Enterprise respondents in focus - Enterprise data collection and quality assurance

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Enterprise respondents in focus - Enterprise data
collection and quality assurance

• Quality in Official Statistics Rome 8-11 July
  2008
• Hannele Orjala, Statistics Finland

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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
  2007-2011
• Developing respondent services and relations
• Conclusions

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Production process of statistics
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- Direct data collection
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- Administrative and register sources
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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 Confederatio
  ns of Finnish Industries The Finnish Vehicle
  Administration commercial sources

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Direct collection vs. the use of administrative
datafrom Tax Authorities in statistics on
enterprises
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 (lt1)
110 000 For the enterprises in direct
collection some data are taken from
administrative sources.
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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
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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

Cost-efficiency
Accuracy
Timeliness
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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
  hotels management software
• Use of Statistics Finlands definitions for data
  and service interface
• Technique XML Web Services
• After reception, data is submitted to the
  standard validation process

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Data providers hotel management system
Choose the month and send the report
Choose report to Statistics Finland
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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

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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

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Developing respondent services and relations
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http//www.tilastokeskus.fi/keruu/index_en.html
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http//www.tilastokeskus.fi/keruu/yritys_en.html
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http//www.tilastokeskus.fi/keruu/tiedonkeruupalve
lu_yrityksille_en.html
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Enterprise data collection service - List of the
data collection inquiries
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Co-operation with respondents and data providers

• Co-operation with the business sector (employers
  association)
• Permanent working group since the early 1990s
• Establishment of new statistics and revisions of
  existing ones
• Channel for the business sectors 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

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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

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Thank you for your attention!

• Contact information
• Hannele Orjala
• Director, Business Trends
• Statistics Finland
• email hannele.orjala_at_stat.fi
• tel [phone]
• Also
• Jussi Heino, email jussi.heino_at_stat.fi
• Johanna Leivo, email johanna.leivo_at_stat.fi
• www.stat.fi/index_en.html

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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