Custom Object Data Destruction With Policy-Based Retention Control
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Solution Overview
Problem
Enterprises face challenges in managing data destruction to comply with varying data retention and privacy requirements across different countries and industries, while minimizing resource usage and adhering to regulations like GDPR, especially in cloud-based applications that are customized for specific end-users.
Innovation Solution
A system for data destruction management is implemented, involving the creation of data destruction and information lifecycle management objects linked to custom objects, grouped into audit areas with defined retention policies, and scheduled for destruction based on these policies, with verification through destruction logs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is retained longer to comply with varying regional regulations, then compliance reliability is improved, but resource usage increases
Solution Approach 1:
The system segments data into different categories (custom objects, standard objects, archived data) and applies different retention policies to each segment based on regional regulations and business requirements. This allows selective retention of only necessary data, improving compliance reliability while minimizing resource usage by not retaining all data uniformly.
Solution Approach 2:
The system dynamically changes retention parameters (retention periods, destruction timing) based on regional regulations, data types, and compliance requirements. By adjusting these parameters selectively for different data segments and regions, the system achieves compliance reliability without uniformly increasing resource usage across all data.
2Adaptability or versatility
If manual data destruction processes are used, then flexibility in handling different regulations is improved, but operational efficiency deteriorates
Solution Approach 1:
The system creates a universal automated framework that handles multiple regional regulations and data types through a single integrated process. The automated data destruction system can adapt to different regulations (GDPR, HIPAA, SOC2, etc.) and data categories without requiring manual intervention, thus maintaining regulation adaptability while significantly improving operational efficiency.
Solution Approach 2:
The system enables self-service automated data destruction where the system automatically identifies, schedules, and executes data destruction based on predefined policies and regional regulations. This eliminates the need for manual data destruction processes while maintaining the ability to adapt to different regulations through configurable policies.
3Reliability
If comprehensive data tracking and verification are implemented, then compliance reliability is improved, but system complexity increases
Solution Approach 1:
The system implements automated feedback mechanisms through destruction logs that track and verify data destruction activities. The logs provide automatic confirmation that data destruction has occurred according to scheduled policies, ensuring compliance reliability without requiring complex manual verification processes. The feedback is automatically generated and stored, simplifying the overall system while maintaining reliability.
4Productivity
If automated data destruction scheduling is implemented, then operational efficiency is improved, but risk of non-compliance increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring retention policies, destruction schedules, and compliance rules before data destruction is needed. Regional regulations and retention requirements are established in advance, and the automated system executes pre-planned destruction schedules that have been validated for compliance. This preliminary configuration ensures that automated operations maintain compliance reliability while achieving operational efficiency.
Data Source
AI summary
In some embodiments, there is provided a computer-implemented method for data destruction management including creating a data destruction object linked to a custom object; creating an information lifecycle management object linked to the data destruction object; grouping the information lifecycle management object into an audit area comprising information lifecycle management objects having a similar context, wherein a data retention policy is created, while in the audit area, for the information lifecycle management object; scheduling a data destruction batch job selecting a data destruction object for destruction which is mapped to information lifecycle management object; and destroying, based on the scheduling, one or more data of the customized object; and verifying the destroy based on a check of a destruction logRelated systems, methods, and articles of manufacture are also disclosed.