OKR for PI Redaction

Objective:

Implement a PI (Personally Identifiable) removal initiative to enhance data security and compliance, enabling safe storage and broader use of call center data.

Key Results:

Develop and Implement PII Redaction System:
- Design and deploy an automated system to redact PII (e.g., credit card numbers, social security numbers) from call center speech-to-text data with 99% accuracy by Q4 2024.
- Ensure the redaction process meets compliance standards, reducing data risk by 90% within the next two quarters.
Enhance Data Storage Security:
- Successfully migrate 100% of the redacted call center data to non-PCI compliant infrastructure by the end of Q4 2024.
- Achieve a 50% reduction in storage costs by moving data to more cost-effective, non-PCI compliant environments.
Enable Machine Learning and Analytics:
- Implement a secure pipeline for using redacted data in machine learning models, including audit calls, with 95% data integrity.
- Develop and deploy at least 3 new machine learning models using redacted data for call auditing and analysis by Q4 2024.
Facilitate Cloud Migration:
- Identify and migrate at least 5 applications to the cloud, leveraging redacted data, by the end of Q4 2024.
- Ensure all migrated applications maintain data security and compliance, with zero incidents of PII exposure.
Monitor and Optimize Redaction Process:
- Establish a continuous monitoring system to track the effectiveness of PII redaction, with monthly reports on performance and improvements.
- Conduct bi-quarterly audits to ensure the redaction process remains compliant with evolving regulatory requirements.

Additional Initiatives:

Conduct training sessions for relevant teams on handling and processing redacted data.
Collaborate with the legal and compliance departments to ensure the redaction system meets all current and future regulations.
Launch an internal communication campaign to inform stakeholders about the benefits and progress of the PI removal initiative.