Identifying bad data can be effectively managed by:

Identifying bad data can be effectively managed by allowing users to report issues. This approach leverages the frontline experience of users who interact with the data directly. By providing a mechanism for users to flag inconsistencies or inaccuracies, organizations can tap into valuable insight that might not be captured through standard auditing or data management processes. This can lead to quicker identification of data issues and continuous improvement in data quality.

Allowing users to report issues not only identifies problems but can also encourage a culture of data stewardship within the organization, where users feel responsible for maintaining data integrity. This proactive approach helps organizations stay responsive to data quality issues rather than relying solely on periodic reviews or retrospective audits.

In contrast, while keeping a detailed record of data entries contributes to traceability, it does not actively engage users in the process of identifying errors. Auditing data only once a year would likely result in the missed opportunity to correct errors in a timely manner and may allow bad data to persist for long periods. Regularly training staff on data entry is beneficial for improving the quality of data at the point of entry; however, this does not replace the need for a responsive system for reporting problems as they arise.