Data protection reliability refers to processes that ensure that personal data is collected legally and stored securely, never shared with others or used in violation of a person’s rights. It encapsulates everything from ensuring that data collection tools adhere to industry standards, educating data collectors and establishing clear guidelines for data management.
It is crucial to distinguish between the reliability of data (such as whether the same outcome could be obtained when the measurement were repeated) and data validity (such as whether it accurately measures what it is supposed to measure). While data reliability is focused on consistency (such as whether the exact result could be achieved in the event of a repeat measurement) However, data validity is more concerned with the accuracy of the data (like whether it accurately measures what it is intended to measure).
Unreliable data may have adverse consequences. For instance, if a company relies on data that is not reliable for making decisions or for deciding on its strategy, it could end up wasting resources or investing in unprofitable projects. It could also reduce trust between employees, customers as well as partners and erode accountability. In some cases, the use of unreliable data could lead to legal and regulatory consequences.
Reliable data collection is a complicated task but there are many methods to achieve this. Adopting standard methods, educating the data collectors, and providing reliable tools are some of the most effective methods. It is also essential to establish clear policies for data retention and establish feedback loops to allow users to report errors. It’s also essential to ensure data integrity by ensuring all systems are properly backed up and and recover processes function as they should.
