1. Innovations in Data Collection and Management February 2009 Geoff Bascand

2. Overview Innovations can help increase efficiency, reduce respondent load and improve data quality This session will discuss: –Examples of innovation –Why innovation matters –Challenges in innovation –Opportunities

3. Modernisation of Statistics Production Common vision - reduce time in data collection processing to provide more resource for analysis Key themes: –The results have been mixed –Still a real commitment to standardisation –Less optimistic view on time to achieve standardisation Q) Is there an opportunity for shared learning on modernisation approaches?

4. Proposed Load Limits for businesses Size of businessMaximum number of Stats NZ data collections Maximum time taken (hours) SmallThreeFour MediumFourSix LargeSevenTen Extra LargeNo limit

5. Load hotspots by time taken Hours takenLargeMediumSmall 15 minutes3 59711 53527 807 30 minutes26462463 751 One hour1 8349 24218 851 Two hours3 9196 7172 111 Three hours1 9832 1851 191 Four hours1 0302932 051 Five hours45612790 Six hours2274137 Seven hours134416 Eight hours5941 Nine hours301 10 hours1311 15 hours2534 20 hours62 25 hours31 25+ hours43

6. Number of businesses surveyed and respondent load

7. Respondent Load Need to ensure willing supply of information Common strategies for reducing load: –Demonstrating value of information collected –Reduce load on respondents –Make it easier to respond –Identify and manage areas of unreasonable load Q) Should there be an international Respondent Load standard?

8. Use of administrative data & standard reporting Reduce direct survey activity and/or increase range of statistics Innovations: –register based Censuses –strong relationships with software providers to enable dynamic extraction of data to meet statistical needs Statistical methods can focus on administrative data quality and plugging the gaps

9. Strong and targeted relationships Understand your respondents, and develop customised solutions The Navajo nation example, helped influence: –form design –mode of data collection –the value of promotion via third party partners e.g.. community based organisations Q) Are we rigorous enough when measuring the effectiveness of innovations?

10. CRM technologies Centralised customer management enables: –Creation of targeted relationships –Identification of areas of overlap and load –Improved efficiency Innovations include combining call management infrastructure and multi modal collection Q) Should we investigate developing an integrated CRM for respondents and data users?

11. Web collection Web collection can – reduce load and costs as well as increase data quality Several good examples of web collection Standardisation and integration needed between modes Q) What are the opportunities for web collection beyond Census?

12. Operations Research Use scarce resources wisely Use behavioural psychology and statistical methods to: –Improve user and respondents experiences –Reduce costs in data collection –Data mining techniques –Optimising call times

13. Some Opportunities and a Challenge Opportunities –Expert working group on standardisation of processes and technology? –An international Respondent Load standard? –Integrated CRM for respondents and data users? Challenge –To use rigour when measuring the effectiveness of innovations