Published on: September 30, 2025 at 4:37 AM

How to Conduct a Data Protection Impact Assessment (DPIA)

A Data Protection Impact Assessment (DPIA) is not just a compliance formality — it is a structured, proactive process for identifying, evaluating, and addressing potential privacy risks in projects or data processing activities. It is an essential element of the “privacy by design and by default” principle under the General Data Protection Regulation (GDPR). Under GDPR Article 35, organizations must perform a DPIA whenever a planned data processing activity could pose a high risk to individuals’ rights and freedoms.

This requirement applies across industries and organization sizes, from startups developing innovative apps to large corporations deploying new data analytics tools. Failing to conduct a DPIA where it is required can result in significant administrative fines — up to €10 million or 2% of annual global turnover — as well as reputational damage and loss of customer trust. Even if not legally mandated, many organizations choose to conduct a DPIA voluntarily because it improves transparency, strengthens security, and demonstrates accountability to regulators and clients.

This guide explains the full DPIA process step-by-step, supplemented with practical examples, common mistakes to avoid, and expert tips. By the end, you will understand not only how to conduct a DPIA in compliance with GDPR, but also how to make it a strategic tool for protecting personal data and building trust.

Step 1: Determine If a DPIA Is Required

The first step is to determine whether your planned processing meets GDPR’s high-risk threshold. Article 35 specifies that a DPIA is mandatory when the type of processing — particularly when using new technologies — is likely to result in a high risk to the rights and freedoms of individuals. The European Data Protection Board (EDPB) has issued guidelines outlining criteria that indicate when a DPIA is required.

• Introducing new or innovative technologies such as facial recognition or AI-based decision-making
• Processing large-scale sensitive data (e.g., health, biometric, racial, or political data)
• Monitoring publicly accessible areas or individuals' online behavior systematically
• Processing personal data to make automated decisions that produce legal or comparably significant impacts on individuals.
• Processing children’s personal data, particularly in online services

Example: A retail company plans to implement AI-driven CCTV with facial recognition in all stores. This involves systematic monitoring of public spaces and the use of biometric data — both clear triggers for a DPIA under GDPR.

Tip: If unsure, err on the side of caution. Even if a project does not strictly meet the criteria, a voluntary DPIA can help identify potential risks early and serve as evidence of due diligence in the event of a regulatory investigation.

Step 2: Describe the Processing Activity

Once you have established that a DPIA is needed, document the planned processing in detail. This section should be comprehensive enough that a third party, such as a regulator, could understand the scope and purpose without needing additional clarification.

• Describe the nature of the processing (collection, storage, transfer, deletion)
• List the types of personal data involved
• Identify the categories of data subjects (e.g., customers, employees, children)
• Specify the purpose(s) of processing and the lawful basis under GDPR
• Determine the individuals, organizations, or third parties who will be granted access to the data.
• Outline data storage locations and retention periods

Example: An online health platform plans to collect patients’ medical histories, prescriptions, and contact details to provide telemedicine services. The data will be stored in encrypted databases in the EU and shared with partner pharmacies for prescription fulfillment.

Clearly documenting these details not only fulfills a GDPR requirement but also sets the stage for identifying potential risks in later steps.

Step 3: Assess Necessity and Proportionality

This step ensures that the planned data processing is both essential for the stated purpose and proportionate in scope. GDPR emphasizes data minimization — only collect and process what is strictly necessary.

Ask yourself:

• Is each data element you collect essential for the purpose?
• Assess whether it is possible to accomplish the intended purpose while collecting and processing a smaller amount of personal data?
• Are there alternative methods that would be less intrusive?

Example: If you are creating a customer loyalty program, do you truly need customers’ dates of birth, or would just an email address suffice? Collecting unnecessary data increases risk without adding real business value.

Tip: Be prepared to justify your data choices to regulators. In GDPR compliance, proportionality holds equal importance to necessity.

Step 4: Identify and Assess Risks

At this stage, you evaluate possible risks to the rights and freedoms of data subjects, taking into account potential threats to the confidentiality, integrity, and availability of the data.

Common risks include:

• Unauthorized access or hacking
• Data leakage or accidental disclosure
• Misuse of data by authorized users
• Errors in automated decision-making that unfairly affect individuals

Example: A recruitment platform that uses automated CV screening may inadvertently discriminate against certain groups if its algorithm is biased — a high-risk scenario affecting individuals’ rights.

Evaluate both the likelihood and impact severity of each identified risk. Risks that are both highly likely and severe require more robust and immediate mitigation measures.

Step 5: Define Risk Mitigation Measures

Once risks are identified, plan and document specific measures to address them. These can be technical (encryption, access controls) or organizational (training, policy enforcement).

• Encryption and pseudonymization of personal data
• Strict role-based access control
• Regular penetration testing and vulnerability scans
• Staff training on data protection policies

Example: In the recruitment platform scenario, you could mitigate bias by conducting regular audits of the algorithm, retraining models with diverse datasets, and including human oversight in decision-making.

Tip: Record not only the measures you implement but also the reasoning behind them. This helps demonstrate accountability.

Step 6: Consult with Key Stakeholders

GDPR encourages — and in some cases requires — consultation with stakeholders, particularly the Data Protection Officer (DPO). Involving experts from IT, legal, compliance, and business units ensures a well-rounded assessment.

• Internal stakeholders: DPO, IT security team, compliance officers
• External stakeholders: Data processors, third-party vendors, affected user groups

Example: A school implementing biometric attendance must consult with parents, teachers, and the local education authority to ensure the system is acceptable and compliant.

Stakeholder consultation increases transparency, builds trust, and can reveal overlooked risks or better mitigation options.

Step 7: Document and Review the DPIA

The DPIA process should be documented thoroughly. Include the processing description, risk assessment, mitigation measures, and consultation outcomes. This document should be stored securely and be available for regulatory review if requested.

A DPIA is not a one-time exercise. It should be reviewed and updated when:

• There are significant changes to the processing activity
• New technologies are introduced
• Risks evolve due to external factors

Example: If your recruitment platform later adds video interview analysis powered by AI, you must update your DPIA to address new risks.

Common DPIA Mistakes to Avoid

Organizations often fall into these traps when conducting a DPIA:

• Starting the DPIA too late in the project lifecycle
• Focusing only on technical security and ignoring human factors
• Failing to involve all relevant stakeholders
• Not updating the DPIA when changes occur

When a DPIA Is Not Required

While DPIAs are crucial for high-risk processing, they are not necessary for every data activity. Low-risk, routine processing such as basic payroll for employees or managing a contact list for internal use typically does not require a DPIA. However, organizations should still apply privacy by design principles and maintain documentation to justify their decision.

Conclusion

Conducting a Data Protection Impact Assessment is both a legal requirement under GDPR and a best practice for managing privacy risks. By following a structured, step-by-step approach — from determining necessity to documenting outcomes — organizations can protect individuals’ rights, comply with regulatory obligations, and build stronger trust with stakeholders.

Treating DPIAs as a living, evolving process ensures that privacy considerations keep pace with technological changes and shifting regulatory landscapes. In a world where data breaches and privacy concerns are front-page news, a well-executed DPIA is one of the most powerful tools an organization has to safeguard its reputation and its customers.