Last quarter, we kicked off the inaugural eDiscovery Project Manager (PM) spotlight, highlighting some of the incredible talent powering client success in litigation and investigation projects. OpenText™ Discovery PMs are the magic behind the curtain, helping corporate legal departments, law firms, and even government agencies squeeze every ounce of horsepower out of OpenText Discovery’s award-winning suite of AI-enable legal technology. They live inside of OpenText™ Axcelerate™, helping clients design and execute the best workflows to accomplish different goals. Just as each law suit has unique facts and arguments, each project has nuanced challenges that good PMs will respond to and adjust for.
In today’s PM spotlight, we feature Matthew “Matt” Stavisky. A lawyer by background, Matt joined Recommind (now part of OpenText Discovery) in 2012. His experience working as a document review attorney exposed him to every major review platform on the market and was a crucible for learning to communicate with attorneys, judges, and other litigation professionals. Prior to entering law, Matt worked as a ski instructor where he was one of the first professional ski instructors to don a helmet to set a positive example for budding skiers. Now, a skier not wearing a helmet is the exception, not the rule.
How is a PM like a skiing instructor?
You can’t just strap on skis with no experience and still get to the bottom of the slope. Well, you can… but it’s going to be a bumpy ride. Rather, you should start slow. Take some lessons. Learn from an expert, who has years of experience in the industry. One method is abject terror and likely injury; the other can be a lifetime of fun.
Likewise, in eDiscovery you can’t buy an off-the-shelf application with no experience and still get to the end of the discovery process without some bumps and bruises along the way. In my role as a PM, I spend a lot of time training our clients and users not only on the technology, but on the eDiscovery process. As in skiing, there are a lot of ways to get down the mountain and the straight line isn’t necessarily the best one.
Walker Hartz, Matt Stavisky, and the entire OpenText PM team have been an incredible asset to our eDiscovery review process. They have been extremely responsive and accommodating to all of our eDiscovery needs. Matt has been tremendously helpful in coordinating projects with myself and external counsel. Matt is an excellent Axcelerate user training resource as well. It is clear that Matt has a great deal of experience with eDiscovery, Axcelerate, and litigation in general. I always feel comfortable with Matt managing my projects, and look forward to continued success with Matt in the future.
Dean Carilli, eDiscovery Specialist, Mount Sinai
On the importance of good equipment
Using the right equipment is extremely valuable but it’s nothing if you aren’t willing or able to change and grow with the new technology. I grew up skiing in the straight ski era. The longer the ski, the better. When curved skis came out I was initially reluctant to switch but once I tried them I could never go back. Combining the new technology with good technique made carving turns so easy it felt like I was cheating.
eDiscovery is the same. I started as a document reviewer 13 years ago. At that time most workflows involved a linear review process. That is basically a straight-line review of each and every document. For some cases, that works fine, but in general its far from the most efficient way to find the relevant documents for a lawsuit. I was exposed to Axcelerate when the team was still pioneering the use of AI for eDiscovery. We called it predictive coding and it basically learned from human review decisions to “find more like this.” The machine learning algorithms were doing the work of hundreds of reviewers. I saw this trend evolve in real time and I thought that as a document review attorney, I was about to become obsolete. I knew it was time for a change so what better place to go than the company pioneering the technology? That’s how I landed at Recommind (now OpenText).
Since then, AI has transformed the legal industry, but in ways I didn’t expect. Instead of document reviewers being obsolete, they became an integral part of the discovery process. Here at OpenText, we use a supervised machine learning process where reviewers code a couple documents as relevant or not relevant, the AI learns from those decisions and suggests additional documents that may be relevant, and the cycle repeats. To try to prevent bias from the reviewers, my approach to document batching [the process of assigning groups of documents out for review], is that I don’t even tell the reviewers that it’s an AI recommending these documents. I just batch them out and say: “Please review.” As they complete the process, the AI makes better and better recommendations until we exhaust all of the relevant data and we can confidently say the project is complete.
But now that the use of machine learning in law is mainstream, equipment is more important than ever. Different eDiscovery applications approach AI in different ways. And humans approach AI in different ways as well. Some legal professionals still look at AI with skepticism—either worried it might take their job or make a mistake. While AI is an important piece of equipment, it isn’t the “easy” button. You can still incorporate traditional search tools: keywords, phrases, and metadata. As an eDiscovery PM, my job is to help the review team put together an efficient and effective review strategy. Often that strategy involves a combination of old techniques and new. I may, for example, take a set of AI suggested documents and then run some search terms over the results. This could help me get a set of suggested documents that are more likely to be relevant.
Keeping the edge in a changing ecosystem
A good foundation is key to success. Don’t skip the basics. Understand how and why applications are setup a certain way so you can explain to clients and deliver the best service possible. I started as a case analyst and worked my way up responsibilities, contributing to different departments like training and Cloud Services. At each stage of my career I got to develop new skills. I learned how to organize projects, how to use the technology, and how to teach. A good PM has to synthesize all these skills in their delivery.