Who can blame corporate counsels for pushing back on litigation costs, especially since discovery requests are growing, and there’s exponentially more material to be reviewed as data and content proliferate?
Their pain is understandable: A Rand Institute of Civil Justice study of e-discovery costs found the biggest chunk – 73 percent – stems from the actual review phase. (The average cost of a discovery runs $3 million, another study by the Compliance, Governance and Oversight Council found.) Save money on document reviews and the entire discovery function starts becoming more cost efficient.
All roads lead to technology these days, and that’s where the solution lies for the document review process. Specifically, the Rand study pointed to supervised machine learning – the same kind of assistive technology that Esquify is built around – as having huge potential to streamline and improve the process.
But even though all roads lead to technology, they still tend to be less traveled – at least when it comes to document reviews. While we at Esquify are seeing a lot of interest on the client side on the efficiencies we can help them gain in time and money through our use of assistive solutions, the legal field – clients and firms – still has a way to go.
Dean Gonsowski, kCura’s vice president of business development, recently examined the matter in a blog post on the Fast Forward Labs blog, noting that data scientists are the likeliest drivers of machine learning throughout the organization. To shift attitudes within its legal department and capture the benefit of informed text analytics strategies, Gonsowski made three recommendation:
- Understand the technology- Among other things, the legal team needs to grasp the different “flavors” of machine learning and its role: “Machine learning and other text analytics tools help augment lawyers’ decisions. They do not need to take control of the process.”
- Prove its defensibility in court- Gonsowski notes several decisions where judges have specified the use of assistive technologies because of their “greater consistency, proportionality and cost savings.”
- Try it in cases that would be a good fit- Incorporating these techniques into a review strategy can prove them out more broadly. It helps, Gonsowski notes, to have a “thorough understanding of the best practices and proven workflows for the chosen technology...”
Gonsowski suggests that machine learning and assistive technologies are in the emerging stage among early adopters, but will become the standard for attorneys in the future.
We believe that future isn’t really so far off. We’re experiencing growing traction, particularly among corporate legal departments that are insisting their law firms use our services to make the document review process less costly and more efficient. Outcomes like a 90 percent-plus improvement in reviewer time and overall cost-savings of 20 percent to 40 percent are winning them over.