Enterprise respondents in focus - Enterprise data collection and quality assurance Quality in Official Statistics Rome 8-11 July 2008 Hannele Orjala, Statistics Finland

16 June 20081Hannele Orjala 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 Developing respondent services and relations Conclusions

16 June 20082Hannele Orjala Production process of statistics gathering of data Storing of data Compiling of statistics Dissemination of statistics via multiple channels – Web serv methods, concepts and classifications Collection and - Administrative and register sources - Direct data collection

16 June 20083Hannele 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 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

16 June 20084Hannele Orjala Number of enterprises Direct Administrative collection data Structural Business Statistics (4%) Business Register (5%) over Short Term Business Statistics turnover (1%) wages and salaries 93 (<1%) For the enterprises in direct collection some data are taken from administrative sources. Direct collection vs. the use of administrative data from Tax Authorities in statistics on enterprises

16 June 20085Hannele Orjala Response burden: enterprises included in data collections by size category of personnel in 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

16 June 20086Hannele 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 20087Hannele 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 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

16 June 20088Hannele Orjala Data providers hotel management system Choose the month and send the report Choose report to Statistics Finland

16 June 20089Hannele 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 Hannele Orjala Program for developing business data collection 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

Developing respondent services and relations

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16 June Hannele Orjala Enterprise data collection service - List of the data collection inquiries

16 June Hannele Orjala 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

16 June Hannele 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 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 Co-operation with data providers and respondents

16 June Hannele Orjala Thank you for your attention! Contact information: Hannele Orjala Director, Business Trends Statistics Finland tel: Also: Jussi Heino, Johanna Leivo,

16 June Hannele 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