About This Episode
Next Mile Episode 137: How Financial Advisors Can Turn Messy Data into Actionable Results with Verity Larsen. A conversation about wealth management, fintech, and the future of financial advisory firms.
with Verity Larsen · March 24, 2026
Next Mile Episode 137: How Financial Advisors Can Turn Messy Data into Actionable Results with Verity Larsen. A conversation about wealth management, fintech, and the future of financial advisory firms.
A lot of people have been talking about I want to get my data collected into a single source. And so they start with that initiative, but they don't actually think about what do they want to do with that information once it's all together. They have been hearing for so long that everybody's building data warehouses and data lakes. And so they just think, "Oh, well, this is what I got to do.
I got to get all my data in a central location. " For what purpose? What is the end result? What are you trying to do with that information?
And how are you going to do that? And so many people are not looking at that second phase. Hey everybody, welcome back to another episode of Next Mile. I'm your host, Kyle Van Pelt, co-founder of Mile Marker.
And today I am joined by Verity Larson. If you've been hiding under a rock and you don't know who Verity is, Verity is the founder and CEO of Versoft Consulting. And if you're looking at this on video, she told me just before we came on air that this is the longest her hair is going to be for quite some time cuz she's getting ready to go chop a whole bunch of it off. So that is her personal fact and I think that's pretty awesome.
In addition to the fact that she just got back from Cancun, Mexico with the Versoft team celebrating an awesome year. Verity, thanks so much for hanging out with us on Next Mile today. Thanks for joining the show. Thanks for having me.
Look forward to talking with you. Of course. All right, I ask everybody the same first question, Verity. So I've had a hundreds of these conversations at this point and I've found everybody has their own unique path to this industry.
Some people follow traditional family footsteps path. Other people didn't even know this was an industry they could work in and they came in through the side door after a different career. But whether their path is traditional or untraditional, I found everybody has what's called a money moment in their life. And that's that moment where the light bulb clicked and you decided this is it.
This is the industry where I want to spend my career. So for you, what was that money moment that led you to have this conversation with me today? That's a really interesting question. So my background, I got started in this industry simply as getting my degree in computer information systems.
So having that technology background and it was dating myself, but end of the dot com bubble burst and I'm out there looking for jobs in anything technology and sending out probably close to 150 resumes just trying to find a job. And there was one firm that actually responded to me and it was an asset management firm here in the Portland Oregon area where I live. And went in, had an interview. I knew nothing about the financial services industry, let alone investment management.
But what do you know, they ended up hiring me. As far as how I evolved into what I'm doing today as a consultant, it definitely stemmed from that job and really getting to understand the industry itself and what investment management is. And understanding that I really wanted to expand my horizons and get exposed to more technology, more integration, more automation, any way to learn new things, be challenged by different technology, things like that. So my background has always been on the tech side, but certainly in this industry, I worked at that firm for about eight years and then I went on and worked at Advent Software, now owned by SS&C, as an implementation consultant.
And then from there, really decided I wanted to be vendor agnostic. And so that's who we are today is we're a boutique consulting firm that has no holds to any specific vendors. And we simply are helping with selection as well as implementation and just overall improvements to the entire tech stack used by asset managers, wealth managers, RIAs, single and multi-family offices, even some trust companies. And this is completely a constant learning experience and I think that's what I love most about this job.
Like every day is something new. Every day is a new challenge or a new way that a user is doing something in their firms. That's what I like. I like a challenge and I love opportunities to learn new things.
That's awesome. I love that as background. Okay, so one of the horror stories, quote unquote, that you've told me before and that we've heard before is when you get brought in late into like a system conversion project, right? So these things are all over the place.
It's turned into a messy ball of yarn. You've got to validate the system the original system data. You've got to do all kinds of things. These projects that people think are supposed to be one or two months balloon into nine, 12, longer, right?
I'd love to hear you talk about what can make these projects so challenging and then why it seems easier on the surface, but then it's kind of that iceberg problem of, "Oh, once you get underneath, it gets challenging. " And that's what creates these enormous gaps in expectations for how long somebody thinks it will take versus how long it's actually going to take. Yeah. Well, certainly there's a number of reasons.
One is most people assume that their data is clean and it's not. Especially when you're talking about years and years of history. And so when someone's looking at doing transaction history conversion or any sort of large data set that has covered years and years of information, there's just likelihood that there's garbage. And of course, garbage in means garbage out.
So if you hand over bad data to a vendor or even a third party like us where we do conversions, and then that data ends up ends up getting loaded into the system, well, of course, once you try to validate that data, it's likely going to be garbage out as well. So first and foremost, a lot of things, you know, people are assuming it's clean data and so they think that validating that data is going to be easy and it's not. And then of course, when you're doing a conversion, your data is being transformed. It's not identical to what you took out of the system.
It has to be transformed and changed to work with the new system that it's going into. So there's a lot of data mappings that have to take place. And of course, if that data is not mapped correctly, then you're going to also have more problems. And it depends on who's doing the data mapping.
Is the vendor doing the mapping? Are you as the user who knows your data involved in that mapping? Sometimes that mapping doesn't happen correctly. So again, when you come to validating that history, it's bad.
But yes, we've we've had these these issues where clients are going through a conversion. They're leaving one system and moving to another and they hand over their data to the vendor. The vendor converts it and then they just think magically everything is going to match and align and everything looks great. And that just isn't what happens.
That's not reality. And so getting in there and figuring out what happened, you know, what needs to be corrected, who's responsible for correcting things, you know, that then becomes this iterative process to do clean up and check, clean up check, clean up check. And that's how things expand into nine or 12 months long and certainly delays projects. So certainly we like to encourage that people are looking at changing systems or even expanding or or adding on like data warehousing services, something like that, make sure you actually do some scrubbing of your data in advance.
So your source data is actually accurate and you know what you have. You also know maybe what problems to expect should that data get moved into different system. Yeah. I'm totally with you on that.
I mean, we have those conversations all the time where it's like, "I can't fix your data before we bring it into what we're doing at Mile Marker, right? " So if we bring it all together, I can absolutely show you all of the areas where it needs to be dealt with and fixed and everything, but you're absolutely right. We can't make those problems of the past go away just because of what we're doing now. And that is something that they have to participate in.
We always like to say, "We need the people who know what the right answers to the data are to help us on this. " And so 100% agree with you when it comes to that type of thing. I know people always have a lot going on or whatever, but this is a problem that persists basically across 100% of the firms that we speak to. And you know, maybe it's varying degrees of what this looks like, but why is data getting wrong or years of data kind of, you know, falling apart?
Like what causes this problem and why is it so hard to kind of stay on top of for RIAs? Yeah. Well, first of all, I'd say if you go back and look historically, there is a big change, especially when you're talking about portfolio data, right? Account level data, transactions and the like.
In 2012, there was regulations put in place that held the custodians accountable for cost basis, whereas historically they weren't. So prior to 2012, the accuracy of data from a custodian just simply wasn't there. Unless you actually had a portfolio accounting system where you were owning and controlling your data and making sure that it was clean and accurate. And then of course, what level you actually took accountability for in keeping that data clean, it was a very large challenge just to make sure that data was accurate.
And again, it revolved around what were your processes internally to make sure that you kept that data accurate. But then after 2012, there was that change and now custodial data, I think, is way, way better than it was, you know, 13, 15 plus years ago. So, depends on how much history you're working with. If you're going to data prior to 2012, that accuracy diminishes greatly.
I mean, it's almost like night and day difference. After 2012 and of course even more recently, data is so much cleaner just because of the source. So, that's one key consideration. But secondly, it does come into what are your processes?
How are you ensuring the accuracy? Even when I talk to firms, not even outside from portfolio accounting data, it's also about like your CRM. And most people that are using a CRM system, very rarely historically have they actually had any sort of administrator. Somebody that's really responsible for overseeing the system, making sure that people are entering data correctly, that they're populating the right fields, that they're putting in the right information, making sure that there's actually like kind of rules and requirements around the data.
Some of this even relies on the systems themselves and how they've advanced in technology. I mean, for example, there were systems in the past where you literally had a text or a check box as a field. And so, if you were putting in numbers into a field, it had no way to verify if you were mixing numbers with text, right? But now systems, of course, have add-ons, so it's not just Boolean or text or it's numeric field or date format, whatever.
There's more control that's been put in to some of the software platforms, which helps ensure accuracy of data and compliance. And then of course, there's just making sure you're setting up the system correctly where maybe certain people aren't even supposed to have access to edit certain types of data or ensuring required fields are actually being populated. All of these different processes, a lot of firms just haven't had the right things in place to ensure that they've set up their system properly and have these what your requirements are as a firm. So, if you don't have those in place, then you do start getting away from clean data.
So, not having the oversight by somebody that's making sure that data is being entered correctly and it's being maintained correctly, but also not having the system structured properly so that people aren't being forced to enter clean data. Mhm. Does that make sense? That makes a ton of sense.
That makes me think about one of the big pieces of value proposition for Verity Software firms and maybe those who are listening to this is you won't just get on a call and then scope out the project and go get started. Part of what you all do is you do multi-level interviews throughout the firm to really understand what's going on with the technology, what's happening expectations-wise, things like that. And there seems to pretty regularly be a disconnect between what certain people in the organization think are happening versus what's really happening. You know, hey, I thought we had these processes that you were just describing, Verity, where people were verifying this, putting in the right thing, doing all of that, but yet you're telling me it's not happening.
So, talk to us about that interview process and talk to us about why so often there's a disconnect between different layers and levels of the company. Yeah. You're right. We do like to get in and do those interviews.
And what we explain to users as this is about a day in the life. We want to actually do screen shares. I mean, we honestly used to do these in person where we go in the office and literally sit at a person's desk and almost like watch them work and see what they were doing. How are you opening an account?
What does that look like? If you're on the marketing side and you're doing sales initiatives and outreach, what are you doing? What are the buttons you're clicking? What are the applications you're accessing?
What information are you putting into the systems? What information are you trying to retrieve out of the systems so you're generating reports, things like that. And just getting a better sense of what they're doing day in and day out and how they use their systems. That's where, of course, we see just a simple like let's just take like a client service rep, right?
You can have, let's say, five of them at one firm. And every single one of them is doing things differently and could be night and day difference. Some could just be a slight tweak to a process and they get the the job done. But the way they go about it could be very, very different.
That is a very, very common occurrence. And you of course you might say like how does that happen? Well, it just happens over time. People naturally are going to change the way they do things just by the way that they're comfortable or with however tech savvy or not they are.
Could also be whoever trained them and how long ago they learned the system. Again, the tools are changing on a pretty frequent basis. So, if somebody was trained 10 years ago versus somebody was trained two years ago, the way at which things were done were probably a lot more manual for the person that was trained 10 years ago and they continued to do things more manually versus the person that was trained two years ago on the same system, you know, it's more systematic and streamlined. So, there's a lot of reasons for it, but ultimately what we need to do is figure out who's doing what, how are they doing it, what are the end results that they need to get.
And that end result is really the critical factor. As anytime we're trying to look at improvements to processes or even transitioning to new tools or technology, it's really about what is the end goal. You don't ever want to repeat or recreate old processes in new technology, right? You need to adapt and change and accept a new way of doing things as long as your clients, management, executives, the board of directors, whoever it is, is getting the information that they need, is getting your meeting client satisfaction, you you know, you're you're doing your job.
That's the end goal. And as long as you're doing that, that's all that we're trying to ensure is retained. Mhm. So, that makes me wonder, okay, what are the most common reasons why people are calling you?
Is it a conversion like, hey, we've just had it with this other system and we want to move to another one or, hey, we bought some firm that's on a different one, can you help us? Or are there other main things that you're seeing that are, you know, that are leading to these interviews and things like that? What are the most common reasons people are hiring Verity Software? Sometimes it's firms that are simply fed up with whatever they have and they just go, we're having problems left and right, whatever it is, or we don't like the vendor we're working with and we're just tired, we want out.
And then sometimes it's just where they know that they need to change because they need to provide support and additional services that they're not able to currently meet with their technology. And then I'd say lastly, it's because they hear everybody talking about stuff like AI. Do we dare we say that word and bring it into the topic, but everybody is talking about it now and so everybody feels like they have to they also have to talk about it and they have to learn more about it. So, people either feel like they're they're required to get into it because everybody else is doing it or they already have something that is pushing them into a change.
Those are usually the main reasons we get engaged. Now, at what stage do we get engaged with people? Sometimes they go off and they're evaluating technology themselves and they've been doing it for a year. And then they come back and they're like, we've been talking to 20 different vendors and we just don't know where to go or what to do and there's new people coming into the business all the time.
I'm like, yeah, that's why we do what we do, right? And it's like don't spend your time and efforts doing that level of involvement because that's our expertise. Just like you're a homeowner, you know, yeah, you could go and rewire your house. You certainly could do that or replumb your house.
But you're probably not going to do that. You're going to go hire an expert, somebody that actually knows it and can do it 10 times faster than you could do it, right? And so, that's a lot times why we like to get involved, but I digress. And the point is, when we get involved, sometimes it's because people have been going down these rabbit holes by themselves and then finally are just like, uh, I'm fed up, I'm tired about this.
I need to get some help and then they'll pull us in. Sometimes they've actually gone through and actually made a selection and they're halfway through an implementation and then the project looks like it's going to get delayed and it just keeps going on and on and the team is getting frustrated and burnt out and they don't see an end in sight and they just know that they need help. We get called in there. It's kind of like all these different stages.
Ideally, of course, we want to get involved as early as possible, but we're always there to help people at whatever stage they're at. Yeah, you're planning missions and your rescue missions, right? Planning missions tend to go a little smoother than rescue missions. Correct.
So, okay, I want actually want to double click on that, too, because I feel like this is a conversation I have pretty frequently as well. I understand that people will get to a place where they feel fed up with a certain piece of technology. And one of the questions we often get at Milemarker's, "Hey, are there certain vendors that are better when it comes to a data perspective or data sharing perspective or whatever? " Because maybe we're a little frustrated with this tool or we're frustrated with that and we're thinking about changing and whatever else.
And obviously, I'm not saying people should never change, but I just have this deeply held belief in our space that the grass is green where you water it. Like most most people have just not really taken the time to really learn how a lot of these systems work or whatever, and they tend to be fed up with something that they would be equally as frustrated with if they went to a different solution or maybe they would just find something new to be frustrated with. So, maybe this is a broad question, but in your experience, like how do people actually make themselves successful with the technology that they have? Because no matter who you are, no matter how great the tech is, changing is painful.
Not just from the conversion process, but you've got to change management process, you've got all of these sort of things. So, that's just something we hear a lot, and I'm curious to hear your thoughts on, how do they make themselves successful? How do they be less fed up? How do they not burn the team out as much with these tools that have a lot of power behind them, but you just got to learn how to use them?
Yeah, I'm so glad you brought that up. And I think that that's probably the thing that I'm I experience some of the most frustration with with clients is especially where they just go, "We're fed up with whatever we have, we're going to change. " And they're not even open to discussing how they can actually make their current technology work for them. But to your point, that is way less effort in the long run than changing to new technology.
And in many cases, that is truly a doable thing. Yeah. >> Like I said, the only time that I think that really looking at ripping out whatever you have and putting in something completely new is if you're really advancing on different services or just simply offering something or need supportability for something that your system currently doesn't offer. Multi-currency is a good example.
If your system just simply can't support multi-currency and yet you are now supporting global clients, got to get a system that's going to be able to support that, right? There's no ifs, ands, or buts about it. You you just have to replace the system. But if you're just talking about I don't know, sometimes even just adding an a different asset class or you just want better reporting, there are things that you absolutely can do with your current technology that doesn't require a rip and replace.
I wish that more people would actually take that approach. But it's certainly is something that we do a lot of. And I guess what I'd add is we call it a business process review. Mhm.
So, that BPR is really just coming in, assessing what your business does, what does your business need? Cuz it's not just current operations and current roadblocks and challenges that you're having, but also what is what are the initiatives of the company? What are they trying to achieve in the next 3 to 5 years? And then making sure that you plan around all of those things with changes in the current technology.
The other thing is I was even inferring before is because so many systems nowadays are cloud-based platforms, these cloud-based systems, they are constantly [snorts] changing. They are adding on new features and abilities and integration and automation and workflows and all these things. And yet so many people are simply using the software the same way as the day that they initially implemented it. And they don't even realize how much more has been added to the software that could actually help support them more.
And so, it's technology they're already paying for. It's already there. It's free. They just have to take advantage of it.
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Hey Next Mile listeners, Jessica here from Milemarker. You know, we talk a lot about reaching that next mile in your business journey. But let's be for real for just a sec. If you're an advisor, how much time are you spending wrestling with data instead of actually advising your clients?
[music] I've worked firsthand with tons of advisors over the years helping them achieve real success and break through growth. But I keep seeing the same roadblocks everywhere. Brilliant advisors stuck spending hours pulling reports from their different systems trying to create meaningful client presentations and struggling to get >> [music] >> a clear picture of their firm's growth. Does this sound familiar?
Here's what I've learned. The advisors who are scaling and growing aren't necessarily smarter. They've just figured out how to get control over their data. That's exactly why I joined Milemarker, because [music] they've built a solution that changes everything for how you manage and grow your firm.
At Milemarker, we specialize in three game-changing areas for firms like yours. Streamlining your data management so all your systems talk to each other, automating those repetitive reporting tasks that eat up your valuable time, and creating seamless advisor and client experiences [music] that actually help you grow your firm. The difference is night and day. Instead of spending your evenings pulling together client reports, imagine having that data automatically organized and presented [music] exactly how you need it.
Instead of guessing about your firm's performance, imagine having real-time insights that help you make strategic decisions. If you are ready to stop being held back by your data and start using it to fuel your growth, I'd love to have a conversation with you. >> [music] >> We're offering Next Mile listeners a complimentary consultation to explore exactly how we can help you transform your advisory practice. Don't let outdated processes keep you from reaching that next mile in your firm's growth.
Visit milemarker. co and mention the Next Mile podcast, and I'll personally make sure to get the insights you need to take control of your data and scale your practice. Because your time should be spent building your business, not buried [music] in spreadsheets. All right, I'm going to get nerdy with you for a second because I know you've spent a lot of time in the data of a bunch of these systems the way we have.
And this is maybe as much for my curiosity as anything else, but I am fascinated by the fact that a lot of these systems will calculate a very common metric differently from each other. For example, net new assets, like the way that some systems will classify an account transfer as an outflow or distribution even though it's not a distribution, right? Or the way certain systems handle RMD calculations versus others. This feels like kind of a universally agreed-upon thing.
Why do all of these different companies and systems calculate them differently, which can also lead to people feeling crazy about how this and and leading to I'm so fed up, I want to go to a place that can calculate this the right way. So, talk to us about that. And then, hey, if you are somebody who's experiencing that, is there a way that you can sort of make that work for you or adjust it based off of what you were just answering before? Yeah.
Well, I'll even throw on an additional wrench to that, and that is that even some of the older systems, the systems that have been out there for 30 years, you actually had your own control whether or not you used certain transaction codes or not. And you could almost like book things the way that you wanted to, not necessarily how the system was intended to be used. >> Yeah. >> So, you have multiple layers here, whether or not people were using the systems the way they're intended to be used, but also the differences between systems and how they code transactions or they calculate a formula.
Performance, of course, is another great example, right? Everybody has a different formula for performance. And yet everybody is technically in compliance according to SEC or if you do GIPS or whatever requirements, FINRA, whoever it is that you're reporting to or regulated by. It's extremely frustrating.
So, all I can say is each firm has their own perspective. Sometimes when the software is being developed, whoever is developing it is simply going, "Well, I don't see that there's a need for this much granularity. " And so, they're consolidating things into a larger bucket, whereas somebody else may have more detail in different types of transactions. And of course, different types of transactions roll up into how assets might be calculated, what transactions get included in a calculation.
So, to me, it's just simply back to who developed the software and who ended up coming up with this idea that this is how the system should calculate. I mean, it really is no more than that. It's just everybody just kind of does it differently. But it's a very important consideration cuz like I said, when we do our conversion projects, we're simply helping clients validate the data got converted correctly.
That's another key distinction is understanding the differences between two systems. And you have to know how one system is treating something versus the other because there's just simply differences between the two platforms, and you will never be able to get them to be identical. Never. Yeah, it's wild.
It's wild I mean, I understand that there can be a difference of opinion on is this equity, you know, this type of asset class or this type of asset class. So, everybody has to create their master security list and stuff, but you know, when I think about bookkeeping, right? Like there's only two ways to do bookkeeping. You can do cash base or you can do accrual base.
I mean, that's it. Like there's two standards. So, it's just wild to me that we can do bookkeeping, which really when you get down to it is what portfolio accounting and performance reporting is so varyingly different. That is a wild thing to me that we have not standardized like these are the one or two ways that you would book these things, but I digress as well.
100%. I don't know what to tell you and it's just that is the way it is and unfortunately, so many people in the industry don't understand that and they do think it's just a one-for-one, you know, they're just identical. That's also why people think, oh, well, we're just going to implement this new system. We just pluck out this data and we load it in here and boom, just like that.
It matches and it's perfect. Like that will never ever happen. You know, there's always going to be differences and there's going to be mapping and you know, this yeah. That's also why even in the work we're doing now, trying to build AI like agents to help with the conversion, to help with this validation and yet every data set ends up being different.
Like I said, some firms even have used the system differently than it was intended to be done and so when you think like a deposit should be captured as this type of transaction, the firm ended up using something different and it's just I don't know, just constant challenges that you have to work through every conversion, every data set, every vendor is doing things differently. Yeah, that's candidly that's one of the reasons why we're being so successful at MileMarker 2 though is because we're able to look at all of those differing ways that data is being presented, that they've worked with it, that they've changed it, that they've adopted it and we can make it work as opposed to, well, it has to fit the way that this thing sees data. So, providing some of that old school granularity, I guess, and flexibility to what they're doing. You mentioned AI a little bit.
I would be remiss if I didn't kind of, you know, somewhat tongue-in-cheek ask you about what you were just saying. Somebody's on the phone with you and they say, well, Barry, why can't I just vibe code something that will solve some of these problems, right? I'll just get AI, I'll prompt it a couple times and it's just going to give me a solution to the to the issue. I'm sure you're probably running into some of those things right now, too.
What would your response be? Oh, I'm running into it all too often. It's pretty frustrating, you know. >> [laughter] >> Um right now, like AI is still so new.
Yes, it is advancing quickly, but it's not perfect and it still needs a lot of human not just oversight, but knowledge and input in order for it to be accurate and also, you're talking about what is your data? How accurate is your data? And where are you relying on that data from? And so, yeah, can you spit out a bunch of code from these AI vendors out there?
Of course, you can, but is it accurate? Is it going to actually be generating something accurately off of your data? Likely not if you don't actually know what it's doing. That's where there still is a lot of hand-holding that is needed in all of this work effort and I'm sure that you're seeing that as well.
Like there still is understanding and experience needed. You can't just go slap some AI onto something and expect it to be perfect right now. That's just not where we're at. That's I think one of the biggest conversations that we're having on a weekly basis right now is that AI without context, it's powerful, but it's not going to provide you the full results that you want.
And with MileMarker, we're able to provide a lot of that context because now you're taking something like Claude and it can safely look at your data, right? As opposed to just using all of the data that it's been trained on or things along those lines. And then you can start to do some cool stuff because it's like, all right, there's work that's been done, it can validate, it can look at your actual real stuff versus, hey, here's a prompt, it's kind of generic because I don't want to send my data outside to an open LLM or any of that type of stuff and then I'm just going to take what you give me and do the best that I can with it. So, I agree, but I do think it's an exciting time when it comes to some of that stuff.
And I think [snorts] it's just going to provide more flexibility more flexibility than ever. I know. I mean, I'm very excited about what's going on. Now, I do think that there's going to be a lot of consolidation that's coming up, too and that's something that a lot of companies that we're talking with, not the vendors, but the users themselves that are like, well, should I go with this system or this system or this system, you know?
And every single day there's a new vendor popping into the space offering agentic workflow automation and you know, whatever and it's just like, okay, do you use one of these 20? Like and of course, which one is going to be around, you know, a year, two years from now? I think that that's even myself, I'm a little wary of, you know, it's like I just don't know who to stick with at this point. It's kind of like, well, let's just keep trying them all and we'll see like what funding, what backing they have and then also, how easy it would be to find a replacement if needed, you know, you don't want to go and spend all this time and effort to put tools and technology in place and then in a couple years be worried that the company is going to go under because they didn't make it and then what do you do when you were building operational efficiency around that and that's a pretty impactful side to your business.
So, you know, it's considerations that that everybody has to make, but there is going to be consolidation with all these technology tools. They just can't last. They won't last. Yeah.
I think I agree with that. We just got back from Future Proof in Miami and there was so much excitement around a lot of the AI tools and there's a bunch of really cool stuff that is being created, but one of the conversations that happened over and over again in my breakthrough meetings or in other conversations that I was having is they said, you know, this is all really exciting, but it sort of just feels like the same problem we've been having just with AI attached to it, which is every tool that I use now has some sort of AI component, but none of them talk to each other with the AI component. So, they're just applying AI on top of what they have, but not across the entire, you know, suite of data that we have or whatever. So, now I feel like I've just got more tools with AI that don't necessarily talk to each other and then oh, by the way, 80 plus new companies have sprouted up in the past whatever that are all AI focused, agentic this or you know, whatever that I have to be responsible for evaluating and they said it it kind of is paralyzing because it doesn't feel like it's a full solution.
It feels like they've just, you know, kind of added onto their house rather than rebuilt the foundation. Correct. Yep, and everything still has remained so siloed, right? Everybody has these AI tools in their own software, but everything is still so siloed and that's what people have been trying to get to and want to get to is getting their data consolidated, bringing things all together, being able to use it holistically and that's the keyword, using it, right?
And so many people are still struggling with that. So, it's great that all these tools are out there, but it still is very, very siloed. And people are just feel like, oh my gosh, now I'm just adding more to my tech stack. I thought I was going to be bringing things down, consolidating and reducing the technology that I have to use and now I'm adding more to it, which makes it just more complex and requires more time and effort to to manage.
Yeah. All right, I need to talk my book for a second, but it's more holistic. So, I think it was about a year ago, you had said something like you're seeing a lot of firms talk about data lakes or data warehousing, but you hadn't really seen a ton of adoption. And then, I don't know, six months, eight months ago, Josh Brown from comes out and he's like, hey, coming out of these Future Proof retreats, all we're hearing about is CEOs talking about data lakes, right?
Data lake this, data lake that, like they're trying to get AI ready, they're trying to do this, they want to do data lakes. That's what launched we did a whole campaign called Data Lake Summer where we were helping with that, but then before we even got on, you were talking to me about a lot of the prospects you're speaking with, firms you're talking with maybe have tried this data lake thing, haven't seen a ton of success, you know, haven't figured it out yet. What do you think is the current state of data lake or data warehouse adoption in wealth management today and where are you seeing the sticking points? I think a lot of people have been talking about I want to get my data out there and collected into a single source and so they start with that initiative, but they don't actually think about what do they want to do with that information once it's all together.
So, it's like they've they have been hearing for so long that everybody's building data warehouses and data lakes and so they just think, oh, well, this is what I got to do. I got to get all my data in a central location. For what purpose? What is the end result?
What are you trying to do with that information and how are you going to do that? And so many people are not looking at that what I'd say is a second phase, all right? It's just like, oh, well, we just need to get our data to this data lake. And so that's just becomes the key initiative and they're working on that.
I was sharing with you earlier, we have a prospect we're talking to right now and she said they've been working on their data lake for two years and they still have absolutely nothing that is useful. She's like, all I want is I want to be able to query for some of my historical information. I want to be able to pull up accounts from five years ago and I can't do it and they've been working on it for 2 years. You know, so people are spending time and effort on this, but I don't see it resulting in anything fruitful for them.
And likely it's because they're just going about it the wrong way. So, yes, people are talking about it. Some people are doing something about it, and even fewer people are actually successful with it. Yeah.
So, in your expert consulting opinion, what do you think people should be doing with the data lake? Talk to the experts. Talk to the people that actually do this. Talk to firms like you.
Talk to people like me, cuz I think that's the problem is again, they get caught up in the hype and say, oh well, this is what we need, or maybe they even have a larger ownership, you know, they're part of a larger company, they might be a subsidiary, and the company is saying, well, this is what we're doing as a as an organization overall, and they go, okay, well, I guess we got to get our data into this thing. But again, for what purpose? What are you going to do with that data after the fact? After it's all in one place.
And having a plan of action. What are the tools you're going to be using, and making sure that whatever you're building is actually going to work with those tools. Again, technology changes, so were you building something in in SQL 2 years ago, but now maybe it makes sense to use a provider like you guys, like Milemarker, or does it make sense to go and put your data in Snowflake because it's, you know, needs to be shared with a much broader organization? I mean, like, just understanding it, and using relying on experts has to be the first step.
I know that sounds sounds cliche as you and I are here talking about it, but it is. Like, why are you going through all the time and the expense of doing this, and what's the end goal? Yeah. I think that's also it, too.
There's a pretty big hidden cost in doing it yourself of you have the cost for the build out, but, you know, what we've heard from people too is the maintenance and the ongoing ended up being way more than they originally planned for. It's not that they didn't plan for that, but it ended up being a lot more than they expected. Whereas if you can get economies of scale by working with a partner, it's very valuable. Absolutely.
Yeah. How many firms I've talked to have said that their roadblock has been that they understand and and have expected that they needed to hire additional staff just for the maintenance of these data lake houses. And do you need to do that? I mean, maybe you do, maybe you don't, maybe you partner with somebody, but yeah, that's a huge cost consideration.
Yeah, I love it. All right, I'm going to put you on the spot a little bit. So, you've been well versed on some of this, but let's assume somebody has a data lake, they've done all of the stuff, and they come to you and they say, okay, we've got everything. Verity, what's the number one use case that we should be going forward with phase one, step one, the first thing we should do once we have all of our data in one place that's going to create efficiency for our firm or create success out of this project.
They hire you to do that. What's the number one thing you tell them to do once they get all their data in one place? Probably one of two things. Ultimately, it just comes down to reporting, and I'd say either it is about improving the client experience, so the end investors, right, that you are servicing, making sure that they have anything and everything that they have ever wanted, right?
I think that that's the thing we're seeing, and that's been the trend for a long time. Back in the day when I first started, you were lucky getting quarterly statements. And now everybody investors want information on demand. They won't when they want to know what their return is or how much money they have in their portfolio today, they want to see it today.
You know, so I think it's just making sure that that information is accessible and is relevant for the clients is probably first and foremost, and that you're making that accessible for them. Secondly, of course, is using that data as business intelligence for your organization, and making sure that you're using that to actually grow your business. I mean, I don't know any entrepreneur out there, myself included, that doesn't want to grow their business. And you need that information to understand your wins, your losses, where you're seeing opportunities from, where there's additional assets from existing clients that you can go after.
I mean, there's so many things. How much time are you spending on clients that are really not profitable for you, right? They might be sucking a ton of time from you, but they're some of your lowest revenue generating clients, right? So, just all of those different narratives, to me, it's about just business oversight and proper business intelligence to start making better decisions as an organization.
I love it. Great answer. All right, we're going to move into the final segment of the show that we call the Milemarker Minute, a series of lightning round questions aimed to get to know you a little bit better, have some fun. So, are you ready for the Milemarker Minute?
Let's try it. Go for it. >> Okay. Verity, if you could travel anywhere in the world you've never been to before, where would you go?
Australia. Okay. Are you a mountains person or a beach person? Mountains all the way.
Okay. What is the best road trip you've ever been on? Ooh, probably a long time ago. I took a road trip to visit friends in college traveling from Wisconsin down south.
Yeah, that sounds pretty good. What's the best flavor of ice cream? Chocolate. That's a classic answer.
You know, I hear that very rarely. You think you would get more just chocolate, but I appreciate that. Respect. And then, so the name of our company is Milemarker.
Milemarkers are a symbol of progress along a journey, and that's one of the reasons why we did this because we believe the journey's never done, but we always want to be measuring our progress. So, with that preamble, one of the questions I love to ask people is to finish this sentence. And this can be for you personally or professionally, but progress is blank. Constant challenges and knowledge growth.
I love it. That's a great answer. Okay, and then last question for you. There's an alternate universe, and in this alternate universe, Verity Larson cannot do anything that has to do with financial services or financial services technology or consulting.
In this alternate universe, what is your career? I'd be giving tours of like Egypt. Okay, let's go. >> that.
>> [laughter] >> Tour guide in Egypt is a solid answer. I love it. Verity, you made it through the Milemarker Minute. I had a lot of fun on this conversation with you.
I think you dropped a ton of practical, tactical, insightful knowledge about how firms should be approaching their technology. So, thanks so much for carving out the time to come and have this conversation with me and share your insights with the audience today. Thank you so much. Thanks for having me.
Of course. All right, everybody, that's been another episode of Next Mile. Please make sure you click follow or subscribe wherever you're paying attention to this, and if you'd be kind enough, leave us a review so other people can find the show that have never heard it before. But until the next episode, enjoy every mile.
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