The Future of Ediscovery: Changes in Data Formats and Storage
This is the final post in our multi-part series covering our ebook on the ins and outs of ediscovery. In this series, we’ve covered the ediscovery basics, including the history of the Electronic Discovery Reference Model (EDRM); core technical ediscovery concepts; and the technologies powering ediscovery.
To wrap up our series, we’d like to share our thoughts on the future of ediscovery, including those changes we can expect to see in data formats and storage.
Changes in Data Formats and Storage
Discovery must necessarily stay current with corporate trends and best practices for data formats and storage.
As discoverable evidence has spread from papers in filing cabinets to word processor documents to emails to chats, electronic discovery has had to remain in lockstep. The cloud and modern collaboration tools have vastly increased the palette of communication options corporations may use; all must ultimately be supported in the process of discovery. If future entities use holographic displays to communicate, electronic discovery vendors will surely clamor to add hologram support to their processing tools.
Furthermore, we expect that cloud storage will also alter the way collections are done. Collection tools today are complicated beasts that must effectively hoist data stored in a broad array of on-premises and remote locations. As cloud computation and storage become increasingly pervasive across industries, the process of collection will actually become simpler. In a decade, forward-thinking companies will simply connect their cloud storage repositories directly to the processing pipelines of their discovery vendor of choice and be off to the races.
Increased Adoption of Cutting-Edge Computer Science
Discovery review and analysis will continue to track the cutting edge of computer science to make sense of the massive and increasing volumes of incoming data.
Electronic communication is easier to create than ever before, and with voice input, videoconferencing, and chat continuing to pick up steam, it will get easier still. Telecommuting and social networks will continue to broaden the opportunities for digital content creation. All of this data will be discoverable in the right context. The end result: larger and larger corpus sizes for discovery.
While corpuses will grow inexorably, we do not expect the court system’s timelines to lengthen proportionately. Discovery software will have to do more with less—and it will, by leaning more heavily on computer science. Discovery is a deep, multidisciplinary problem that draws from a rich range of computer sciences, often at the very limits of scale. It will benefit from advances in artificial intelligence, storage, search, distributed systems, data visualization, and human-computer interaction. All of these are areas of active research at universities today, and discovery vendors will increasingly find themselves reading the latest academic papers to get an edge on the competition. This bodes well for the state of the industry.
Improved User Experience
The entire process will continue to become more user-friendly.
Some enterprise tools become more esoteric as they grow more specialized, requiring deep domain expertise and training to use. Discovery is a slab in the bedrock of law and deserves far greater accessibility. It is essential to litigation, investigations, mergers and acquisitions due diligence, and more, and simply cannot be relegated to the domain of a few experts. We see the modern trend toward more usable discovery software persisting, potentially exposing tiers of complexity depending on the user, the use case, and the volume of data. Competition on user-friendliness is a good thing and can only aid in access to justice—and a lowering of blood pressure in lawyers and litigation support staff everywhere.
