Most core eDiscovery costs (outside of attorney review) stem from over-collection of electronically stored information (ESI). While direct collection costs can seem inexpensive, law firm Nelson Mullins notes that “over preservation tends to have its own costs relating to storage of large amounts of electronically stored information (ESI) and the resources needed to manage it; leads to increased downstream e-discovery costs associated with collection, processing, and review.”
Traditional eDiscovery workflows typically involve broad and manual collection efforts, followed by on-premise hardware-based processing, and finally upload to review. These inefficiencies extend projects by often weeks while dramatically increasing cost and risk with bloated data volumes and many manual data handoffs.
Proportionality-based eDiscovery is a goal that all judges and corporate attorneys want to attain. Under Federal Rule of Civil Procedure 26(b)(1), parties may discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. However, attorneys representing enterprises are essentially flying blind on this analysis when it matters most. Prior to the custodian data being actually collected, processed and analyzed, attorneys do not have any real visibility into the potentially relevant ESI across an organization. This is especially true in regard to unstructured, distributed data, which is invariably the majority of ESI that is ultimately collected in a given matter.
If accurate pre-collection data insight were available to counsel, that game-changing factor would enable counsel to set reasonable discovery limits and ultimately process, host, review and produce much less ESI. Counsel can further use pre-collection proportionality analysis to gather key information, develop a litigation budget, and better manage litigation deadlines. Such insights can also foster cooperation by informing the parties early in the process about where relevant ESI is located, and what keywords and other search parameters can identify and pinpoint relevant ESI.
A solution to these challenges is the utilization of index and search in-place technology. Indexing and search in-place in this context means that a software-based indexing technology is deployed directly onto file servers, laptops or even in the cloud to address cloud-based data sources. This indexing occurs without a bulk data transfer of the data. Once indexed, the searches are performed in a few seconds, with complex Boolean operators, metadata filters and regular expression searches. The searches can be iterated and repeated without limitation, which is critical for large data sets.
Mandi Ross, CEO at Insight Optix explained how she applies proportionality when advising lawyers and judges through custodian interviews, coupled with detailed keyword search term analysis based upon the matter’s specific claims and defenses. She noted that technology such as X1 greatly enables the application of her practice in real time: “The ability to index in place is a game-changer because we have the ability to gain insight into the data and validate custodian interview data without first requiring that data to be collected.”
But it is important that the technology employed truly enables index-in-place, with the indexes deployed directly onto the laptops, file shares or cloud servers where the data exists. Some providers will market their tools as such, but the indexing and searching actually takes place in their platform at a central location. Data must first be copied and collected off of laptops and file servers and migrated over the network to get the indexing engines. This does not scale for eDiscovery. For information about X1’s index-in-place technology, X1 Enterprise Platform, please visit us here.