LexisNexis has acquired Ravel Law and I’ve been seeing it discussed from every angle in both the general business press as well as my favorite sources for library and legal news. Ravel Law’s data algorithms, predictive analytics and data visualization for case law supported by Lexis’ financial resources and market clout could make for a powerful combination.
Predictive analytics has been a hot behind-the-scenes topic for quite some time now. Sadly, it has been overshadowed to a large degree in the popular press by the more controversial and “sexy” topic of artificial intelligence. Perhaps this merger will finally bring the topic to the forefront.
Many of us have been watching Ravel grow with great interest and excitement. We have also watched two things with a degree of concern:
- The legal industry’s somewhat nascent regard for predictive analytics
- Ravel’s apparent struggles in gaining traction within law firms
This merger could very well tackle both issues at once. Lexis has the power and reach to bring Ravel into firms of all sizes and the marketing machine to make predictive analytics a “household” term in the legal field. Here’s hoping!
LexisNexis / Ravel comments from research experts
I asked the LibSource virtual research team for their take on this recent LexisNexis acquisition. As daily users of these systems and others to service our clients in law and business, they are the true experts!
James Hurley, Deputy Director and direct supervisor of the team had this to say:
“In my opinion, if Ravel Law’s “bread and butter” will be fully merged into Lexis’ already vast collection of authoritative materials, this is a win/win. With any major incorporation of one product into another, there are bound to be trade-offs for all interested parties. We’ll have to wait and see how this one plays out.”
I’m going to parse the other comments we got from the LibSource legal research team based on a few themes that emerged.
Admiration for Ravel Law and the Caselaw Access Project
One researcher expressed her admiration for Ravel:
“I’ve long thought Ravel Law had tons of potential, even way back when it used to link out to Wikipedia (I think that was it). It didn’t have the robust historical primary law collection then, but it made case analysis visually accessible in a uniquely refined way.”
And there is concern about the possible outcome of the Ravel Law / Harvard Caselaw Access Project:
“This is a social and culture issue, not just a commerce question for me. I was disappointed, but not surprised that Ravel was purchased by one of the big 2 or 3. Although both Ravel and Lexis have made public statements about their continued commitment to the “open access for all” to the law, I am at best cautiously optimistic.”
Legal research competitiveness
The concern that the big players will continue to get bigger as small players either get acquired or knocked out of the competition came up from a few researchers:
“If every innovative upstart is bought out, it is so easy for change to go in limited directions. Not to mention that competition is critical to keep legal research economical. We all know when there is little to no competition, it’s the seller that sets the price, not the market.”
This view is supported by another researcher who also remains hopeful of the good that could happen:
“My general verdict is that things become lower-quality and higher-cost the second they get bought by Lexis. That being said, it’s always possible that with more cash, Ravel will have the means and resources to do some really cool stuff with analytics and machine learning.”
Regarding the cost side, my colleague Robyn Rebollo at CCM offers her assessment and advice to subscribers of both Lexis and Ravel.
Legal research has always been dominated by Lexis and Westlaw, yet legal startups have been shaking things up. No doubt there’s a whole new crop of college students sitting in their dorm rooms, much like Ravel Law’s founders, thinking of innovations that will be the next disrupters.
Integrating Ravel Law data analytics and visualization
Improved analytics and visualization are exciting capabilities, for both legal researchers and lawyers, and it’s the reason behind this acquisition. Along those lines, the topic of integration came up with a few of our researchers:
“I’ll be interested to see whether Lexis integrates the technology into its own case law collection, or if it lets it continue as a standalone product, like it did with Intelligize. The press release makes it sound like a fuller integration, which will give Lexis a leg up in case law versus Westlaw, which I think it desperately needs. If integration into an existing product is the company’s plan, then both researchers and clients win.”
How Lexis has handled Intelligize was included in another comment on integrating Ravel:
“Intelligize is another example of a recent acquisition, and right now it remains as a stand-alone product. I think the key with Ravel Law is taking its power and data-driven functionality, which attorneys and researchers love to have at their fingertips, and putting it behind the wheel of what Lexis already excels at.”
Yet there is also a problem of “bloat” and added complexity:
“While I fully appreciate the breadth and depth of Lexis and Westlaw, even the simplest need requires multiple steps. And the introduction of AI will certainly add to the complexity at least in the short run.”
“As a user of the free version (of Ravel), I have to say it was really nice not to jump through so many hoops to get to a needed case.”
However LexisNexis chooses to add Ravel’s technology into the family, we are hopeful that usability remains top-of-mind.
Artificial intelligence and machine learning in legal research
One person on the LibSource research team shared an insightful view about leveraging the best of every legal support resources to address both the logic of law and the ambiguities:
“I’d like to see researchers and data scientists working more closely together on curating data sources and generating actionable deliverables. I think discussions around the idea of the law as being both a logical machine (a, therefore b, therefore c) as well as a system of values and ambiguities (a, but we cannot ignore caveats d and e, and f is clearly an unprecedented circumstance) are fascinating. Data analytics and machine learning have the potential to really alter the course of that conversation.”
But at the end of the day, trust and reliability matter the most, especially as research technology and information services continue moving forward as the road is being built:
“Attorneys love analytics and easy ways of slicing and dicing facts and figures. And while they’re largely interested in big picture trends, they also need to feel confident that such conclusions are based on reliable and consistent data sources. This goes for librarians and researchers as well. Once we find either missing or duplicative data, it’s hard to trust a resource again.”
Without trust, legal predictive analytics could inflict much more harm than good.
As active users of a variety of legal information tools and services, we will continue to monitor LexisNexis, Westlaw, Bloomberg and other players joining the field.
Meanwhile, don’t hesitate to contact us with your own questions and comments. I’d love to hear your opinion!