Data Privacy Impact Screening Template – Free Word Download

Data Privacy Impact Screening Template – Free Word Download – Copy and Paste Wording Below

Introduction

In the modern digital landscape, data privacy is no longer just a legal checkbox; it is a fundamental component of trust between an organization and its stakeholders. The Data Privacy Impact Screening (DPIS) is a critical project management tool designed to identify risks associated with the processing of personal data at the earliest possible stage of a project. Unlike a full Data Protection Impact Assessment (DPIA), which is a comprehensive and often lengthy legal document, this screening tool acts as a “triage” mechanism. It helps project managers and privacy officers determine if a full DPIA is necessary or if standard privacy controls are sufficient.

This document serves two primary purposes. First, it acts as an inventory mechanism to catalog exactly what data the project will touch, process, store, or delete. Second, it serves as a risk radar, highlighting potential compliance pitfalls related to regulations such as the GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act), and other local data protection laws. By completing this screening early in the project lifecycle (ideally during the initiation or planning phase), you prevent costly re-engineering of systems later. It is far cheaper to design privacy into a system from the start than to bolt it on after the code has been written or the process established.

This template is designed to be comprehensive. It requires you to look under the hood of your project and ask difficult questions about data flows, third-party vendors, and consent mechanisms. You will find detailed guidance below each section to help you complete it thoroughly. Read the instructions carefully, and remember that when in doubt regarding data privacy, it is always safer to over-report risks than to ignore them.

Section 1: Project Scope and Context

1.1 Project Metadata

Instructions:

This section establishes the administrative baseline for the screening. It connects the privacy screening to the specific project artifact. This is essential for audit trails. If a regulator ever asks why a full DPIA was not conducted, this document serves as the evidence that you assessed the risk and made a calculated decision.

  • Project Name: [Enter the official project name]
  • Project ID/Code: [Enter unique identifier]
  • Project Manager: [Name and Contact Info]
  • Project Sponsor: [Name and Contact Info]
  • Privacy/Compliance Officer Contact: [Name of the person reviewing this form]
  • Estimated Project Start Date: [Date]
  • Estimated Go-Live Date: [Date]

1.2 Brief Project Description

Instructions:

Provide a high-level summary of the project. Do not just copy the project charter; specifically describe why the project exists and how it involves data. Focus on the user journey and the information flow.

Guidance for Completing Section 1.2:

Avoid technical jargon where possible. Imagine you are explaining the project to a privacy regulator who does not know your internal acronyms. Focus on the “who, what, and why” of the data processing.

Example:

  • Poor Description: “We are migrating the CRM to the cloud to optimize SQL queries.”
  • Good Description: “We are migrating our Customer Relationship Management (CRM) system to a cloud-based vendor. This involves transferring the records of 50,000 existing customers, including their contact details and purchase history, to a new environment to improve customer service response times.”

Tips for Success:

  • Be honest about the scale. If you are processing millions of records, state it here.
  • Highlight the benefit. Why is this processing necessary for the business?

Section 2: Data Inventory and Classification

2.1 Types of Data Processed

Instructions:

This is the core of the screening. You must categorize every type of data the project will handle. Place an ‘X’ or a checkmark next to all applicable categories. If you select any category in the “Sensitive/Special Category” column, a full DPIA is almost certainly required.

Table Mapping: Data Categories

General Personal Data (PII)Sensitive / Special Category DataBusiness / Non-Personal Data
[ ] Names (First, Last, Maiden)[ ] Racial or Ethnic Origin[ ] Anonymized/Aggregated Data
[ ] Email Addresses (Personal/Work)[ ] Political Opinions[ ] Company Financials (B2B)
[ ] Physical Addresses[ ] Religious or Philosophical Beliefs[ ] Generic Inventory Lists
[ ] Phone Numbers[ ] Trade Union Membership[ ] Weather/Environmental Data
[ ] IP Addresses / Device IDs[ ] Genetic or Biometric Data (Face ID, Fingerprint)[ ] Software Code (Proprietary)
[ ] Social Security / National ID Numbers[ ] Health Data (Physical or Mental)[ ] Vendor Contracts (Non-PII)
[ ] Financial Data (Credit Card, Bank Acct)[ ] Sex Life or Sexual Orientation
[ ] Employment History / CVs[ ] Criminal Convictions or Offenses
[ ] Photos / Videos of Individuals[ ] Data of Minors (Under 13/16)

Guidance for Completing Section 2.1:

  • General PII: This is any data that can identify a living person, either directly or indirectly. Even an IP address counts as PII in many jurisdictions because it can be traced back to a specific user.
  • Sensitive Data: This data requires higher protection levels (often called Article 9 data under GDPR). Processing this data usually requires explicit consent or a substantial public interest justification.
  • Minors: If your project involves children, strict regulations like COPPA (in the US) or the GDPR-K (in Europe) apply. This is a major red flag for risk.

Tips for Success:

  • Do not guess. Ask the technical architects what fields are in the database schema.
  • If you are unsure if a data field is “sensitive,” assume it is until proven otherwise.

2.2 Volume and Scale

Instructions:

Privacy risk is often a function of volume. A spreadsheet with 10 names carries less risk than a database with 10 million. Estimate the total number of data subjects (people) involved.

  • Estimated Number of Records: [e.g., <100, 100-1,000, 1,000-10,000, 10,000+]
  • Frequency of Processing: [e.g., One-time migration, Daily batch, Real-time streaming]
  • Duration of Retention: [How long will the data be kept? e.g., 6 months, 7 years, Indefinitely]

Guidance for Completing Section 2.2:

Be precise about retention. “Indefinitely” is rarely an acceptable answer in modern privacy law. You must have a schedule for deletion. If you do not know the retention period, mark this as an action item to define immediately.

Section 3: Data Lifecycle Mapping

3.1 Collection

Instructions:

Describe exactly how the data enters your environment.

  • Source of Data: [e.g., Directly from user via web form, Purchased from third-party vendor, Scraped from public web, Employee HR intake]
  • Notice/Consent: [Has the user been notified? Is there a checkbox? Is it implied consent?]

Detailed Step-by-Step Guide:

  1. Identify the input: Look at every interface where data enters. Is it a mobile app? A paper form? An API call from a partner?
  2. Check the transparency: Did the user know this was happening? If you are buying a list from a vendor, did that vendor have permission to sell it?
  3. Document the mechanism: If consent is collected, where is that record stored? (e.g., “Consent is stored in the Marketing Database with a timestamp”).

Example:

“Data is collected directly from the customer via the ‘Sign Up’ page on the mobile application. The user must click a checkbox to agree to the Terms of Service and Privacy Policy before the data is transmitted.”

3.2 Storage and Security

Instructions:

Where does the data live, and how is it protected?

  • Primary Storage Location: [e.g., AWS S3 Bucket, On-premise Server Room B, SharePoint Folder]
  • Geographic Location of Server: [e.g., USA, Germany, Singapore, Unknown]
  • Encryption Status: [e.g., Encrypted at rest, Encrypted in transit, Plain text (High Risk)]
  • Access Controls: [Who can see this? e.g., Admins only, All employees, Public]

Guidance for Completing Section 3.2:

  • Geography matters: Data residency laws (like in China, Russia, or the EU) often dictate that data cannot leave the country of origin. You must know where the physical server sits.
  • Encryption: “Plain text” means if a hacker steals the file, they can read it. “Encrypted” means they only see gibberish. Always aim for encryption.

3.3 Usage and Processing

Instructions:

What are you actually doing with the data?

  • Purpose of Processing: [e.g., To ship products, To analyze trends, To serve targeted ads]
  • Automated Decision Making: [Yes/No. Does an algorithm make decisions that affect the user without human intervention? e.g., Credit denial, Job application filtering]

Tips for Success:

Automated decision making is a high-risk activity. If your project involves AI or Machine Learning that impacts a person’s life (like a loan approval), you will almost certainly need a full DPIA and human-in-the-loop safeguards.

3.4 Transfer and Sharing

Instructions:

Who else sees this data?

  • Internal Sharing: [Does Marketing share this with HR? Does IT see it?]
  • External Vendors/Processors: [List all third parties. e.g., Salesforce, MailChimp, AWS, Google Analytics]
  • Cross-Border Transfers: [Will data move from the EU to the US? Or from one region to another?]

Guidance for Completing Section 3.4:

Vendor risk is your risk. If you share data with a vendor and they get hacked, your company is often held liable. You must list every vendor here so the legal team can check if a Data Processing Agreement (DPA) is signed.

Section 4: Regulatory Trigger Checklist

Instructions:

Answer the following “Yes/No” questions honestly. This section acts as the primary logic gate for determining if a full DPIA is required. A “Yes” answer usually indicates elevated risk.

Screening QuestionYesNoUnknown
1. Does the project involve processing Sensitive/Special Category data (Health, Biometric, Political, etc.)?[ ][ ][ ]
2. Is the data being used for automated decision-making or profiling with legal/significant effects?[ ][ ][ ]
3. Does the project involve systematic monitoring of a publicly accessible area (e.g., CCTV)?[ ][ ][ ]
4. Will you be processing data of vulnerable subjects (children, employees, mentally ill)?[ ][ ][ ]
5. Will data be transferred outside of its country of origin to a country with weaker privacy laws?[ ][ ][ ]
6. Does the project involve matching or combining datasets from different sources?[ ][ ][ ]
7. Is this a new use of technology (e.g., Facial Recognition, AI) not previously used by the company?[ ][ ][ ]
8. Will the processing prevent data subjects from exercising a right or using a service or contract?[ ][ ][ ]
9. Is the volume of data large scale (e.g., thousands of people)?[ ][ ][ ]

Guidance for Completing Section 4:

  • Question 2 (Profiling): If you are tracking user behavior to predict their future purchases, that is profiling.
  • Question 6 (Matching Data): If you take a list of emails from Marketing and combine it with a list of patients from a hospital database, you are creating new insights that might be invasive. This “aggregation risk” is significant.
  • Question 7 (New Tech): Regulators are wary of new tech. If you are deploying something “cutting edge,” expect higher scrutiny.

Section 5: Risk Identification and Mitigation

Instructions:

Based on the answers in Sections 2, 3, and 4, describe the specific privacy risks you have identified. Then, propose a mitigation strategy. This shows you are proactive.

5.1 Identified Risks

Format: [Risk Description] + [Potential Impact]

Examples of Risks:

  • Risk: “We are collecting physical addresses for a contest, but we do not have a deletion schedule.” -> Impact: “Data may be kept forever, increasing the impact of a potential breach.”
  • Risk: “The vendor we are using is based in a country without a data adequacy agreement.” -> Impact: “Legal non-compliance with GDPR transfer rules.”
  • Risk: “Users are not explicitly told their data will be shared with advertisers.” -> Impact: “Reputational damage and potential fines for lack of transparency.”

5.2 Proposed Mitigations

Instructions:

For every risk listed above, propose a fix.

Examples of Mitigations:

  • Mitigation: “Implement an automated script to delete contest data 30 days after the winner is selected.”
  • Mitigation: “Sign Standard Contractual Clauses (SCCs) with the international vendor.”
  • Mitigation: “Update the user interface to include a clear, granular consent pop-up before data collection.”

Tips for Success:

You do not need to solve every problem right now, but you must identify the path to the solution. If the mitigation is “Purchase encryption software,” note that budget approval is required.

Section 6: Screening Outcome and Recommendations

Instructions:

This section is usually completed by the Privacy Officer or the Project Manager in consultation with Legal. It determines the “Go/No-Go” status from a privacy perspective.

6.1 Recommendation

Select one of the following outcomes:

  • [ ] Level 1: Low Risk / No Action Required.
    • Definition: The project processes only non-personal business data or anonymized data. Standard security controls are sufficient.
  • [ ] Level 2: Medium Risk / Standard Safeguards Required.
    • Definition: Personal data is processed, but it is not sensitive. Standard privacy notices and vendor contracts must be in place. No full DPIA needed, but document the controls.
  • [ ] Level 3: High Risk / Full DPIA Required.
    • Definition: The project triggers one or more “Yes” answers in the Regulatory Trigger Checklist (Section 4). You must pause and complete a full Data Protection Impact Assessment before proceeding to development.

6.2 Next Steps

Instructions:

List the immediate actions required based on the recommendation above.

  1. Action: [e.g., Draft Privacy Notice] | Owner: [Name] | Due Date: [Date]
  2. Action: [e.g., Schedule full DPIA Workshop] | Owner: [Name] | Due Date: [Date]
  3. Action: [e.g., Review Vendor Security Certifications] | Owner: [Name] | Due Date: [Date]

Conclusion – Data Privacy Impact Screening Template – Free Word Download

The Data Privacy Impact Screening is a living document. It captures a snapshot of the project’s privacy posture at a specific moment in time. However, projects evolve. Scope creep occurs. New data fields are added. If the scope of your project changes significantly (for example, if you decide to start collecting health data in a project that was previously only for financial data), you must revisit this screening.

Completing this screening diligently protects the organization from fines and lawsuits. More importantly, it protects the people behind the data. By designing for privacy now, you build a robust, trustworthy product that respects user rights. Ensure that this document is saved in the central project repository and that the Privacy Officer has signed off on the results before moving to the execution phase. A “Level 3” risk rating is not a project killer; it is simply a signal that careful navigation is required. Use the insights from this screening to inform your project plan, budget for security tools, and allocate time for legal reviews.

Meta Description:

A comprehensive Data Privacy Impact Screening template to identify privacy risks, inventory data, and determine if a full DPIA is required for project compliance.

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