July 15, 2011 | Daisy

Case Study – Features to Speed up the Review Process

The Challenge
Data to Review: 2.6 TB of data
Size of Review Team: 3 person team
Deadline for Review Completion: 45 days to review

While every matter varies and certainly there are many ways to tailor a review process and workflow, a recent experience with a review job was successfully performed in the Sfile platform by a small team of lawyers in California that we believe deserves special mention.

The following example highlights the methods where Sfile’s advanced capabilities with search and tagging features facilitate the review of large amounts of files and minimize attorney review burden.

This particular matter started with over 2.6TB of data that needed to be processed.  This bulk of data was culled down to a feasible data set through De-NISTing and De-Duplication.  The final set for review was roughly 600,000 e-mail and user files.


ESI Process and Analysis
Because of the strict time schedule, Sfile’s unrivaled processing speed was essential. Sfile's proprietary High Performance Computing (HPC) Parallel Processing Engines perform at top speeds of up to 200+ GB per hour, per single server. It took longer to directly upload the data than it took to process.

This top performing processing and analysis allowed the assessment that there were as much as 5 duplicates of each item within the data set. However, since custodial ownership of the documents was relative to the determination process, all the data needed to be brought into the Sfile review system.

Bulk Tagging
The initial step was to create a master categorization tag for the first unique document in the system.  With an improved feature that allows a reviewer to view the duplicate documents while looking at the first unique item, the initial data set review was decreased 80%. A unique tag was combined with the 40-50 keywords and custodians that were provided to create sub-categories to assist in speeding up the review process. 

Determining Duplicates at a Glance
Once the initial sets had been defined, the reviewers could review a single document and then make the decision to apply the determination to all duplicates or just that singular instance. 

Reports
To assist with deep data mining, reports and tags were generated that allowed them to view potential e-mail threads based upon captured Subject data in the ESI and dtSearch.  Applying that information to the unique category tag and sorting results according to needs allowed the users to identify possible near-duplicates very quickly and make singular and/or global determinations accordingly. 

Results
Review Team: 3 satisfied lawyers
Days to Complete Review: 25 days

Using this process, the client was able to finish the review in less time than was needed. The Sfile partner worked with their Sfile Engagement Manager to perform an elaborate process of data mining, saving search results, and cross-referencing data to gain a tremendous insight into the review items and safe meet the very tight deadlines