As previously mentioned, there is a broad range of severity of data integrity issues.
These issues may be intentional or unintentional mistakes.
Intentional
Intentional issues are a result of clear falsification, alteration or manipulation.
Unintentional
Unintentional mistakes are usually caused by vulnerabilities in systems or processes, or mix-ups.
All of these issues can, and usually will, result in data integrity problems.
Unintentional mistakes, such as errors, may add up and result in data accuracy problems, such as samples being incorrectly labeled or product mix-ups.
Challenging for the Culture
Errors like these are challenging for the culture, as if not addressed, they will often lead to a culture where more severe problems like falsification or selectively choosing passing results is common.
Companies must take steps to prevent both intentional and unintentional data integrity issues from occurring.
These problems should be addressed immediately, and with the proper level of oversight based on severity to prevent these types of issues from spreading or occurring again.