Rationalising Data Collection Automated Data Collection from Enterprises

Topics Introduction n Automated data collection n National experiences n Conclusions n Juha-Pekka Konttinen

Introduction User needs vs. response burden vs. burden on statistical authorities n More efficient

Automated data collection in accommodation statistics Data in XML format is generated from the

Data collection in accommodation statistics Juha-Pekka Konttinen 31/10/2012 6

Experiences in Automated data collection n Once the accommodation establishment has implemented the system

Encountered problems / challenges in Automated data collection n The implementation seems to be

Conclusions Electronic and automated data collection has led to a notable reduction in processing

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Rationalising Data Collection: Automated Data Collection from Enterprises Seminar on New Frontiers for Statistical Data Collection 31. 10. 2012

Topics Introduction n Automated data collection n National experiences n Conclusions n Juha-Pekka Konttinen 31/10/2012 2

Introduction User needs vs. response burden vs. burden on statistical authorities n More efficient ways of collecting data / new data sources n Automated data collection n Juha-Pekka Konttinen 31/10/2012 3

Automated data collection in accommodation statistics Data in XML format is generated from the respondent’s management system into a specified file n The file is sent directly as an encrypted electronic transmission into NSI’s database n The procedure is more or less automatic n Data is validated both logically and manually, if needed, before it is transferred to the production database in NSI n Juha-Pekka Konttinen 31/10/2012 4

Juha-Pekka Konttinen 31/10/2012 5

Data collection in accommodation statistics Juha-Pekka Konttinen 31/10/2012 6

Juha-Pekka Konttinen 31/10/2012 7

Experiences in Automated data collection n Once the accommodation establishment has implemented the system l Response burden is practically zero (earlier/other collection modes 30 min – 2 hours) l Compilation burden reduces l NSI receives data earlier l More time to analyze and go through data l Improved quality on statistics Juha-Pekka Konttinen 31/10/2012 8

Encountered problems / challenges in Automated data collection n The implementation seems to be slow because l Lot of different kind of software / inappropriate / no software at all l Global software houses consider one country as a small market l Lack of resources / interest / money Juha-Pekka Konttinen 31/10/2012 9

Conclusions Electronic and automated data collection has led to a notable reduction in processing and compilation burden in Statistics Finland n Automated data collection has led to a major reduction in response burden in accommodation establishments n Implementation problematic n Improves also l Feedback to establishments l Timeliness and quality l Comparability n Juha-Pekka Konttinen 31/10/2012 10