Compliance beyond borders: Navigate global data privacy

Although most data protection and privacy laws are largely based on the European Union’s GDPR, the differences in legal definitions, infrastructure requirements, and compliance paths require companies to follow jurisdiction-specific solutions.

The result is that one size doesn’t fit all.

Multinational companies need to architect and customize their data protection and privacy programs to meet the needs of individual jurisdictions. It becomes the joint responsibility of CIOs, CISOs, DPOs, and CDOs to bring their firms to compliance.

In this blog post, we take a look at the challenges faced when navigating global data privacy regulations and what strategies multinational companies can adopt to efficiently tackle each.

Common challenges in navigating global data privacy compliance

A. Divergent legal frameworks

Since GDPR came into force and emerged as a benchmark for contemporary data protection frameworks, there has been a worldwide trend in the enactment of data protection laws. 137 out of 194 countries have put in place their respective legislation to secure the protection of data and privacy, with 15% more in place.

Companies operating across borders find it difficult to navigate a complex patchwork of regulations. Navigating the global data privacy landscape requires dealing with the variation in definition of personal data, user expectations, and technology constraints (e.g., data localization restrictions in China) across different jurisdictions.

For instance, CCPA, the governing data protection law in the United States, varies from the GDPR in the European Union in terms of scope where each applies, data subject rights, non-compliance penalties, enforcement (strong, with significant fines for GDPR; private right of action for CCPA), etc.

Maintaining operational efficiency, like streamlining data flows and putting privacy controls in place that cater to diverse requirements, adds to the resource-intensiveness of business processes. Additionally, striking the right balance between data privacy and data utility can be tricky, especially when discovering ways to collect, process, and analyze data for marketing and personalization objectives while respecting individual privacy rights.

B. Cross-border data transfers

While cross-border data transfer has been the staple of the digital age, the usual suspects like privacy, security, and national sovereignty have constantly blocked its smooth passage. As concerns about individual rights, digital security, and geopolitical power plays erupted, cross-border data transfers have become increasingly cumbersome.

As different countries have their own data privacy and security regulations, these regulations overlap and contradict each other, creating confusion about which data protection measures should be implemented. Moreover, data privacy laws keep being constantly updated and revised. Sometimes, existing laws are even scrapped and replaced.

For instance, the previous EU-US Privacy Shield under Schrems II judgment was invalidated by the European Court of Justice, citing it as incompatible with protecting EU citizens’ data from potential US government surveillance.

As a successor to the EU-US Privacy Shield, the EU-US Data Privacy Framework (DPF) became effective on July 10, 2023. With its stronger safeguards and independent redress mechanisms, it facilitates the transfer of EU personal data to participating organizations in the United States.

While facilitating data flows, the EU-US DPF triggers a range of compliance obligations, including making updates to data transfer agreements, necessitating upgrades to secure data infrastructure, ensuring robust internal review processes for dispute resolution, etc.

C. Data subject rights and consent

The definition of key terms like “personal data,” “consent,” and “legitimate interest” for data processing significantly changes for different countries. For example, what constitutes “consent” under GDPR might not be the same for another country.

GDPR requires consent to be “freely given, specific, informed, and unambiguous.” In the US, consent requirements are sector-specific and comparatively less stringent. In Canada, consent being defined as “any voluntary agreement” is rather broader than the GDPR’s.

The degrees and interpretations of data subject rights vary with each jurisdiction. For example, the “right to be forgotten” under the GDPR allows users to request deletion of their data in certain circumstances; in the US, sectoral regulations and state laws provide limited erasure rights for data subjects to exercise.

This inconsistency in definitions makes it difficult for organizations to implement consistent data practices across borders, leading to non-compliance.

Strategies for navigating global data privacy compliance

A. Conducting comprehensive data mapping and inventory

Conducting a comprehensive data mapping and inventory is a stepping stone in achieving a seamless, secure, and compliant data governance framework. Locating where the data is, how it is moving, and how it is being used enables valuable insights in enhancing security, optimizing data management, and achieving compliance.

A step-by-step guide to conducting comprehensive data mapping and inventory:

• Identify all data sources where personal data is collected, stored, processed, or transferred. Data sources comprise systems, databases, applications, and devices where data could be found in both structured and unstructured form.
• Categorize data on the basis of types, sensitivity level, and origin. Types include personal data, health data, financial data, etc. Origin includes internal (data generated within an organization) or third-party (data acquired from external sources, such as third-party applications, social media platforms, etc.).
• Map the flow of data across IT systems, processes, and geographical boundaries, identifying all data transfers, recipients, and purposes. Data mapping creates a holistic picture of how information flows within and beyond an organization.
• Document details pertaining to each data asset. Documentation details include the format, retention period, legal basis for processing, and security measures in place. Documentation helps maintain the record of processing activities (RoPA) required by data privacy regulations like GDPR, CCPA, PIPL, etc.

B. Implementing robust data protection impact assessments (DPIA)

A DPIA is a systematic process to identify, analyze, and mitigate risks arising out of the processing of personal data on the privacy rights and freedoms of individuals. While the specific requirements for DPIAs vary widely across international regulations, some regulations explicitly mandate organizations to carry out DPIAs.

For instance, GDPR requires DPIA when the type of processing, in particular the use of new technologies under specific situations like large-scale processing of personal data, systematic monitoring of publicly accessible areas, or extensive profiling, may result in high risks to individuals. The UK GDPR additionally mandates DPIAs for the processing of children’s personal data.

On the contrary, some regulations explicitly mandate DPIAs but encourage them based on the risk assessment of the processing activity. It means, regardless of specific regulations, DPIA may be required when the processing involves high-risk data (e.g., health information, financial data, etc.), cross-border transferring of data to a country with lower data protection standards, etc.

Steps to implement DPIAs:

• Conducting a robust DPIA begins with determining the scope of the analysis: whether the assessment is for a specific project, department, or entire organization. Defining the scope helps concentrate the impact assessment on specific processing activities instead of spreading the resources thinly across the organization.
• Identify all the data processing activities, including internal and cross-border transfers, to understand the organization’s data landscape. Map the flow of data from collection to storage, processing, and disclosure.
• Assess the data protection risks and impacts of each processing activity on an individual’s privacy. Some common risks associated with processing activities include unauthorized access, data breaches, discrimination, profiling, collecting more data than necessary, and a lack of transparency.
• Implement appropriate safeguards like encryption, access controls, data minimization, transparency measures, and obtaining informed consent to minimize identified risks. Furthermore, conducting regular internal and external audits can help organizations proactively identify and address risks.
• Document the entire DPIA process, including methodologies, findings, and mitigation measures.

The road ahead: Proactive approaches to global data governance

Navigating the mazy world of global data privacy regulations can be daunting for companies with a multinational presence. The patchwork of diverse legal frameworks, complexities of cross-border transfers, and non-uniformity with consent and data subject rights further add to the challenges. However, by adopting a strategic and proactive approach like conducting comprehensive data mapping and inventory and implementing robust data protection impact assessments, companies can not only achieve compliance but also reap the benefits of responsible data governance.