Transcript

[00:03.280] – Vidur Gupta

Hi. I’m excited to welcome Beth to our show. And, you know, Beth needs no introduction, but amongst other things, having built and sold one of the most well known lenders, she’s also considered to be a highly data driven CEO, and that’s what makes her even more interesting. So, Beth, thank you for joining us today.

[00:31.960] – Beth O’Brien

Thank you for having me. I’m excited about this. There are very few people who share my glee for data the way that you seem to. And the notion that I could actually be dating or being wed to my data is actually something that’s even more exciting for me, which is probably saying something about my lack of hobbies. But that’s okay. We can get into that later.

[00:59.700] – Vidur Gupta

Thanks, Beth.

[01:00.530] – Vidur Gupta

So, you know, why don’t we start with some history, like, you know, going way back, you know, to high school. Do you have an enduring memory of high school math, or.

[01:11.860] – Beth O’Brien

Yeah, I have to say I loved high school math, which, again, probably speaks to my lack of hobbies. But high school math was fascinating for me, and luckily, I went to a pretty fantastic suburban public high school. But I think they were very flexible and allowed me to take math classes with, you know, outside of the grade. It wasn’t really regimented in. So it was, for me, it was really interesting, because my memories of high school math are actually in these kind of more interesting groups of older people and kind of trying to figure out, like, who was who and what was what in high school was hard enough, but that was actually kind of an interesting piece of it. But, again, math was great for me because there was always an answer. As you obviously get into more sophisticated math, there aren’t very specific answers sometimes, but certainly in high school, the good and best news about math was that you could come to a really concrete answer at the end, which I loved.

[02:11.480] – Vidur Gupta

Absolutely. So following on from that, what or who built your data muscle, if you could.

[02:19.600] – Beth O’Brien

Who built my data muscle? Well, that’s. That’s kind of also, I think, a fairly interesting question. I, you know, I didn’t really, I think, fully develop my data muscle until I started running kind of not full blown companies, but at least parts of companies or, you know, divisions or something in a company, because, you know, there’s that almost cliched notion that you can’t measure what you can’t manage, what you don’t measure. And I know people say that all the time, and it sounds great, but it actually became really true for me. So it wasn’t until I was actually managing things that I realized how important data was. And that’s the internal data. Right. And I actually have a different relationship with internal data and external data. Playing the field is a little bit differently than being at home with your data. But I feel somewhat the same. But I feel differently about the two types of data. But the idea that until you’re measuring something, you don’t really fully understand the impact of the data that you’re using or that you’re looking at, that’s true.

[03:30.830] – Vidur Gupta

That’s true. And was it in banking that you first used it in the way you.

[03:36.820] – Beth O’Brien

Outlined it was, well, I guess technically banking, although I think the first time I was really, I could appreciate some pieces of the data, had more to do when I was running some of the investor relations on our, in a real estate fund at Goldman and just seeing how people reacted to different things that we were doing. That’s the only thing that for me is pretty exceptional about data, is that you can have all the best instincts in the world. And I think in order to be a great entrepreneur or to be a good business person, you do need decent instincts, and you can’t let data drive you completely. But you have to be open to the fact that sometimes the data speaks to you and tells you that you’re wrong and that you have to question your instincts with it. And so, like, for example, you know, I have very specific marketing ideas, and sometimes my marketing people would come to me and say, well, have you thought about this type of photo versus that one, or these colors versus that? And my instincts are usually spot on when I say, no, orange is so much better than blue for this.

[04:38.910] – Beth O’Brien

But if you do a little bit.

[04:39.750] – Beth O’Brien

Of a b testing sometimes out on the big world Wide Web, and you let other people see what you’re doing, the data will come back to you and say, you know, beth, you are wrong. It is an orange type of people are going to click on orange and people are not going to click on blue or whatever it is. That’s kind of one of the nice love hate, push pull things with data, is that it can validate your instincts, which is fantastic and always makes you feel good. But sometimes it can really smack you in the face and say, hey, you’re wrong, and you have to be willing to at least listen to it, even if you want to tweak it somewhere.

[05:15.340] – Vidur Gupta

That’s true. That’s absolutely true, and I’m glad you think that way. So, going back to something you said about a time where you used it, tell me about a time when it truly inspired you or transformed the way you thought about a problem.

[05:31.000] – Beth O’Brien

So when we first started corevest, back when it was colony american homes, one of the earlier projects that we had was to use some data visualization tools, which I wasn’t really that familiar with. I mean, I was always one of those people who pulled it all in excel and, you know, was pretty good at saying, okay, make a pie chart, make a line chart, whatever. But as you know, some real visualization tools have come on the market, and certainly about ten years ago, they were starting to really take some, you know, they were really starting to get good and, like, you could really see something. And so the first time I was able to put together a dashboard that showed both our internal data coming in and some of the purchase data that we had, it blew my mind.

[06:18.560] – Vidur Gupta

Right.

[06:19.100] – Beth O’Brien

It really, and it was the visualization of the data that really impacted it for me and made me realize just how useful it was. And I’ve always been a large consumer of data, and even before it was really, it was even really common, I could read spreadsheets and poured through the numbers. And as I said earlier, I actually really like math. And so that was, it wasn’t that difficult to do. You know, I could, I could get my way around in Excel, Excel. And actually, I’m so old. We used lotus at one point, but the visualization tools just completely expanded my ability to look at things both on a trending basis and on a static basis. And I think that’s one of the things that when you can get deeper into your data and you see the different uses, you start really parsing it down and saying, okay, here’s my static data, or here’s my dashboard for what I’m doing this month. Quarter over quarter, whatever. But the trending data will really tell you something about what’s happening in your business.

[07:21.260] – Vidur Gupta

Absolutely.

[07:21.750] – Beth O’Brien

And not everybody’s stores. That was the other thing I learned from, even from starting to implement some of these visualization tools, is that the way you store your data from the beginning is going to impact how you’re able to consume your data later. And again, these all sound so easy and true, but anyone who has spent hours and hours recreating the field that their manager needs will really fully understand that.

[07:47.840] – Vidur Gupta

No, absolutely. Absolutely. That’s a very powerful insight, actually.

[07:51.920] – Beth O’Brien

Yeah.

[07:52.460] – Vidur Gupta

And on the data visualization side, do you have any top tips or any learnings from having implemented one nearly a decade ago?

[08:01.960] – Beth O’Brien

Look, it was one of the earlier ones, and it was fantastic. And I still remember even the first couple times people came on site for due diligence. And I would show them things. And even the external parties, you know, the rating agencies, the warehouse lenders, the different people were always kind of blown away by my ability not just to show them something like a PowerPoint, but to pull up what would normally be a PowerPoint and manipulated for them. Right. Like the ability to actually say, okay, here’s my slide on whatever metric or whatever, you know, loan attribute you’re talking about. But then I could show them. Well, over the past six months it was this way, or our asset management data, us this and the next twelve months, it could be like the prospective view on it. And I think it really opened like the outside people hadn’t really seen someone put together that type of a presentation for them before. I’m sure people are all doing it now, but also inside, that was the other thing that was very clear to me. I came out of some larger institutions in my background in order to get something like that spun up usable.

[09:10.120] – Beth O’Brien

Pulling data from all your different data warehouses and everything. I mean, it could take a year and a half, just get the approvals and the, you know, the sign offs and is it, you know, SAS compliant? Is it this, is it that? Whereas when you’re in, when you’re working in your own company and you’re an entrepreneur, it doesn’t matter, you may have institutional backing, you can get these things up and running quickly.

[09:31.090] – Vidur Gupta

That’s true.

[09:31.810] – Beth O’Brien

And you can use them for the thing. You don’t have to audit the, you know, your clicks to know whether your market campaign is good based on the visualization data. Now, and I’m not saying you shouldn’t audit the data going into things for certain uses, but your ability to pivot, move quickly, manipulate these type of programs, really was a game changer for me.

[09:54.180] – Vidur Gupta

Absolutely, absolutely.

[09:55.670] – Vidur Gupta

And so if I’m a business leader in 2024, I obviously have heard of data, I’m being, you know, pressure to use it. What’s your advice to other CEO’s when it comes to.

[10:09.780] – Beth O’Brien

So I think I’m going to break this one down into the internal external idea again, because my views have been evolving a little bit. Certainly on the internal data.

[10:23.590] – Beth O’Brien

The biggest.

[10:24.400] – Beth O’Brien

Advice I would give anyone is from the beginning, build whatever you’re doing in a way that milestones and captures any inputs that you have. So many people, myself included, will come up with a new plan or a new process, and everyone’s using the system to kind of push something through. Like let’s take a loan origination system, for example. You know, the, it’s a. It’s a conveyor belt. And so you’re basically using an Los to get a loan from the beginning to the end. But if what you really want to do is manage that process, you need to know, how many days did it take me to do this piece of the process, that piece. If you’re not milestone along the way, you’ll never be able to measure the stages or you’ll never really understand. And I think so many people are focused on their primary objective, which is to move the loan through the system, that they forget that six months from now, twelve months from now, I may want to understand, did the refi loans move faster than the acquisition loans did? So by capturing field, having a consistent. Having, capturing it consistently, and then milestoning it along the way, you’re going to be able, you’re going to come up with uses for your data that you didn’t know you needed when you were capturing the field.

[11:40.580] – Beth O’Brien

Now, with respect to external data, I will tell you, I spent years building out a data warehouse by buying publicly available mortgage data, putting it together in a way, cracking the code on how to look at different things for the private lending space, and really felt it was a competitive advantage of mine. I’m not sure I would ever do that again, because what you can get on the market externally now is fantastic. The quality of the data, I never felt the quality of the data was any good. And one of my little mantras was, always, your best data is your own data. And even when we were back at colony, we took the colony american homes data on their rehabs of the homes, and the way that they were looking at rents and everything, on the equity portion. And we used that to build out how we felt about the debt and what should be the benchmark for renovations or what should be like. There were people selling that data, but it was to me that your internal data, the stuff that you knew was accurate, was your best data. Now that I see what’s coming from, because of AI, because of the better data, because of people that were in larger originators and who have spun out and built data sets, you can actually buy quality data that’s meaningful and you can manipulate it in a way that’s meaningful.

[12:57.980] – Beth O’Brien

And so I would say you can leapfrog some of that early planning and designing stuff that we had done in order to have a competitive event. Now you won’t have a competitive advantage because anybody else can buy it, too, but hopefully you can build out your advantage by how you utilize it. Yeah, like how you are a consumer of that data. And again, that for me is combining what you know to be your own data with what you are getting from the outside. And can you marry those two things together to provide insight?

[13:30.520] – Vidur Gupta

That’s a very valid point. And it’s interesting how you segment them into internal and external data. So leading on from that, how do CEO’s build a data culture in their company? Because they might be data driven like you, but how do you engender.

[13:47.550] – Beth O’Brien

What’s interesting is that not everyone in your organization is going to have the same appreciation of data. That is clear. And not everybody consumes it as much as I do. Like, I think if you’re copied on an email that has an attachment, you’ve read the attachment every once in a while, you’d be surprised it’s not the case. Not everybody does open each attachment and actually read the data, which I do. I think it actually shocks people when I get back on the phone with them and I say, yeah, but like, you know, in the third tab, blah, blah, blah, and they’re like, what are you, like, how are you reading this so fast? You know? But I think by measuring people objectively with data and using it to help your examples and showing your managers how the data actually impacts what they’re doing, you will get more people on side than offside. And even people who didn’t think they were, people love to like rely on their instincts because that’s what got them to whatever successful point they’re in. And I never want to tell them not to rely on their instincts because I’ve probably hired them for a combination of their skills and instincts.

[14:56.690] – Beth O’Brien

Right. But you can hone that by using the data and figuring out where, where your instincts are particularly strong and where they’re not. It doesn’t mean you’ve given up on kind of managing yourself just because you are consuming the data.

[15:11.550] – Vidur Gupta

Right, right. Interesting.

[15:13.730] – Beth O’Brien

So, but I think it’s a real cultural shift for some people, though.

[15:17.990] – Speaker 3

Right, right.

[15:20.830] – Vidur Gupta

And you’re saying you got to break it down into smaller parts and show them the value.

[15:27.150] – Beth O’Brien

Yes, yes.

[15:29.470] – Beth O’Brien

Because they, no one really, people don’t immediately see the value. They think it’s one more step, it’s harder. Why do I have to fill in all these fields? Like, this is slowing me down.

[15:42.430] – Vidur Gupta

Right.

[15:43.310] – Beth O’Brien

But if they can actually get the benefit of it, when you say to them, like, wow, I think we need to make this process change because it’s, you know, we made a small change once in really small change that made a huge difference, and it really came out of the data on how we were doing term sheets, there was a certain approval that we did prior to issuing term sheets, and it was prudent to do this approval. I’m not saying it’s not from a business perspective and an instinct perspective, you would want this approval to issue a term sheet. However, when we actually dug into the data, we saw that we were only converting 30% of the term sheets, and so 70% of the time, we were spending what was an important step on business opportunities that didn’t actually come to fruition.

[16:33.590] – Vidur Gupta

Right.

[16:35.020] – Beth O’Brien

So I said, well, what happens if we took that important approval and made it the day after you signed a term sheet, everybody’s like, oh, you can’t do that. Because if you did that, maybe they, you made issue a term sheet that wasn’t perfect. I said, well, you haven’t, you haven’t countersigned it yet, and you haven’t even kicked anything off. You haven’t hurt anybody. You’ve just issued a term sheet. It’s not binding. It’s what you think it’s going to be. And then you do this one specific check before you sign, before you countersign it, but after it comes back and they’re, wow, I don’t know what it looked like a retrade. So anyway, we decided to test it for a few months. Not one term sheet got, not one term sheet had to be backed down from. And all of a sudden, we were spending all of this kind of important confirmatory time on term sheets that were actually going somewhere. And so all of a sudden, 90% of what you were working on was actually becoming real opportunities versus 30% of the same type of. And again, the behavior itself was an appropriate behavior.

[17:42.270] – Beth O’Brien

It was happening at an appropriate time, but the data was telling us that probably we were, you know, we were expending too much time on something that wasn’t giving us a business left. It was a tiny process change that actually didn’t change the client experience and enabled us to focus on the live deals versus the potential deals, which sounds like a reasonable thing to do. It’s just that we wouldn’t have gotten there without the data.

[18:07.440] – Vidur Gupta

Yep, absolutely. And you talked about measuring it and then managing it. So clearly, in this case, you were measuring it, which allowed measuring the time.

[18:17.180] – Beth O’Brien

Between submission, and we were also measuring the time between submission and term sheet signature. And it was getting longer and longer because of this process, which, I mean, I said longer and longer, like a day and a half to two days or half a day to a day. But it can actually matter in this particular stage of the business development.

[18:35.680] – Vidur Gupta

Right.

[18:36.060] – Beth O’Brien

Getting it out quickly gets you top of mind.

[18:40.030] – Vidur Gupta

Yep, yep. Absolutely.

[18:41.840] – Vidur Gupta

That’s a fantastic.

[18:42.440] – Beth O’Brien

So we were measuring it, and it was because it was extending that we started to look into it more. But actually, it wound up having a process change that we weren’t anticipating. We weren’t measuring for that process change, and still, that’s what we got. When you actually consume the data, that’s what we got from it.

[19:00.450] – Vidur Gupta

Right. Got it.

[19:03.090] – Beth O’Brien

And it’s kind of like a really simple change. I mean, it didn’t actually affect, like I said, the client experience or how good the term sheets were, because the same process still happened. We just switched to two pieces in the timeline.

[19:20.090] – Vidur Gupta

Yep, yep.

[19:21.390] – Vidur Gupta

And it impacted that specific milestone three times. So it’s pretty meaningful.

[19:26.160] – Vidur Gupta

Yeah. Interesting. Very interesting.

[19:29.770] – Vidur Gupta

So on that note, like, what is.

[19:32.720] – Vidur Gupta

The balance of, you know, how do you parlay instinct or, you know, experience?

[19:41.350] – Vidur Gupta

If I’m a CEO, should I. Is there a balance of instinct versus data that I should shoot for, or is that a case by case situation?

[19:53.110] – Beth O’Brien

So, look, I think you always want to rely on who you are and what got you to your success. And the data is just a whole nother piece. I’m not sure it’s a percentage as long as you’re open. The biggest issue is people who either only perform the data to or look at things and only see what confirms what they’re already thinking. And if something seems like it’s not confirming what they’re thinking, they say, what’s an outlier? Or that’s not. Or you come up with all these other things. The important thing is just to be open to what you’re reading and understand that there’s no. There’s really. There should be no bias there. And sometimes it really doesn’t mean that you need to make a change. There’s other more important human factors. But as long as you’re open to it, if you’re not just wed to your own way of being all the time, I think you’ll find the right balance.

[20:52.370] – Vidur Gupta

Thank you.

[20:53.190] – Beth O’Brien

It’s very hard. People get very, you know, like, as soon as you make a decision and you’ve gone through all this, you’ve done all this analysis, it’s very hard to stop and say, hey, this was the wrong path, and go back down another path.

[21:07.030] – Vidur Gupta

Yeah, yeah.

[21:09.030] – Vidur Gupta

And being humble enough to accept that is another challenge. Right?

[21:12.820] – Vidur Gupta

Yeah.

[21:12.980] – Beth O’Brien

And also not just humble enough to accept it, but also maybe egotistical enough to say, okay, fine, I’ll change my mind, right. I’ve got more information. And not hold yourself back from it. Like just say, hey, I have more information now I can go in a different path. I wasn’t wrong to go down the path. That didn’t prove right.

[21:34.780] – Vidur Gupta

Right.

[21:35.310] – Beth O’Brien

I did it based on the information at the time. Now I’m going to make a different one. As long as you do it quickly and you do it with purpose, I think making mistakes is fine.

[21:44.820] – Vidur Gupta

Right, right.

[21:47.620] – Vidur Gupta

Interesting. Cool. So just changing tracks a little bit to more geeky stuff about data sets, you talked about internal and external data. Like, what data set do you think is most overrated based on your experience?

[22:03.210] – Beth O’Brien

What’s overrated? Definitely some of the external is overrated. If you can’t consume it in a way that helps you in your business, it doesn’t matter how interesting it is. It actually, for me has to have a bottom line impact. And certainly in the mortgage industry, there is so much publicly available data that it could just be huge. And there can be a point where the data is so much that it’s uninformative.

[22:32.950] – Vidur Gupta

Right, right.

[00:22:36.070] – Vidur Gupta

Yeah, no, I agree.

[22:36.950] – Vidur Gupta

I definitely agree.

[22:40.750] – Beth O’Brien

I can’t consume all the mortgage data in the world. I mean, luckily I try to focus in on business purpose, which is actually hard to parse out of the, or used to be harder. Now it’s getting easier to parse out of what’s the kind of overall mortgage market? Because the overall market is so enormous. I mean, that’s one of the interesting things about the space that we’re playing in, is that the data set itself, I mean, it’s the largest market in the world. So the data set itself is probably the largest data set in the world. And so you can talk about big data all you want and how great it is and how enormous, and we have all these data points, but if it’s not usable and it’s not consumable, who cares?

[23:19.060] – Vidur Gupta

Right, right.

[23:20.720] – Vidur Gupta

So you talked about business purpose, usability of data, and consumability of data as sort of the. Is there a rank order in them or doesn’t matter?

[23:31.460] – Beth O’Brien

Yeah, I don’t know. I think consumability is the most important thing for me. And again, I got there through visualization tools. I think other people can get there through different ways. You know, all of us have, all of us have different ways of approaching what would come out of an Excel spreadsheet. Not everyone’s visual, but I very much am.

[23:55.600] – Vidur Gupta

Right, right.

[23:57.220] – Vidur Gupta

That’s very interesting. Thanks, Beth. And one other question is like, what is the one time data truly saved you in it saved me.

[24:12.620] – Beth O’Brien

You know, I can’t think of something that’s incredibly interesting, just. Only that it saves me on a regular basis when I start looking at things for, you know, look, we have a quarterly board meeting coming up and we start pulling together the materials and everything is pretty much you’re thinking like, what am I going to say this time? Like, you know, the year over year is this, that, I mean, it gets kind of, you’re just kind of a drone at some point. And yet I always find there’s something interesting in what’s being pulled together for me that I wasn’t really anticipating. And that piece that’s interesting tends to be what it is that we spend time talking about at the board meeting and people then walk away thinking, wow, she’s pretty insightful. When I feel like I got lucky because there was something in the term sheet conversion data that made me think, wow. Hadn’t really been thinking about how, you know, I hadn’t really been thinking about the lifecycle lending portion of what we’re doing. But now that I’m looking at how many of our bridge borrowers and term borrowers overlap with something, I can really see the value add we’re adding someplace else or, you know, some other topic like that.

[25:27.250] – Beth O’Brien

And it winds up. It winds up saving me in that it makes the meeting so much more interesting and looks like I was doing it on purpose. But usually it’s something that comes out of the data that comes to me in the preparation.

[25:37.500] – Vidur Gupta

Very cool.

[25:38.460] – Vidur Gupta

That’s a fantastic story. Thanks, Beth. So parting data, you think it’s cool.

[25:43.550] – Beth O’Brien

Because you like data. Like, there are people who would listen to this and be like, wow, that is not cool. That is not cool.

[00:25:51.540] – Vidur Gupta

That is very cool. I think that’s a fantastic story and I’m glad you run board meetings that way.

[25:58.780] – Beth O’Brien

I tell you, that’s the beauty of measuring things and getting data and consuming it, is that it sparks you or it should. It should spark you to think and to do things differently and to, or realize that some of the things that you’re doing right are actually working and you didn’t even know you were doing it right.

[26:22.160] – Vidur Gupta

That’s true. That’s true. Interesting.

[26:25.600] – Vidur Gupta

Any parting thoughts for non data driven CEO’s?

[26:31.730] – Beth O’Brien

If you’re non data driven, get somebody to put some pie charts together for you. Put them in nice colors. Do something so that you don’t think of it as data. You think of it as more of, you know, anyway, for CEO’s, I don’t know. I think, you know, there is no one who can appreciate decent bar charts if they’re done correctly. I think really it’s astounding what you can see that you knew, but you didn’t know it as clearly until you see it.

[27:10.880] – Vidur Gupta

Right? Right.

[27:12.990] – Beth O’Brien

And then you won’t even have to worry about it. I think people who say they don’t like data are just reacting to the fact that they’re numbers rather than seeing the numbers kind of, you know, do their own little dance on the page.

[27:26.520] – Vidur Gupta

That’s fantastic. That’s a very eloquent way of putting it. And I’m so glad you said it.

[27:32.880] – Vidur Gupta

In the way you did. Yeah. Thanks, Beth.

[27:36.160] – Vidur Gupta

This is fantastic. Thanks again for your time today, Beth. Thank you.

[27:39.580] – Beth O’Brien

I really appreciate it. Thank you. Can’t wait to consume some more data.

[27:45.800] – Vidur Gupta

Fantastic, both of us. Thanks, Beth.

[00:27:49.280] – Beth O’Brien

All right, thank you.