1. MEDSTAT IV GSBPM and other international standards
Training Course
« GSBPM »
Rome, 25 – 27 July 2017
GSBPM and other international standards
Marina Signore
Director of Research, Data collection directorate, Istat
FACILITY FOR EUROMED DIALOGUE AND EXCHANGE OF BEST PRACTICES
MEDSTAT IV
Europeaid/136489/DH/SER/MULTI – Lot 1
NOM Prénom
Fonction

2. How GSBPM relates to other international standards and frameworks
TABLE O CONTENT
Modernisation of statistical activity
definition of production process and discussion with participants
relationship with GAMSO
relationship with Quality frameworks

3. UNECE High-Level Group for the Modernisation of Official Statistics (HLG-MOS)
 To promote common standards, models, tools and methods to support the modernisation of official statistics;
To drive new developments in the production, organisation and products of official statistics
To ensure that there is a maximum of convergence and coordination within the statistical "industry".

4. Modernisation of official statistics
Challenges for Official Statistics
Modernisation
New competitors in producing statistics
New data sources available (e.g. Big data)
Increased costs and quality problems to collect data
Reduced budgets for official statistics
Emerging information needs
Join efforts
Increase cooperation
Interactive and low-cost cooperation
Sharing of skilled resources
Sharing tools, methods, standards
Adopting common solutions
More with
less

5. Supporting Standards Group
The goal of the group is to find ways how to develop, enhance, integrate, promote, support and facilitate implementation of the range of standards needed for statistical modernisation.
It has operational responsibility for the maintenance and development of the Generic Activity Model for Statistical Organizations (GAMSO), Generic Statistical Business Process Model (GSBPM), and the Generic Statistical Information Model (GSIM), and the documentation of the Common Statistical Production Architecture (CSPA).

6. What’s happening? GSIM Review GSBPM Review Metadata Glossary
Workshop on Integrating Geospatial and Statistical Standards 
6 - 8 November
Stockholm 
What’s happening?
GSIM Review
GSBPM Review
Workshop on Integrating Geospatial and Statistical Standards 
6 - 8 November
Stockholm 
Metadata Glossary
Quality Indicators

7. GSBPM and GAMSO When have they been developed?
Current version v5.0 - December 2013
First release v1.0 – March 2008
GAMSO
Current version v1.1 - January 2017
First release v1.0 - March 2015

8. GSIM and CSPA When have they been developed?
Current version December 2013
Current version v1.5 - December 2015

9. Common purposes of the standards
Improve communication by introducing a common language
Gain efficiency (rationalise processes, information, flow, assign responsibilities,..)
Support industrialisation process (re-use of methodologies, tool, software, sharing of solutions,…)
Build staff competencies around the standards (enhance capabilities)

10. The GSBPM What about big data? Mixed-sources?
The GSBPM
The Generic Statistical Business Process Model (GSBPM) is an international standard that can be used to document any kind of statistical business process, from the more traditional survey to the administrative data acquisition or to the statistical compilation
What about big data?
Mixed-sources?

11. Overarching processes
Business process
Level 0
Level 1
Overarching processes
Level 2

12. Generic Activity Model for Statistical Organisations - GAMSO
What is GAMSO?
It describes and defines the activities that take place within a typical statistical organization. It extends and complements the Generic Statistical Business Process Model (GSBPM) by adding additional activities needed to support statistical production

13. Interrelations among the standards
GAMSO
Supporting activities
Output
The information flow
Input
Production process
Output
GSBPM

14. How GSBPM relates to other international standards and frameworks
TABLE O CONTENT
Modernisation of statistical activity
definition of production process and discussion with participants
relationship with GAMSO
relationship with Quality frameworks

15. Definition of Statistical (Business) Process
Definition of Statistical (Business) Process
The Statistical Business Process is not defined in the GSBPM
Work is in progress within the Metadata Glossary group to define it but the definition is not ready yet
Some elements for discussion

16. What do we find in the GSBPM?
What do we find in the GSBPM?
The 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
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.

17. What do we find in the GSBPM?
What do we find in the GSBPM?
Whilst the typical statistical business process includes the collection and processing of data to produce statistical outputs, the GSBPM also applies to cases where existing data are revised or time-series are re-calculated, either as a result of improved source data, or a change in methodology. In these cases, the input data are the previously published statistics, which are then processed and analysed to produce revised outputs
As well as being applicable for processes which result in statistics, the GSBPM can also be applied to the development and maintenance of statistical registers, where the inputs are similar to those for statistical production (though typically with a greater focus on administrative data), and the outputs are typically frames or other data extractions, which are then used as inputs to other processes

18. GSIM: Definition of Business Process
GSIM: Definition of Business Process
The set of Process Steps to perform one of more Business Functions to deliver a Statistical Program Cycle or Statistical Support Program.
For example, a particular Statistical Program Cycle might include several data collection activities, the corresponding editing activities for each collection and the production and dissemination of final outputs. Each of these may be considered separate Business Processes for the Statistical Program Cycle.

19. GSIM: Definition of Statistical Program Cycle
GSIM: Definition of Statistical Program Cycle
A set of activities to investigate characteristics of a given Population for a particular reference period.
A Statistical Program Cycle documents the execution of an iteration of a Statistical Program according to the associated Statistical Program Design for a certain reference period. It identifies the activities that are undertaken as a part of the cycle and the specific resources required and processes used and description of relevant methodological information used in this cycle defined by the Statistical Program Design.

20. GSIM: Definition of Statistical Support Program
GSIM: Definition of Statistical Support Program
A program which is not related to the post-design cyclic production of statistical products, but is necessary to support cyclical production.
This type of program will include such functions as metadata management, data management, methodological research, and design functions. These programs correspond to the horizontal functions shown in the GSBPM, as well as programs to create new or change existing Statistical Programs..

21. Metadata Glossary: definitions for GAMSO
Metadata Glossary: definitions for GAMSO
Activity is what we do.
An activity is something that occurs over a period of time and acts upon or with entities; it may include consuming, processing, transforming, modifying, relocating, using, or generating entities. (Source PROV-O)
Activities are grouped into 4 activity areas i.e. Strategy and leadership, Capability management activities, Corporate support and Production.
Capability is what enables us to do an activity.
An ability that an organisation, person, or system possesses. Capabilities are typically expressed in general and high-level terms and typically require a combination of organisation, people, processes, and technology to achieve. (Source The Open Group Architecture Framework (TOGAF).)
Capabilities provide the agency with the ability to undertake a specific activity. A capability is only achieved through the integration of all relevant capability elements (e.g. methods, processes, standards and frameworks, IT systems and people skills).
Process is how we do an activity

22. How GSBPM relates to other international standards and frameworks
TABLE O CONTENT
Modernisation of statistical activity
definition of production process and discussion with participants
relationship with GAMSO
relationship with Quality frameworks

23. GAMSO Common vocabulary and framework
basis for resource planning within a statistical organisation
basis for the measurement of costs of producing official statistics in a comparable way
tool to help assess the readiness of organisations to implement different aspects of modernisation, in the context of a proposed “Modernisation Maturity Model”
support risk management systems

24. Activity areas The GAMSO comprises three hierarchical levels.
The top level comprises four broad activity areas
The production area is described by the GSBPM

25. Strategy and leadership
high-level strategic activities that enable statistical organisations to deliver the products and services needed by governments and communities nationally and internationally

26. Understand national and international directions and factors
Determine vision, mission and strategic goals
Determine organizational value proposition
Determine and communicate values and expectations
Create interest and awareness
Develop strategies for achieving organizational goals
Prioritise capability portfolio
Prioritise statistical product and service portfolio
Define (annual) statistical programme
Allocate project and programme portfolio budgets
Build and maintain internal statistical and professional excellence
Ensure general coordination and alignment
Define general organisational policies
Publish policies, guidelines and normative documents
Build and maintain strategic relations, nationally and internationally
Build and maintain external statistical excellence
Advance inter-agency and international collaborations
Secure support for statistical product and service and capability portfolio
Coordinate the national statistical system

27. Capability management
support the successful development and monitoring of the capabilities that underpin an organisation's ability to conduct its business.
promoting the re-use and sharing of infrastructure (statistical and technical), both inside the organisation and across organisations, thus facilitating harmonisation and coherence of statistical outputs.

28. Capability management
Identify disruptions and capability improvements
Propose capability improvement projects
Manage capability improvement programmes
Undertake background research
Develop detailed capability requirements
Design capability solution
Build and release capability solution
Manage capability development project
Maintain capabilities
Promote capabilities
Evaluate capabilities
Support design
Support operations
Support use externally

29. Corporate support
These activities cover the cross-cutting, functions required by the organisation to deliver its work programme efficiently and effectively.

30. Manage business performance
Manage change and risk
Manage legislation & compliance
Maintain accounts (including assets and liabilities)
Manage procurement and contracts
Manage suppliers of equipment, office supplies and services
Manage employee performance
Manage and develop skills
Manage talent
Manage recruitment
Ensure succession planning
Manage IT assets and services
Manage IT security
Manage technological change
Manage cross- cutting statistical methodologies
Manage confidentiality
Manage disclosure control

31. Manage cross- cutting statistical methodologies
Manage confidentiality
Manage disclosure control
Manage documents and records, including destruction and archiving
Manage knowledge
Manage information standards and rights
Manage metadata and data
Manage communications and media relations
Manage stakeholder consultations
Manage cross- product user support
Manage data sharing agreements
Manage data transfer
Manage environmental, mechanical, and electrical needs
Manage arrangement of office space
Manage distribution of offices within space

32. Manage quality framework
Manage quality assurance tools
Manage quality documentation

33. GSBPM overarching processes
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
Statistical framework management
Strategic planning
Statistical program management
Provider management
Customer management
Statistical component

34. Metadata and Quality Management
NSI strategy, activities, leadership,…
Institutional level
Process and
Product level
Statistical production process and its output: statistical information
Statistical component

35. Metadata and Quality Management
Institutional level
Process and
Product level
Statistical component
Examples and suggestions from participants

36. Quality management Institutional level
the tools, the models, the documentation system are defined/implemented at a corporate level for the whole Institute
Statistical component
Manage quality framework
Manage quality assurance tools
Manage quality documentation

37. Quality management Process quality Product quality
This process includes quality assessment and control mechanisms. It recognises the importance of evaluation and feedback throughout the statistical business process
Statistical component
the tools, the quality control activity, the quality indicators are implemented/calculated for each phase and sub-process

38. Metadata management Institutional level Metadata systems
Manage documents and records, including destruction and archiving
Manage knowledge
Manage information standards and rights
Manage metadata and data
Metadata systems
Metadata standards
Classifications ……
Statistical component

39. Metadata management Process/ Product level Statistical component
Metadata are generated 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

40. How GSBPM relates to other international standards and frameworks
TABLE O CONTENT
Modernisation of statistical activity
definition of production process and discussion with participants
relationship with GAMSO
relationship with Quality frameworks

41. Quality Management Frameworks
The CoP and the QAF for the European Statistical Systems (
Statistics Code of Practice for the European Neighborhood South countries (2016) ?inheritRedirect=true&redirect=%2Feurostat%2Fpublications%2Fleaflets
The UN Fundamental Principles and the UN NQAF (National Quality Assurance Framework) ( ualityNQAF/nqaf.aspx)
There are also other models (ISO 9000 Norms, EFQM Excellence Model - European Foundation for Quality Management,……)

42. Why is it important?
Because we need to agree on common definitions and on a common background of what quality means
Share information on ongoing activities at international level
At national level
the objective is to establish, in a specific organisation, a system of methods and tools guaranteeing the adherence to minimum requirements

43. How?
Have a quality framework in place to guide quality management implementation
Knowledge of quality dimensions, errors sources, errors’ impact on final data
Use of international standards to model the statistical processes to improve efficiency
Use of international standards to model the activities that support statistical production
Develop and implement quality guidelines
Do not forget the users and stakeholders: do we provide information that satisfy their needs, how easy is for them to access statistical information, how satisfied are them,….

44. Participation of everyone Decisions based on facts
Common features
TQM is a Management Philosophy based on a set of Core Values
Customer Focus
Process Orientation
Committed Leadership
Participation of everyone
Decisions based on facts
Continuous improvements
Quality Tools

45. The Deming cycle

46. Plan Do Check Act - Indentify objectives / purposes
- Define success metrics
- Put a plan into action!
- What you have planned
you implement!
Inputs
outputs
PROCESS
OK!
Not OK!
Plan
Act
Check Do
Integrate the learning generated by the entire process
- You can correct, you can adjust your goals
You can change the methods
- ... You Plan again ...
(Study)
- Outputs are monitored and checked
- Identify progress and success, or
- Problems and issues for improvement

47. The Deming cycle
Systematic series of steps for gaining valuable learning and knowledge to continuously improve processes and products
A never-ending cycle for improvement!!!

48. GSBPM and Quality Frameworks
Quality management for the whole Organisation
Statistical component
Quality management for the Single Statistical Process

49. GSBPM and Quality Frameworks
General principles
Indicators for the whole organisation
Framework to plan and develop quality work
…….
Statistical Output
Statistical Processes
Statistical component
Institutional Environment

50. GSBPM and Quality Frameworks
Statistical Processes and Products
Reference Model to implement quality work at process level
Indicators to be calculated for each statistical process
…….
Statistical component

51. An example: auditing CoP Principle 4: QAF
There is a regular and thorough review of the key statistical outputs using also external experts where appropriate
QAF
A plan for implementing Quality reviews. e.g. internal or external auditing, self-assessment for key statistical outputs; systematically for process reengineering. An organisational structure for quality reviews. Training of internal auditors. Reference documentation. Action plans. Feedback from users. Deployment of outside experts. Benchmarking with other statistical authorities to identify good practices
Statistical component

52. An example: auditing GSBPM Other ideas?
Which phases and sub-processes do you want to audit.
Set targets to be met for each or some phases
Decide what indicators should be calculated and checked during the auditing
Other ideas?
Statistical component