OpenText’s Eric Willis and Adam Barr explain how the right legal management system maximizes the value of data, producing more-informed results with fewer demands on high-value custodians.

CCBJ: Describe the scope of the matters you work on.

Eric Willis: We typically work with medium to very large global corporations that are highly regulated or have serial litigation. For example, we see a lot of IP and commercial litigation.

Adam Barr: More broadly, we help manage a pretty wide range of legal data needs—everything from IP litigation, as mentioned, to employment matters, regulatory responses and internal investigations. Our approach is the same no matter what. Let’s focus on the best decisions for the business, the goals of the case and what the client wants to get out of it.

What challenges are your corporate clients facing?

WillisCorporate law departments are seeing a deluge of increasingly large and complex data sets. They’re also getting pressure from executive teams to run their departments like a business—being more efficient and working within budgets. But many companies still throw matters over the fence to outside counsel—sending their data to that firm, which may then send it to their preferred vendor or multiple vendors. Across their litigation profile, corporate clients may have data at any number of law firms or vendors. That creates inefficiencies and increases risk. Such a model also makes it nearly impossible for law departments to aggregate and leverage case data to spot trends, manage outside counsel and other vendor costs, and identify additional opportunities to better manage their department.

Barr: With the emergence of GDPR and, soon, our own domestic regulations, our clients have a growing burden to protect sensitive information. This is not only related to regulatory requirements around personally identifiable information (PII), but also their interest in protecting sensitive information from data breaches and insider threats, like unannounced products, unaccused products or financial reporting.

Getting their arms around the universe of sensitive data is very reactive process for corporate legal departments. Transitioning that reactive process to a centralized, efficient one produces better results, whether results are measured by cost or risk or data security.

How are you helping clients address these challenges?

Willis: There isn’t a technological silver bullet to address the sensitive data and other emerging problems our clients face. Where technology doesn’t get us all the way there, we provide the services and solutions to bridge the gap.

Barr: Growing demands can create chaos, so our approach is to simplify and centralize everything – streamlining operations, identifying where gaps and inefficiencies exist, automating processes and using, where we can, machine learning and AI techniques to hone in on important data faster. These are the goals OpenText Insight, an enterprise eDiscovery platform, and our enterprise services support.

Willis: The key to successful legal data management is centralization. As one example, rather than throwing data over the fence, Insight’s core repository houses documents and data that are likely to be reused from matter to matter. One of the core repository’s primary benefits is its ability to support the reuse of decisions—including redactions—and documents from prior cases. The core accommodates a collect, process and review once strategy, if you will, allowing our clients to produce these documents as many times as needed in current and future cases.

Particularly in IP litigation for large companies, for example high tech and life sciences, the same custodians are interviewed time and again across product lines and the same underlying technical documents are collected. In the traditional model, with each new case, those documents are collected, reviewed and produced again. That’s often not necessary in IP litigation where there’s overlap between product lines. We’ve been very successful in collecting those materials and reviewing them for their substance beyond responsiveness to a particular matter. For one client, we reviewed a few thousand documents once and have produced them many thousands of times. There’s been more than a five-fold return on investment to date.

Barr: Centralization allows us to cut out redundancies and, at the same time, build up information about the data as it’s used again. When you can look at custodians in a case and really understand them without having to look at hundreds of thousands of documents, it gives you an advantage from the start.

Willis: For example, perhaps a client has a custodian who is regularly involved in litigation. We know from past matters that 75 percent of this custodian’s documents contain unannounced products. We know we want to collect differently from this custodian, or at the very least, we know this is going to be a very expensive document review so we can make an informed decision about how we’re going to manage that custodian’s data.

Beyond the benefits of centralization, there’s tremendous value in standardization. That is, determining best practices, memorializing them early in the process, and helping enforce them. By having best practices memorialized, we can be the first line of defense in enforcing those standards. With one of our very large corporate clients, just creating those standards and driving them on their behalf helped bring the cost per decision for review down 83 percent.

BarrWhen everything gets handled in a similar way, you create more alignment with the client, their law firms and other vendors. It allows us to then work on gaps and improvements.

Explain the structure of your platform. How does the design create more efficiency?

Barr: OpenText Insight has evolved over the past few years because data volumes are growing so much. To have a system that can scale as volumes get into the millions or hundreds of millions, our clients needed something very powerful. Today, our platform can handle large volumes, and provides a good amount of flexibility in how we manage information.

Another advancement has been in the integration of machine learning. When the idea of technology-assisted review in our industry came out, people were afraid of it. Creating a machine-learning process with Insight Predict that is scalable and based on continuous active learning has removed much of the complexity. It’s changed the whole dynamic and economics of document review in our customers’ favor. Now, when they adopt it, they see it’s a game changer.

Willis: With better data categorization, statistical analysis, and automated services including redactions, we’re helping solve the challenges of identifying and protecting sensitive data upfront, whether that be potentially privileged documents, PII, trade secret data, or other guarded buckets.

OpenText Insight’s core also supports automation, whether that be automated data loading in inbound services or automated review workflows. Once data is in our workflow, we can move documents from phase to phase within the review, all the way to production.

Knowledge management is the final piece. It is only possible because we have the underlying core repository and knowledge OpentText and our clients have been able to extract from the data and documents. Gathering information and storing information across all of our cases for the history of time allows us to aggregate that data and provide meaningful reporting.

Reporting comes in two forms: the day-to-day reporting to run a project effectively, and the high-level reporting that helps corporate counsel make informed business decisions at the law department level. Our Insight Business Intelligence layer helps you better understand what types of cases are costing you more, so you can focus efforts and drive efficiency around those cases. We can provide law firm and vendor analysis that helps you understand which are costing you the most and which are giving you the most bang for your buck.

In what areas are you innovating?

Willis: One of the areas that we’re developing a solution for is how frequently and at what level the client is touching high-profile custodians. Custodians can get the mistaken impression that the legal department is not doing its job because every week, outside counsel asks them the same questions. We have lots of information about these custodians already, so we are focused on making the interview process and data collection process much less painful for these custodians—and for everyone involved.

While we continue to invest in review efficiency, we have great technology in place to support document review, from the smallest to the largest matters. As such, we are focusing much of our innovation efforts in those areas outside of review that have historically been neglected. We have already figured out how to effectively leverage past coding decisions, redactions, and even documents collected. We’re now exploring how best to retain, and importantly, use all the other things we learn from case to case—understanding the aggregate, and having available specific details where needed, to make informed decisions.