Last month I participated on a panel at kCura’s Relativity Fest presenting real-world scenarios of Relativity use. The session received such a positive response at Relativity Fest that I wanted to share more broadly my story describing a case in which Lighthouse leveraged Relativity to fast track large volumes of data in response to a government investigation.
The background is that we were engaged to support an HSR 2nd Request review and production and also the related civil litigation. Deadlines for the HSR were short and unchangeable and the terabyte volume of the collection grew well beyond initial estimates. The review workflow we introduced needed to support multiple outside counsel and a review firm, each with differing focus, while also maximizing the use of overlapping work product. In addition to complicated review workflows, we were faced with demanding Department of Justice specifications for production and privilege logs as well as careful scrutiny of our technology assisted review (“TAR”) process and results.
Relativity’s strength in handling a large review dataset was showcased when, after collecting nearly 6 TB of data, our workspace grew in short order to nearly 4.25 million items. Relativity’s ability to handle a workspace that size with concurrent loading, exporting, and multiple reviews enabled us to avoid splitting workspaces and having to transfer work product between them to keep each in sync. We worked to devise an aggressive database optimization scheme to control the fragmentation that naturally occurs with nearly 100 users in the database. In addition to a large number of records and concurrent users, we were able to keep the database going with well over 700 fields and thousands of choices.
Several concurrent reviews were being conducted by different counsel – for Privilege, QC, and deposition preparation in the 2nd Request and fact investigation and deposition preparation in the civil matter. Relativity allowed us to develop custom review interfaces specific to each type of review, while still being able to reuse of some decisions made by different groups of reviewers. Relativity’s flexibility was crucial here, especially as the review evolved and field names changed or we needed to merge decisions into new fields. Granular security also played a role as certain information needed to be visible to one or more parties while excluding another.
In order to secure DOJ acceptance of the use of TAR we needed to both describe our process, including our validation method using Relativity, and facilitate an additional DOJ validation review. We harnessed Relativity’s random sampling script for both, using it to create statistically significant validation review batches of the TAR results from a third-party tool and create sample sets that the DOJ selected from to perform its own review in a separate workspace. Relativity’s flexibility to seamlessly integrate TAR results from another tool at several different stages of collection and review and our ability to use a Relativity-developed script as an important tool in our workflow allowed us to avoid disruption of the review process.
Pushing Relativity to track document decisions, report results to the client and their counsel, and facilitate generation of the privilege log was also essential to our success in this matter. A complicated matrix of tagging, field values, and textual input became the basis for review batching, identification of the production documents, and population of the data necessary for a defensible privilege log. The review and privilege log portions included use of Lighthouse-developed processes that are integrated into Relativity. Relativity’s ability to accept various input from other tools, relate these fields for review setup and result presentation, and export the data in various formats was essential to meet the demands of this complex project.
If you have experience pushing Relativity beyond its standard capabilities to accommodate large or non-standard workflows, I’d love to hear your story. Email me at email@example.com.