Complying with GDPR is crucial for businesses that collect and process customer and client data. IT teams, developers and engineers have had to get creative to ensure their systems meet the stringent requirements of GDPR. Data tracking, rebuilding infrastructure, and enhancing security measures all have the potential to add complexity to everyday activity. Such activity may qualify for R&D tax relief, which can help businesses offset the costs associated with GDPR compliance.
In the digital space, there is a saying, “If the service is free, then you are the product” which is true for our engagement with online platforms. The EU introduced GDPR in 2018 to protect users’ data rights, giving them control over how their data is shared and used. Although the UK is technically exempt from GDPR after Brexit, it introduced the Data Protection Act (2018), which is essentially the UK’s version of GDPR and allows UK companies to operate within the EU if they comply with it.
The importance of GDPR compliance
GDPR compliance means a company is committed to being open and honest about data usage. They commit to treating data with respect and only collect data when they have the necessary permissions from the end user. They also must keep data safe and notify users if any security breaches occur.
Almost five years since the enactment of these regulations, companies still require assistance to fully comply with the new laws. If companies were trading before the rules came into effect, it is probable that their systems and infrastructures were not constructed to comply with such regulations. The complexity for companies to catch up with the laws has been increased by the growth of cloud computing. Cloud computing has amplified the complexity of how data is dealt with, managed, stored, and shared. Additionally, it prohibits users from having absolute ownership of their data.
Challenges and complexities of GDPR compliance
Larger organisations such as Meta have a global network of data warehouses and procedures that were put into place almost a decade before the regulations were announced. These data warehouses were not built with data protection rights in mind. Something as simple as tracking the journey of a user’s data as it flows through Meta’s environment requires them to rebuild entire platforms and rethink major operational processes. This, in turn, has a ripple effect on marketers, publishers and 3rd party platforms that integrate with major social media sites, using them as both data sources and communication channels to reach their customers.
In addition, organisations use different sources to gather data, resulting in overlapping, conflicting or inaccessible data sources. If data is properly managed, it becomes possible for the developers to build accurate and complete user profiles. Organisations risk non-compliance if they fail to keep identity data accurate and to a minimum.
Furthermore, GDPR has started a global movement of data regulations, with many countries beginning to publish their own laws and regulations on data protection rights which are not necessarily aligned. It’s becoming nearly impossible for companies to just tweak their infrastructures to remain compliant. The continuous development of regulations worldwide forces companies to rethink data management strategies to keep up with evolving regulations.
Data management challenges
Compliance is an uphill battle, especially for larger, more established tech organisations as regulators move towards a more ‘privacy by design’ world. Organisations are forced to either rebuild their infrastructures from scratch or attempt to manipulate their data pipelines which are old, complex, and far from compliant. Experts are arguing that a fresh start is the only way forward which is opening the gates for these organisations to start undertaking a significant amount of innovation.
Companies need more knowledge to build systems that comply with data protection laws. Consequently, they conduct research and development to create new data-handling procedures and infrastructures. New cloud computing mechanisms are being built from scratch, with features like tagging data packets for tracking purposes and investing in security to prevent breaches. They also redact sensitive information during transfers without consent. Technological challenges are prevalent because these innovations are being integrated into existing infrastructures that cannot be stopped or changed during end-user interactions.
It’s not just the digital giants like Meta or Alphabet who face the issues of reconfiguring or rebuilding their data management systems. Small and mid-sized companies are experiencing it too. Even start-ups beginning their data development journey are having to find new ways to tackle the issue. It’s one of the quieter, less talked about aspects of Tech innovation compared to AI or quantum computing. However, R&D in this space is crucial for organisations as they must build or reinforce their data management foundations.