Process and technology: utilizing their respective strengths
Technology-based approaches are often preferable when direct, infallible control over data assets is required, or where human processes to exert control over data are likely to be error-prone or difficult to scale.

Examples of this would be the automated detection of personal data in heterogeneous IT environments -- typically through machine learning -- detection of suspicious activity and data breaches, the masking or pseudonymization of personal data or automatically purging all data associated with an individual that has invoked the right to erasure.

These tasks, if left to humans to conduct manually, would be unfeasible: The scale of data involved is simply too great, and the risk of human error too real. Solutions that directly exert technical control over the data are required in these cases, and simply documenting the process involved is not sufficient to meet GDPR's requirements.

A commonality of technology-based solutions is that they directly "touch" the data, and do not depend on human intermediary action to manually make changes to individual files or pieces of data. Whenever direct changes are required to files, such as changes in policy, deletion or relocation, having a solution that can directly exert those controls in an automated manner -- with the click of a button -- is an asset. (See GDPR, Cloud Changing Security Pros' Priorities – Report.)

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Process-based approaches, on the other hand, are preferable when the compliance requirement being met is, itself, process-oriented in nature.

The majority of GDPR's articles are process-based rather than technical, and focus on building repeatable workflows that take advantage of dedicated roles and responsibilities within the organization. Keeping records of processing activities (Article 30), notifying supervisory authorities of a personal data breach (Article 33) and conducting data protection impact assessments (Article 35) are all examples of strongly process-oriented requirements that cannot be fulfilled exclusively via direct technical control over data.

An organization that is striving to meet these requirements must first build an internal process for meeting these requirements, and have a method in place for documenting and monitoring that living process.

That's where process-based solutions come in.

They provide a software system to manage existing human roles and delegate tasks, giving users a place to conduct necessary steps associated with the process -- such as completing risk assessments -- and keeping an auditable trail of all the steps and actions taken in that process.

Most process-oriented solutions provide customizable workflows that can be adapted to the individual organization's existing roles and requirements. Process-based solutions excel at process management, helping create repeatable templates for internal processes, and automatically documenting the steps and parties involved so that they may be presented to regulatory authorities.

With that in mind, the requirements of some articles will be best met with a technology-based approach, while others will benefit from a process-based approach. But the typical enterprise does not have the budget or time to evaluate a different solution for every article of GDPR that needs to be met.

In seeking compliance solutions, most organizations are looking for a product that can meet the largest number of GDPR requirements in a single platform.

This is why hybrid solutions -- with aspects of both technology-based and process-based approaches -- will ultimately provide the broadest compliance coverage.

They also have the potential to become more deeply rooted in enterprise culture by addressing both sides of the equation: direct control of data ties them to data assets and meets technical requirements, while process management tools make them sticky for users.

Two camps may be forming in the GDPR compliance vendor landscape, but the ultimate winners will likely be solutions that successfully adopt aspects of both approaches, applying each for their respective strengths.

Related posts:

• GDPR: The New Price We Pay for Data Privacy
• EU's NIS Directive Compounding GDPR Burdens & Confusion
• GDPR: Your Enterprise Security Checklist

— Paige Bartley is a Senior Analyst covering data and enterprise intelligence for Ovum.

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