Predictive Coding & The “Risk-Averse” Attorney: Top 3 eDiscovery & Compliance Use Cases (Part 2)

Read part one

Fear of the unknown, the risk of something going wrong, and expensive pricing models are impeding faster adoption of predictive coding technology. Part 1 of this article explains why some of these concerns are well-grounded despite the fact that at least seven different courts have already addressed the role predictive coding technology can play in addressing eDiscovery and compliance challenges. Part 1 also explains how some of these concerns can be mitigated by understanding the important role of statistics and by choosing solutions that automate statistical calculations in a defensible manner.

Despite this guidance, some attorneys may feel overwhelmed by the current state of predictive coding technology and they will be inclined to remain on the sidelines until the technology and case law evolve. If you find yourself in the “wait-and-see” camp, this article just might convince you that the time to try predictive coding has arrived. Here in Part 2, the top 3 eDiscovery & compliance predictive coding use cases for the “risk-averse” attorney are discussed. Each of the use cases summarizes different situations where users may be able to reap the rewards of predictive coding while minimizing the risk of something going wrong.

Regulatory Inquiries

Regulatory inquiries by the Securities and Exchange Commission (SEC), the Department of Justice (DOJ), or other federal agencies might not be cause for celebration, but using predictive coding technology to respond to government inquiries more effectively and with minimal risk may be a silver lining. In a strange way, the interests of the enforcing agency and the party under investigation are sometimes aligned because some investigations are less adversarial than typical litigation. This is true in situations where civil investigations may yield less motivation for the type of gamesmanship that might arise in litigation. Gamesmanship doesn’t make sense for many private sector organizations who want to maintain a positive relationship with the government to avoid having a perpetual bulls-eye on their back. Similarly, the government must ultimately sift through electronically stored information (ESI) productions as part of their investigation even though resources tend to be limited. The more this information can be culled down to the most relevant files by the responding party, the less information the government must review.

In fact, a recent Wall Street Journal article about the proposed merger of Anheuser-Busch InBev NV and Mexico’s Grupo Modelo SAB illustrates the government’s willingness to work with parties interested in using new technology. In response to an inquiry by the Justice Department’s antitrust division, lawyers claimed more than a million documents would require review to satisfy the request for more information about the merger. Rather than reviewing all of the documents manually, the lawyers used predictive coding technology to streamline the process after receiving the Justice Department’s blessing:

“With the blessing of the Justice Department’s antitrust division, the lawyers loaded the documents into a program and manually reviewed a batch to train the software to recognize relevant documents. The manual review was repeated until the Justice Department and Constellation [another company involved in the transaction along with Crown Imports, LLC] were satisfied that the program could accurately predict relevance in the rest of the documents.”

An attorney representing Constellation and Crown Imports explained that the companies spent 50% less than they would have spent using more traditional means. A Justice Department spokeswoman added that the antitrust division has worked with other parties who choose to use this “new technology” to comply with civil investigative requests. She went on to state that the division has also used predictive coding technology for reviewing investigative documents internally. Although the Journal reported that agencies like the SEC and the Federal Trade Commission (FTC) were more guarded about their use of predictive coding, the article stated that the FTC acknowledged allowing the use of predictive coding on a “case-by-case” basis. In short, using predictive coding to help comply with a governmental inquiry or even a discovery request in litigation can be a safer haven for the risk-averse attorney when the other side agrees.

Internal Investigations

Similar to governmental investigations, many internal investigations require poring through massive amounts of information to ferret out the truth. Since many internal investigations are less likely to invite immediate scrutiny from other parties, they too may be good candidates for leveraging predictive coding technology. Investigators typically enjoy using tools like discussion threading, concept searching, and keyword searching to help them identify key players as well as hot documents quickly. The ability to use predictive coding technology in conjunction with these and other tools without scrutiny from other parties adds another powerful analytic tool to the investigator’s arsenal while introducing minimal risk.

Incoming Document Productions

Those who prefer to avoid the type of unpleasant bickering that overshadowed the first known case to address the use of predictive coding technology (Da Silva Moore v. Publicis Groupe) need not forgo using the technology altogether. Although the technology is largely viewed as a tool for segregating relevant and non-privileged documents prior to document production, that is not the only way predictive coding can be used. Predictive coding can be equally valuable for analyzing incoming document productions from opposing parties or non-parties. That is because the most advanced predictive coding tools rank documents by degree of responsiveness so attorneys can home in on the most important documents quickly. The resulting ability to assess cases faster and more efficiently makes case preparation easier, more comprehensive, and less expensive. Provided the particular predictive coding tool chosen is not too expensive or difficult to use, the technology may be a great way for attorneys to test the benefits of predictive coding without scrutiny from opposing parties or the court.

Conclusion 

Predictive coding is promising new technology that can save time and money while improving the accuracy of document review. Given the evolutionary state of predictive coding technology today, the quality and price of these tools may vary dramatically and most require the employment of an expert. However, that should not be an excuse for ignoring technology that could be superior to other technologies and approaches if that technology can increase efficiency, save time, and reduce costs. Rather than staying on the sidelines, a better bet is to choose the right predictive coding tool, establish a defensible process, and pick the right use case. That is a safe bet, even for the most risk-averse attorneys.

About the Author

Matthew Nelson

About the Author
Matthew Nelson is the author of the legal industry’s first straightforward overview of predictive coding technology titled: Predictive Coding for Dummies. He is an attorney and legal technology expert with more than a decade of experience helping organizations address electronic discovery, regulatory compliance, and other information governance related challenges. Mr. Nelson has written extensively about the impact of information growth on law and technology and his work has been widely distributed in publications including Forbes, Corporate Counsel, and the ABA Law & Technology Journal. He has also been invited to address a wide array of organizations including American Corporate Counsel, Nevada’s High Technology Crime Task Force, Stanford & Hastings Law Schools, and numerous mid-sized and Fortune 500 Corporations. He is a member of the Sedona Electronic Document Retention and Production Working Group, the Electronic Discovery Reference Model, and the California and Idaho State Bars.