Transparency in E-discovery? Save It for Your Clients
Disclosing your e-discovery process won't foster cooperation from opposing counsel, but your clients will love you for it.
February 13, 2018 at 08:00 AM
6 minute read
Civil litigation doesn't have to be uncivil, or so the idea goes. In the spirit of cooperation, well-intended judges and discovery practitioners will often encourage litigants to share as much information as possible about how they plan to meet their discovery obligations. Yet such disclosures can turn out to be counterproductive to cooperation, triggering unnecessary disputes and costly motion practice.
To be certain, communicating clearly and accurately in meet-and-confer conferences (mandated by FRCP Rule 26(f)) is both appropriate and expected. Further, in symmetrical litigation—where both parties have to collect, cull, review, and produce similarly-sized data volumes to each other—it seems only logical to proactively demonstrate the kind of openness you hope to see from the other side.
However all this transparency adds risk: The more you disclose about your discovery process, the more data points there are for opposing counsel to challenge. Did you miss any steps? Fail to document any issues or exceptions? Change course on your predictive coding (aka technology assisted review or TAR) protocol? Any divergence from, or perceived inadequacies in, your discovery plan could trigger challenges down the line in the form of a motion to compel or other demands for additional discovery.
Litigator Anna Mercado Clark, a partner at Phillips Lytle, has seen the effects of “varying degrees of transparency during the meet and confer process.” She says, “Cooperation should not result in one party exerting extensive control over another's discovery process or the application of a heightened discovery standard.”
Yet this is what can follow from excessive openness during discovery—and the advent of predictive coding has brought the issue of transparency to the fore.
|The Balance Between Discretion and Transparency
“Courts are split as to the degree of transparency required by the producing party as to its predictive coding process,” writes Magistrate Judge Katharine Parker of the US District Court for the Southern District of New York in a November 27, 2017 court order in Winfield v. City of New York.
In the ensuing 28-page opinion, the court considers and rejects a series of plaintiffs' requests for additional disclosures surrounding the city's allegedly flawed predictive coding process. Yet, in light of a series of documented discovery missteps by the city, the court is persuaded to provide an additional measure of transparency to plaintiffs in the form of result validation: It directs the city to deliver random samples of non-responsive, non-privileged documents for the Plaintiffs to review.
The balancing act performed in Winfield follows a five-year body of case law consistently affirming the right of producing parties to use predictive coding, yet offering limited and sometimes inconsistent guidance regarding process transparency.
In Dynamo Holdings v. IRS Commissioner (2014), Judge Ronald Buch of the United States Tax Court issued a full-throated endorsement of a producing party's discretion to decide how to meet its discovery obligations, including with the use of predictive coding (which had been challenged by the IRS Commissioner as an “unproven technology”):
“[T]he Court is not normally in the business of dictating to parties the process that they should use when responding to discovery. If our focus were on paper discovery, we would not (for example) be dictating to a party the manner in which it should review documents for responsiveness or privilege, such as whether that review should be done by a paralegal, a junior attorney, or a senior attorney. Yet that is, in essence, what the parties are asking the Court to consider–whether document review should be done by humans or with the assistance of computers.”
Intriguingly, however, a follow-up opinion nearly two years later showed the dubious fruits of transparency in this case, as the court considered and denied a motion from the IRS to compel a full release of all of Dynamo Holdings' collected documents. The opinion details how the company went to great lengths to satisfy the IRS with broad productions and disclosures over a protracted period—even letting it guide the predictive coding process itself—only to have the IRS ultimately reject the results altogether.
And all of this after an undeniably open and collaborative review process.
|The Better Place to Direct Transparency
Openness about discovery does have its place, however, and that place is with corporate clients eager to know more about their outside counsel's efforts. In a 2017 survey commissioned by OpenText, Ari Kaplan Advisors interviewed 35 corporate legal operations professionals from primarily Fortune 500 companies. Only 46 percent of them reported having sufficient visibility into the discovery processes of their outside counsel. Indeed, many interviewees indicated that they rarely receive valuable discovery reports from outside counsel (even as they reliably receive bills from them).
Modern discovery platforms with business intelligence (BI) technology make it far easier than ever before to visualize and report on the status of discovery, including the results of predictive coding for prioritized review. Legal teams (without SQL or other specialized skills) can generate up-to-the-minute charts with metrics on data volumes, progress, and review efforts, including who tagged what, when, and how.
Even further, BI visualizations let legal teams prove their discovery efficiency—or lack thereof—with simple metrics that show whether they're spending their time reviewing mostly relevant or irrelevant content. For example, a 50 percent efficiency score would indicate that 1 of every 2 documents reviewed by humans was confirmed relevant, a testament to the team's effective culling and use of prioritization technology.
Sharing a positive efficiency score with your client is a great way to demonstrate accountability and ensure satisfaction through what is typically the costliest phase of any matter. And showing consistent results across multiple matters is a great way to ensure you'll always be their first call for outside counsel.
That is a kind of discovery transparency that is both sorely desired and likely to support a sustained, cooperative relationship.
Hal Marcus is the Director of Product Marketing for OpenText Discovery. A licensed attorney, Hal practiced as a Wall Street litigator before commencing a career in technology that now spans over 20 years. He writes about practical applications of artificial intelligence, machine learning, advanced analytics, and business intelligence, particularly in the realms of information governance, e-discovery, and compliance.
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