PIA vs. DPIA: Understanding the Differences and When to Conduct Each
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PIA vs. DPIA: Understanding the Differences and When to Conduct Each

As a Data Protection Officer (DPO) for several small businesses, ensuring compliance with privacy and data protection laws is a critical responsibility. Two key tools used in privacy risk management are the Privacy Impact Assessment (PIA) and the Data Protection Impact Assessment (DPIA). While both assessments help organizations identify, assess, and mitigate risks associated with processing of personal or personally-identifiable information (PI/PII), they serve different purposes and apply under different circumstances. Understanding the relationship between a PIA, a DPIA, and the concept of a privacy risk threshold is essential for ensuring compliance, reducing regulatory risk, and protecting customer trust.

What is a Privacy Impact Assessment (PIA)?

A Privacy Impact Assessment (PIA) is a broad evaluation of how an organization processes personal data and the potential privacy risks involved. PIAs are often voluntary (unless required by internal policies or regulations) and serve as a proactive approach to privacy management.

Key Features of a PIA:

1) Scope

Evaluates the privacy risks associated with any new or existing data processing activities, including websites, software, marketing initiatives, sales platforms, CRM, customer support, HR systems, or more recently online AI services.

2) Focus

General privacy concerns, compliance with privacy principles (lawfulness, transparency, data minimization, etc.), and the potential impact on individuals.

3) Requirement

Not legally mandated in most cases (consult your general counsel or outside privacy counsel), but considered a best practice for organizations committed to privacy.

Often contractually required by customers in B2B relationships where your organization is considered a "Data Processor".

4) Outcome

Identifies whether a higher risk threshold is met, triggering the need for a DPIA.

Getting started with a PIA will require establishing:

  • a data processing inventory (see Annex A below),
  • data flow diagrams (DFDs) showing how the data is collected, stored, processed, shared, transferred across geographies, and eventually destroyed, and
  • a list of potential Risks to the data subjects.

A PIA acts as a screening tool, helping organizations decide whether further risk analysis is required. If a PIA determines that data processing presents "high risks" to individuals' rights and freedoms, a DPIA becomes mandatory under GDPR (Article 35) or other relevant regulations.

What is a Data Protection Impact Assessment (DPIA)?

A Data Protection Impact Assessment (DPIA) is a legal requirement under GDPR and other data protection laws when processing activities pose a high risk to individuals' rights and freedoms. DPIAs are mandatory for high-risk processing activities and go deeper than a PIA by conducting a detailed risk assessment and mitigation planning. Not performing regular DPIAs will almost certainly result in a negative finding and significant penalties if your organization experiences a personal data breach. (NOTE: Having DFDs in place that include critical privacy and security controls is critical to an effective DPIA.)

Key Features of a DPIA:

1) Scope

Focuses on high-risk data processing activities, including automated decision-making, profiling, large-scale processing of sensitive data, and surveillance technologies.

2) Focus

Legal compliance, security risks, risk mitigation measures, and potential harm to data subjects.

3) Requirement

Mandatory under GDPR when a processing activity is likely to result in high risks.

4) Outcome

Identifies risks, proposes mitigation strategies, and determines whether processing should proceed or be modified.


The Role of a "Privacy Risk Threshold" in Determining When a DPIA is Required

A Privacy Risk Threshold is the criteria used in a PIA to evaluate whether a DPIA is necessary. If a PIA determines that data processing meets or exceeds a high-risk threshold, a DPIA must be conducted.

Common Privacy Risk Threshold Indicators:

  • Processing of Special Category Data – Includes sensitive personal data such as health records, biometrics, or criminal history.
  • Automated Decision-Making & Profiling – If decisions significantly impact individuals (e.g., AI-based credit scoring, job applications, or insurance pricing).
  • Large-Scale Data Processing – If processing involves a large volume of personal data, covering many individuals or multiple datasets combined.
  • Surveillance & Tracking – Use of CCTV, facial recognition, employee monitoring, or behavioral tracking.
  • Children's Data Processing – When processing underage individuals’ personal data.
  • Use of Emerging Technologies – AI, IoT, or other high-risk digital innovations.

If any of the above risk factors are present, the organization must conduct a DPIA to ensure compliance and minimize privacy risks.


Bottomline: When to Conduct a PIA vs. a DPIA

PIA vs DPIA
When to Conduct a PIA vs a DPIA


Why Small Businesses Should Care

Many small businesses mistakenly assume that DPIAs only apply to large corporations, but GDPR and other privacy laws apply to all businesses processing personal data. Conducting PIAs helps small businesses avoid unnecessary DPIAs while ensuring they only conduct DPIAs when truly necessary.

By implementing a structured PIA-DPIA process, businesses can:

  • Demonstrate proactive compliance with privacy regulations.
  • Reduce legal and regulatory risks by addressing high-risk processing before regulators step in.
  • Protect customer trust by minimizing privacy risks and ensuring ethical data use.

Conclusion

Understanding the difference between a PIA and a DPIA is essential for CIOs, CISOs, and DPOs managing compliance risks in an era of increasing regulatory scrutiny. A well-structured risk threshold assessment within a PIA ensures that DPIAs are only conducted when truly necessary, balancing compliance obligations with business efficiency. Small businesses that take a proactive, risk-based approach to privacy assessments will be better positioned to navigate evolving data protection laws and maintain customer trust and regulatory compliance.


Annex A - Building a Data Processing Inventory

The key here is to start simply with a list of the PI/PII elements that your organization will either Collect or Process (or both).

Follow that by listing each type of "Processing" that will be performed on each element of PI/PII. This can be as general (e.g., "Used by Customer Service to contact individual customers when necessary.") or as specific (e.g., "Used to uniquely identify the individual when running a background or credit check.") as needed to get started. Starting with general processing activities is a good practice. That can always be followed with a more granular view of each type of processing if/as necessary.

For each type of processing activity in your Inventory, consider describing the following attributes of each individual activity:

Activity

  • Name of the Processing Activity

Purpose

  • Intended Result
  • Data Subject’s intent
  • Data Controller’s Purpose
  • Data Processor’s Purpose
  • Collection Medium
  • Business Criticality

Nature of the Processing

  • Personal Data Collected
  • "Special Categories"
  • Regulatory Requirements
  • What is the Source of the Personal Data?
  • How is Data Collected?
  • How is Data Used?
  • How is Data Stored?
  • Is the Personal Data shared with other parties?
  • What Measures are taken to ensure other parties comply?
  • How is Data Retained and Deleted?

Scope

  • How many Data Subjects are affected by this processing?
  • How "much" Personal Data is collected (per Data Subject)?
  • How often is Personal Data is collected?
  • What geographical area does the processing cover?
  • How are cross-border "Data Transfers" handled?

Context

  • Nature of Company's Relationship with Data Subject?
  • Does the Data Subject have control?
  • Does Purpose/Processing align with Data Subject's Expectations?
  • Is the Processing Activity "novel" in any way?
  • What is the state of Technology in this area?
  • Do the Data Subjects include "Children"?
  • "Any issues of Public Concern w/ this Processing (e.g., Covert Surveillance)?"

Necessity and Proportionality

  • Legal Basis for this Processing?
  • Any other way to achieve the outcome?
  • Does the Company ensure Data Minimization?
  • Does the Company ensure Data Quality?
  • How does the Company support Data Subject Rights?

Risks to the Data Subject(s)

  • Threats
  • Vulnerabilities
  • Likelihood
  • Consequences
  • Impact (Severity)

#privacy #dataprivacy #privacyregulations #privacyrisk #dataprotection #dpo #pia #dpia #ceo #generalcounsel #cio #ciso #boardofdirectors #boardroom

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Richard Sant

I Help CEO's at high growth, future focused companies to gain a competitive edge and grow revenues in excess of £25M by successfully delivering innovative IT, Digital and Data Transformations

5 天前

Thanks Scott, As a Non-Exec of a publicly funded organisation Its so important to take a proactive approach to compliance - thanks for sharing

Mark Dunning

I help CEOs at international professional services companies reduce cybersecurity risk by 50% by building global information security programs and transforming IT teams.

5 天前

Scott Foote Great explanation of the difference between a PIA and DPIA. I particularly like that you called out the value for small businesses. They often don't invest because of resource constraints but it is better to have the planned cost of a DPIA than the unplanned cost of a GDPR fine and all the legal costs that go with that.

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