1 1 Indicators for Managing and Improving the Data Collection Process Sindre Børke and Jonas Dahl, Division for Data Collection Methods, Statistics Norway

2 Looking around Eurostat focus on quality issues through several years Statistics Norway –Quality Issues at Statistics Norway –Systematic Quality Work in official Statistics – Theory and Practice –FOSS; A Standardisation Programme  Development of standardised working prosesses, methods and systems  A system for systematic quality measurements and control  Organisation and human resource development supporting this

3 Defining a Project Information for Different Levels of Management –Continuous Quality Improvement Part of the Statistical Value Chain Questionnaire-based Data Collection, and Editing on Micro Level Limited Number of Indicators

4 Indicators ”Specific and measurable elements of statistical practice” Defined by parameters Representative for the component it indicates Easy to interpret (Easy to collect data)

5 Indicators definitions

6 Groups of Indicators Illuminating stages in the value chain –choice of instrument(s) and designing questionnaires –respondent “behaviour” (incl use of support-telephone and ) –progress in data collection (effect from reminders etc) –non-response –the merging of data in multi-mode design surveys –controls and corrections

7 Sick leave questionnaire – respondents’ telephone calls

8 Groups of Questionnaires Not all indicators are relevant on all questionnaires Use of indicators means comparing Clustering of questionnaires to create meaningful comparisons (benchmarking)  Year, Quarter or Month  Business or Huseholds/Persons  Interview/selfadministration  ….

9 Response rates – development over time

10 Recurrent surveys Comparisons/development over time –Expected results of changes in questionnaire or process Stability in processes

11 Hotel statistics questionnaire – Electronic Data Delivery

12 Summing up No standards set, but observing level in each indicator Following recurrent surveys over time, identifying changes Benchmarking comparable surveys

13 Experiences so far Split up is necessary to establish relevance –Small steps on the value chain –Groups of comparable questionnaires Criterias for clustering are not established Some interesting indicators will be difficult (expensive) to establish Project challenge to keep focus on definitions, leaving the interpretation and action to others

14 The near future in the project Reformulating targets and ambitions Some more results in demo-version Defining indicators Clusering questionnaires Data collection design for defined parameters (implementing project results)