Which practice will help address limitations in data?

Having others perform an independent evaluation of the data is a valuable practice for addressing limitations in the data. This approach introduces a level of objectivity and can uncover biases or blind spots that the original data collectors may not be aware of. Independent evaluations can highlight discrepancies, validate findings, and provide fresh insights that enhance the understanding and reliability of the data.

When data is independently evaluated, it can also be assessed for its completeness, accuracy, and relevance. This practice encourages critical thinking and can lead to more robust conclusions than relying solely on the original dataset or analyses.

In contrast, collecting exhaustive and broad data may lead to information overload without effectively addressing quality or relevance. Restricting data to past performance alone can limit the scope of analysis, making it difficult to draw current insights. Additionally, using data from a single source poses risks of bias and limits the variety of perspectives necessary for a comprehensive understanding of the situation. Thus, independent evaluation stands out as a proactive measure to improve data integrity and decision-making outcomes.