Organizing duplicates for manual review involves systematically grouping potential duplicate records in datasets to prepare for human assessment. This process differs from automated deduplication by prioritizing human judgment on ambiguous cases. It typically involves sorting records into groups where similar entries (like near-identical customer profiles or product listings) are clustered together for efficient side-by-side comparison.

In practice, this is commonly applied in customer relationship management (CRM) systems like Salesforce, where sales teams review duplicate contact entries before merging. E-commerce platforms also use this approach; moderators might group similar product submissions (e.g., "Wireless Headphones X200" vs. "X200 Wireless Headset") in platforms like Magento or Shopify to prevent catalog clutter.

Key advantages include increased accuracy in handling nuanced duplicates and adaptability to unique business rules. However, manual review scales poorly for large datasets and requires trained reviewers. Ethical considerations involve ensuring consistency in decision-making. Future enhancements include AI-assisted grouping tools that pre-sort records based on match probability, accelerating the process while maintaining human oversight.