How to Simplify Data Compliance Management for Tech Startups
Lean operating conditions can quickly push less immediate challenges like data compliance to the bottom of your priority list. However, the increasing cost of noncompliance is driving a surge in awareness and accessible options for small teams.
Data protection supervisory authorities across Europe have issued a total of EUR1.64bn (USD1.74bn/GBP1.43bn) in fines since 28 January 2022. A year-on-year increase in reported GDPR penalties of 50%. Effective planning and automation are essential for tech startups to manage data compliance. This article will discuss the steps small teams handling lots of data can take to manage data compliance effectively.
Start with a Plan
Creating a data compliance plan is essential for effective data governance, as it outlines the data processes for data storage, data usage, data transfer, and data destruction procedures.
A Data Protection Impact Assessment (DPIA) is a good starting point for businesses. This is a process designed to identify risks associated with the processing of personal data and to minimize the risks. A comprehensive data compliance plan will help you mitigate risk and choose the best-fit compliance options for your team.
A well-planned approach to compliance addresses data regulation laws and provides guidelines to ensure that personal data is protected and privacy standards are met. Once you have an understanding of your data’s journey, you can begin to create an effective data compliance plan.
A comprehensive data compliance plan will help keep your business in good standing while also protecting user data. It is also important to document processes, create audit trails, define intervals for data reviews, and train teams accordingly.
Leveraging Privacy by Design
Greater regulation means greater exposure on several fronts for organizations that do not comply with their privacy and security obligations. Under GDPR, fines of up to 2% of global revenue or €10 million (whichever is higher) may be imposed, plus the possibility of individual lawsuits. Change management also becomes more expensive in the late stages of the software development life cycle.
Cost of poor quality (COPQ) is defined as the costs associated with providing poor-quality products or services. The cost of poor quality includes 3 categories: appraisal, internal failure, and external failure costs. Poor design architecture can cost software companies the trust of their users. It also takes time and resources to repair industry reputation damage.
New technology developed in accordance with high-security measures from the initial stages saves resources and significantly improves user safety and protection. This approach also gives organizations better control and accountability over their data.
Privacy by design is a practice that emphasizes privacy concerns at the outset of data processing practices rather than applying features retroactively. It’s one of the guiding principles of the GDPR.
The concept of privacy by design maximizes the amount of privacy inherent in technological solutions and minimizes any risks that stand as obstacles to personal privacy. This approach reduces the amount of extensive and expensive post-production work. The long-term benefits of implementing privacy by design into every step of the software production process outweigh the short-term cost associated with it.
Automate as Much as Possible
Businesses face several challenges trying to achieve data compliance using manual processes alone.
Challenges can include:
- Inaccurate and inconsistent data collection
- Difficulty identifying data needed for compliance due to the large scale of data being collected
- The human element remains the main concern in data protection, and almost all successful attacks and breaches have been based on human error
Manual processes also limit the efficiency of compliance processes, leading to inefficiencies and poor onboarding onto new systems. To overcome these challenges, organizations should automate their compliance procedures using tools such as Scrut, Skyflow, HIPAA One, and AuditBoard.
Data compliance automation tools include software solutions that automate the process of following various regulations and standards to maintain the integrity and availability of regulated data. By automating compliance processes, businesses can improve accuracy and streamline collection procedures. This enables organizations to collect, control, and analyze data at various points in its lifecycle and generation the necessary alerts when analysis reveals a possible compliance violation.
Automated processes also save organizations significant amounts of time compared to manual processes as well as reduce costs in the event of a data breach–an average of $1.55 million less than those without automation.
Tech startups that manage to simplify compliance management can focus on core competencies rather than being bogged down by complex and time-consuming compliance procedures. This also allows smaller organizations to refine data management processes and create more efficient operations.
Organizations that leverage the planning, processes, and tools to facilitate data compliance can reduce the risk of human error, streamline collection procedures, and minimize compliance risk.
