1. Adaptation of the SBR to changing external conditions Søren Schiønning Andersen, Statistics Denmark (ssa@dst.dk)

2. 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

3. 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

4. Our point of departure re registers

5. Basic data model for our SBR

6. Main sources for the SBR

7. Six recent challenges to our SBR 1)Change to a key administrative source 2)Change to the underlying business model 3)Adaptation of the SBR to 1) and 2) 4)Challenges to content from political strong users 5)New supra-national requirements 6)In-house requirements for improved productivity

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. Pros and cons … summing up Benefits / advantagesCosts / disadvantages  High coverage (depending on requirements for legal registration)  High quality (if data are validated by the administrative body and updates are well coordinated)  Reduces costs  Reduces administrative burden on business  Supports frequent statistics (if updated on a current basis)  Potentially more timely data (depending on technical set-up and administrative processes)  Administrative definitions can deviate from statistical needs and definitions  Problems regarding match and consistency  Use of different classifications (and different use of the same classifications)  Limited possibilities for collecting supplementary data (because of burden considerations and division of responsibility/competence)  Reluctance among enterprises regarding data exchange (necessitates assurance of confidentiality and “documentation” of positive cost/ benefit ratio)  Dependency on providers  Vulnerable to political and/or administrative changes  Potentially less timely data

15. Key differences between SBRs and ABRs AspectSBRABR PurposeSupports production and dissemination of aggregate statistics Supports binding legal or admini- strative decisions about individuals ContentFocus on economic phenomena – at institutional and productive level Complex approach to units Focus on legality and responsibility of individual operations (More) simple approach to units ConsequencesNeutral - no direct consequencesDefines rights and obligations – direct consequences Relation to policies IndirectDirect Political weight“Light” – intangible benefits The SBR is a “bi-product” “Heavy” – tangible implications The ABR is the “main” product Time perspectiveBasis for coherence and compara- bility over time – complex approach Basis for decisions with effect from date of registration – simple approach Quality philosophy Multi-dimensional approach Data are accurate when equal to a real value – which is often unknown “Sufficient quality“ is unclear More simple approach Data are accurate when equal to the self-perception of the unit “Sufficient quality“ is (more) clear

16. 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

17. Thank you for your attention! Any questions or comments?