A tool for managing the quality of statistical processes: Quality Gates

1. A tool for managing the quality of statistical processes: Quality Gates Paul Schubert Head, Statistical Services Branch November 2011 National Statistical Service Seminar Series

2. Overview • Motivation • What are Quality Gates • Attributes of Quality Gates • Six Components of Quality Gates • Outcomes of Quality Gates • Further information

3. Credibility and Integrity

4. Statistical Risk • The chance or likelihood that something could go wrong in the statistical process that impacts on the quality or integrity of the statistical outputs produced.

5. The statistical cycle

6. Efficiencies • Budgets have decreased • Demand for statistics have increased • Timeliness • Getting it ‘right’

7. What are quality gates? "checkpoints or decision points at various strategic places in a statistical process at which the quality of the process (and data) at or up to that point is explicitly assessed"

8. Attributes of Quality Gates Planned in advance of issues occurring Knowledge Management (e.g. create a store of corporate knowledge) Constantly reviewed and revised

9. Attributes of Quality Gates Collaborative – provide a model of accountability and responsibility for collection processes Communicate openly the progress/issues associated with collections, throughout the cycle Proactively managing risk – can save time and $ in the long run

10. Six components of quality gates Placement Quality measures Roles Tolerance Actions Evaluation

11. 1. Placement Assigning priorities Related to risk profile of collection cycle Want to detect errors 'upstream‘ What can go wrong? When can this problem occur? What impact can it have?

12. Placement of quality gates Handover Within

13. Areas of risk changes to processes, systems, methodologies data transformations overlap / coordination / integration with other areas knowledge management

14. 2. Quality measures Choose good indicators of potential problems Prioritise! Definitions May need to drill down Time series useful How would we know if this problem occurred?

15. 3. Roles Owner area Operational person / Gate Keeper Stakeholders Gate definition Gate assessment / sign-off Who is responsible? Who will this affect?

16. 4. Tolerance Driven by user requirements Consider size of natural variation, sampling errors, level of detail, importance of outputs Need to form expectations Historical data may help Predetermined! What is an acceptable level of quality?

17. 5. Actions reflect extent of the problem reflect consequences "traffic lights" concept What will we do (if there is a problem)? Who needs to be informed?

18. 6. Evaluation evaluation of processes evaluation of quality gates What has this information told us about our quality? How can we improve in the future?

19. Example of a Quality Gate • Information paper 1540.0 Quality Gate example

20. Outcomes from Quality Gates Quality, Business processes and responsibilities well-defined and known by staff Statistical risk explicitly identified & assessed Explicit sign-off occurs at Quality Gates

21. Outcomes from Quality Gates Quality Measures clearly defined and understood Errors identified earlier (and fixed) Improved analysis of data throughout the process in relation to fitness for purpose of outputs

22. Outcomes from Quality Gates • Efficiencies long term • Errors identified earlier • Processes evaluated in terms of quality management (improvements identified) • Possible time reductions in when ‘things’ are done • Cost savings due to changes in ‘how’ things are done • Reduction in ‘wasted’ resources because of not identifying errors until too late

23. Outcomes from Quality Gates • Continuous improvement • Quality and issues identified during process can be used to help declare the quality of the statistical outputs

24. Further information • Quality Management of Statistical Processes Using Quality Gates, Dec 2010, (cat.no. 1540.0) on the ABS website. • http://www.abs.gov.au/ausstats/abs@.nsf/mf/1540.0 • Quality Page on ABS website – December 22nd, 2011