ISO/TS 8000-65:2020 pdf download – Data quality — Part 65: Data quality management: Process measurement questionnaire.
5.2.2 Data quality strategy management The purpose of data quality strategy management is to establish the long-term goals for data quality across the organization, and short-term objectives to achieve those goals. The outcomes of data quality strategy management are as follows and are the basis for the questions about data quality strategy management (see Table 3). — Top management is committed to the improvement of data quality to agreed levels at the organizational level. — A data quality strategy is created, describing the vision, long-term goals, an implementation roadmap and short-term objectives, which are defined in terms of quantitative outcomes. — A framework is created for establishing and reviewing the data quality strategy. — Results are evaluated to determine the performance of the data quality strategy, leading to the strategy being updated as necessary. — The data quality strategy is communicated throughout the organization.
5.2.3 Data quality policy/standards/procedures management The purpose of data quality policy/standards/procedures management is to capture rules that apply to performing the processes data quality control, data quality assurance, data quality improvement, data-related support and resource provision consistently across the organization. The outcomes of data quality policy/standards/procedures management are as follows and are the basis for the questions about data quality policy/standards/procedures management (see Table 4). — Policies are defined in terms of fundamental intentions and rules that guide the organization as to which actions are appropriate and which are inappropriate in performing data quality management. — Standards are defined to support data quality management. NOTE These standards include those covering formats for expressing data requirements, measurement methods, how to sustain data quality when changing supporting technology, and the infrastructure of computer hardware and software systems. — Procedures are defined to specify in detail how the organization performs data quality management. — Policies, standards and procedures are communicated throughout the organization, covering the consistent application to data quality management.
5.2.4 Data quality implementation planning The purpose of data quality implementation planning is to identify the resources and sequencing by which to perform the processes data quality control, data quality assurance, data quality improvement, data-related support and resource provision across the organization. The outcomes of data quality implementation planning are as follows and are the basis for the questions about data quality implementation planning (see Table 5). — A scope and target are defined for data quality in accordance with the data quality objectives. — Implementation plans are established in detail. — Manpower, financial and technology resources are allocated and managed to ensure successful execution of the implementation plans. — Roles, responsibilities and authorities are allocated and controlled to cover all aspects of data quality management. NOTE ISO 8000-150 2) provides detail on roles and responsibilities that contribute to effective and efficient data quality management. — Progress is monitored against implementation plans to achieve improved data quality. — Performance results are evaluated to report to top management on the effectiveness of the implementation plans, with those plans being updated as necessary based on the results.