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Adaptation of the SBR to changing external conditions Søren Schiønning Andersen, Statistics Denmark (ssa@dst.dk). Outline. Background and purpose The three basic registers - our point of departure The integration of the SBR with the CABR The sources Recent challenges Pros and cons
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Adaptation of the SBR to changing external conditionsSøren Schiønning Andersen, Statistics Denmark (ssa@dst.dk)
Outline • Background and purpose • The three basic registers - our point of departure • The integration of the SBR with the CABR • The sources • Recent challenges • Pros and cons • Key differences between SBRs and ABRs • Overall learning points
Purpose • To describe: • The interface and integration between our SBR and the main sources, especially the CABR • Recent challenges to our SBR and how we have tried to cope with these challenges • How these changes have affected our ability to fulfil the objectives of the SBR (coverage, quality, usage, costs) • Our main learning points from these challenges
Six recent challenges to our SBR • Change to a key administrative source • Change to the underlying business model • Adaptation of the SBR to 1) and 2) • Challenges to content from political strong users • New supra-national requirements • In-house requirements for improved productivity
Challenge 1: Change to a key source • Cause: • e-Income from CCTA register replaces old source • Obligatory monthly employment data at LKAU level • Effect: • Re-design of process and IT system (1 man-year) • Improvements to timeliness/frequency, relevance and accuracy • Increased usage of SBR • Conclusion: • Pro-active communication at an early stage is key • Data definitions must comply with statistical needs • The CCTA must have self-interest in data quality • Follow CCTA’s project all the way to implementation
Challenge 2: Change to the business model • Cause: • “Web-reg” due to new administrative usage of CABR • Cost reductions in the CABR • Change in the underlying perception re BRs • Effect: • LLUs were no longer followed over time – fundamental change to the business logic • High quality potential, but also high risks. We will see … • So far, it has meant more work for SD • Conclusion: • Keep statistical concepts and needs on the agenda – try to give as much as possible in return • Exploit the advantages and avoid the disadvantages
Challenge 3: Adaptation of the SBR • Cause: • Necessary response to challenge 1 and 2 • Effect: • Functionality re LKAUs had to be built-up in SBR instead • Less tight relation with CABR – more freedom … • Work processes changed from administrative to statistical units • Extremely costly compared to available resources • Conclusion: • Keep it (more) simple – it is very hard to get resources to change very complex systems that only benefits SD • I.e. we need to be more realistic and modest when we define requirements
Challenge 4: Strong political pressure on ABR • Cause: • Pressure to re-use data in order to reduce burden • Digitalisation and productivity of the public sector • Data must fulfil more purposes – also from strong players • Effect: • Data will have direct effects on data subjects • The relative weight of statistical needs will diminish • New incentives and sources of errors are introduced • Net quality effects are difficult to assess • Conclusion: • Monitoring of new initiatives • Proactive communication and advice to admin. users • The overall system must remain sustainable
Challenge 5: New supra-national requirements • Cause: • New EU Regulation with additional requirements (EGs) • Data needs are not covered by the CABR • No other administrative source (share holder register) • Effect: • We must rely on commercial data • Data on EGs and MNEs are already in high demand • Conclusion: • Ensure that new supra-national requirements for the SBR are incorporated in a coming administrative register • Avoid parallel systems becoming permanent
Challenge 6: How to do more with less … • Cause: • Recurring cost reductions in the NSI • Currently, our SBR do not cover all units in agricultural surveys - a separate farm register is maintained • Effect: • Integration of missing agricultural units into the SBR • Actuality and accuracy of data on farms will increase • Coherence will improve • Conclusion: • The main sources/systems must be exploited to maximum extent • Redundant data and systems should be discontinued • Traditions and “cultures” are difficult to change
Key learning points for SD • In order to better fulfil our role and objectives we must: • Manage our partnerships better – we are not strong enough alone • Communicate proactively – we cannot wait for others to contact us • Always be part of the solution – not part of the problem • Manage our risks better – otherwise they seem to manage us • Keep things simple – balance ambitions with abilities
Thank you for your attention! Any questions or comments?