Prioritising Statistical Outputs: example from UK

1. Prioritising Statistical Outputs: example from UK Aileen Simkins Deputy Director (Health, Public Service Productivity)

2. Background • UK Statistical System is decentralised • ONS produces many but not all Government Statistics • ONS – Statistical work organised: • 1 Sources Directorate • 3 Analysis Directorates (coming down to 2) • 1 Methodology Directorate • Sources and Analysis Planning Group plans and prioritises ONS statistical work

3. Why prioritise? • ONS funding set 5 years, requirement for efficiency savings • New UK Statistics Authority – overview of work programme • Demand from users for improved statistics in key areas (e.g. migration) • No clear basis for prioritising e.g. social v economic • Ageing or frail systems – make room for spend to save improvements, innovation

4. Prioritising Outputs – An Overview 4 components: • Establish the funding available • Prioritise existing high level outputs • Prioritise proposals for new work • Consultation

5. Prioritising Existing Outputs • “Map” of high level outputs with estimated total costs (across boundaries) • Criteria that could be scored for each output • Agreed “weightings” for each criteria • Directors independently scored each output against the criteria

6. Prioritising Existing Outputs: Criteria 1)Customer Impact a) National Government & Devolved Administrations = 20% b) Other public authorities (incl. regional/local government) = 10% c) EU = 5% d) Media = 5% e) Academia and Researchers =5% f) Businesses & voluntary sector = 5% g) Citizens = 10% 2) Legal Obligation 20% 3) Strategic Fit = 10% 4) Capability = 10%

7. Prioritising New Work • Identified and costed potential projects – 4x£ • Each Director chose a shortlist of projects in their own area • Each Director then considered all shortlisted projects and chose preferred package to fit £ • Directors jointly compared scores and agreed ranking of projects • Sought extra money from key users for some work

8. Consultation Two stage public consultation • Phase 1 (Summer 2007) – seeking views on statistical priorities - 89 responses • Phase 2 (Autumn 2007) – seeking views on proposed package of new work - 37 responses

9. Summary • It wasn’t easy • It was worthwhile • Achieved a good degree of consensus – within ONS and from users - about priorities • But nothing stays still... further reviews of affordable work; emphasis on co-funding • Real need – review spending and delivery of statistics for public use, across all providers