Review stages allow review managers to organize and track documents throughout the review process. This involves creating and prioritizing review stages, establishing parameters for reviewing documents, and assigning reviewers.
By organizing documents into review stages, you can control user access to each stage, customize the review decisions, and monitor the progress of each stage.
In order to better understand how to leverage review stages, we will start by reviewing the fundamental concepts that govern how stages work. We will then go into step-by-step detail about how to use review stage attributes to optimize your review.
A review stage is a manner of organizing documents for review for a specific purpose. You can have multiple review stages, but each review stage is completely independent in terms of documents being marked as complete and metrics. However, through the use of search syntax, you can have documents flow from one review stage to another.
Within a stage is a source. Sources are a specific set of documents to be reviewed. Sources can be prioritized within a review stage and the documents within each source will deduplicate against the documents from other sources within the same stage.
For example, say you need to conduct a 1st round review on a targeted set of documents collected from your client. You set up a review stage called “1st Round Review”. Within that stage, you can have one or more sources derived from foldered documents, ad-hoc searches, and/or saved searches. In this case, let’s say you wanted to focus on three groups of documents:
- Any documents dated between 01/01/2001 and 01/01/2002
- All emails (regardless of date) where Vince Kaminski, Sara Shackleton, or Richard Sanders are the custodians
- All Word and PDF documents containing the terms contract(s) or agreement(s)
Each one of the above searches can be a unique source within your 1st Round Review stage. While the documents within the various sources may overlap, DISCO will automatically deduplicate those documents so your team only reviews each document once. If you did want the same documents reviewed more than once for different purposes, you can create a separate review stage for each additional workflow.
You also have the option to rank the sources, which will determine the priority order for batching. Any documents existing in more than one source will be included in the highest ranking source. Additionally, if you choose to group your review stage by source, you can add security to the source groups so that they can only be reviewed by designated reviewers.
In the example above, you can rank the sources so that any duplicate search results are contained within the source, which focuses on emails from Kaminski, Shackleton, or Sanders. Let’s say you only want Ann, Bob, and Charles to review these key emails. You can set the security so that they are the only reviewers that can pull these batches of these documents for review. For the remaining two sources, you can rank them so that documents containing the words contract or agreement are batched first, followed by any documents from the 2000-2002 date range. These documents can be batched out to any member of your review team.
In addition to versatility in establishing contents and priorities, review stages utilize just-in-time batching. This means that a batch is generated at the moment a reviewer requests it. This reduces batch administration time and allows for sources or priorities to be updated during the course of the review.
The searches in the above example returned more than 200,000 documents, all of which are part of the 1st Round Review stage but not yet placed into discrete batches. What if you learned that your date range search was incorrect but the review has already been started? DISCO allows you to go into the 1st Round Review and update the date range search. Once this change is made, all new documents meeting the revised search criteria will be brought into the review stage. When a reviewer checks out the next batch, they will be assigned documents that reflect the revised search criteria. DISCO's ability to adjust review stages and recalculate the documents being batched also plays a key role in an AI predictive prioritized review.
Once a batch is checked out, it is considered to be “materialized." Materialized batches will not be affected by any changes to the review stage contents or prioritization. This ensures that documents are not altered while the reviewer is conducting the review.
The last key concept to understand about review stages is that once you set the content, priority, and create your decision pane, there is nothing more to do than monitor the review. Reviewers will be able to check batches in and out as needed. You will be able to reassign a batch if required, but otherwise, it is not necessary to prepare batches of documents for your reviewers. Again, even if you update the stage or more documents are added to the database that meet your criteria, DISCO will automatically update the review stage and ensure those documents are batched out. If a reviewer checks in an incomplete batch, DISCO will automatically re-batch any documents that are not finalized.