From Pricing Models to BI Dashboards: How Morgan Lewis Operationalizes Data
How do you turn legal data into trusted insight across one of the world’s largest law firms?
In this episode, Jennifer Mapp, Senior Director of Data Management and Analytics at Morgan, Lewis & Bockius LLP, shares how her team built a firmwide data foundation that empowers attorneys and business leaders to make faster, smarter decisions. From launching business intelligence dashboards that replaced hours of manual reporting to expanding the firm’s knowledge management program into a structured data governance model, Jennifer explains how credibility, collaboration, and consistency turned raw data into real value.
She walks through how Morgan Lewis connects internal and external data to create unified profiles for over 15,000 cases. Jennifer also breaks down how the firm measures success (adoption, quality, and attorney feedback), the importance of starting small instead of waiting for perfect data, and how cross-functional collaboration is setting the stage for responsible AI readiness across the firm.
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ENTEGRATA | OVERRULED BY DATA | JENNIFER MAPP
Episode Transcript
This has been generated by AI and optimized by a human.
[00:00:00] Jennifer Mapp: It's gonna be an ever evolving strategy and process. Like what I tell my team is data governance is never gonna end. It's gonna continue, continue and continue. Because our data evolves, we get more and more information. We're gonna continue to think about other things that would enhance our our data information.
[00:00:18] Jennifer Mapp: So just really having a base of how you would approach data governance is gonna be a good start, and then you can start to build upon that.
[00:00:29] Tom Baldwin: My name's Tom Baldwin. This is Overruled By Data, the podcast for law firms looking to start their data journey or accelerate the journey they're already on.
[00:00:36] Tom Baldwin: Brought to you by Entegrata. Today's guest helps one of the largest law firms in the world turned raw data into business insight. Jennifer Mapp is the senior director of data management and analytics at Morgan Lewis, where she leads a team that collects, prepares and presents data. For firm decision making and advanced analytics in support of legal services and core business objectives.
[00:01:01] Tom Baldwin: She previously led pricing and project management at another AM Law 50 firm, and brings a rigorous financial and operational lens to data. Her work sits within an organization investing seriously in AI readiness and responsible adoption. From strategic partnerships with Thomson Reuters, that gives lawyers early access to AI driven products.
[00:01:19] Tom Baldwin: To a firm wide AI task force and cross-functional collaboration models that align use cases, governance and risk management. Jen, welcome to Overruled By Data.
[00:01:30] Jennifer Mapp: Thank you Tom, and thanks for that introduction. Thanks for having me.
[00:01:34] Tom Baldwin: So we always like to start these off with a little bit of background on our guest and kind of what brought you to data.
[00:01:40] Tom Baldwin: So, you know, if you could just sort of give us a sense of your pathway into legal data, a little bit of your personal background and journey. What was your path? From where you started to get you to where you are now, focusing on legal data.
[00:01:54] Jennifer Mapp: Sure. So I started at another firm in the Philadelphia area, Dechert.
[00:01:58] Jennifer Mapp: Um, I started there in their pricing and project management department. I recently graduated from business school with a degree in MBA in finance, and I really wanted to get outside of just traditional accounting roles and more into a financial analysis role. And there was a role available at Dechert where they were starting a pricing and project management department.
[00:02:19] Jennifer Mapp: So I started there in that department and eventually, after about five years, left that department, um, and that firm to move to Morgan Lewis in more of a revenue management role. And I think that that really helped me into the data management and analytics role that I'm in today because it allowed. For me to work with a lot of different practices.
[00:02:41] Jennifer Mapp: At Dechert, that role was more of a centralized role that worked with all of the practices in terms of helping put together budgets put, putting together pricing models, as well as when I got to Morgan Lewis and worked in revenue management, it was really spanning all of the different practices and I think that that helped me really understand not only things about pricing structures, financial models.
[00:03:02] Jennifer Mapp: Things that I had a lot of experience with in terms of my finance background, but also all of the different aspects of legal services there are, how it can affect staffing models, fee structures. Thinking about, you know, the work expectations, scope, legal strategy, staffing. I think all of that information and having to understand, you know, as much as I could about that information to help.
[00:03:24] Jennifer Mapp: Put together those budgets, those pricing models really led me to understand all of the in intricacies and ins and outs of data that Affirm will have on their clients and on their matters. And so I really think that that helped me have that understanding, but also it helped me learn how important it is to present data, how important it's to communicate the results and the insights that people can take away and take action on.
[00:03:48] Jennifer Mapp: Because as business teams who are very familiar with data, we are in information. Numbers day to day, and we don't really sometimes think about communicating that information to an end user and giving that information to them and sort sort of saying what the action is or the ask is after sort of a high level review of that information.
[00:04:07] Jennifer Mapp: So I think, you know, working in pricing, revenue management. That really helped me because it not only had the financial acumen of what the expectations are at a law firm, but also all of the information associated with clients and matters, what's important to legal teams and attorneys, and how to present that information in the best way.
[00:04:27] Tom Baldwin: It, it's interesting you talk about sort of that, that last mile of presentation. I think as a, as numbers people, we sometimes forget. Who the consumers are. Right? Right. They don't have an MBA most of the time. And you, when you think about that, that journey, what did that experience in pricing and revenue management teach you about?
[00:04:46] Tom Baldwin: Data quality? How you drive adoption and usage. 'cause it's one thing just to provide a mountain of data to a lawyer. It's another thing that they actually read for. Open it, read it. And then take the action that you were hoping they'd take.
[00:04:59] Jennifer Mapp: Right, right. Well, you know, with pricing, we had to be, you know, as, and it's never, it was never perfect or a hundred percent in terms of, you know, our financial models, our profitability models, but we had to be as accurate as possible and made sure that we created really solid business roles when we were modeling different types of rate structures and financial arrangements.
[00:05:21] Jennifer Mapp: So those were. Making sure that the data was correct. We had business roles around what our model looked like. That was really important with pricing, um, especially to make sure that we're managing financial expectations that the firm expects for those different arrangements. Adoption also was extremely important.
[00:05:38] Jennifer Mapp: I mean, when I started in pricing and revenue management, it was a new function for the firm, so having solid information and data was really important to make sure that we were seen as credible. That's really important to adoption as well, because if you're giving a lot of information that doesn't seem correct, it's gonna be less adopted than anything that you're putting forward or putting in front of an attorney or, or a legal team.
[00:06:02] Jennifer Mapp: So we, we really had to be solid on those business roles for adoption, but also thinking about how to not overcomplicate information that's provided. How do we provide results? How do we welcome feedback so that we can use that to. Modify sort of the model and make sure that it's presenting the results that they're expecting.
[00:06:23] Jennifer Mapp: So it was something that we really had to think about in terms of adoption. I think about that a lot here at Morgan Lewis is how do we get adoption for things that are new, ideas that are new that may seem a little bit challenging into the firm. We conduct a lot of proof of concepts. That's something that we do with the firm a lot, um, and Mor to Lewis to show what an investment in organizing and providing data could look like for an end user, so that even if it may be a fake dataset, they can see if this dataset was collected on a regular basis.
[00:06:55] Jennifer Mapp: We can provide you with these results that you can utilize for conversations with your clients or ways to gain new client work. So that's worked really well for us in terms of adoption. To assist with some of our continued data collection and validation efforts.
[00:07:10] Tom Baldwin: I love that. That's a really cool idea. I might circle back on that if we get time.
[00:07:14] Jennifer Mapp: Yeah, definitely.
[00:07:14] Tom Baldwin: One of the other things I always like to ask folks is the moment where you thought, gosh, data needs to be a core capability for us, and not just an afterthought, was there like an aha moment where. You weren't able to turn around something fast enough or the data was wrong because it wasn't tied out to something that you could rely on, was there, do you have a moment like that?
[00:07:36] Jennifer Mapp: Yeah, I mean, I think that it has always been a priority in the minds of all of the business teams and legal teams at the firm. I think the moment where it really clicked for us that it had to be more of a structured approach to data management and data governance was when we felt the need to expand our knowledge management program and we.
[00:07:58] Jennifer Mapp: Needed to continue to support our attorneys and clients with their information on our experience to connect that data with other data sources for different needs. And so we realized that if we did wanna expand the ability to share our experience with our attorneys, with our clients, we really had to focus on the data, work closely on business rules, data quality risks related to sharing information, and again, how we present that data in a more normalized, concise way.
[00:08:26] Jennifer Mapp: So we identify during that process the need for a structured data governance program, a data dictionary, to even identify all the data points that the different users work with, what those data points mean, who owns that information, what systems that data sits in. And that would also help us identify where there may be some issues where we may need to conduct some data cleanup projects or just understand the flow of information and change the.
[00:08:53] Jennifer Mapp: Flow if there are some issues with the way the data is being presented and it's incorrect or inaccurate. So that part of that knowledge management program really helped us start to structure how we wanted to manage and look at data, not just within the knowledge management team, but across business teams.
[00:09:10] Jennifer Mapp: And so that data governance program, though, that is consistent. Multiple business teams who work in different systems, they work with different data that may not be owned by knowledge management, but it is data that's utilized across different business teams with attorneys for different use cases. So we felt the need that those teams would need to collaborate more and to clearly define the data that they own.
[00:09:33] Jennifer Mapp: That other users could be working with. And especially now with the expansion of AI bringing AI tools on, it's really important that, you know, we wanted to make sure we had our data in order, or those tools wouldn't be helpful with the bad data that we have. So that was really the point that clicked for us that we needed to have a more structured approach to our data management.
[00:09:55] Tom Baldwin: And that was at Morgan Lewis, right. So even before then, was there a time at Dechert where. You had that same sort of aha moment where like you didn't have what you needed and that that was a lightning rod for you?
[00:10:08] Jennifer Mapp: Yeah, I, I, I think so. And you know, it was very interesting. As I mentioned, it was a new function at Dechert, so there were a lot of things that.
[00:10:15] Jennifer Mapp: We didn't know that we needed, and we sort of along the way of developing financial models, thinking about our profitability model to start to build out these rate structures. There are a lot of things that we had to learn on the fly to be able to get to the place where when I left Dechert, where we were able to pull historic matters, um, look at those matters with the legal teams budget for, you know, upcoming work.
[00:10:39] Jennifer Mapp: So I think the point that it probably clicked was. When the firm before I joined the firm realized that they needed to stand up that pricing and project management function because it was needed. Clients were asking for different types of fee structures. They wanted more insight into the work that was being done on their cases and their matters.
[00:10:58] Jennifer Mapp: And I think it really clicked for the firm when clients were coming to them with those requests and that sort of made them say, okay, we really need a dedicated function for, you know, not just helping us. Set rates, but think about how we would budget our matters, what type of assumptions should go into that, how we develop that and present that to clients and how we manage that ultimately moving forward.
[00:11:21] Tom Baldwin: We could probably spend a whole hour on this, but I have one off script question for you, which is more and more firms are thinking about pricing functions, trying to set up pricing functions. In fact, I think you and I first met when we were both doing pricing, uh, many moons ago. If you, if you had like one or two pearls of wisdom for somebody setting up a pricing function for the first time at their firm, what would they be?
[00:11:45] Jennifer Mapp: I mean, I guess it would be to just start somewhere, right? Like you're not gonna be able to tackle knowing how to set up a budget or a pricing arrangement for every type of engagement that comes to the firm. But I think, and also maybe starting with. Someone, a partner at Champion who, you know, has a client that, like I said, may need, they may be asking for budgets or, or more, uh, sophisticated pricing arrangements.
[00:12:12] Jennifer Mapp: Start there. See sort of what you can do in terms of, you know, working with that partner or that attorney to. Think about are there like kind cases that we can model this after thinking about how we can set up those pricing models, right? And think about, it doesn't need to be necessarily over complicated.
[00:12:29] Jennifer Mapp: A lot of the work that we did was in Excel, right? But we want to put together just generally, okay. Think about just using business rules and, and just business terms. How can we think about. Revenue costs, profit, but then also, like I said, working maybe with that attorney or that partner to think about, okay, well let's talk through this.
[00:12:51] Jennifer Mapp: What could lead to some work outta scope or going over budget? Like what are things that we would need to consider and helping develop that kind of mindset I think is important because that's gonna translate to other practices, other types of work. Even if it's different types of work, but thinking about what that assessment would look like to be able to put together something that, like I said, may be just starting in Excel and make it more and more sophisticated as you learn more.
[00:13:17] Tom Baldwin: So, switching gears, I, I always like to ask folks that things that they're most proud of, was there a, a North Star project or an analytics or data management initiative that clearly changed how teams or folks in leadership roles at the firm made decisions?
[00:13:34] Jennifer Mapp: Yeah, so data that was the North Star project for me at Morgan Lewis, I would say, was when we implemented our business intelligence dashboards.
[00:13:44] Jennifer Mapp: Uh, at the firm, not only to our managing partners, but also to all of our partners and our associates on things like utilization. And what we realized early on when I started at the firm in a different role in revenue management is that a lot of the business teams who were conducting the financial reporting, the analysis, we're doing it in a very manual way.
[00:14:05] Jennifer Mapp: They were writing code, it would take them hours and hours to create an analysis or a report, which would take away from the time that they would be able to provide some insight into the information and really review the information and then give the requester not just the information to review, but here's what we see in terms of trends.
[00:14:24] Jennifer Mapp: That's, you know, about clients or you know, the work that's being done in a particular practice month over month. And we quickly realized that there needed to be a more advanced tool put into place that not only one set the same roles, regardless of who was in the tool. Because we, what we would also find is that if you got a report from one team and you ask the same question and got a report from a different team, it could be two completely different answers.
[00:14:50] Jennifer Mapp: So we realize that that's a problem, right? So. We had to take a step back, set those roles for, you know, all of that financial information so that we were all on the same page, but then look into are there some tools that we can put into place that would make it easy for those, that business team who's doing all of that reporting and writing code to more easily pull the information, be able to drill down into realtime information more quickly, and then be able to spend more time on providing those insights to the requesters.
[00:15:21] Jennifer Mapp: And so we. Looked at some different tools, uh, and we utilize Qlik as our, uh, business intelligence dashboards. And we went through the process of really thinking through how we would wanna set the information up, making sure that it wasn't over complicated, but we had a lot of different views with a lot of different data points that are usually asked for by, you know, managing partners or responsible partners on their clients.
[00:15:45] Jennifer Mapp: And then took a lot of. S detailed time to put together something to put it in their hands to conduct training so that now it's more easier to pull information, answer questions, be proactive with different insights for different reasons, like business development or managing operations of a practice.
[00:16:04] Jennifer Mapp: And so, you know, what we've heard and we get continuous feedback on is now it's just so much easier to get into the information. It helps with quicker decision making and it makes, you know the information that they're trying to review, less static and more interactive.
[00:16:17] Tom Baldwin: One of the things that our crack agent of researchers dug up about you, was that a presentation you did at Legalweek talking about curating metadata, both internally and externally?
[00:16:28] Tom Baldwin: Is there a project there that you'd be willing to talk about where you kind of operationalize that, that metadata concept with internal, external, and matter profiling? This is a topic. Other guests have talked about, which is the like holy grail of getting data passively collected about what we know about a matter or a client or a person.
[00:16:47] Jennifer Mapp: So we, through that knowledge management program that we were expanding, I guess about five years ago now, we recognize that we also have resources available that we can utilize to pull in. Metadata about our matters more to give us more information about our experience. You know, it's very difficult, you know, attorneys are very busy.
[00:17:07] Jennifer Mapp: Um, it's very difficult to be able to have them fill out a form or sit and have an interview with them or tell me, you know, send me all of your documents and we'll go through them and pull all that metadata out. And there are, but there are some resources that we can utilize that have already done some of that work for us.
[00:17:22] Jennifer Mapp: So we utilize one of our resources specific to litigation to. See what data they had available via an API and how we could we pull that data and connect that data to our internal matters so that we did have a lot of that enhanced information, that enhanced profile experience to be able to present to our, our attorneys.
[00:17:41] Jennifer Mapp: We, we worked with the consultant, but we also pulled in a program and ETL program that would help us build business logic to basically match. The information that we had in this litigation resource with our internal dockets. So we used of course, some data points like docket numbers or case numbers, case names, jurisdictions.
[00:18:01] Jennifer Mapp: Those were all things data points that that particular source had available. Those are all data points we have internally available through our Docketing system and our docketing process. And we thought about how do we build some business logic in the event that the data that we're keeping internally may be.
[00:18:18] Jennifer Mapp: A little bit inaccurate. Maybe a number is missing, A letter is missing from our docket number, but if we have some other data points, like a case name, like a jurisdiction, and that seems to match what we're finding through this other third party resource, that's probably the right case. So we were able to come up with and develop some business logic that would connect that information and then go through an approval process to.
[00:18:42] Jennifer Mapp: Information that's brought in and kind of sign off and say, okay, that looks right. That looks right, that looks right. And then we were able to push that into our internal experience management database, which is Foundation. So we went through a, a lar, a long process of doing that. And um, I know a lot of companies are doing know how to do that now.
[00:18:58] Jennifer Mapp: They're presenting, you know, things like matter connectors, things like that, which I wish we would've had, you know, three, four years ago. And we were building all of this internally, but it was, you know, good experience to even. You get into the data, understand the data even more, to be able to put that process together.
[00:19:14] Jennifer Mapp: And now we're able to use that process to refresh that data on a daily basis. So now we have, you know, information on over 15,000 cases on our matters about judges. We were in front of courts, we were in front of motions that happen for particular, you know, litigations, results of those litigations outcomes.
[00:19:32] Jennifer Mapp: And that's really helped to enhance a lot of the information that we have. We can even still work with a, a partner, an attorney and just say, does this information seem correct or is there anything else you wanna add to that? And it's usually a great starting point to work with attorneys to then continue to add even more information that may not be available in that resource.
[00:19:50] Jennifer Mapp: So that was, you know, one of the really concrete examples that we've utilized that has really just been enhanced. And we did a lot of as well mapping on the backend to ensure that. Had normalized lists of courts, judges. We didn't have, you know, the five names for one particular court. All of that information is more easily searchable.
[00:20:10] Jennifer Mapp: Um, it's more easily usable. So we also, with that sort of external data, bringing that in, we also thought about how do we make sure that that data comes in normalized and more concise so that it's easy to present and to search on it
[00:20:24] Tom Baldwin: with all the different, this is amazing by the way. Thank you for sharing that.
[00:20:28] Tom Baldwin: With all the different programs you have in place, how are you measuring impact to firm? Are you looking at adoption? Are you looking at time to insight, accuracy, uh, at any kind of revenue metrics? How are you looking at the overall kind of efficacy of your efforts?
[00:20:44] Jennifer Mapp: So we look at a couple of different things.
[00:20:46] Jennifer Mapp: I mean, we don't really look at necessarily revenue, but we do look at some KPIs, like how many users we have, how many searches we have month over month. And a lot of times we look at some qualitative information too. But we do regularly look at, you know, usage of our platform. The number of matter profiles and client profiles we're able to enhance.
[00:21:08] Jennifer Mapp: How much third party data we're able to bring in and integrate into our, our database. We look at, uh, matter profiling efforts. So as we go practice through practice and start to work with some of those leaders to start to collect more information about our matters and enhance our matters, what does that look like in terms of how many matters?
[00:21:26] Jennifer Mapp: Is that group enhancing just through discussions or them filling out a survey? We also look at, and it helps us understand the breadth of information that we have and that we can provide to our attorneys, those different KPIs. We also try to get a lot of qualitative feedback from attorneys and business teams just to understand if the information is helpful, if it's useful.
[00:21:46] Jennifer Mapp: We just wanna make sure you know that they are able to utilize the information, their needs, their inquiries, their use cases. We also wanna know how easy it is to get to the information. Now that we're collecting it, we're storing it. We're providing it in some downstream systems. So we really try to get that feedback as well to understand, you know, are the things that we're doing, does it make sense?
[00:22:08] Jennifer Mapp: Is it helpful? Does it make things more efficient for the individuals who need that information? We also wanna continue to understand, are there any gaps we can solve for? So those are things that we also look at in addition to a lot of those different KPI metrics, um, in terms of, you know, the information that's being provided.
[00:22:27] Tom Baldwin: Thank you for that. That's, that's really cool. So, we talked about stuff that you're proud of. I also, again, the spirit of this show is really to help educate folks and give folks, uh, a glimpse into what to do and some things what not to do. And so when you look back at your career working with data, we wanna kind of talk about maybe some things you would do differently, some opportunities for, um.
[00:22:49] Tom Baldwin: For a pivot or a miss, just flat out something that you whiffed on, which, look, I've done plenty of that in my career. No. What was like for you when you, when you all think about AI readiness, was there a a piece that you underestimated?
[00:23:02] Jennifer Mapp: I think there definitely was a piece that we underestimated. I would say it was a lot of governance and I think that that was most underestimated and probably not even just with.
[00:23:14] Jennifer Mapp: As part of AI readiness, but just when we started our knowledge management program, I think, you know, having people take ownership of data is really difficult when they necessarily haven't taken full ownership of it. And that's really needed for the development of AI tools and just generally using more and more information.
[00:23:33] Jennifer Mapp: So, you know, having people take ownership of data, establishing, you know, data stewards at the firm, like having standards, having policies and security controls. That's really. Underestimated, but it's extremely important to be ready to utilize ai.
[00:23:48] Tom Baldwin: It's such a hard thing because I do think that firms understand the importance of governance.
[00:23:53] Tom Baldwin: And in some firms I've talked to, they actually lead with governance before they touch a single piece of data, which I would argue maybe is a bit overkill, but what's like a workable, what's a realistic uh, or governance and practice inside a law firm that is workable and. Sustainable.
[00:24:15] Jennifer Mapp: We recognized the need for a more structured.
[00:24:20] Jennifer Mapp: Data governance, um, effort. And I think that, you know, what's workable is making sure that you have those things like data owners taking ownership of their data sets, having data stewards, data champions. Having a lot of, you know, processes developed, best practices developed are really important to make sure, and, and those are all things that are in data owners' minds, but making sure that you have that sort of established and set, and you go back to that when you're working with.
[00:24:50] Jennifer Mapp: Different data sets or different teams or standing up a new tool or just trying to make sure that a tool that you're always been utilizing is working for the firm and working for the team that needs it. Making sure that, you know, you develop processes to assess data requirements when new tools are being developed.
[00:25:07] Jennifer Mapp: Meeting regularly, my team meets regularly to discuss data projects, data issues, the need for normalization of certain data sets. Sometimes we had to take a new lens to when we, we may turn around. Make a decision that's completely different than we did initially, but we, when we continue to think about it and talk about it, it'll only help make sort of our data model, our data operating model better.
[00:25:27] Jennifer Mapp: And like I said, we've developed processes to assess data. We've tried to think about how do we tackle, normalize data sets, normalize lists, list by list, like court list, office locations, thing, all things that you would imagine would be normalized, but. Are not necessarily, especially across different systems and you, us being such a big firm, we have so many systems, so many different silos of information.
[00:25:53] Jennifer Mapp: Really trying to get to that information and making sure we apply those standards is really important and takes a long time. And we also identify priorities for cleaning up data. That's really important to think about. What's the important data that you really need that is frequently asked for and is frequently needed to help with.
[00:26:11] Jennifer Mapp: Different things, like I said, like business development, like just operations of a particular practice or a client just asking us, do we have experience in this jurisdiction? So that's really important to think about, like what those priorities are for looking at information, cleaning that up, and collaborating with those data on owners on the best approach for cleaning that up and implementing correct processes moving forward to keep that data as clean as possible.
[00:26:35] Tom Baldwin: If there was a project you could redo or rewind in a data initiative that you'd do differently, either in terms of the way you scoped it, the sequencing of it, tooling, or any of those things, what would you do differently? There was one you had to take back or redo. Yeah,
[00:26:54] Jennifer Mapp: so one that comes to mind was a piece of our implementation of our experience management database.
[00:27:02] Jennifer Mapp: We were taking data from the existing database and you know, moving that over and importing that. There was one particular data set that we didn't take a lot of time to, I would say, address the data issues within that data set and we kind of just moved that data over. Thinking, okay, well it's just as clean or just as, um, not because everything's not super clean at all, but it kind of models the same data that we've already moved over so there shouldn't be any issues.
[00:27:35] Jennifer Mapp: And didn't realize until we moved that information over that no, it completely came over completely different. We didn't review it enough to make sure that some of this information. Really shouldn't have been brought over or was incorrect or just in a format that didn't make sense for the way that we brought it over.
[00:27:53] Jennifer Mapp: So it took a lot of efforts after that to. Make that data fit into the experience database. Took a lot of, you know, just sort of auditing, making changes and things like that. But it did, I think, help us identify when we're working on those type of projects moving forward. It's really important to sit with the information, understand it, see how, what's the best fit or what's the best place and format for that before anything is sort of.
[00:28:21] Jennifer Mapp: Moved over into some other database or some other file to really come up with a real thorough strategy and invent yourself in the information so that you know what's the right way to handle it moving forward so that on the other side, you don't have to spend so much manual time cleaning it up. And that really helped I think with.
[00:28:38] Jennifer Mapp: Future projects. Now understanding if there is some sort of process that we have to move data from one place to another, let's really immerse ourselves in the information, understand what makes sense, what format it makes sense in, and how it could translate to similar types of data that's already there and, and maybe how do we handle that in a more concise way that it's not so disconnected.
[00:29:02] Tom Baldwin: Makes sense. Uh, and Foundation projects are tricky anyway, right? Yes, very. They're never, never straightforward. Very tricky. Most firms are, are this, there's this continual ebb and flow of, of buy versus build. And a firm like Morgan Lewis, you've got, you're one of the largest law firms in the world. You've got more resources than a lot of firms, but yet you still have a lot of strategic partnerships, and you've been very thoughtful about that.
[00:29:30] Tom Baldwin: How do you all make the decision to buy, build, or co-develop?
[00:29:35] Jennifer Mapp: That's a great question. I mean, we try not to build too much. You know, what we always tell ourselves is we're not a technology company, we're a law firm, but we recognize the need for the ability to build things internally where needed. We do have a group that there are digital transformation and user experience team, and for new requests.
[00:29:56] Jennifer Mapp: Of some sort of tool that that may be client facing or maybe internal. They go through an assessment of what the requirements are. Are there tools that we already have available to us internally that could handle the need? Does the need cross different practices or is it very specific and niche? And they go through an assessment process where.
[00:30:16] Jennifer Mapp: They think about that, how much those that would cost if we would build that internally and go through sort of an approval process. If the, the decision is yes, this would be good to, to build internally, but we try to avoid as much as possible, building more and more tools and really think about are there tools that we could we utilize that we already have available to us?
[00:30:36] Jennifer Mapp: Or is there something out there that could meet the needs of something that we would want to develop or customize? And can we. Can we scale that so that it is not only for one specific niche use case, but we, it can be utilized for. Multiple use cases across different P practices. So it can be on a case by case basis, but you know, if there's anything that's gonna be rolled out firm wide and something we, we see that, you know, this would be great, um, for, you know, the entire firm and, and really meet needs that we don't have from with our internal tool or something that we could build internally, then we may look to, to partner with a vendor and, and buy something.
[00:31:17] Tom Baldwin: Shifting gears to kind of looking ahead, right? And this is always such a tough thing to crystal ball anything past, you know, six, 12 months. But as you look at the future of data analytics and ai, what are you seeing? If we start with the skills and, and teaming what, what skills for lawyers. And for business professionals do you see in the next 12 months becoming really important?
[00:31:43] Jennifer Mapp: So, I mean, I think for lawyers, I think the skills are just gonna be learning how to make, you know, AI tools beneficial for what they're doing. You know, I was on a great webinar yesterday about prompting and the, the secret to prompting with AI tools, and I think that that's gonna be really important for, you know, lawyers, professionals as well to really have education around.
[00:32:06] Jennifer Mapp: What AI tools are available, what AI tools do for, and how that can support, you know, their practice, what they're working on, their client work, what the risk is around utilizing those AI tools, but really making those AI tools work for them for those specific use cases. And understanding how to interact with those different tools is gonna be really important.
[00:32:26] Jennifer Mapp: And I think that's why a lot of firms, um, as I've seen, you know, focus a lot on education, education around ai. Just what all of these different sort of AI tools could do, what all of these different terminologies are when it comes to ai. Uh, as I mentioned, a, a great webinar that Thomson Reuters had yesterday was about prompting and how to unlock your prompting skills.
[00:32:47] Jennifer Mapp: So really getting a lot of that knowledge and education and figuring out. How AI tools can work for them and help them is gonna be really beneficial for them. And give them, you know, the, what they're hoping is more time for, you know, case strategy, other high level tasks, um, is what, you know, we're hoping that, you know, those tools that we utilize Will, will do for our attorneys and our legal teams.
[00:33:07] Jennifer Mapp: So I think that that's gonna be really important. But there is also gonna be a lot of synergies. It's gonna continue between different departments. Knowledge management, finance, business development, because, you know, those tools are gonna require, uh, depending on, you know, what a firm is building. But if it's definitely utilizing internal data, it's gonna be data from a lot of different teams, um, data owners that utilize that data and that data is gonna need to be centrally located and connected and credible for any tools that are being either, you know, developed on top of the firm's data or.
[00:33:41] Jennifer Mapp: They're just utilizing the firm's data, so continued collaboration across those, those departments. It's gonna be extremely important to be able to collaborate and be AI ready for our attorneys and, and the tools that we're using.
[00:33:54] Tom Baldwin: When you think about practical advice, you mentioned earlier, like with the pricing function, just start small, get going, and don't worry about it being perfect right out the gate.
[00:34:04] Tom Baldwin: Th this is a pro, like when you work in legal, the idea that something's not gonna be perfect. Is a hard thing, right? We're trained right from an early, from birth, uh, whether you are a lawyer or working in a law firm in a, uh, support capacity, you've gotta, it's gotta be perfect. And so firms really kind of grind themselves down to the bone to figure out, like, I've gotta have this perfect before I get started.
[00:34:30] Tom Baldwin: For firms are kind of in that mode where they are waiting for perfection. What would be your message?
[00:34:36] Jennifer Mapp: Same. It's not gonna be perfect, um, when you start, but you have to start somewhere. So I think that you can just start small by identifying one problem, one data issue that may come up frequently, one data set issue that may come up frequently.
[00:34:51] Jennifer Mapp: That if there was some way to fix it and there was some process that could be put in place that would make that data correct more credible, then you know. You can think about what that would look like thinking about then, you know, if you find sort of, like I said, one data point, one data set, start to to think about.
[00:35:10] Jennifer Mapp: You know, how you would assess making that data better? Think about where the data lives, what downstream systems it does or doesn't feed into. How you can address the data issue. What, what could be a process to put in place for maintaining that act, that data more accurate moving forward? So starting small, thinking about, you know, one place to start that will really help set the base for.
[00:35:31] Jennifer Mapp: Thinking about data governance as a whole and creating a strategy, and then that will allow you to have that strategy in place to then start to go into other areas to help manage the information more accurately. Um, there are gonna be times where strategy has to be adjusted, just depending on, you know, like I said, you could start somewhere then realize that's not gonna be the right process, or the process can't be the same for every data point, every data set, because.
[00:35:57] Jennifer Mapp: It's different because of different systems, different people who, you know, own that information. But just having a base of, I need to think about processes where that data lives, what downstream systems that data feeds into, that will really help set the base for having a strategy and then moving forward with, like I said, thinking about other priorities, other data sets, and then it's gonna be an ever evolving.
[00:36:24] Jennifer Mapp: Strategy and process. Like what I tell my team is data governance is never gonna end. It's gonna continue, continue and continue. Because our data evolves, we get more and more information. We're gonna continue to think about other things that would enhance our our data information. So just really having a base of how you would approach data governance is gonna be a good start and then you can start to build upon that.
[00:36:49] Tom Baldwin: And of taking that, that topic and, and double clicking on it a little bit. You mentioned in a, in a previous talk or, or, or, or, uh, article, this concept of trigger based capture and incremental centralization of data for reuse. So if someone said, Hey, in 90 days I wanna be able to demonstrate something, what's a small concrete action a firm could take, whether it's locking in the taxonomy for.
[00:37:14] Tom Baldwin: A very small subset of a practice for capturing area of law or high volume matters, or defining authority of sources for five golden records. What, what would be a thing that you might suggest a firm look at doing? So they can put a little meat on the bone from a, Hey, I told you we're gonna start small.
[00:37:32] Tom Baldwin: Here's something we did, and show a small win in 90 days.
[00:37:35] Jennifer Mapp: Sure. Yeah. I mean, I think that. You know, taxonomies are, are great. I mean, that's a, that's a great place to start to really come up with taxonomies, normalize lists of information and applying that to, you know, your current data sets to show, okay, now this information, it, it, it is more easily, sort of categorized more easily to search on.
[00:37:57] Jennifer Mapp: I think with, as an example, things like matter profiling, you know, that is a really difficult feat. I know for a lot of firms you could start with one type of work, three to five data points that you could work with an attorney on. And you know, I go back to that proof of concept idea, putting something together to say, okay, if we started with this one type of work, let's say we were able to collect these three to five data points and we had data for, you know, a hundred matters.
[00:38:25] Jennifer Mapp: Look what we could. Produced to you that you could utilize in any of your conversations, your inquiries, you just understanding sort of what's happening with your portfolio of work. That really has been, like I said, very helpful for us because once they sort of see that end result. It sort of clicks that, okay, this makes sense that we should start collecting this data and let me, let me help you with the process of doing that.
[00:38:50] Jennifer Mapp: So I think that's something really easy. You could do, you know, in the first 90 days, three months, you could say, let's start with one type of work, one attorney, or, and then once you start to. Show that, and especially to other attorneys or other practices, then the light bulb starts to go off and say, oh, this will be really great if we had something like this on our type of information.
[00:39:13] Jennifer Mapp: Right? And now we know that there are processes in place to do that, and there will be some end result of us sort of. Spending time to collect that information or work with that team to collect that information. So I, you know, I would say start small. Same thing, you know, with the data strategy. Find something, um, a champion that, you know, was always wanted to, to be able to do something like collecting matter data or come up with a more normalized, concise list for courts in their SharePoint site that they manage their data in.
[00:39:43] Jennifer Mapp: Whatever that, that thing would be, that would sort of. Be the, oh, this is what's in it for me. Sort of end result is really helpful. And that starts momentum on being able to continue those efforts.
[00:39:55] Tom Baldwin: Last question. Lots of firms come up with a multi-year roadmap for data. They get, they hire a consultant or they come up with their own strategy, but along the way, you've gotta show those near term warrants, any rule of thumb for how you sequence projects and expand with analytics or ai.
[00:40:13] Tom Baldwin: On top of that.
[00:40:15] Jennifer Mapp: Yeah, I mean, I think, like I said, data projects, they're never ending. The roadmap is infinite. So I think that, you know, I go back to that idea of prioritizing what's important. What's the important information that your team or the firm wants to prioritize to get right? And use that as like the first quick win, right?
[00:40:36] Jennifer Mapp: If it is something like. We, we don't have all the information about clerkships for all of our, our staff, and we wanna be able to get that our attorneys, and we wanna be able to get that information more easily. Okay. Well, you know, start with that as a first project for a quick win, but continue to have a larger data roadmap that would, and usually that first project, quick win, probably points you to the next right project.
[00:40:59] Jennifer Mapp: Mm. Because clerkship data is personnel data. It's attorney data. Attorney data is important to get right because, you know. We are selling our experience, our services, to get client work and we need to have experience about our attorneys, uh, and our, our legal staff, correct. So that we can present our experience in the way that we need to either maintain our current client work or get you client work that could help.
[00:41:23] Jennifer Mapp: That first quick win could help you get to, okay. We need to as a net sort of larger project. Start with attorney data and let's make sure that we have all of that right and all the systems that that touches, or all of those different use cases. So that will really set the stage for future projects. And then taking the time to determine, you know, how you should organize your data.
[00:41:42] Jennifer Mapp: Like I said, taxonomies needing conventions, that's all really important. It's gonna be beneficial, it's gonna be needed for any AI tools or analytics to be helpful in the end. So all of that upfront work is gonna be, is gonna be really important. You know, the roadmaps infinite there, the, the infinite.
[00:42:00] Jennifer Mapp: There will always be different data sets that you'll come across. There'll always be, you know, ways that you can enhance your information. So just continuing to think about what you high level want your focus to be. If it's. Enhancing your matter information and client information. If it's cleaning up data as well, if it's making sure that you're pushing data into the right systems, having those high level goals and then understanding how you get to those goals and what the priorities are, I think will, that will set your multi-year data roadmap, but also allow you to have some quick wins internally.
[00:42:33] Tom Baldwin: Well, Jen, thank you so much for sharing your journey and insights with us today. That's it for this episode. For those of you listening, if you enjoyed the conversation, hit that subscribe button so you never miss another episode. Thanks for listening and we'll see you next time on Overruled By Data.
[00:42:47] Jennifer Mapp: Thanks, Tom. Thanks for having me.
[00:42:50] Tom Baldwin: That's a wrap for this episode of Overruled By Data. If this podcast resonated with you, if you took one or two things away from it, you want to hear more from law firm leaders that have been there and done that hit the fall button.
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