3 Data gathering and processing
3.6 Quality management

Quality is an essential element at all levels of processing. Statistics Canada’s reputation as the best statistical agency in the world is based on the quality of its data. To ensure the quality of a product or service in our survey development activities, both quality assurance and quality control methods are employed.

Quality assurance

Quality assurance refers to all planned activities necessary in providing confidence that a product or service will satisfy its purpose and the users’ needs. In the context of survey conducting activities, this can take place at any of the major stages of survey development: planning, design, implementation, processing, evaluation and dissemination.

Examples of planned activities include

• improving a survey frame,
• changing the sample design,
• modifying the data collection process,
• improving follow-up routines,
• changing the processing procedures,
• revising the design of the questionnaire.

Quality assurance attempts to move quality upstream by anticipating problems before they occur and aims at ensuring quality via the use of prevention and control techniques.

Quality control

Quality control is a regulatory procedure through which we

• measure quality;
• compare quality with pre-set standards, and
• react to the differences between measured values and established standards.

Some examples of this include controlling the quality of the coding operation, the quality of the survey interviewing, and the quality of the data capture.

The objective of quality control is to achieve a given quality level with minimum cost. Some assurance and control functions are often performed within the survey unit itself, especially in connection with the tasks of data coding, capture and editing. Several of these procedures are automated, some partially automated and others employ purely manual methods.

Differences between quality assurance and quality control