According to William Deming's kp Rule, which approach is recommended for data review?

The recommended approach according to William Deming's kp Rule emphasizes the importance of conducting inexpensive reviews on all cases. This method ensures thoroughness and comprehensiveness in data governance, allowing for the identification of errors and areas for improvement across the entire dataset. By focusing on all cases, the process becomes proactive rather than reactive, fostering a culture of quality assurance and continuous improvement.

Conducting inexpensive reviews helps maintain high data integrity without incurring significant costs and allows for timely detection of inconsistencies or inaccuracies. This approach ultimately supports the goal of achieving better overall data quality and outcomes. In contrast, limiting reviews to only expensive ones or focusing solely on recent cases could lead to oversight of potential issues in other data segments, hindering the overall effectiveness of data management efforts. Additionally, relying solely on feedback for data review can result in missed opportunities for self-assessment and improvement, as it may ignore systemic issues that are not yet captured in user feedback.