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Enterprise respondents in focus - Enterprise data collection and quality assurance
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Transcript of Enterprise respondents in focus - Enterprise data collection and quality assurance
Enterprise respondents in focus - Enterprise data collection and quality assurance
Quality in Official Statistics Rome 8-11 July 2008Hannele Orjala, Statistics Finland
16 June 2008 2Hannele Orjala
Contents of the presentation
The production process of statisticsThe use of administrative data and enterprise surveys
Electronic and automated data collection A program for developing business data collection 2007-2011 Developing respondent services and relations Conclusions
16 June 2008 3Hannele Orjala
Production process of statistics
gathering of data
Storingof data
Compilingof statistics
Disseminationof statistics viamultiplechannels – Web services – Publications
Keepers ofadministrativedata files
Enterprisesandcorporations
Individualsh ouseholds
Publicadministration
Enterprisesandcorporations
Research
Media
Ordinarypeople
Feedback and continuous, systematic improvementSuppliers andsources of data
Dataprocessing
Datausers
Production process of statistics
Metadata: Interperetation of contents, process steering, data management,statistical methods, concepts and classifications
Collection and
- Administrative and register sources
- Direct data collection
16 June 2008 4Hannele Orjala
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 RegistrationNational Board of CustomsBank of FinlandPopulation Register CentreState TreasuryLocal Government Pension InstitutionConfederations of Finnish IndustriesThe Finnish Vehicle Administrationcommercial sources
16 June 2008 5Hannele Orjala
Number of enterprises
Direct Administrative collection data
Structural Business Statistics 8 000 (4%) 180 000
Business Register 25 000 (5%) over 500 000
Short Term Business Statisticsturnover 2 000 (1%) 250 000wages and salaries 93 (<1%) 110 000
For the enterprises in direct collection some data are taken from administrative sources.
Direct collection vs. the use of administrative datafrom Tax Authorities in statistics on enterprises
16 June 2008 6Hannele Orjala
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
* enterprise = liable to pay VAT on business operations, and/or employer enterprise or included in the withholding tax register
1-4 5-9 10-
Data supplier not in database 1 001Size category not known 1 329 0 0 1 329 17,90- 9 41 092 158 2 41 252 13,210-49 11 455 2 412 57 13 924 88,350-249 882 1 481 450 2 813 100,0250 - 73 221 382 676 100,0Total 54 831 4 272 885 60 995 18,0% 89,9 7,0 1,5 100,0
Percentage of active
enterprises
Size category of personnel
Total
Number of data collections
16 June 2008 7Hannele Orjala
Electronic data collection (xcola), primary objectives
Simplifies data collection process Reduces need for human resources Reduces other data collection costs Improves the quality of collected data Decreases non-response Speeds up the data accumulation 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 %
Timeliness
Cost-efficiency
Accuracy
16 June 2008 8Hannele Orjala
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
16 June 2008 9Hannele Orjala
Data providers’ hotel management system
Choose the month and send the report
Choose report to Statistics Finland
16 June 2008 10Hannele Orjala
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
16 June 2008 11Hannele Orjala
Program for developing business data collection 2007-2011
ObjectivesImprove 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
16 June 2008 13Hannele Orjala
http://www.tilastokeskus.fi/keruu/index_en.html
16 June 2008 14Hannele Orjala
http://www.tilastokeskus.fi/keruu/yritys_en.html
16 June 2008 15Hannele Orjala
http://www.tilastokeskus.fi/keruu/tiedonkeruupalvelu_yrityksille_en.html
16 June 2008 16Hannele Orjala
1234567-8 Enterprise name
Name of data collectionName of data supplier
Start of data collecting
Frequency of data collecting
Contact person for data supplier
Annual inquiry on foreign trade in services
Yritys Oy 2.1.2008 Yearly Satu NieminenInformation technology and electronic commerce in enterprises Yritys Oy 2.1.2008 YearlyFinancial statements inquiry for enterprises (TILKES)
Yritys Oy 2.1.2008 Yearly Jaakko MurolaEnterprises' research and development Yritys Oy 23.3.2008 Yearly Satu Nieminen
Job vacancy survey Yritys Oy, Helsinki 7.6.2008 QuarterlyBusiness Register inquiry for multi-establishment enterprises Yritys Oy 1.2.2008 Other regular interval Satu Nieminen
Enterprise data collection service - List of the data collection inquiries
16 June 2008 17Hannele Orjala
Co-operation with respondents and data providers
Co-operation with the business sector (employer’s association)Permanent working group since the early 1990sEstablishment of new statistics and revisions of existing onesChannel for the business sector’s data needs
Co-operation with large enterprisesLarge enterprise co-ordinator and the large enterprise working group
Network with administrative data providersRegister Board Committeeco-ordinators at Statistics Finland
Bilateral contacts
16 June 2008 18Hannele Orjala
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 ondirect data collections/automated direct data collectionservices to data providers and enterprises (large)methodological exploitation of administrative data
ToolsProgramme for the development of data collections from
enterprises 2007-2011Co-operation with data providers and respondents
16 June 2008 19Hannele Orjala
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
16 June 2008 20Hannele Orjala
Appendix: Assessment of quality in statistics Evaluation of processes:
Self-assessment - incl. internal auditing of statistics
Peer reviews International evaluations
and auditing (e.g. OECD, Eurostat, IMF)
Quality Award Competition Quality of products:
Methodological descriptions Quality descriptions: available both printed and online Direct feedback from users of statistics, media
Quality with data suppliers: Co-operation, feedback