This process is present throughout the model. It is closely linked to Phase 9 (Survey Evaluation), which evaluates individual instances of a statistical business process. The wider quality management process, however, has both a deeper and broader scope. In addition to evaluating iterations of a process, it is also necessary to evaluate separate phases and sub-processes, ideally each time they are applied, but according to an agreed schedule at a minimum. Metadata generated by the different sub-processes are also of interest as an input for process quality management. These evaluations can apply within a specific process or across several processes that use common components.
Quality management also involves the evaluation of groups of statistical business processes, and can therefore identify potential duplication or gaps. All evaluations result in feedback, which should be used to improve the relevant process, phase, or sub-process, creating a quality loop. Quality management can take several forms, including:
Quality management can take several forms, including:
- Seeking and analyzing user feedback;
- Reviewing operations and documenting lessons learned;
- Examining process metadata and other system metrics; and
- Benchmarking or peer-reviewing processes with other organizations.
Evaluation normally takes place within an organization-specific quality framework, and may therefore take different forms and deliver different results within different organizations. There is, however, general agreement among statistical organizations that quality should be defined according to the ISO 9000-2005 standard: “The degree to which a set of inherent characteristics fulfills requirements."
Quality is a multi-faceted, user-driven concept. Dimensions of quality that are considered most important depend on user perspectives, needs, and priorities, which vary between processes and across groups of users. Several statistical organizations have developed lists of quality dimensions, which, for international organizations, are being coordinated under the leadership of the Committee for the Coordination of Statistical Activities (CCSA).
The multiplicity of quality frameworks enhances the importance of evaluation of the benchmarking and peer-review approaches, and while these approaches are unlikely to be feasible for every iteration of every part of every statistical business process, they should be used in a systematic way according to a pre-determined schedule that allows for review of all main parts of the process within a specified time period.