Quality in Official Statistics: Some Critical Issues

1. Quality in Official Statistics: Some Critical Issues Lars Lyberg Statistics Sweden Q, May 6, 2010 Email: lars.lyberg@scb.se

2. Looking Back • Statistical Process Control (30’s and 40’s, Shewhart) • Neyman’s landmark paper 1934 • Fitness for use, fitness for purpose (Juran, Deming) QM science building up, customer recognition • Small errors indicate usefulness (Kendall, Jessen, Palmer, Deming, Stephan, Hansen, Hurwitz, Tepping, Mahalanobis), nonsampling errors recognized 1944-1953. • Decomposition of MSE around 1960 • Data quality (Kish, Zarkovich 1965)

3. Administrative applications of SPC (late 60’s) • Quality frameworks 70’s • CASM movement 80’s • Quality and users 80’s • Business Excellence Models • ISO, TQM, Six Sigma, Kaizen, Lean, PDCA, BPR • Quality assurance and quality control • Standards and Quality Guidelines

4. This Week’s Conference • Quality reporting and metadata • Quality management • Quality indicators, paradata, performance • Frameworks and standards • Errors and users • Design and harmonization • Data collection

5. Back to the Future: What’s Critical? • Standard errors and confidence intervals do not include all error sources • Design, risk assessment and allocation of resources • Specifications, operations and control • Building capacity • Benchmarking, efficient production, processes and paradata

6. Standards and guidelines, best practices, theories • International surveys • Users’ perceptions of quality • Do not leave key processes behind • Global coordination, benchmarking, training, conferences and workshops • The element of continuous improvement