Course 2: Quality Assurance
At the 41st session of the UN Statistical Commission in February 2010 the first substantive item on the agenda was a paper by Statistics Canada that advocated the development and use of a National Quality Assurance Framework (NQAF) by national statistical offices (NSOs) and that outlined the possible structure and contents of such a framework The paper was very well received; 19 NSOs provided comments; and it was agreed that there would be further development of a generic NQAF template.
Many NSOs are involved in a comprehensive range of quality initiatives and activities but without an over-arching framework to give them context or explain their relationships to the various quality tools. A NQAF is such a framework, providing a single place to record or reference the full range of quality concepts, policies and practices. It provides a systematic mechanism for ongoing identification and resolution of quality problems, maximising the interaction between staff across the NSO; it gives greater transparency to the processes by which quality is assured and reinforces the image of the NSO as a credible provider of good quality statistics; it provides a basis for creating and maintaining a quality culture within the NSO, it is a valuable source of reference material for training, and it is a mechanism for exchanging ideas on quality management with other producers of statistics within the national statistical system, and with other NSOs and international statistical organizations.
The aim of this course is to describe the elements of a quality assurance framework, and, through examples, to illustrate how such a framework can be constructed and implemented. The first module of the course covers the development of general quality concepts and instruments. It outlines existing quality policies, models, objectives and procedures; it explains the role of a quality assurance framework and where it fits in the quality toolkit, and it provides a standard quality terminology.
The second module of the course deals with the development of quality assurance procedures that need to be covered by the framework, from the identification of data needs and initiation of surveys, through survey design, data collection, processing and dissemination, to evaluation. It covers all aspects of process and output data quality, including user, provider and stakeholder relationships, statistical infrastructure, coordination of the national statistical system, and metadata.
The third module concerns the development of quality assessment mechanisms, covering the construction and collection of quality indicators, setting and monitoring quality targets, and defining and introducing a comprehensive quality assessment program including self-assessment and peer review.
The fourth module covers the development of related, but less statistical aspects of quality and performance management, including planning, promoting efficiency, sharing good practices, change and risk management, determining recruitment and training needs, developing and conducting training courses, maintaining a continuous improvement program and quality culture, and determining appropriate quality and performance trade-offs and reengineering initiatives.