Data Privacy and GDPR Compliance in 2019

May 25, 2019 marked the one-year anniversary of the European Union's General Data Protection Regulation (GDPR) enforcement. This landmark legislation has fundamentally altered how organizations worldwide collect, process, and protect personal data. As we reflect on the first year of this regulatory sea change, it's clear that data privacy has evolved from a legal obligation to a strategic business imperative. This comprehensive guide explores the current state of GDPR compliance, lessons learned, and how organizations can navigate the expanding global privacy landscape.

The Evolving Data Privacy Landscape

The privacy regulatory environment continues to develop rapidly:

GDPR's Global Impact: Influencing privacy regulations worldwide
Expanding Regulatory Scope: New laws emerging across regions and jurisdictions
Enforcement Maturation: Regulators becoming more active and sophisticated
Consumer Awareness: Growing public expectations around data protection
Privacy as Differentiator: Organizations leveraging strong privacy practices as competitive advantage

Data Privacy Landscape

These developments are shaping how organizations approach data privacy in 2019 and beyond.

1. Enforcement Reality

How regulators have applied GDPR in practice:

Notable Enforcement Actions

Google's €50 Million Fine: French authority CNIL's penalty for transparency and consent violations
British Airways' £183 Million Intention: UK ICO's proposed fine for security failures affecting 500,000 customers
Marriott's £99 Million Intention: UK ICO's proposed penalty for data breach affecting 339 million guest records
Smaller Company Actions: Numerous penalties for basic compliance failures
Sectoral Focus: Particular attention to adtech, healthcare, and financial services

Enforcement Patterns:

Proportionality Principle: Penalties generally reflecting company size and violation severity
Remediation Emphasis: Focus on corrective measures alongside financial penalties
Complaint-Driven Approach: Many investigations initiated by individual complaints
Cross-Border Cooperation: Developing coordination between national authorities
Educational Component: Using enforcement to establish compliance expectations

Key Insight: While catastrophic fines have been rare, regulators are increasingly willing to impose significant penalties for serious violations, particularly those involving inadequate security measures or fundamental failures in transparency and consent.

2. Compliance Challenges

Areas where organizations continue to struggle:

Common Difficulty Areas

Data Mapping Complexity: Identifying and categorizing all personal data across systems
Legitimate Interest Balancing: Properly applying this legal basis for processing
Consent Management: Implementing truly GDPR-compliant consent mechanisms
Data Subject Rights Fulfillment: Efficiently handling access and deletion requests
Vendor Management: Ensuring third-party compliance throughout the supply chain

Compliance Challenges

Implementation Realities:

Resource Intensity: Significant time and budget requirements for comprehensive compliance
Technical Debt Impact: Legacy systems creating particular compliance difficulties
Ongoing Nature: Recognition that compliance is a continuous process, not a one-time project
Interpretation Uncertainty: Continuing questions about applying principles to specific scenarios
Organizational Resistance: Cultural challenges in adapting to privacy-by-design approaches

Key Insight: Many organizations have achieved basic compliance but continue to refine their approaches as regulatory expectations become clearer and internal privacy maturity increases.

3. Business Impact

How GDPR has affected organizational operations:

Operational Effects

Data Minimization: Reduction in unnecessary data collection and retention
Process Formalization: More structured approaches to data handling
Security Enhancement: Improved data protection measures and breach response
Vendor Scrutiny: More rigorous assessment of service providers
Documentation Emphasis: Increased focus on accountability and record-keeping

Strategic Implications:

Privacy as Trust Builder: Organizations leveraging strong practices to enhance customer relationships
Data Quality Improvements: Better data hygiene leading to more valuable insights
Innovation Constraints: Some initiatives delayed or redesigned due to privacy concerns
Global Standardization: Many multinational companies applying GDPR standards worldwide
Competitive Differentiation: Privacy capabilities becoming market differentiators

Example: Microsoft has positioned privacy as a core brand value, extending GDPR rights to all customers globally and developing privacy-enhancing technologies as competitive advantages.

Effective approaches based on first-year learnings:

1. Data Governance Frameworks

Establishing sustainable privacy management:

Governance Components

Privacy Steering Committee: Cross-functional leadership oversight
Data Inventory Maintenance: Ongoing mapping and classification processes
Policy Framework: Comprehensive, accessible privacy documentation
Training Program: Role-specific privacy education
Compliance Monitoring: Regular assessments and audits

Best Practice: Integrate privacy governance with existing information governance and security frameworks rather than creating parallel structures.

2. Operationalizing Data Subject Rights

Efficiently handling individual requests:

Implementation Approaches

Request Intake Standardization: Consistent channels and verification processes
Workflow Automation: Technology-enabled request management
Cross-Functional Coordination: Clear responsibilities across departments
Response Templates: Standardized formats for common requests
Exemption Management: Properly applying legitimate limitations

Best Practice: Implement a centralized case management system that tracks requests from intake through fulfillment, ensuring timely responses and creating an audit trail.

3. Vendor Management

Ensuring third-party compliance:

Effective Strategies

Risk-Based Assessment: Tailoring scrutiny to data sensitivity and processing scope
Contract Standardization: Developing template clauses and agreements
Ongoing Monitoring: Continuing oversight beyond initial assessment
Collaborative Remediation: Working with vendors to address compliance gaps
Certification Leverage: Utilizing recognized privacy certifications in evaluation

Vendor Management

Best Practice: Create a tiered approach to vendor management that allocates resources based on the risk level each vendor represents to your privacy program.

4. Privacy by Design Implementation

Embedding privacy into development processes:

Practical Approaches

Privacy Impact Assessments: Systematic evaluation of new initiatives
Design Requirements: Clear privacy specifications for product development
Technical Controls: Implementing privacy-enhancing technologies
Testing Protocols: Verification of privacy functionality
Documentation Integration: Building privacy into project artifacts

Best Practice: Develop privacy design patterns and reusable components that development teams can incorporate into products and services, making compliance easier to achieve consistently.

5. Breach Readiness

Preparing for potential incidents:

Key Components

Response Plan: Clearly defined roles and procedures
Detection Capabilities: Systems to identify potential breaches
Assessment Framework: Methodology for evaluating notification requirements
Communication Templates: Pre-approved messaging for various scenarios
Regular Simulation: Tabletop exercises to test readiness

Best Practice: Conduct cross-functional breach simulations that test both technical and communication aspects of your response plan, identifying and addressing gaps before a real incident occurs.

Navigating emerging regulations worldwide:

1. California Consumer Privacy Act (CCPA)

Understanding America's first comprehensive privacy law:

Key Provisions

Broad Definition of Personal Information: Including inferences and probabilistic identifiers
Consumer Rights: Access, deletion, and opt-out of data sales
Disclosure Requirements: Detailed privacy notices and response procedures
Limited Exemptions: Narrowly defined exceptions for certain data types
Enforcement Mechanisms: Both regulatory action and private right of action

Implementation Considerations:

GDPR Alignment: Leveraging existing compliance for CCPA readiness
Key Differences: Addressing unique CCPA requirements beyond GDPR
Operational Impacts: Adapting processes for California-specific provisions
Documentation Updates: Revising notices and policies for compliance
Technical Requirements: Implementing "Do Not Sell My Personal Information" functionality

Best Practice: Conduct a gap analysis between your GDPR compliance program and CCPA requirements to efficiently extend existing capabilities rather than building parallel processes.

2. Brazil's Lei Geral de Proteção de Dados (LGPD)

Preparing for South America's major privacy regulation:

Essential Elements

GDPR-Inspired Framework: Similar fundamental principles and rights
Legal Bases for Processing: Multiple grounds including consent and legitimate interest
Data Protection Officer Requirement: Mandatory DPO appointment
Cross-Border Transfer Restrictions: Controls on international data flows
Significant Penalties: Fines up to 2% of Brazilian revenue

Strategic Approach:

Leverage GDPR Foundations: Extending existing compliance to cover LGPD
Local Adaptation: Addressing Brazil-specific requirements
Implementation Timeline: Preparing for August 2020 enforcement
Organizational Readiness: Establishing necessary roles and responsibilities
Documentation Localization: Adapting policies and notices for Brazilian context

Best Practice: Prioritize appointment of a DPO with knowledge of both Brazilian legal requirements and your organization's data processing activities to guide compliance efforts.

3. Other Regional Developments

Tracking privacy regulations worldwide:

Notable Frameworks

India's Personal Data Protection Bill: Comprehensive framework with data localization requirements
Thailand's Personal Data Protection Act: GDPR-influenced law with significant penalties
Japan's Amended APPI: Enhanced individual rights and cross-border transfer controls
South Korea's PIPA: Stringent consent requirements and processor obligations
UAE and Middle East Regulations: Emerging frameworks with unique regional considerations

Global Privacy

Strategic Implications:

Compliance Scalability: Designing programs that can adapt to multiple jurisdictions
Regional Variations: Understanding key differences between frameworks
Implementation Prioritization: Focusing resources based on business footprint
Monitoring Developments: Tracking evolving requirements across regions
Global Minimum Standard: Establishing baseline practices applicable worldwide

Best Practice: Develop a regulatory monitoring system that tracks privacy developments in your key markets, providing early awareness of emerging requirements that may affect your operations.

Privacy Program Maturity: Moving Beyond Compliance

Evolving from regulatory requirement to business advantage:

1. Privacy as Competitive Differentiator

Leveraging strong practices for market advantage:

Strategic Approaches

Transparent Communication: Clearly explaining data practices in accessible language
Enhanced User Control: Providing granular choices beyond regulatory minimums
Privacy-Preserving Innovation: Developing products that minimize data collection
Trust Building: Emphasizing privacy as core brand value
Customer Education: Helping users understand privacy implications and protections

Example: Apple has positioned privacy as a key differentiator, implementing features like App Tracking Transparency and Privacy Nutrition Labels that exceed regulatory requirements while resonating with privacy-conscious consumers.

2. Data Ethics Frameworks

Moving beyond compliance to responsible data use:

Framework Components

Ethical Principles: Defining values that guide data decisions
Assessment Methodology: Evaluating initiatives against ethical standards
Governance Structure: Oversight mechanisms for ethical questions
Training and Awareness: Building ethical thinking throughout the organization
Stakeholder Engagement: Incorporating diverse perspectives in data decisions

Best Practice: Establish an ethics review process for high-risk data initiatives that considers not just what is legally permissible but what is responsible and aligned with organizational values.

3. Privacy-Enhancing Technologies

Implementing technical solutions that enable both privacy and innovation:

Emerging Approaches

Federated Learning: Machine learning without centralizing sensitive data
Differential Privacy: Adding noise to datasets while preserving analytical utility
Homomorphic Encryption: Computing on encrypted data without decryption
Zero-Knowledge Proofs: Verifying information without revealing underlying data
Secure Multi-Party Computation: Collaborative analysis without sharing raw data

Example: Google has implemented differential privacy in its Chrome browser and analytics products, allowing useful insights to be derived while protecting individual user data.

4. Privacy ROI Measurement

Quantifying the business value of privacy investments:

Measurement Approaches

Risk Reduction Valuation: Quantifying decreased likelihood and impact of privacy incidents
Operational Efficiency: Measuring improvements in data management processes
Customer Trust Metrics: Tracking privacy's impact on retention and engagement
Regulatory Overhead Reduction: Assessing streamlined compliance costs
Innovation Enablement: Evaluating privacy's contribution to new offerings

Best Practice: Develop a balanced scorecard of privacy metrics that connects program activities to both risk reduction and business value creation, demonstrating privacy's contribution to organizational objectives.

Preparing for the Future of Data Privacy

Anticipating developments that will shape privacy requirements:

1. Artificial Intelligence Governance

Addressing privacy implications of AI systems:

Emerging Considerations

Algorithmic Transparency: Explaining how AI systems use personal data
Automated Decision-Making Rights: Implementing human review capabilities
Training Data Privacy: Ensuring compliant data sources for AI development
Bias Prevention: Mitigating discriminatory outcomes from algorithms
Purpose Limitation: Restricting AI applications to specified use cases

Strategic Implication: Organizations should develop AI governance frameworks that incorporate privacy requirements from the earliest stages of development, ensuring systems are designed for compliance.

2. Internet of Things Challenges

Managing privacy in connected environments:

Key Considerations

Notice Delivery: Providing transparency without traditional interfaces
Consent Mechanisms: Obtaining permission in ambient computing contexts
Data Minimization: Limiting collection in sensor-rich environments
Security Requirements: Protecting distributed data across multiple devices
Children's Privacy: Safeguarding vulnerable users in connected homes

Strategic Implication: Product designers should incorporate privacy considerations into IoT development from conception, creating devices that respect user privacy by default while still delivering value.

3. Biometric Data Protection

Safeguarding increasingly sensitive identifiers:

Critical Protections

Heightened Security: Implementing strong protection for biometric templates
Revocability Mechanisms: Allowing replacement of compromised identifiers
Proportionality Assessment: Ensuring necessity of biometric processing
Alternative Options: Providing non-biometric choices where possible
Transparency Requirements: Clearly explaining biometric data usage

Biometric Privacy

Strategic Implication: Organizations should approach biometric data with particular caution, implementing specialized protections and considering the ethical implications of collection and use.

4. Data Sovereignty Requirements

Navigating localization mandates:

Emerging Trends

Geographic Storage Requirements: Mandates to keep data within national borders
Processing Restrictions: Limitations on where data can be accessed or used
Transfer Mechanism Evolution: Changing frameworks for cross-border data flows
Conflicting Legal Obligations: Navigating contradictory requirements across jurisdictions
Cloud Architecture Implications: Impact on distributed computing models

Strategic Implication: Organizations should develop data architectures that can adapt to localization requirements while maintaining operational efficiency, potentially through regional data centers or partitioned cloud environments.

Conclusion: From Compliance to Data Stewardship

As we move beyond the first year of GDPR enforcement, it's clear that data privacy has become a fundamental business consideration rather than merely a legal requirement. The most successful organizations will be those that:

Build scalable privacy programs that can adapt to evolving global requirements
Embed privacy considerations throughout product development and business operations
Leverage privacy as a trust builder and competitive differentiator
Invest in privacy-enhancing technologies that enable innovation while protecting data
Develop ethical frameworks that guide responsible data use beyond compliance minimums

By approaching privacy as an opportunity for responsible data stewardship rather than just a regulatory burden, organizations can build sustainable practices that create value while respecting individual rights. The future belongs to companies that can effectively balance data utility with privacy protection, creating trusted relationships with customers in an increasingly data-driven world.

Remember that privacy compliance is not a destination but a journey of continuous evolution—one that requires ongoing adaptation, learning, and refinement as both regulations and expectations change.

This article was written by Nguyen Tuan Si, a data privacy specialist with experience helping organizations develop and implement effective privacy programs across various industries.

Data Privacy and GDPR Compliance in 2019 - One Year Later