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Pushing forward with ASPIRE

The ASPIRE framework enhances statistical quality reporting by implementing thorough quantitative measures of quality changes in statistical products. Developed by Heather Bergdahl, Paul Biemer, and Dennis Trewin, this system emphasizes accuracy while identifying key error sources. Annual reviews involve self-assessments, quality interviews, and checklist evaluations to ensure objectivity. Despite potential weaknesses like reliance on external evaluators, ASPIRE has led to substantial improvements in quality declarations and practices, guiding organizations toward statistical excellence.

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Pushing forward with ASPIRE

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  1. Pushing forward with ASPIRE ASystem for Product Improvement, Review and Evaluation Heather Bergdahl, Paul Biemer, Dennis Trewin Q2014

  2. Background • Quality ReportingtoMinistryofFinance • Request for quantitative and objectivemeasuresofqualitychanges in statistical products • Externalevaluatorstoensureobjectivity • Focus on Accuracybutotherqualitycomponentspossible • Ten key statistical products • Inspiration for improvementwork

  3. Sourcesof error by product

  4. Quality criteria • Knowledge (of the producers of statistics) of the risks affecting data quality for each error source, • Communication of these risks to the users and suppliers of data and information, • Available expertise to deal with these risks (in areas such as methodology, measurement or IT), • Compliance with appropriate standards and best practices relevant to the given error source, and, • Plans and achievements for mitigating the risks.

  5. Guidelines/ Checklists

  6. The review process • Self assessment and documentation sent toevaluators • Quality interview • discussion of notable changes, • review of quality declarations, • progress made on recommendations, • assignment of preliminary ratings using the checklists, • review of assigned ratings, discussion of results, and recommendations for improvement • Control, feedback, possiblecorrection and finalisingof ratings • Process repeatedannually

  7. Results – Labour Force Survey

  8. Results: Structural Business Statistics

  9. Strengthsof ASPIRE approach • comprehensive covering error sources and criteria that pose risks to product quality • checklists are effective for assigning reliable ratings • ASPIRE identifies improvement areas ranked in terms of priority

  10. Possibleweaknesses • Does not measure the trueaccuracyof a statistical product • Relies on the skills and experienceof external evaluators, and also on the information provided by the productstaff– certainsubjectivity

  11. Concrete Results • Methods developed to explore measurement error • Improved quality in quality declaration information • Increasing activity in the area of planning for studies and improvement projects • Major redesign for Living Conditions Survey with substantial improvements • Higher scores for those who systematically make use of methodological staff • In summary, no quickfixestoimproveAccuracy.

  12. ASPIRE – pointingustowardsexcellence and beyond… £ ½  ¼ ˜

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