Data Minimisation

Data minimisation is a privacy principle that requires organizations to limit the collection, use, and retention of personal data to what is necessary for a defined purpose. Instead of gathering excessive or unnecessary information, organizations evaluate what data is genuinely required to deliver a product, provide a service, meet legal obligations, or fulfill legitimate business needs. Applying data minimisation reduces unnecessary exposure of personal data and simplifies governance.

In practice, organizations often collect more information than they need due to legacy systems, broad application forms, duplicated databases, or undefined business requirements. Excessive data collection increases storage costs, complicates governance, expands the impact of potential data breaches, and makes compliance more difficult. By implementing data minimisation, organizations reduce privacy risks while improving operational efficiency and data quality.

The Digital Personal Data Protection Act, 2023 incorporates the principle of data minimisation by requiring personal data to be processed only for the specified purpose for which consent has been obtained or where another lawful use applies. Collecting or retaining personal data beyond what is reasonably necessary may increase compliance risks and undermine responsible data governance.

In practice, gaps emerge when:

• Application forms request information that is not required for the stated purpose.
• Personal data continues to be collected because of outdated business processes.
• Multiple teams independently collect the same information from individuals.
• Retention policies allow unnecessary personal data to accumulate over time.
• Organizations cannot justify why certain categories of personal data are collected.

Organizations address these challenges by reviewing data collection practices, defining clear processing purposes, implementing retention controls, and periodically assessing whether personal data remains necessary. Within Privy, capabilities such as data discovery, classification, data mapping, and governance workflows help organizations identify unnecessary personal data collection and strengthen privacy governance.