3. Define Accuracy

A Principle based approach

‘Principle Based’ Implementation of the GDPR starts with defining an organization-wide privacy protection policy, wherein all PLASTICFAD principles are addressed in combination with all stakeholder categories.

The principles in Article 5 are reflected in a number of important articles of the GDPR, such as Articles 6 to 9, 12 to 22, 25, 30 and 32.

Many organizations which lack an organization-wide privacy protection policy, will likely implement the GDPR ‘rule based’ (= strictly based on the articles of the GDPR) on the departmental level.

The risk of this approach is that each department determines its own interpretation of how an article should be explained for its business operations. Consequently, this approach can lead to differences in interpretation and inconsistencies, as a result of which the costs of implementation can not be adequately controlled.

These problems can be avoided by clearly defining the principles at the strategic level on which the implementation of the underlying articles of the GDPR will be based.

The principles ‘Purpose Limitation’ and ‘Lawfulness’ were explained in my previous blogs and today we’ll have a look at the principle ‘Accuracy’.

Accuracy

Accuracy means that personal data elements which are incorrect in view of the purposes for which they are processed must be deleted or rectified without delay.

The data must be as accurate, complete and up-to-date as is necessary to fulfill the specified goals.

Approach

The controller should therefore:

  • take all reasonable steps to ensure that personal data are correct;
  • ensuring that the source of personal data is clear;
  • be aware of which infringements may occur on the accuracy of personal data;
  • ensuring that the collected personal data remain up-to-date and complete and, if necessary, corrected or supplemented.

The accuracy of personal data is closely related to the purpose for which they were collected and processed.

Poor quality personal data can have a significant negative impact on the efficiency of an organization, while high-quality data is often crucial to a company’s success.

Some of the main ways in which the accuracy of personal data can be identified and improved are shown here:

Accurate data sources

The controller must identify the correct data sources, both internally and externally, to determine and improve the quality of incoming data. Incorrect data may be the result of the migration of data from one database to another, the presence of incorrect values ​​or even time-related data changes. It is important to determine the cause of incorrect data.

Set data quality targets

It is important that companies set realistic goals to improve data quality. Top management must understand the basic problems that affect the accuracy of their data and set realistic goals. The personal data must be examined on the basis of:

  • efficient data capture,
  • data entry and
  • effective coding.

Avoid overload

A manager must ensure that the people involved in the data entry process are not pressured to deliver expected results from the beginning. If data entry specialists are overloaded with work, this can lead to errors when entering data.

View the data

Review is an efficient way to check the accuracy of the data. The controller must include an efficient way to check and verify the data entered.

It is always good to hire a team of quality assurance professionals who can assess the data and help to largely reduce data errors.

Automate error reports

Using advanced software is always a plus. Generating automated error messages is a common practice among leading companies today.

Determining accuracy standards

The controller should adopt very robust quality standards for data entry, such as:

  • matching,
  • geo-coding,
  • data monitoring,
  • data profiling,
  • linking.

This ensures that the data entered meets predefined data standards that in turn help improve the data quality.

Create a good working environment

Having a good and healthy working environment helps employees to make fewer mistakes and therefore has a direct influence on the accuracy of the data. The controller is responsible for providing data entry professionals with a healthy working environment that helps maintain their focus.

Next time, we’ll focus on the principle of Storage Limitation. Please follow my posts to stay informed. Feedback and comments are appreciated!

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