Legal Tech: How to Streamline Your eDiscovery and Plan for the Future 

If you're thinking that there's got to be a better, cheaper way of getting this information, you're right. Custodian questionnaires have proven to be an efficient, effective tool not just for uncovering where potentially relevant data resides, but also for gathering facts about legal matters as well. Legal teams can send questionnaires electronically to custodians anywhere in the world, allowing for quick, comprehensive replies. Responses supplied on questionnaires can be used to spotlight areas needing more attention, point counsel in the direction of additional people who might have relevant data, or simply provide helpful background information. In-person interviews might still be necessary at some point, but with the help of questionnaires, fewer interviews will have to be conducted, and those that are will be more productive.

Data collection is another aspect of ediscovery that was once done in person, but can now be almost entirely handled remotely, saving money and time. Once upon a time, technicians traveled across the country and internationally to collect data for legal matters, but even before the pandemic, that practice had dwindled significantly.

Between advancements in truly remote, forensically sound, data collection solutions and the widespread adoption of cloud computing technology, it's now possible to collect data safely, easily and securely from just about any resource or device anywhere in the world. Some rare cases might still require a technician to gather data on-site, but that should be the exception, not the rule.

Utilize Technology to Exclude Non-Relevant Data

A typical legal matter might involve the collection of hundreds of thousands of documents, of which only a small percentage will have any relevance to the issue at hand. The challenge is to make sure that the non-relevant documents are identified and excluded as early in the process as possible so that they don't take up precious (and costly) time in attorney review.

Targeted data collections are the first, and arguably most important step you can take to cut data processing and review costs from the outset. Using tools and processes such as De-NISTING and Known File Format (KFF) elimination, you can eliminate system files, program files and other background data that didn't originate from users, now at the very point of data collection, eliminating the costs of processing and filtering that data later in the process as has been done in the past. There's no question that these types of files are extraneous, so the more quickly you eliminate them, the better.

Once data has been collected for a legal matter, additional data processing and analysis tools can further reduce the amount of data that ends up being hosted and loaded into review platforms. The functions built into data processing platforms have been largely standardized, so the biggest deciding factor will be how well ediscovery professionals understand and use these tools to their full potential. In addition, advanced features like early case analytics, advanced email threading and cross-custodian near deduplication can drastically reduce the total amount of data loaded to review platforms.

Machine Learning-Powered Document Review

It is not uncommon for document review alone to incur over half of all ediscovery costs — sometimes as much as 80%. So, any technological tool that can efficiently carve away a chunk of those costs is money well spent. In addition to the early-stage tools mentioned above, artificial intelligence and machine learning technology can improve the accuracy of the review process while reducing the need for humans to personally review every responsive document.

Even the most experienced, sharp-eyed human reviewers are still human. We're not built for the repetitive task of reviewing thousands of documents, and boredom and fatigue are inescapable. Machines, on the other hand, are built for exactly that kind of work, and have become sophisticated enough that they can consistently outperform humans.

Machine learning systems (also known as technology assisted review (TAR)) can learn as they review data and make connections between documents that humans might not. Humans still play a vital role, however, by giving the systems ongoing input to inform the quality of their results. The combination of human guidance and machine intelligence can elevate the results and reduce your overall costs in cases of any size.

Yes, these services and software solutions do come at a cost. But the money you spend on the front end of the process will come back many times over by vastly reducing the number of documents that require human review.

The Value of Planning

Inefficiency is frustrating, particularly when there's a looming deadline and a lot of money being spent unnecessarily. When both human workers and financial resources are under extra strain, it's even more important to streamline processes wherever you can. By taking advantage of modern ediscovery technology and workflows, you can immediately take some of the weight off your shoulders and prepare for times ahead.

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Brian Schrader, Esq., is President & CEO of BIA, a leader in reliable, innovative and cost-effective ediscovery services and digital forensics. With early career experience in information management, computer technology and the law, Brian co-founded BIA in 2002 and has since developed the firm's reputation as an industry pioneer and a trusted partner for corporations and law firms around the world. He can be reached at [email protected].