In this week’s podcast, LEGALTECH MATTERS host and legal industry analyst Ari Kaplan talks with Andrew Shapiro-Zysk, Senior Manager for Reporting and Data Analytics at Berry Appleman & Leiden, about the skills that are most valuable for law firm data professionals and how they collaborate with their peers in knowledge management, practice support, and training. Also, how automation, data science, and AI initiatives can create a competitive advantage for a law firm. Read transcript
Meet Our Guests
Attorney and legal industry analyst
Ari Kaplan is an attorney, author, and leading legal industry analyst. As the host of his own long-running Reinventing Professionals podcast, he has interviewed hundreds of leaders in the legal profession since 2009.
Senior Manager for Reporting and Data Analytics, Berry Appleman & Leiden
Andrew is a business intelligence professional with over 14 years' experience in the legal field with a focus on US immigration law. He received a law degree from the University at Buffalo School of Law.
Welcome to LEGALTECH MATTERS, a Litera podcast dedicated to creating conversations about trends, technology, and innovation in modern law firms and companies - big and small.
00;00;15;13 - 00;00;31;15
Welcome to Reinventing Legal. I'm Ari Kaplan, and I have the privilege today of speaking with Andrew Shapiro-Zysk, the Senior Manager for Reporting and Data Analytics, Berry Appleman & Leiden. Hi, Andy, how are you?
00;00;32;03 - 00;00;33;28
I'm well, Ari. Thanks for having me.
00;00;34;10 - 00;00;42;25
So, it is my privilege and I'm looking forward to this conversation. Tell us about your background and your role at Berry Appleman & Leiden.
00;00;44;07 - 00;01;10;04
My background is primarily a legal one. Not surprisingly, given the title of the podcast. But I didn't start out doing data analytics and reporting, which is what I do for Berry Appleman & Leiden. As you noted, I'm the Senior Manager for Reporting and Data Analytics. I oversee all of the reporting of the data crunching analysis for our clients, for our internal legal teams.
I have a team of about a growing team of about, I think about 11 people now and we manage all of the data needs of our firm and our clients. My background, I started out as a Poli-Sci major and then went to law school. But in between Poli-Sci and my undergrad in law school, I worked for five years at a boutique immigration law firm in Buffalo New York, right on the border and primarily interested in immigration law, which is what Berry Appleman & Leiden specialized in.
And then after I graduated law school in 2008, unfortunately entered a business market in 08 that was the recession, and jobs were hard to come by. Having just passed the bar exam and so I took some contract positions for a while. And one of those was working for a large multinational corporation, doing reporting data analytics. And I had no background in it, but I got trained on the job.
And I did that for six years. And then I heard of a position in Boston for somebody who had an immigration law background, as well as reporting data and analytics background. I was like, hey, this is perfect. This is the melding of my experience to date, my career. And that's sort of when I started doing this, Berry Appleman & Leiden is my second immigration law firm doing this type of same type of work. Different at BAL but could talk about that. But yeah, I've been doing it now for in this sort of current role, probably for almost nine years.
00;02;47;02 - 00;02;56;01
Given that you've served in a technical role at both a corporate legal department and a law firm, how do the two types of organizations treat data differently?
00;02;57;10 - 00;03;27;10
I mean, I can only speak to my experience, which has been at one large corporation. While I was there the reporting was mainly I mean; it was mainly around some case management in terms of what is our inventory of work that we have. But it was mainly focused while I was there around the financial aspects. So, a lot of, as you may know, a lot of large corporations you know, utilize huge amounts of outside counsel assistance.
And the company I was working for in the health care industry had to engage outside counsel for licensing, for risk management, for employment discrimination, and you name it. And so, they needed a way to manage all of that billing and all of that case management was all these hundreds of small accounts, small law firms across the country. And that's where I came in and managed the web-based application off the shelf application that they had licensed.
And I sort of fell into the role of administering it, as well as administering the reporting aspect of it. And that was really mainly where we crunched the data. Things may have changed since then. I mean, that was, I said, almost going on nine years ago. But yeah, it wasn't so much crunching big data or forecasting at least when I was there, was more around the financial end of things.
00;04;22;05 - 00;04;29;20
You and I share the fact that we both got degrees in political science and then went to law school actually doing a double major.
And I mean, who does this in our high-profile lawyers?
00;04;32;22 - 00;04;51;13
I thought that getting a political science degree would lead me to law school. But then I did economics thinking I needed something practical and now you're doing data analytics and you're crunching financial information. What skills are most valuable for law firm data professionals to have in this current market?
00;04;52;21 - 00;05;32;10
Depends what type of role you're playing for somebody in my role, which is more of a managerial supervisory type role for the big picture. For me, it's one you have to be able to see the big picture, understand business. I understand what the business needs. I always say, and this may come up later in the conversation, but I'm a true believer that in order to be successful doing data analytics, you need to be both a data analyst, but as a business analyst as well, you need to know the subject matter to be a subject matter expert in terms of not fully expert, you need to be at attorney level, but you need to know what your firm or business does. What do they sell, what do they offer, how do they do it, what kind of data they track? Why is it important? What are the trends in the industry? What might they need to know? Or developments, especially in the kind of law I'm in - administrative law. Government's constantly changing things which have an impact could ripple across your clients.
And so, my having a legal background and immigration law specifically allows me to be successful in what I do and understand in sort of anticipating what the firm might need or our clients might need. So having that knowing the business is very important in my opinion. Also, I think some basic skills are around organizational. I think one thing that benefits people who have a legal background is if you're studying for the LSATs, you know, you those logic games, everybody, so that when they're preparing for the real set, that kind of thinking comes in very handy when you have to think about how am I going to get to this data I need, what kind of I need to join data from this table to this table. And if things think about how to make connections in sort of the abstract. And I found that's helped me very much. And then the managerial management level also knowing how to do the job that you're asked to do. So granted, I'm not a SQL expert. I'm not a Python expert or a lot of the other tools out there, but mean I can do some pretty good SQL. I'm learning. And you know, but I know Python. I know power be. I'm not an expert in it, but I know enough of it that when I ask my team to do something, I know what I'm asking. I know it's possible not being so disconnected from what's happening on the ground with your team being able to understand how the different tools work that they have access to, how they can use the data differently.
So, educating yourself if you don't have a background in data analytics, but even if you do one staying current with the business, but it's also staying current with the technology out their best practices within the data industry that allow us to be successful.
00;07;44;12 - 00;07;49;17
Where can people most effectively obtain some of these skills?
00;07;50;26 - 00;08;11;05
Depends where you're coming from. If you're coming from, you're already in the legal fields and the field you want to get into. If you're already with the law firm reaching out to the data team you have at your firm, if you do have one and asking to learn more about it or have a good old fashioned and informational interview.
Right, or seeing how you can use their services more, involve more sort of an initial step and then there's a lot of really valuable online trainings available. When I say that I'm, you know, one of my growth, all of the things I'm doing this year to help me grow as a professional is to really learn Python well. And so, I there's a site called Udemy, which has great meaning.
It's a huge amount of offerings and everything you possibly imagine when it comes to depth, analytics and reporting, very inexpensive and very thorough. And there's other sites like that. There's also a site called General Assembly, which is in-person, where you can go in different cities and sit in classes and learn. That's actually how I learned SQL many years ago when I first started doing this.
So yeah, there's a lot of great stuff out there to help you learn and a lot of the tech is even open source, too. So, I mean, there isn't necessarily a financial barrier to entry necessarily. A lot of the trainings are inexpensive so yeah, I think that's where you would start. Summarizing, I'll find out what your firm is already doing.
If they're not doing anything, maybe find out what other firms are doing and then, you know, start educating yourself.
00;09;29;18 - 00;09;38;25
How do law firm professionals in data analytics, knowledge management, practice support, and general training collaborate.
00;09;39;29 - 00;10;03;26
This is something near and dear to my heart that I do very well at BAL. If I can have a shameless plug there, it's actually one of my most enjoyable aspects of my job at BAL. We have one of our values, at BAL that was called one BAL, which is the idea that across the firm, whether it's different legal teams or there's different operational groups, we all work together to push forward the mission of the firm.
And I love working with our knowledge management group, our practice support group, our product management group, and the way we work together. The reason why I love it so much, because it's so critical given to be so much more successful in your data offerings, the value you bring to the firm, if you're not shy and you're enthusiastic about working with these other groups and they all sort of feed into each other.
So, like the way I like to think about it is a wheel you have, what data are you collecting it and why are we collecting it? That's sort of what your KM group comes in, your knowledge management. They're the ones who are staying on top of developments in the legal field. In our case, immigration law, they're the ones who are working with their product management group to ensure that we're capturing these data points in our proprietary immigration case software management tool.
And I'm usually involved in those conversations because I'll know a lot of times what the business leaders are asking me to report on. And so, I'll get together with our KM group and say, hey, are we planning to roll out some updates to and capture this data by using some of the data we should be capturing to respond to this development?
Or this business need and then we work with our product management group to update our different applications to capture that data. And are there better ways of capturing it? So maybe we are making it a required field. Maybe we want to maybe just want to build business logic. We want to build it around, make sure it's easy to capture and capture that the way we want to capture it. And then I work with our practice support group whose job is to sort of oversee the work that our paralegals, our migration assistants are doing. And so, they're the ones you're saying you need to make sure you enter this data that's critical to what we need to report on. And if you're not putting the data and even then, we've just created spaces to collect it, if you're not doing it, it's garbage in, garbage out when it comes to reporting.
So yes, you can see it's sort of like we all have to work together if we're going to be successful. Otherwise somebody could come to me and say, Oh, I need to report on X, Y and Z, but I might be like, Oh, well, either we don't track that on our system, sorry, or we do track it, but no one's filling it in and so having that synergy across those teams, I think is just it's super critical.
And it helps me too, though, because then I know also at the same time, like what's bubbling up with our KM group. What are some initiatives that our support group is doing to increase data entry or some things changing that maybe I need to know about? Maybe weaving or reporting on DAB, there's a better way of doing it based on how the teams are entering or where they're entering it.
Having those relationships, I think is critical.
00;12;39;24 - 00;12;44;04
What kinds of matters do you apply new business intelligence tools.
00;12;45;14 - 00;13;25;18
For right now? As you may know, the big I don't want to say hype because it's real is machine learning. It's around forecasting, it's around being able to take large amounts of data and basically build a model that will learn as you enter more data into it. And I mentioned forecasting, so I can give you an example. So, let's say you file a certain type of immigration application for certain immigration benefit, and you want to know based on a number of different factors, like what kind of job your client is applying for, for this for national, what's their educational background?
Where's the job located in the country? Different factors you can take you know, account that you'll matter to the government. And then basically it is you can create a model that says, okay, plug in all this data and keep doing it. And give us the opportunity to predict what is the likelihood of our success on approval or denial of that case based on these factors.
And over time, as that model crunches that data you get to know, okay, we now know that in order to minimize the risk of denial, fifth client says, oh, we want to apply for this position in this industry or this field, or we can and they have this educational background, we can say, Okay, well, we recommend that we put them in this job, or we recommend that they're not going to be successful.
They're going to need to at least have two more years of experience along with their bachelors or whatever it may be. But, you know, taking that model that tells us allows us to predict likelihood of something. So that's one thing where a lot is going on right now. Also, another big one is automation and that's where machine learning comes in as well.
And also bringing data scientists in in order to build intelligent models, to predict things and take action which helps you be faster, helps minimize where you do staffing. So those are, I think are two huge ones, too. I mean, obviously, one that's been going on for a while now has been dashboards, an interactive dashboard where you're not just providing somebody a report for them to look at and Excel, but you're basically aggregated in that data, underline them to slice and dice it on their own using tools such as Microsoft Power PI or Tableau or just some other ones out there.
Tableau and BI are the big ones right now. Also, there are some other tech on there are around natural language searching. So basically, you take a database, you overlay an application that allows end users to do natural language searches like they wouldn't Google and basically mine your data that way. So, I mean, there's a lot of tools out there, but yeah, you can use them in different ways if you need just to provide somebody a very basic report of this is what you have open and here's the status of it.
Then you can use a good old SQL and give them an Excel spreadsheet if they're a VP or a senior partner and they want to be able to have a 10,000-foot view and drill down on a bit if I want to do a dashboard. If you were working with your robotic process automation team to automate things or to do a more predictive analytics, you might want to veer in the data science machine learning area.
So, depending on what you're trying to do. So, there's a lot of opportunities to apply the right track.
00;15;59;03 - 00;16;04;10
Are there key types of information that should be on every legal professional's dashboard?
00;16;05;18 - 00;16;25;07
Yes, I mean, the two big ones that jump out obviously are your inventory. What cases do we have open more cases are in progress. What cases can we close out and see some kind of heatmap to identify cases that are in a bad position or could be in a bad position soon? If you don't take action, maybe something's overdue.
Maybe something's going to be overdue. Maybe something has been touched a while and it's getting stale. Make sure you identify those. So, I think inventory and sort of the status of your inventory. As well as financials. Any partner, senior attorney or is going to want to know how are we doing on billing? What do we have hanging?
What can we bill on that we haven't billed for and then on top of all of that, I would say and obviously, there's other things you can do, but those are the two big ones. But then not just providing that data as it is but also being able to take that data and say, okay, this is what we're doing right now.
What was it like last year? What's the year over year? What's the month over month? How are we trending that gives context to the data and allows you to see like, okay, we're at 2.4 million. That's great. Oh, actually this time last year or three. So not so great. I think giving that context is certainly important. And then the nice thing about a dashboard is you can drill down.
So, if someone sees something, they're like, oh, this doesn't seem right, or why is this they can sort of drill down to the case level or the invoice level or whatever and get it good and be able to find out themselves what might do to ameliorate a situation.
00;17;38;23 - 00;17;47;04
Just having formal data science and AI initiatives in place, give a law firm a competitive advantage?
Again it depends what you're trying to do. I mean, having data science or AI, more advanced analytics gives you a competitive advantage in two main ways. One is it allows you to do the work you're doing better and faster. You have increased insight you can automate more, you can get more lean and reduce some of the waste and do things faster and more straightforward fashion.
And that crunching that data allows you to see where you can be lean, where is the waste. And then also I think and then meeting your clients need more and more. Clients want to reduce costs which I'm definitely seeing in the industry. Maybe that's not that's nothing new, probably. Right. That's always been the case. They want you to do more for less money.
So how do you do that when you become more lean you automate more and then also you provide your clients with added value. Be able to say like, sure, we can handle this case for you, but also this for like BAL and immigration. Our clients are large corporations or even small businesses who have an immigration program that's part of their H.R. function.
Is to have an immigration program where they're have their set of foreign national employees. And it's very valuable to them to report to their upper management, to say Here's what we have on staff who are sponsoring for immigration status. Here's how that's been growing. That's how it's trending in our law firms, able to tell us that we're forecasted to do X, Y, and Z in terms of volume and legal fees.
They're able to predict for us how things might be changing in the immigration field. Based on the data they're able to crunch because they're a large immigration law firm and they have a lot of data that they can anonymize and aggregate into machine learning models and things like that to help give our clients additional insight into things they should and should not be dealing in or be ready for.
Those are two key areas where not just doing the basics, not just throwing out a report that says, hey, here's how much you spend or hey, here's a report of all the people we we're currently managing for you, right? So that added value. But at the same time also give you an added value, but at the same time being able to reduce costs.
00;19;59;07 - 00;20;03;24
What effect has the pandemic had on how law firms view the value of their data.
00;20;04;22 - 00;20;25;02
For the law firm, the business side, I think this applies to both the law firm as well as the client companies. Is initially beginning of the pandemic, it was like, okay, we're going to have a huge economic downturn. Everything's shutting up. Everything's closing the doors for now. People are not going to the office. How's that going? Impact the economy.
People are losing their jobs. They're not going to buy as much as it impacts our clients. And so, I know for us right out the gate was to internally within the firm what to start really monitoring how we were growing, what was happening to our case. Cases were opening week over week, month over month based on the prior year.
And then how are we recovering or have we recovered from the pandemic. And so that's something that we weren't doing before but then now that's a report and analysis that we started doing that we now do every single week. And our partners and equity partners find that extremely helpful now to okay, every week how are we trending based on the previous year and have we recovered in certain areas?
Have we not recovered in certain areas? Why is that? And so that's one area. Pandemic helped another area for clients. Not sure how this impacts other fields like immigration, which is when you're in the U.S. on an immigration status majority of the time where you're located in the U.S., or your job location is extremely critical. There's legal ramifications to changing your work location and not notifying the government of it and also other salary-based things that come into play.
And so, for our clients alike, all of a sudden, they are still working from home, and they have to determine okay. Are they is their address. They're working from home in line with what we said, their address is going to be only applied for their visa. And so, we get a lot of that going on. We're still doing some of that because a lot of companies have not had both fully returned to the office yet.
And so, we have to make sure that our clients recovered legally, make sure we would filing all the proper amendments to let the government know, hey, this person's not working in this location, at this location. And then if the change has been material enough with notify the government of that material, change should make other changes. So that's another big part is for our firm, at least in our industry, is around knowing where people are and what kind of work they're doing.
And then just like I said, financials overall for us internally as well as for our client because they're dealing with, they may be having downturns, they may need to be well changing staffing, whether that's hiring less, foreign workers, hiring more, you know, it all depends. But that's the primary way things are changed. The pandemic is more of a focus on the economy and how that impacts things.
And probably more economic report, more financial reporting.
00;22;47;20 - 00;22;53;08
This program is called Reinventing Legal. How is your work ultimately impacting that objective?
00;22;54;01 - 00;23;35;17
Not just like a broken record, but I think a couple of things I mentioned before around automation, around and coming leaner. You know, that's something that when you properly use your data, so you have good data, you're collecting good data. And again, it's sort of to our harkened back to that talk about how your different KM and practice squad and product management teams all work together is if you have really good data sets that are reliable, that allow you to do things like use Python or other tools to automate processes, to build machine learning models that can predict things and forecast things that allows you to sort of change the game.
So, a firm that's doing that versus a firm that's not doing that, I believe that firms have a competitive advantage because, one, they're offering more to they're doing in a leaner fashion, which allows them to be competitive on pricing. And there's also other things you can develop and provide. So, I'll give you a couple examples about my firm, Berry Appleman & Leiden.
And we recently have started to spin off more and more LLC outside of the firm where we're offering then to consumers directly or to other law firms tool that we've developed in-house based on whether it mainly is our product management team, but also working with my team at times to see, okay, what kind of data do we have?
How can we use our big data given the size of our firm, how we provide other value to people who are necessarily clients indirectly of the firm? So I'll give you one example, is we have a company called Dun CI and we have an app called True Time and True Time App, which you can get on the Apple Store or on the Google Store is a tool, an application app that basically allows you to go in and if your is a matter whether you're working with a client, BAL or you're a client of another law firm or you're doing you're presenting yourself and allows you to go in and put in the what type of application filed with the government and to get a very accurate prediction of when that application will adjudicate it. Because right now, if you're given U.S. immigration and citizenship, U.S. Citizenship and Immigration Services website and looked at their processing times for different types of applications, it's a huge range and they're very frequently inaccurate. So, you might be like, oh, I got some vacation coming up, but I'm still waiting for my H-1B renewal to come in.
It's been it's three to six months. I don't know what to deal with that. Using our app, you can get a much more accurate prediction of when it's going to be done that because my team initially work with our product management team to crunch all our data and using different mathematical formulas and things to determine, okay, based on the data we have and that we're seeing, we can predict much more accurately when an application might be adjudicated.
And so, we're like, hey, let's take that outside of the firm. Let's offer this as a product to everybody. That's how you start to innovate more in the field. You sort of change the game if you're, you know, especially when it comes to building your own tech, using your data to help provide value. And then sort of you can sort of spin those things off as its other offerings.
But those are some things I'm really excited about at BAL right now, that kind of stuff.
00;26;08;21 - 00;26;22;27
This is Ari Kaplan for Reinventing Legal, and it has been my honor to speak with Andrew Shapiro-Zysk, Senior Manager for Reporting and Data Analytics, Berry Appleman & Leiden. Andy, thanks so very much.
Thank you for listening to LEGALTECH MATTERS. Be sure to subscribe wherever you get your podcasts.