1. Business architecture
ESTP course on Structural Business Statistics
17 October 2012 – Luxembourg
Wim Kloek
Unit B1 Quality, methodology and research
Eurostat

2. Vision for the next decade
Meet new user needs
and improve quality
with less resources and
with less burden
Reference: COM(2009) 404

3. Two questions on the vision
Your opinion
Suggestions for implementation

4. Some ideas Integrate processes Use administrative sources
Data warehouse
Use of new information technologies
Share standard tools
Collaborative methodological development

6. Advantages of integration
Less double work
More profitable to share IT-development and to invest in human resources
Higher level of harmonisation between countries
Higher coherence over domains (new output)

7. Examples of integration
The European Enterprise group register
European sampling
Coordination of sampling (to spread the response burden or to match with variables in an other domain)
Standardisation of data and metadata description (GSIM, SDMX)
Standardisation of process description (GSBPM)
Establishment and spread of best practices

8. Disadvantages of integration
Difficult to manage; bounded rationality
Not necessarily in line with subsidiarity (e.g. use of administrative sources)
Less flexibility
Not all official statistics via NSI
百花運動

10. Some observations on the Generic Statistical Business Process Model (GSBPM)
Only core business processes are covered, not policy, management or other supporting processes
GSBPM has a lot of detail, but still not sufficient for integration or common development
No strict order of steps
GSBPM assists to describe processes in a standardised way, but gives no direction to development

11. Example: validation
Current process: validation by Member State, validation by Eurostat, feedback
Double work, time consuming feedback mechanisms
Sharing of validation rules
Goal: global coherence of data
Requires: common revision strategy, but also common understanding of the integrated process (tasks, responsibilities)

12. Administrative sources advantages
No response burden
Rich in detail (e.g. region, micro data)

13. Administrative sources how to use
Direct replacement of survey observations
Model (use correlation)
Integrate in the statistical business register (better stratification of samples)
Circumstantial validation and interpretation

14. Administrative sources disadvantages
Continuity of the source
Control over definitions (risk of data driven definitions)
Incentives for over/under reporting
Control over the executive practices
Statistical independence from policy
National in character: comparability

15. Administrative sources: metadata/output
How to assess data quality for statistical data based on a mix of survey data and administrative data
How to explain to users
- the way the data was produced
- the quality of the data

16. Data warehouse: requirements
Why not put all information in one database?
Links between the units
Metadata, standardisation
Replication requires traceability of changes
Revision strategy
How do we validate imputations, model estimations?
Linking national warehouses?

17. European Statistical System ESS
Member States + Eurostat
Establishing statistical legislation
Steer the implementation of the vision
Some resources (money) for collaborative work
System?

18. Conclusions Ambitious vision Implementation Challenges
Standardisation and integration of processes (GSIM, GSBPM)
Use of administrative sources
Sharing
Challenges
Managing complexity
Managing change
Financial and legal restrictions