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SayPro Review and analyze feedback from prior loops to improve data quality.

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SayPro Primary Responsibility: Review and Analyze Feedback from Prior Loops to Improve Data Quality
Objective
As part of SayPro’s commitment to continuous improvement and research excellence, all relevant teams are responsible for reviewing and analyzing feedback from prior feedback loops to systematically enhance the quality, accuracy, and relevance of data outputs across projects.

SayPro Key Responsibilities
Retrieve Feedback from Previous Research Cycles

Access documented feedback from:

Monthly SCRR reports

Peer review comments

Stakeholder consultations

Internal audits and quality assurance reviews

Analyze Patterns and Recommendations

Identify recurring issues, such as data inconsistencies, incomplete topic coverage, or gaps in analysis.

Highlight best practices and improvement suggestions made by reviewers, analysts, and partner organizations.

Integrate Lessons Learned

Apply insights from past feedback to refine:

GPT prompt designs

Data collection tools and methodologies

Validation processes and reporting structures

Update project workflows and templates to reflect improvements.

Collaborate with the Research Office

Engage with the SayPro Economic Impact Studies Research Office to verify if changes align with current standards.

Participate in team reviews to ensure feedback is acted upon and implemented effectively.

Document Improvements and Adjustments

Record how feedback has been addressed in the current research cycle.

Maintain an internal log of changes and lessons learned for future reference and team learning.

Outcomes and Impact
Improves overall data quality by addressing known gaps and weaknesses

Strengthens credibility and consistency of SayPro research outputs

Enables adaptive research practices that evolve based on real-world input

Builds institutional memory and a culture of accountability and learning

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