Why the data was collected
Archives New Zealand (Archives) is responsible for regulating information management (IM) in the public sector, in accordance with the Public Records Act 2005 (PRA). Our remit covers both central and local government. Monitoring is a key regulatory tool for assuring that public sector information is being well-managed. It is critical for maintaining confidence in the quality and stewardship of information, and for empowering public sector organisations to lift their performance. Regular surveys are one of the core mechanisms Archives uses to collect information for monitoring purposes.
The survey collects quantitative and qualitative data about IM practice to help us to:
- Form a picture of how well public sector organisations are performing as-a-whole against the requirements of the PRA and good practice IM.
- Track improvements in organisations’ performance over time.
- Identify risks, challenges, opportunities and emerging trends affecting IM in organisations, so we can feed this intelligence into responsive regulation.
- Provide public visibility of organisations’ IM performance.
How the data was collected
The annual survey covers all central government organisations, referred to by the PRA as ‘public offices’, except for Ministers of the Crown and school boards of trustees. It also covers local authorities (i.e. councils) but excludes council-controlled organisations.
The 2019/20 survey was sent to 270 public sector organisations, including:
- 192 public offices, which were required to respond by direction to report (s31, PRA).
- 78 local authorities, which were invited to respond.
A questionnaire was delivered via the online survey tool Survey Monkey and was open from 20 July to 7 August 2020. Executive Sponsors from organisations in scope were invited to participate and were asked to coordinate their organisation’s response.
How the data was cleaned-up
The published dataset is a modified version of the full dataset extracted from Survey Monkey. The modifications involved:
- Removal of incomplete and duplicate responses.
- Removal of individual respondents’ names and contact details.
- Numbering of the questions as they appeared in the questionnaire, to facilitate re-use.
- Cleansing of punctuation that was corrupted during export, e.g. macrons.
