1. in a changing environment
Beijing, 2004, session 2
Nico Heerschap
The role of the
Business Register
in a changing environment
at Statistics Netherlands

2. Content: Old / current situation - changing environment
2/14
Content:
Old / current situation - changing environment
Ideal situation
Strategy for the short and medium term
The role of the Business Register
25 min.

3. Organisation of SN: Business statistics (BES) Social statistics (SRS)
Macro economic statistics (MSP)
Technology and facilities (TNF)
Two distant locations

4. Types of statistics in the Division of Business Statistics:
Production (mainly for NA)
Short term (mainly turnover)
Investments
International trade
Thematical
Energy, Technology, Environment, Health, Agriculture,
Transport, Crime, Culture, Tourism
Business Register / Baseline

5.          Old situation: Output Throughput Input Statistic 1
Product view
Old situation:    
Output
CR3
CR2
CR1
CRx
Throughput
Input BR
Statistic 1
Statistic 2
Statistic 3
Statistic x
ESB     

6. Changing environment:
Changing needs of customers: more integrated, coherent
and quicker. New theme’s emerge
Growing competition in the market place
Pressure to reduce the survey burden on enterprises
Smaller budget: pressure to be more efficient: less staff
but same or more output
New developments in IT and methodology
ESB

7. Disadvantages current situation:
4/14
Disadvantages current situation:
No co-ordination between statistics / separate worlds
No integration of the data overall (quality and consistency)
Sometimes different figures for the same phenomenon
Overlapping customer bases
Same data suppliers approached by different statistics
Little documentation of processes / hardly any mobility
Inefficient processes (e.g. not invented here syndrome) /
high business costs
Conclusion:
The situation within SN is not in line anymore
with a changing environment
ESB

8. Main goals of SN: consistent, quicker, flexibility, one window
5/14
Main goals of SN:
Strengthen the relationship with the customer: integrated,
consistent, quicker, flexibility, one window
New position in the market place: integrating crossroad on
the information highway, knowlegde institute (networks)
Reducing the survey burden by:
- Optimising the use of secondary sources
- Approaching the respondent in its own environment
More efficiency by redesigning the processes and applying
new IT and methodology
Adapt the organisational structure, culture and skills
(7S model of McKinsey)
ESB

9. better and quicker output lower input costs (SN / Enterprises)
In business terms:
better and quicker output
lower input costs (SN / Enterprises)
and lower process costs (higher productivity)
Meaning:
another way of making statistics
with less but more professional staff
ESB

10. Old situation Desired situationP I S C U S T O M E R A
Unanswered
Survey B
needs
burden
burden
Unanswered
Survey
needs
Desired situation E N T R P I S C U O M A B

11.   Output Throughput Input Merge Theme 1 Theme 2 Theme 3 Theme x ESB
One window for data dissemination services
Merge
Output
Throughput
Input
Theme 1
Theme 2
Theme 3
Theme x 
One window for data-collection services
ESB

12.  One window for all output services L
Customers / data-users
Output for
customer
Internal analists
Information
development
Data production
factory
Knowledge institute
(integrated) publication
information development
customer base W O R K F L M A N G E T M E T A D S Y
Output driven
process L
Output
Making of data-marts (selection, aggregation etc.)
Transactional dbase
Data
repository
CBR B A C K O N E S
Transfer data to
Data warehouse
Checking, editing
and micro-inte-
gration
Coupling data
to the backbone(s)
Throughput
External
SBR
Input
One window for all data-collection
All input, primary and secondary 
ESB

13. Dimensions of the data repository:
7/14
Dimensions of the data repository:
(3) TIME
(2) VARIABLES
Administrative
sources
Administrative sources
Administra-
tive sources
Survey-
data
(1) B A C K O N E S
(BR)

14. Main advantages, business case (1):
8/14
Main advantages, business case (1):
A uniform and consistent archive and output database for all
business statistics (one window) with:
- standardised definitions and concepts / structured metadata
- all data in one database, micro-data, aggregates, historical data
- data manipulation / output facilities (StatLine, Eurostat etc.)
- flexible, reproducible and better accessibility data users
Knowledge base for expert groups (tools for analysis, production)
Integration frame
- optimal use of secondary sources
- quality
- coordinated
- less and smaller surveys
- quicker output
ESB

15. Main advantages, business case (2):
8/14
Main advantages, business case (2):
Tool for analysis:
- longitudinal research
- timeseries
- follow big enterprises or a panel of enterprises
- consistency micro-data and corresponding aggregates
Documented
Basis for an output driven process
In line with organisational developments (hybrid organisation)
Reduced survey burden
Customer database
Efficient process (in potentie groot, lange en korte termijn)
- IT / methodology
- Organisational
ESB

16. 10/14
Bottlenecks:
Little experience with integration / very complex process of
checking, editing, imputation and micro-integration
No coordinated backbones
Still limited use of administrative sources
No centralised meta-data systems
No real experience with consistent weighing of data-marts
Controle of data disclosure
No experience with new technologies like dataware houses
Is it possible to control the total process?
Already made investments in short term process improve-
ments (input driven) / quick results

17. Strategy for the short and medium term:
A step-by-step approach
gaining insight
optimal situation as point on the horizon
using already existing improvement projects as the starting point
no cathedral building avoided.
Strategy
one centralised BR for (the maintenance of ) all backbones /
populations (coordination)
one contact centre for all input activities (coordination)
as less production lines as possible
as much standardisation and generic tools and solutions as possible
one output data warehouse for all business statistics
the optimal use of administrative sources at the cost of surveys
one centralised metadata – infrastructure

18. Customers BR Baseline Registrations Enterprises SBR Publication layer
Determine
Statistical needs
ESB-Basis
Metasystem
Information
development
Publication layer
(incl. statistical disclosure control
Process meta system
Data manipulation layer
Data repository layer
Integration layer BR
Statistical
Backbones
SBR
Input layer
Clean (micro)
data (meta)
Approach companies
Multi-channel
Institutional
statistics
(Impect)
Approach regis-
tration holders
Baseline
(secundair)
Functional
Enterprises
Registrations

19. The (changing?) role of the BR
Determination and derivation of statistical backbones / populations
Sampling and weighting frame for all business statistics
Matching frame (e.g. micro-integration)
The bridge between administrative and statistical data
A benchmark
Source for economic demography
Information source

20. Old situation Desired situation
Mainly a sampling frame
Existence of decentralised BRs
No overall coordination
Processing mainly within SN
No units of functional statistics
No metadata and quality indic.
Basis economic demography
Survey burden
Less accessible
Crucial role in coordination / unam-
bigious backbones / no decentralised
BRs
Matching frame. Integration
Information to follow businesses over
time (longitidinal / transversal)
Attention bigger businesses
Regional aspects
A bridge between adminstrative and
statistical data
Processing also outside SN (SBR)
Units functional statistics included
Metadata and quality indicators
User friendly access
Basis economic demography
Survey burden

21. Thank you for your attention
Open questions:
Timeliness of updates of the BR
Inclusion of functional statistics
The connection between BR and CPR
Thank you for your attention