Five Steps to Better Oversight and Control of E-Discovery Spend

What’s in your legal data warehouse? Don’t know? Or don’t have one? If you work at a law firm, there’s no imperative to create a mechanism to share data elsewhere—outside counsel concerns are winning cases. For corporate legal departments, however, it’s a problem: in-house counsel, legal operations professionals and even the c-suite are increasingly asking for more effective oversight and control over e-discovery spend.

“What gets measured gets managed,” the late management consultant Peter Drucker reportedly said. How, in practical terms, are corporate legal departments measuring and managing? Are legal departments incorporating business intelligence (BI) into their day-to-day operations to get the data and analytics they need to be more efficient and manage legal spend more effectively? Continue reading

Four Areas to Reduce Legal Hold and Collection Spend

With organizations allocating up to 50 percent of their legal spend to litigation, savvy legal teams are seeking new ways reduce their e-discovery costs. Improving legal hold management and collection is one place to start.

In this blog post, I will highlight the costliest areas of legal hold and collection per matter for organizations relying on a combination of vendors and firms to help manage the process. I will then compare the costs of these tasks to the costs of using automated cloud-based legal hold and collection software that offers a flat-fee enterprise license for unlimited custodians, holds and data collection. Continue reading

Legal Holds for Smart Teams: Tips for IT Professionals Working with Legal to Preserve Company Data

As I recently wrote about in Law360, when litigation or a government investigation looms, a corporation has a duty to identify and preserve data (documents or other electronically-stored information) that may be relevant to the matter. This requirement, imposed by the courts as well as government regulators, is known as a “legal hold”  or sometimes a “litigation hold.” It stems from the duty to not destroy relevant evidence that may be required for a judicial proceeding.

Increasingly, courts require legal departments and their outside counsel to supervise the preservation process and to certify that reasonable steps were taken. In most cases, lawyers must rely heavily on Information Technology (IT) professionals to execute the mechanics of the hold and ensure data is preserved correctly. After all, IT knows and works with the company’s systems, networks. And, if legal preservation obligations aren’t met properly, penalties for that failure can be substantial. Continue reading

How to Avoid Asian Language Pitfalls in Discovery

A surge in cross-border litigation and enforcement of antitrust and Foreign Corrupt Practices Act violations is subjecting many Asian-based companies to U.S. discovery obligations. While e-discovery is “business as usual” in the U.S., discovery involving companies in Asia is still relatively new—and rife with potential pitfalls.

When parties involved in cross-border litigation or investigations are faced with multi-language documents subject to discovery, including the challenging Chinese, Japanese and Korean (CJK) languages, they must understand how to accurately process and index CJK documents for proper search, review and analysis. Many Western search and review systems were not designed to capture the nuances of CJK language complexities. As a result, they offer sub-optimal search results, sometimes finding too many documents and sometimes missing important ones. An understanding of CJK differences can help you select the right technology and experts. Continue reading

How to Get More Miles Per Gallon Out of Your Next Document Review

How many miles per gallon can I get using Insight Predict, Catalyst’s technology assisted review platform, which is based on continuous active learning (CAL)? And how does that fuel efficiency rating compare to what I might get driving a keyword search model?

While our clients don’t always use these automotive terms, this is a key question we are often asked. How does CAL review efficiency1 compare to the review efficiency I have gotten using keyword search? Put another way, how many non-relevant documents will I have to look at to complete my review using CAL versus the number of false hits that will likely come back from keyword searches? Continue reading

In AI, No Evolution Without Evaluation

At the recent Legalweek New York AI Bootcamp Workshop, I was reminded of a very small, cheap pocket dictionary that I once bought at a book fair when I was in third grade. One day, while looking up definitions, I came across the entry for “bull.” Bull was defined as “the opposite of cow.” Curious, I looked up “cow.” It was defined as “the opposite of bull.” Nothing about both terms referred to bovines, gender or any other defining description. Just that bull and cow are each other’s opposites.

At the boot camp—designed to cover the foundation, use cases and legal considerations to separate the value of AI technology from “the noise”—I learned that “machine learning” is “not expert systems,” and “expert systems” is “not machine learning.” How is this any more helpful than my third grade dictionary? Continue reading

TAR for Smart Chickens

Special Master Grossman offers a new validation protocol in the Broiler Chicken Antitrust Cases

Validation is one of the more challenging parts of technology assisted review. We have written about it— and the attendant difficulty of proving recall—several times:

The fundamental question is whether a party using TAR has found a sufficient number of responsive1 documents to meet its discovery obligations. For reasons discussed in our earlier articles, proving that you have attained a sufficient level of recall to justify stopping the review can be a difficult problem, particularly when richness is low. Continue reading

Review Efficiency Using Insight Predict

An Initial Case Study

Much of the discussion around Technology Assisted Review (TAR) focuses on “recall,” which is the percentage of the relevant documents found in the review process. Recall is important because lawyers have a duty to take reasonable (and proportionate) steps to produce responsive documents. Indeed, Rule 26(g) of the Federal Rules effectively requires that an attorney certify, after reasonable inquiry, that discovery responses and any associated production are reasonable and proportionate under the totality of the circumstances.

In that regard, achieving a recall rate of less than 50% does not seem reasonable, nor is it often likely to be proportionate. Current TAR decisions suggest that reaching 75% recall is likely reasonable, especially given the potential cost to find additional relevant documents. Higher recall rates, 80% or higher, would seem reasonable in almost every case. Continue reading

The Rise of Business Intelligence in the Legal Department

I work with large corporate legal departments involved in large-scale and often repetitive litigation and regulatory investigations, and recently found myself wondering, “Why are corporate counsel using analytics with greater ease and confidence for individual litigation reviews, but not to manage e-discovery spend, track and manage data across cases to make more informed decisions, and improve processes and outcomes?”

Beyond using analytics and reporting tools for one-off cases, how many legal teams, including corporate legal operations officers, really track and manage data across all matters in real-time, at the push of a button? Why’s this so important, what’s holding them back, and how are forward-thinking legal departments addressing these challenges? Continue reading

How Good is That Keyword Search? Maybe Not As Good As You Think

Despite advances in machine learning over the past half-decade, many lawyers still use keyword search as their primary tool to find relevant documents. Most e-discovery protocols are built around reaching agreement on keywords but few require testing to see whether the keywords are missing large numbers of relevant documents. Rather, many seem to believe that if they frame the keywords broadly enough they will find most of the relevant documents, even if the team is forced to review a lot of irrelevant ones. Continue reading