Marcus Belke
CEO of 2B Advice GmbH, driving innovation in privacy compliance and risk management and leading the development of Ailance, the next-generation compliance platform.
Enterprise GRC systems have been considered the standard for governance, risk, and Compliance in large organizations. Also in the Data protection They are often used as central platforms to meet regulatory requirements such as the GDPR implemented in a structured manner. In practice, however, a conflict is increasingly coming to light: The demand for comprehensive governance often clashes with operational realities. The structural weaknesses of traditional enterprise GRC approaches are particularly evident in the area of data protection.
Oversizing: When Systems Are Larger Than the Problem
Enterprise GRC solutions are typically designed to address highly complex, enterprise-wide governance requirements. They cover a wide range of use cases, including financial risks, internal audit, and regulatory reporting. Data protection is often just one module among many.
However, this breadth often leads to an overly complex system. Compared to other GRC domains, data protection processes are often leaner, more operational in nature, and require close collaboration with business units. A system developed for strategic risk management is therefore not necessarily well-suited for the day-to-day work of data protection officers or business units.
The result is complex user interfaces, unnecessary process steps, and low adoption within the company.
Customization Costs: The Price of Customization
Extensive customization is required to make enterprise GRC systems usable for meeting data protection requirements. Standard modules are generally not sufficient to address specific requirements such as processing inventories, data protection impact assessments, or Rights of data subjects implement efficiently.
This customization is not only time-consuming but also costly. It ties up internal resources and external consultants over long periods of time. At the same time, it creates a strong dependence on custom configurations, which are often difficult to document and even harder to maintain.
A particularly critical issue is that with every additional adjustment, the complexity of the system increases, and with it, the risk of errors and inconsistencies.
Change Dependency: Every Adjustment Becomes a Project
Data protection regulations are constantly evolving. New Guidelines, court rulings, or national peculiarities require continuous adjustments to processes and systems.
In a heavily customized enterprise GRC system, any change can quickly turn into a project in its own right. Even minor adjustments can entail extensive coordination, testing, and releases. This significantly extends the time to market for necessary changes.
For data protection organizations, this means they are slower to respond to regulatory developments. This is a clear disadvantage in an environment that requires agility.
Lack of Flexibility: Rigid Structures in a Dynamic Environment
Another key problem is the lack of flexibility. Enterprise GRC systems often follow rigid data models and process logic. As a result, they can only accommodate the specific requirements of business units or country-specific nuances to a limited extent.
However, flexibility is crucial, especially in the area of data protection, where processes are closely integrated with operational workflows. Different business models, technologies, and data flows require adaptable solutions.
If systems do not offer this flexibility, workarounds emerge—for example, in the form of Excel spreadsheets or shadow processes. This not only undermines data quality but also the GRC system’s central control function.
Reading tip: Audit preparation in data protection
Alternative Models: Specialization Rather Than Generalization
Against this backdrop, alternative approaches are gaining importance. Instead of monolithic enterprise GRC systems, many organizations are increasingly turning to specialized models.
These include dedicated platforms for data protection management that are specifically tailored to the requirements of the GDPR are designed for. These solutions often offer preconfigured processes, greater ease of use, and faster implementation.
Another approach involves modular architectures, in which data protection is treated as a separate domain that can be flexibly integrated into existing IT landscapes. APIs and standard interfaces enable seamless connectivity to other systems without the complexity of a centralized GRC monolith.
Low-code and no-code platforms are also gaining prominence, as they enable business units to customize processes on their own without having to rely on time-consuming IT projects.
Time for a Reassessment
If your current enterprise GRC system is reaching its limits in the area of data protection, selective optimization is usually no longer sufficient. A fundamentally different approach is needed.
This is exactly where Ailance comes in: as a specialized, flexible platform for modern data protection management. Ailance offers a clear, application-oriented architecture that is tailored to your organization’s actual processes. Ailance can be implemented quickly, is intuitive to use, and requires no extensive customization.
Use a structured replacement analysis to evaluate your existing setup and discover how Ailance can help you make your data protection organization more efficient, agile, and future-proof.
Identify your potential now and take the next step.
Marcus Belke is CEO of 2B Advice as well as a lawyer and IT expert for data protection and digital Compliance. He writes regularly about AI governance, GDPR-Compliance and risk management. You can learn more about him on his Author profile page.
Questions and Answers
Why Do Enterprise GRC Systems Often Fail When It Comes to Data Protection?
Enterprise GRC systems are typically designed for complex, enterprise-wide governance, risk, and Compliance-requirements. Data protection is often just one module among many in these systems. This results in complex user interfaces and process steps that do not always align with the operational requirements of data protection officers and business departments.
Why are traditional enterprise GRC systems often overkill for data protection management?
Data protection processes are often more operational in nature and require close collaboration with line departments. Systems developed primarily for comprehensive strategic risk management may therefore be unnecessarily complex for day-to-day data protection work and reduce user acceptance.
Why does customizing enterprise GRC systems result in high costs?
Specific data protection processes—such as processing inventories, data protection impact assessments, or handling data subject rights—often cannot be adequately addressed using standard modules. The necessary customization ties up internal resources and external consultants, while also increasing complexity and the subsequent maintenance effort.
Why do changes in highly customized GRC systems quickly turn into separate projects?
New regulatory requirements, Guidelines, court rulings, or national specifics may necessitate ongoing adjustments. In highly customized enterprise GRC systems, even minor changes often require coordination, testing, and releases, which can delay implementation.
Why do Excel spreadsheets and shadow processes still arise despite a centralized GRC system?
When rigid data models and process logic cannot adequately accommodate the requirements of individual business units or country-specific nuances, additional workarounds often arise. Excel spreadsheets and parallel processes can then compromise data quality and weaken the GRC system’s central control function.
What alternatives are there to a traditional enterprise GRC system for data protection?
One alternative is specialized data protection management platforms with preconfigured processes. Modular architectures with interfaces to existing systems, as well as low-code or no-code approaches, can also enable more flexible customization without inheriting the complexity of a centralized GRC monolith.
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