Abstract copyright UK Data Service and data collection copyright owner.
The Public Sector Management Practices Survey (PSMPS), commissioned by HM Treasury as part of a Public Services Productivity Review, was based on the Management and Expectations Survey (MES). It aimed to collect intelligence on the use of structured management practices, technology use, administrative burdens, and barriers to improving organisational practices across publicly funded services.The dataset is in wide-format, where each row references a unique organisation and each column a characteristic or data-point associated with that organisation. Each organisation is classified to a part of the public sector, as well as region, employment size and SIC 2007 code. Survey answers are categorical data-points, stored numerically with categorical mappers provided, to allow numerical values to be converted to strings as required.Management practice scores are included for each level of aggregation: scoring question, section and total. Rounded designed post a-weights are included, and can be used to compile weighted survey results. This pilot survey was sent to ~ 14,500 legally defined public sector organisations. This meant organisations commonly considered as public-sector, such as General Practitioners were excluded.Outside the education and local-health sector, organisations were censused. Local healthcare units (hospitals, clinics etc) where threshold sampled based on employment. Educational organisations (schools) were randomly sampled, but also included a census component based on strata-specific features (size).As this is the first version of the survey, no variable was used to adjust the random sample component by variance of the target variable (management practice score).A total of 1,943 organisations responded to the voluntary survey, a response rate of 13.4%.
Main Topics:
The main topics of the Public Sector Management Practices Survey were:Organisational characteristicsManagement practicesImprovement and innovationAdministrationStaff retentionArtificial Intelligence and technologyEmployment relationsHealth sectorEducation
One-stage stratified or systematic random sample
Self-administered questionnaire: Web-based (CAWI)
