standardised, descriptive additional fields are available to better describe standard items

27. SIDI/SIQual contents IN-DEPTH DOCUMENTATION: Sampling design
Index production methodology …
CONCEPTUAL METADATA
Themes
Units ….
OPERATIONS
Phases
Operations
Sub-operations
DOCUMENTS REPOSITORY
Regulations, Manuals
Questionnaires
Documents (field operations, methods, standards, …)
GENERALISED SOFTWARE
Phases
Software
QUALITY CONTROL ACTIONS
Phase/Non sampling Errors
Preventing
Monitoring
Evaluating
Standard quality indicators
Process oriented
Coverage
Unit non response
Coding
Editing and imputation
Costs
Product oriented
Revision analysis
Timeliness and punctuality
Coherence preliminar/final results
Coherence with other sources
Lenght of comparable time series

28. SIDI/SIQual example of documentation

29. SIDI/SIQual example of documentation

30. Mapping GSBPM and SIDI/SIQual model
ISTAT SIDI/SIQual
1. Specify needs
Planning
2. Design
Frame Development
3. Build
Re-planning
4. Collect
Data Collection
Data Pre-processing
5. Process
Editing and Imputation
Data Processing
6. Analyse
Data Validation
Statistical Disclosure Control
Dissemination
7. Disseminate
Data Storage
Documentation
8. Evaluate
Evaluate (QIs and Quality Control)

31. Reference
UNECE (2013) Generic Statistical Business Process Model GSBPM (Version 5.0, December 2013)
UNECE (2013) Generic Statistical Information Model (GSIM):
Communication Paper for a General Statistical Audience
(Version 1.1, December 2013)
UNECE(2011) Strategic vision of the HLG
UNECE (2017) Quality Indicators for the Generic Statistical Business Process Model (GSBPM) - For Statistics derived from Surveys and Administrative Data Sources. Version 2.0 October 2017