Census Processing

1. Census Processing Baku Training Module

2. Overview • Discuss: • Processing Strategies • Processing operations • Quality Assurance for processing • Technology Issues for processing • Questions

3. Census Processing • Strategic directions need to be established early in the census cycle. • Single most important decision is deciding upon the processing system to be used and the technologies that will be adopted. • These decision needs to be made early enough to enable sufficient time for testing and implementation.

4. Data Processing Cycle

5. Data Processing Cycle • Receipt and Registration • as enumeration area materials arrive, they are checked for completeness and "marked in" • close coordination with Field processes • Preliminary Checking • forms are groomed for later processes, e.g. transcribed if not suitable for later processes • Coding and Data Capture • information is captured off the forms and converted into the classification

6. Data Processing Cycle • Balancing • computer records are checked against the forms to ensure a record has been created for each person and dwelling enumerated • Validation • checks the data to ensure it meets minimum agreed standards • Quality Assurance and Editing • Editing used to make responses consistent with the form/sequence rules/classifications • Imputation used to correct non-response

7. Controlling the workflow • monitoring and controlling work flows needs close attention • Each activity depends on the quality and quantity of the output from previous activities. • Critical that each activity is meeting production targets to ensure that the following activity has sufficient work. • Delays in one activity can lead to costly lost production in the following activities. • Changes in procedures to raise production will have to be carefully considered to ensure that the quality of the data is not adversely affected.

8. Management Information Systems • An essential tool for managers at a processing centre is a Management Information System • The general requirements of a MIS are as follows : • to allow access to information to all managers • to ensure all information is timely and as detailed as possible • to forecast and report on outcomes for future activity within the processing centre • ensure information acquired in one Census, can be utilized for planning in future Censuses

9. Management Information Systems • What to collect : • production rates • flow control • staffing • quality assurance • automatic edits • What to report : • production • automatic edits • quality assurance • feedback to individuals

10. Quality Assurance • Quality of Census data is defined as multi-dimensional, involving elements of : • data accuracy • budget • timeliness • relevance

11. Quality Assurance • Quality Management Framework • Processing of census data is complex - each process relies on the quality of the preceding process. • To assist in obtaining the highest possible data quality a framework incorporating the following components can be established at a processing centre: • quality management system; • quality assurance points for each process; • continuous quality improvement processes; • validation of data.

12. Continuous Quality Improvement • Continuous Quality Improvement (CQI) is a core component of the Total Quality Management philosophy. • CQI aims to continue to improve the quality of the output of a project throughout the life of that project. • A continuous quality improvement approach can be implemented in the following ways : • using teams of processing staff to identify and resolve quality problems; • using quantitative measures of quality, based on discrepancies in the output of the process; and • giving priority to identifying and addressing the root causes of these discrepancies

13. Measuring quality • Quality Assurance Circle (or Continuous Quality Improvement) Measure Quality Implement corrective action Identify most important quality problem Identify root cause

14. Validation • The purpose of validating census data is to identify system problems and ensure data quality for final output. • Final check to ensure that the data produced by the processing system meets the specifications of the editing program and output requirements. • Validating the data before it leaves the processing centre ensures that errors that are significant and considered important can be corrected in the final file • Validating as you process ensures the issues found can be fed into improving the process as you go.

15. Technology Issues • The successful introduction of technology into the processing phase will have a large impact on the overall success of the census. • The nature of census processing (ie the capture and manipulation of large amounts of data) is ideally suited to computerised technology. • Use of technology like imaging and Intelligent Character Recognition (ICR) offers great potential and associated benefits for census processing. • BUT be aware of the lead times and technology infrastructure required for successful implementation of ICR.

16. Technology Options • Data- capture methods • key entry • optical mark recognition • digital imaging/intelligent character recognition • electronic lodgment of forms (eg; Internet) • Coding • clerical/computer assisted • automatic coding

17. Technology Issues • Data Management - issues to consider • networks and infrastructure • data storage • data backups • data security

18. Questions?

19. Working Group Exercise • Working in groups, answer the following: • What issues can reduce the quality of the information processed? • What can be put in place to reduce the impact of these issues?