Automate Quality Control (QC) batching and intuitively share samples. The right tech makes it easy.
QC processes and formal checkpoints are one of the most important components of a document review workflow, helping to deliver more accurate outcomes. But clunky workflows and slow manual interventions can make the whole process hugely frustrating and inefficient. Thankfully, there are two ways to bring huge new levels of efficiency to any document review QC workflow.
Early Review Assessment and why you should start small
Early review assessment is a great way to create a quick feedback loop within the first week or so of a document review. It gives subject matter experts (SMEs) the timely chance to analyze and provide feedback on what document reviewers have produced.
Our project management teams have learned that beginning a document review project with a small, core team of two to four reviewers is the best way to proceed, keeping outcomes and insights tightly focused. After initial iterations and feedback, it becomes time to add more document reviewers to the team.
For similar reasons, our experts recommend beginning the document review with smaller review batches of around 100 documents, instead of the standard 500. Batches should be analyzed for accuracy and fed back on by the SME as soon as they’re completed. That way, immediate adjustments to review protocol can be made. Instructions modified. Review tags changed.
Automating the random sampling process
A large document review will typically be overseen by a smaller, elite team of reviewers. This might be a group of first-rate paralegals known for delivering great results. It’s their job to review batches completed by the rest of the team, often checking only a small sample of the original review batch for accuracy. They make this selection based on how documents were tagged by the review team, manually isolating a random sample from a completed batch.
This manual intervention can be error-prone and hold the review process back. So what if the review platform itself could automatically create new QC batches every time a review batch is completed using requested QC criteria? This would eliminate human error and ensure that samples always match those criteria. This automated approach could also easily conduct QC across all documents that meet that set criteria.
Two powerful eDiscovery features that are making document review QC workflow more efficient
- Share Batch – At any point during a review, a user can choose to share one or more portions of their current review batch with any person on the team or the entire team. This is especially helpful during early review assessment loops.
- Automated QC Workflow – This sets up the kind of template-driven, automated QC workflow we have described, monitoring for completed review batches, creating new QC batches that match the set QC criteria and assigning batches to QC team members. That template may look something like this:
- 10% of documents tagged as Non-Responsive
- 10% of documents tagged as Responsive
- 100% of documents tagged as Hot or Privileged
Streamlining the QC workflow process is a fundamental part of a best practice eDiscovery approach. As you’d expect, innovation-rich Casepoint gives you all the specialist functionality you need to deliver stand-out results.