The term „reliability“ refers to processes that guarantee that personal data is gathered legally, stored in a secure manner and is never shared or used in violation of rights of a person. It encompasses everything from making sure that data collection tools comply with industry standards to the education of data collectors, as well as creating clear guidelines for managing data.

It is important to differentiate between data reliability (such as whether the exact result could be obtained by repeating the measurement) and data validity (such as whether it accurately measures what it was intended to measure). While data reliability is focused on consistency (such as whether the same result would be obtained by repeating the measurement) while data validity is more concerned with the accuracy of the data (like whether it accurately measures what it is supposed to measure).

Unreliable data can have detrimental consequences. If a company is relying on unreliable data to make decisions, it could end up wasting money, or investing in unprofitable initiatives. It could also undermine trust among customers, employees, and partners and cause a lack of accountability. In some instances, the use of unreliable data can even have legal and statutory consequences.

There are numerous ways to improve the reliability of data. Some of the most effective strategies are adopting standard procedures, educating data collectors and providing reliable tools. It’s also crucial to establish clear retention policies for data and create feedback loops that allow users to report errors. It’s also essential to ensure integrity of data by ensuring that all systems are properly backed up and recovery processes work as planned.

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