Innovations in Data Collection and Management February 2009 Geoff Bascand

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

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?

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

Load hotspots by time taken Hours takenLargeMediumSmall 15 minutes minutes One hour Two hours Three hours Four hours Five hours Six hours Seven hours Eight hours5941 Nine hours hours hours hours62 25 hours hours43

Number of businesses surveyed and respondent load

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?

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

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?

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?

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?

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

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