1. United Nations Economic Commission for Europe
Statistical Division
United Nations Economic Commission for Europe
Statistical Division
Towards a Generic Statistical
Business Process Model
Steven Vale, UNECE

2. Steven Vale - UNECE Statistical Division Slide 2
Contents
 Background
 Modelling statistical business processes
 Applicability
 Structure and key features
 Relevance to SDMX
 Next steps

3. Steven Vale - UNECE Statistical Division Slide 3
Background
 Defining and mapping business
processes in statistical organisations
started at least 10 years ago
• “Statistical value chain”
• “Survey life-cycle”
• “Statistical process cycle”
• “Business process model”

4. Steven Vale - UNECE Statistical Division Slide 4
Background
 Defining and mapping business
processes in statistical organisations
started at least 10 years ago
• “Statistical value chain” X
• “Survey life-cycle” X
• “Statistical process cycle” X
• “Business process model” X
Generic Statistical Business
Process Model

5. Steven Vale - UNECE Statistical Division Slide 5
Modelling Statistical Business
Processes
 Reached a stage of maturity where a
generic international standard is the logical
next step
 Many drivers for a generic model:
• “End-to-end” metadata systems development
• Harmonization of terminology
• Software sharing
• Process-based organization structures
• Process quality management requirements
• ...

6. Steven Vale - UNECE Statistical Division Slide 6
Why do we need a model?
 To define, describe and map statistical
processes in a coherent way
 To standardize process terminology
 To compare / benchmark processes within
and between organisations
 To identify synergies between processes
 To inform decisions on systems
architectures and organisation of resources

7. Steven Vale - UNECE Statistical Division Slide 7
History of the Current Model
 Based on the business process model
developed by Statistics New Zealand
 Added phases for:
• Archive (inspired by Statistics Canada)
• Evaluate (Australia and others)
 Three rounds of comments
 Terminology and descriptions made
more generic
 Wider applicability?

8. Steven Vale - UNECE Statistical Division Slide 8
Applicability (1)
 All activities undertaken by producers of
official statistics which result in data outputs
 National and international statistical
organisations
 Independent of data source, can be used
for:
• Surveys / censuses
• Administrative sources / register-based statistics
• Mixed sources

9. Steven Vale - UNECE Statistical Division Slide 9
Applicability (2)
 Producing statistics from raw data
(micro or macro-data)
 Revision of existing data / re-calculation
of time-series
 Development and maintenance of
statistical registers

10. Steven Vale - UNECE Statistical Division Slide 10
Structure of the Model (1)
Process
Phases
Sub-
processes
(Descriptions)

11. Steven Vale - UNECE Statistical Division Slide 11
Structure of the Model (2)
 National implementations may need
additional levels
 Over-arching processes
• Quality management
• Metadata management
• Statistical framework management
• Statistical programme management
• ........ (8 more – see paper)

12. Steven Vale - UNECE Statistical Division Slide 12
Key features (1)
 Not a linear model
 Sub-processes do not have to be followed
in a strict order
 It is a matrix, through which there are
many possible paths, including iterative
loops within and between phases
 Some iterations of a regular process may
skip certain sub-processes

14. Steven Vale - UNECE Statistical Division Slide 14
Key Features (2)
 In theory the model is
circular:
• Evaluation can lead to
modified needs and design
 In practice it is more like
a multiple helix:
• There may be several
iterations of a process
underway at any point in
time

15. Steven Vale - UNECE Statistical Division Slide 15
Mapping
to Other
Models

16. Steven Vale - UNECE Statistical Division Slide 16
Relevance to SDMX
 Process modelling already mentioned in:
• SDMX User Guide
• V2 Technical Standards
• Euro SDMX Metadata Structure
 Common terminology
 If inputs and outputs use SDMX formats,
why not the intermediate processes?

17. Steven Vale - UNECE Statistical Division Slide 17
Standardized process descriptions
Harmonised processes
Rationalization of software
Use of open source and shared components
SDMX between components
Convergence of business architectures

18. Steven Vale - UNECE Statistical Division Slide 18
Next steps
 Several organisations are implementing
this model or similar ones
 Gather implementation experiences and
other comments as input for Part C of
the “Common Metadata Framework”
 Present to the Bureau of the Conference
of European Statisticians
 Role in SDMX?

19. Steven Vale - UNECE Statistical Division Slide 19
Questions and Comments?
steven.vale@unece.org
For more information see the METIS wiki:
www1.unece.org/stat/platform/display/metis