Privacy by Design vs. Data Protection by Design: What’s the Difference?

Data privacy and data protection are two terms that are often used interchangeably, but they refer to different concepts. Privacy by design (PbD) is a proactive approach to protecting personal information, while data protection by design (DPbD) focuses on the technical and organizational measures needed to protect data from unauthorized access or misuse.

At its core, PbD is about building privacy into the development of products and services from the very beginning. It requires organizations to consider how their activities will affect individuals’ rights and freedoms when it comes to their personal information.

This includes taking steps such as conducting risk assessments, implementing appropriate security measures, providing clear notices about how personal information will be collected and used, and offering meaningful choices for users to manage how their data is collected.

On the other hand, DPbD involves implementing and enforcing technical safeguards like encryption technologies or pseudonymization techniques that help ensure that any sensitive data remains secure throughout its lifecycle – from collection through storage and processing all the way up until deletion or destruction.

Organizations must also implement organizational measures like staff training programs, so employees understand what constitutes proper handling of customer data at every stage of its journey within an organization’s systems.

The key difference between PbD and DPbD is that one focuses on preventing harm before it happens while the other focuses on mitigating potential damage after it has occurred. Both approaches should be part of any comprehensive strategy for protecting customers’ personal information. However, PbD should always come first since it helps prevent issues related to privacy violations before they even arise in the first place.

To achieve both PbD and DPbd effectively within your organization you need a robust set of policies outlining how customer data should be handled at each step along its journey within your systems – including who can access it; where and how long it can be stored and what types of security controls are required to prevent data loss.

Additionally, strong enforcement mechanisms will ensure that these policies are followed consistently across all the departments and teams that manage customer data. This could include regular audits or spot checks conducted by internal teams or external third parties depending on your specific needs and requirements.

Finally, don't forget about employee training to make sure everyone understands why these policies exist and their obligations to adhere to them when handling or processing sensitive data.

The National Institute of Standards and Technology (NIST) cybersecurity framework, and its companion data privacy framework can help your team self-manage privacy risk through policies, controls and individual privacy measures. Implementing these frameworks can improve your organization’s overall security posture, strengthen data privacy policies, and better position your business for regulatory compliance.

Data discovery and classification underpin core functions across the NIST frameworks — without visibility to the sensitive data your organization uses, stores, and shares it’s impossible to protect it.

‍Check out the Data Protection Solutions Guide for more best practices and solutions comparisons that can help you and your team achieve data privacy and data protection for your business and its unique requirements.