Enterprise respondents in focus Enterprise data collection and
quality assurance
Quality in Official Statistics
Rome 8-11 July 2008
Hannele Orjala, Statistics Finland
Contents of the presentation
The production process of statistics
 The use of administrative data and enterprise surveys
 Electronic and automated data collection
 A program for developing business data collection 20072011
 Developing respondent services and relations
 Conclusions

Hannele Orjala
16 June 2008
1
Production process of statistics
Suppliers and
sources of data
Feedback and contin uous, systematic improvement
Production process of statistics
Keepers of
administrative
data files
Enterprises
and
corporations
Individuals
h ouseholds
Collection and
gathering of data
Data
Storing
processing of data
Compiling
of statistics
- Direct data
collection
Public
administration
Dissemination
of statistics via
multiple
channels
– Web
services
– Publications
- Administrative and
register sources
Metadata: Interperetation of contents, process steering, data management,
statistical methods, concepts and classifications
Hannele Orjala
Data
users
Enterprises
and
corporations
Research
Media
Ordinary
people
16 June 2008
2
Use of administrative and register sources
The majority of the basic data for economic statistics are obtained from
administrative and register sources
 Principles of the Finnish Statistics Act (2004)
 It is compulsory to use existing data (if suitable)
 Guarantees access to administrative files
 Business ID widely in use


Data sources
Tax Administration
National Board of Patents and Registration
National Board of Customs
Bank of Finland
Population Register Centre
State Treasury
Local Government
Pension Institution
Confederations of Finnish Industries
The Finnish Vehicle Administration
commercial sources
Hannele Orjala
16 June 2008
3
Direct collection vs. the use of administrative data
from Tax Authorities in statistics on enterprises
Number of enterprises
Direct
collection
Structural Business Statistics
Business Register
Short Term Business Statistics
turnover
wages and salaries
Administrative
data
8 000 (4%)
25 000 (5%)
2 000 (1%)
93 (<1%)
180 000
over 500 000
250 000
110 000
For the enterprises in direct collection some data are taken from administrative sources.
Hannele Orjala
16 June 2008
4
Response burden: enterprises included in data collections
by size category of personnel in 2007

60 independent direct data collection processes
A total of some 61,000 enterprise data suppliers
18% of enterprises received at least one data collection*
66% of all enterprise data suppliers received one data collection

All enterprises with over 50 employees received at least one data collection



Number of data collections
Size category of
personnel
Data supplier not in
database
Size category not
known
0- 9
10-49
50-249
250 Total
%
1-4
5-9
Total
10-
Percentage of
active
enterprises
1 001
1 329
41 092
11 455
882
73
54 831
89,9
0
158
2 412
1 481
221
4 272
7,0
0
2
57
450
382
885
1,5
1 329
41 252
13 924
2 813
676
60 995
100,0
17,9
13,2
88,3
100,0
100,0
18,0
* enterprise = liable to pay VAT on business operations, and/or employer enterprise or included in the withholding tax register
Hannele Orjala
16 June 2008
5
Electronic data collection (xcola), primary objectives
Simplifies data collection process
 Reduces need for human resources
Cost-efficiency
 Reduces other data collection costs
 Improves the quality of collected data
Accuracy
 Decreases non-response
 Speeds up the data accumulation
Timeliness
 Reduces response burden
 Enables direct individual feedback for respondents
 Enables previously submitted data browsing

37 % of enterprises answer using electronic data collection
STS statistics electronic submission rate exceeds 80 %
Hannele Orjala
16 June 2008
6
Automated data collection in accommodation statistics
Data is delivered directly from hotel management systems
into our database
 No manual work needed (except to initiate the transfer)
 Software vendors implement a module for the hotel’s
management software
 Use of Statistics Finland’s definitions for data and service
interface
 Technique: XML Web Services
 After reception, data is submitted to the standard validation
process

Hannele Orjala
16 June 2008
7
Data providers’ hotel management system
Choose the month and
send the report
Choose report to
Statistics Finland
Hannele Orjala
16 June 2008
8
Experiences of automated data collection
Trade Magazine for Hotels and Restaurants: “Data reporting is
now extremely easy.”
 Data quality is good
 Data is coming faster than before, just a few days after the
reference period
 Response burden is almost zero, previously 1-2 hours per month
 Costs have been reduced in terms of working hours, mailing and
printing expenses
 Internet form is not used widely because printing and faxing
reports is easier
Co-operation with IT enterprises together with Nordic
Statistical Offices
New: agriculture statistics

Hannele Orjala
16 June 2008
9
Program for developing business data collection
2007-2011
Objectives
 Improve and harmonise data collection from enterprises
and service to enterprise data suppliers, especially large
enterprises
 Replacement of statistics-specific sample frames with a
single frame (Business Register), sample co-ordination
and optimisation
 Standard solutions serving enterprises and treatment of
data in all stages of the enterprise data collection
process
 Reduction of data suppliers’ response burden
Hannele Orjala
16 June 2008
10
Developing respondent services and relations
http://www.tilastokeskus.fi/keruu/index_en.html
Hannele Orjala
16 June 2008
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http://www.tilastokeskus.fi/keruu/yritys_en.html
Hannele Orjala
16 June 2008
13
http://www.tilastokeskus.fi/keruu/tiedonkeruupalvelu_yrityksille_en.html
Hannele Orjala
16 June 2008
14
Enterprise data collection service List of the data collection inquiries
1234567-8 Enterprise name
Nam e of data collection
Annual inquiry on foreign trade in
services
Information technology and
electronic commerce in
enterprises
Financial statements inquiry for
enterprises (TILKES)
Enterprises' research and
development
Nam e of data
supplier
Start of data
collecting
Frequency of data
collecting
Contact person for
data supplier
Yritys Oy
2.1.2008 Yearly
Yritys Oy
2.1.2008 Yearly
Yritys Oy
2.1.2008 Yearly
Jaakko Murola
Yritys Oy
23.3.2008 Yearly
Satu Nieminen
Job vacancy survey
Yritys Oy, Helsinki
Business Register inquiry for multiestablishment enterprises
Yritys Oy
Satu Nieminen
7.6.2008 Quarterly
1.2.2008 Other regular interval Satu Nieminen
Hannele Orjala
16 June 2008
15
Co-operation with respondents and data providers

Co-operation with the business sector (employer’s association)
Permanent working group since the early 1990s
 Establishment of new statistics and revisions of existing ones
 Channel for the business sector’s data needs


Co-operation with large enterprises


Large enterprise co-ordinator and the large enterprise working
group
Network with administrative data providers
Register Board Committee
 co-ordinators at Statistics Finland


Bilateral contacts
Hannele Orjala
16 June 2008
16
Conclusions

The aim is to achieve high-quality and coherent economic
statistics and reduce response burden (see Strategy for economic
statistics and measures proposed for 2008-2012. Statistics Finland 2007)
Development focus on
 direct data collections/automated direct data collection
 services to data providers and enterprises (large)
 methodological exploitation of administrative data
 Tools
 Programme for the development of data collections from
enterprises 2007-2011
 Co-operation with data providers and respondents

Hannele Orjala
16 June 2008
17
Thank you for
your attention!
Contact information:
Hannele Orjala
Director, Business Trends
Statistics Finland
email: [email protected]
tel: +358 9 1734 3582
Also:
Jussi Heino, email: [email protected]
Johanna Leivo, email: [email protected]
www.stat.fi/index_en.html
Hannele Orjala
16 June 2008
18
Appendix: Assessment of quality in statistics

Evaluation of processes:





Quality of products:




Self-assessment incl. internal auditing
of statistics
Peer reviews
International evaluations
and auditing (e.g. OECD,
Eurostat, IMF)
Quality Award Competition
Methodological descriptions
Quality descriptions: available both printed and online
Direct feedback from users of statistics, media
Quality with data suppliers:

Co-operation, feedback
Hannele Orjala
16 June 2008
19