In this episode, you'll hear from the CEO of A-lign, Scott Price, as he discusses the importance of data discipline. A-lign relies on high-quality data to forecast revenue, causing a blend of historian-like disciplines and storytelling to unlock the business's fortune-tellers. This has not only proved to support their incredible growth but has served well in supporting external funding from Private Equity firms. Tune in to hear A Data in the Life of a truly data-driven CEO.
Scott Price is the CEO of A-lign. Scott is a risk advisory professional who has nearly 20 years of experience. He is regarded nationally as a SAS 70/SOC audit resource as he has completed nearly 4,000 SAS 70/SOC audits in his career. Scott's controls based focus allows him to service companies with controls compliance initiatives. In Scott’s role as CEO, he focuses on firm strategy, client delivery and business development efforts.
Dan Rodriguez is the Chief Revenue Officer of CCG. Dan is responsible for all revenue-generation strategy and execution including sales, marketing, strategic partnerships, and customer success ensuring alignment across the organization to execute the company strategy and achieve revenue goals. Dan will also be responsible for conveying value for customers across the entire customer lifecycle.
The show where Dan Rodriguez, Chief Revenue Officer of CCG, goes behind the scenes with the top data and analytics leaders to understand what they really do every day. Discover how they operate: their goals, biggest challenges, budget, what tools they are using, the skillset of their team, setting expectations with other stakeholders. It’s about people who are smart, reliable, funny, and resourceful. It’s learning about their data culture. We are pulling back the curtain on what’s working now and what is not in how they are using data to gain a competitive edge. It’s learning how the best data and analytics leaders do their thing and lead their company to become an intelligent enterprise.
Dan Rodriguez 0:06
Hello, everyone and welcome to a data in the life a podcast dedicated to gaining insight into how successful leaders are becoming data driven and progressing on their journey to become an intelligent enterprise. Or data flows like beer on St. Patty's Day and insights are plentiful. I'm your host, Dan Rodriguez, the founder of CCG analytics where cloud data analytics company here in the US, and I'm joined by a friend of mine, Scott Price, Scott, how you doing today?
Scott Price 0:33
Man? I'm doing great, Dan, I feel like you should talk with an Irish accent. But that might skew the data points. Yes, yes, it might.
Dan Rodriguez 0:43
Scott, why don't you kick us off by telling us a little bit about yourself, your company what you guys are focused on and then we'll dive in.
Scott Price 0:49
That sounds great, Dan. So A-lign is a cybersecurity compliance services provider. Basically, what that means is we help companies align their strategic objectives and their compliance objectives around cybersecurity and risk. And we audit their controls and allow them to demonstrate trust and respect to their stakeholders. We have about 2300 Global clients supported by 330 Global employees. We focus mostly in the SMB market companies in 25 to $250 million of revenue. We've seen tremendous growth and are grateful for the resiliency of the cybersecurity market has been through the global pandemic. And obviously, things have changed in risk with people working from home versus in offices as well. So it's been a interesting sort of 12 month ride for us, the company, I started the company in 2009, as well. So it's been good.
Dan Rodriguez 1:42
Absolutely. And Scott is the founder and CEO, at A-lign. And, you know, I normally start this conversation by asking, you know, what, what digital disruption or what the digital transformation means to your business, but clearly with the business that you're in and the model, it's been a huge part of your story. But you know, one of the ways that we got introduced and had some good conversations together was adding more data centricity into some of your offerings and the way that you're servicing your customers. So maybe give us a little tidbit and how data plays a part in the vision and mission there at a A-lign and where it where it interacts with your business model.
Scott Price 2:27
Yeah, I think we see data, obviously, in all facets of the business, as you look at lead flow, and sales and Predictable Revenue. I am, I'm a big believer in Predictable Revenue that's driven based upon data and how data is captured, and how data moves through the system and the results of that data. And so as we think about our Predictable Revenue and our growth, as we sell work that needs to be serviced by individuals, and obviously, the human capital side takes a while to recruit people as well. And so as we see lead flow coming in for certain services, we know how that lead flow will predict into opportunities. And then we know how that data will translate into the work that we've won. And the type of service that that is, we actually flow that through to the recruiting arm to say, how, how many days is it take for someone to be recruited in this certain service? And how many jobs can a recruiter handle at one time? And how many sourcing interviews can they do?
So as you think about the data from the beginning of the operation, as I think about people flow to service and lead flow for new clients, those are both huge aspects of what we do from an operational side of the business. And then from a delivery side, we're pulling in our clients data constantly to be able to audit their controls over a period of time. And while everyone may receive the same report or the same opinion, so many times the client wants to know, how did I really do? And so I think we're Our next step is and how do you think about this is how data analytics plays into how are we really doing compared to our other 20 299 customers out there that you all have? How does data play into that? So you know, I look at it as our end customers asking for it, the beginning point of our lead flow, and then how we really handled delivery of our service through technology and people. There's data points at play in every facet of our business to make sure we can meet the demand of our clients.
Dan Rodriguez 4:24
Absolutely. And I think there's fortune there when data is critical to your business model and to the way that you deliver a service because it inherently helps build a culture where people understand the value of data and are open to it, which then allows you to really leverage it from an operational standpoint, often when data is not a part of the output that you're delivering to customers, which is becoming less and less today, but it's harder to get over the operational side. You mentioned something to me when we spoke earlier this week that I thought was fascinating. You use the word data discipline. And you talked a little bit about what data discipline means to you and how important that is to being successful with data. So maybe give me a little bit more with for the audience of what data discipline means to you.
Scott Price 5:19
For us, we set up playbooks of how a lead may be capture how transactions to be run, and those playbooks need to be followed. And they need to be followed with the data that's entered that can be seen and analyzed in a very large and scalable format, if you don't have great data discipline, and you're not recording the transaction, the right place. So for example, on our CRM package, if we think about how many touch points did it take for this client to close the deal, and then recording the touch points, not at the opportunity level, but maybe at the account level, then the data is skewed? Because you're taking all these different transactions and placing them in one area, I then can't run the proper analytics, because my data is not recorded correctly, let alone if I'm recording what I should be, but I'm not recording it where it even should. So I can run analytics on that.
So we look at that and say, geez, if you don't have good data discipline, I can't see how our reps performing, does it take them seven touch points to be able to close a deal? Or is it nine? And what is the average was a playbook say, I can't tell if they don't have good data discipline on recording that touch point wasn't an email or what was or was a phone call, then how can I see how my playbooks running because if they're running the plays correctly, and I'm looking and they have good day to discipline, I'm expecting this outcome to happen. If they don't have good data discipline, because they're free typing something related to the client, they're not using the exact drop down menu or things of that nature, then you can't report off of those fields, is the data discipline is so huge, as you continue to scale for us 2300 clients running 50 new clients a month, you have to have this data discipline, because it's not like you have three enterprise enterprise clients or even 30 enterprise clients, because of the market that we serve the data discipline is so important. So we can predict what the outcome should be. Run the transaction, see if it actually gets to that predicted outcome, or adjust our playbook to make sure our outcome is where we think it should be.
Dan Rodriguez 7:25
I love that. And, you know, so often data discipline is stressed, once you've identified, you know, what are the indicators or the KPIs that you're going to use to measure performance. And once you get that, and you start looking at performance, you start asking a lot of questions. And that's typically when you identify, well, crap, it's bad data. So the reason why the numbers look good or look bad, or, or the trend is going up or down isn't because that's the way the business is trending necessarily, it's because we don't have data discipline in some of those areas. So it's always tough, right? Because data discipline is kind of an after effect, as you dig into something, that your data is telling you an insight or a KPI or when you're looking at performance, then you realize, oh, wow, we have data discipline challenges, and you kind of have to go back and revisit what are we doing on the front end, so that we're getting the right data so that I can make this decision? And some companies struggle, just figuring out what are the KPIs we want to look at to move the business much less fixed the data discipline?
So was it as you guys looked into that? I mean, does that resonate with you? Did you kind of go through cycles of looking at, let's say, the lead pipeline, and then realizing, wow, the pipeline is getting really fat or the pipeline's getting thin, and services that we don't expect? And as you dug into it, you realize, Oh, it's not really getting thin? It's just that we don't have good data discipline. Is that kind of how it happened in your history?
Scott Price 8:57
Yeah, I think we saw Dan, the problem of let's report on something. And then we realized we never captured that data to be able to report on it, or it was captured inconsistently, or within a certain drop down field, I think you get into this situation where you we as you think about how do I want the outcome to be what reporting do I want out of it? How do I what decisions do I want to make out of it? And then as you look back, am I capturing the data to be able to drive those reports. And for us, we got to the point of how we classified our lead flow and how it came in. And we call everything a web PPC lead, because we use pay per click, well, there's actually organic leads that come in and PPC leads. And so we didn't separate those at all. So we just gave everything in the same bucket. And then we couldn't see our ROI properly on our paid leads versus our non paid leads, and to be able to determine that.
So I think it's figuring out, you know, you can be you can be as you know, probably way too granular of how you want to segment the data or capture the data on the outset that it becomes It was onerous to to have good data discipline. And so what's the right balance between the data discipline you need to have what fields you need to capture to be able to report it on the aspect that you need to come from.
I think we also looked at it of our assumptions, we started tearing our client base. And as we looked at the tearing of our client base, we saw the fact just even yesterday, that we actually had a 40% upsell and a tear that we didn't think should actually have it that much of an upsell. Well, why was that? Because the assumptions that we made in our tearing were incorrect. And so the data told us the result, the end result, but it said, you should not be selling this much to this tier of clients. But we did. Well, why is that because our the way we set up our assumptions, and our tearing of our clients that we would feed the data into was incorrect.
So I think there's sort of as we look at it as a business, and you all know, much better from from what you all do. Are we capturing the data that we need to be able to report on? And then are we making assumptions about how we're going to group the data and what expectations we have of how this outcome should be? And is it meeting that and when it's not is that because that really occurred that way over our assumptions of how we group the data actually incorrect. And we need to go back and group the data in a different way to create segmentation differently than maybe how we thought about it as well. And so, you know, it's not something unfortunately, as, as you outline that you maybe think of day one, and I'm sure you have clients that it be, you know, for us, we had to go back and do a refactor of our data and everything else to get the outcome that we wanted, and would have been much better if we started with what the end was in mind, or what we're trying to solve for, and what data points we need to drive that.
Dan Rodriguez 11:43
Yeah, it's very, for all the data leaders out there, they're typically the last one to be brought to the dance. And because people think of reporting as a resulting activity, so hey, once we get all the systems in place, and we get all the process figured out, then we'll go talk to the reporting people about what reports we need. And it's quite often the opposite. Like you said, starting with the end in mind figuring out how do we want to manage performance? What does success look like? And what do we believe are going to be the key indicators, then I can go back, as we're implementing these applications and figure out what processes Do we need to have in place to get that data to actually be able to measure that performance in the end.
But we're often brought in, you know, at the point of let's go build the data piece out. And we see that brand new er, peas were put in brand new CRMs. They just recently put in a PLM platform or some other application to capture data. And nobody was involved in that implementation who had an eye on what are we going to do with this data when we're done? Like we're putting all this process in place, but what's the ultimate outcome that's going to drive the business that we're going to want to measure? And that's normally as for last, and like you said, it forces people have to go back, and, and refigure out the front, which isn't the end of the world, because honestly, most people don't know up front, what performance they want to measure. You know, they know big things we want to know, leads and pipeline and revenue and things like that. But when you start digging into what are the lead indicators that drive revenue, you often don't know that until you get into it. And so the cyclical nature, the cyclical nature is somewhat built in.
But yes, we're very often asked to make all those problems be solved on the day to end. And really bad habits happen in it when they're trying to solve all that there. Because you're not solving it on the front end. One of the other challenges that we hear about a lot is getting the folks that you're talking about who are actually entering those activities, who are choosing the dropdowns to be bought in to doing that, because ultimately, it may not help them do their job. And it may not make it more efficient for them to do their job. But it really helps you in the executive team drive performance and predict revenues. So was that a challenge at aligned to kind of get sales or get CSRS or whoever was entering that data to kind of adapt and buy into doing that? Or did you have any kind of success stories there?
Scott Price 14:24
Yeah, you know, I think you you would want every employee in every department to think like an enterprise leader. But so oftentimes, they're focused on their, their, their individual job or their individual department. And they don't think about where the data goes next or what that data flow is. And that was a problem for us as we went through different challenges of data entry, or pricing in the components that go into pricing. And so you know, you try to go through with some of the I'll say the carrot to go hey, here's where the company is going. If we can put this these data pieces in place. Here's how it works. Every other department to make better decisions. And we tried the carrot for a while, and the carrot didn't work. And so then unfortunately have to bring in the sticks sometimes just say, if you don't have the data pieces complete and accurate through some type of a peer review or through a manager oversight, then there's going to be some commission changes associated with that deal as well. And unfortunately, we had to go with it with a stick route. As far as the commission, it quickly brought everybody into line. And we had these data challenges were well understood about why we needed the data, and they were complied with as well.
I think that you see some departments and think like in an enterprise department, and then some, you know, possibly not, and I think it depends upon the department, it may depend upon, you know, whether they were actually in the office prior to the pandemic, working from home, I think there's a cultural aspect as well, in each of the departments understand why I think as we continue to take the understanding of the why and what we're trying to solve for, and how they impact that, and showing them, if you put the right data into place, we're actually gonna have a better opportunity to route to the leads that you do best with, and that you can close quicker, and that you actually will gain a higher commission rate on it. And so I think now that even though we have the stick still in place, I feel like people are doing stuff because of the carrot rather than stick because now they see the fruits of their labor of doing it properly, of what it actually brings to them, which is increased lead flow in the leads a day close best, because the data is so captured well, that we actually can loot use lead routing, to so that we're putting the right leads in front of the right people.
Dan Rodriguez 16:38
Yeah, I think that's that's such a great example. And, and every one of these conversations that I've had on the podcast series, and then in the majority of conversations I'm having with customers, culture is such a hot topic for me, because most of the challenges that I hear, kind of come back to culture ultimately. And to your point, we're all trying to recreate a culture to be data driven, it doesn't just happen. And it's not natural for people. It is nuanced. And honestly, in some departments, being a data ninja is a part of your brand, and is a part of why you're a hero in the company, because you're the one who knows how to do all that data stuff. And so when we come in to try to automate that, or to make it kind of democratized, it's almost a, it seems like it's an intimidation of, you're lessening my value as an employee and as someone who's contributing to the vision here, so you have to overcome those. And you have to help people understand the value of that.
And I agree, you want to do it through carrots, and you want to do it through awareness and desire and, and creating some of that knowledge. But often, to get them there, you have to put more structure in place. And like you said, they realize, over time, the value of doing it, and I love the lead scoring, that's a, that's a great example of lead routing, and putting things in front of people that they have the highest chance of winning, that's a dream. I mean, if you're a salesperson, that's a dream, give me the leads that have the highest chance of winning, I'll sign up for that every day of the week, rather than me having to weed through all the leads that I have no chance of winning or have no qualification standards coming through. That's really powerful. I think that message of structure and then also continuing to have the carrots out there of incentivizing that behavior is, is really good advice. We talked, you mentioned in the beginning, Predictable Revenue. And that's near and dear to my heart. And just the last podcast I had was with a chief revenue officer, friend of ours, Steve Terp, who was talking about forecasting and some of the value of Predictable Revenue. So as you're making these changes, and we focused quite a bit on the intake side of lead scoring and whatnot. But ultimately, I'm sure for you a big part of doing that is to be able to forecast revenue and have an understanding of what is revenue look like what's in the pipeline, Where's it coming from? And are we going to hit our goals? So talk to me a little bit about that journey and forecasting revenue and kind of where your confidence level is today and how much some of the data discipline aspects have played into that.
Scott Price 19:33
Yeah, it's definitely been an evolution for me, Dan, on how Predictable Revenue needs to how you think about the business. In 2018, we took an investment from FTB capital from a private equity firm, and you know, as as a, as you know, as a founder, you go through and say, Predictable Revenue means that I have enough cash to make payroll, and that's good Predictable Revenue for me. And then I can pay my mortgage at the end of the day. And then one of the things you learn is why predicting the business is so important. That means you can influence the outcome of the business as well, where you start looking at how revenue comes into play, and how much revenue is coming from your prior your backlog versus your current year, and how healthy is that backlog as it moves through.
So it's been a tremendous journey for me personally, and something I don't think I appreciated until FTB came in and most recently, in June of 2020, we brought in a new Chief Financial Officer Mike Branca. And what Mike has really brought to the table is, is the fact that we should be able to project our bookings, because that means we were running the sales organization, how we should run it, meaning that we know the deals, we're going to win. And we know the deals that we're going to lose at the outset. And so we have this type of predictable bookings, then we know how those bookings turn into revenue. And we know what staff people are needed on the engagement, we know what tasks are need to be completed to recognize revenue. And we know when those tasks are going to happen. And we are driving the process more than being a participant, we're actually being a leader in the bookings a leader in driving the revenue with our clients versus the wait and see approach, because that shows that we can't predict the business. And in a people centric business, if you can't predict the need for when you have to have the people when they're going to be doing their work, you have a real problem to be able to service in your book of business.
And so what we have figured out is looking at our data of how the the sales translate into revenue over time for us and that waterfall. And that waterfall has been so important for us to talk to our board with about how well we're performing, you can lay out and say we're going to do something maybe at the end of the year, and you may get to that revenue number that bookings number. But as you look at the business on a monthly and a quarterly basis to be able to predict and say, Hey, this is the bookings we're going to get and we know that because of the prior quarters lead flow. And we know that these bookings, of how they materialize in revenue over time, the next quarter, we may get 30% of revenue, the next quarter we get then 60% of revenue in the quarter after that is 10% of revenue. And that's been something that's been huge for us that I did not appreciate at the outset, largely because like I said, as long as there was cash to make the payroll and to pay my mortgage, I predicted the revenue of the business. And as you have involve other stakeholders that aren't involved in the day to day operations, your ability to have great data to be able to predict these things and communicate them out your needs, especially during the pandemic that we had, you know, knowing how revenue was going to come in and play, which turn into cash flow for us and where our cash needs were going to be when you when you had some concerns around your clients paying you for for the services as well.
And so all those things were very important for us. And I think we figured out in the last 12 to 18 months, the the importance of that it helps with if you're looking to borrow money to go do acquisitions and things of that nature, the bankers want to be able to know that you can predict your revenue of how it's coming in based upon your bookings. And then that your predictions that you make actually turn into what reality is. And then as you show that trend line of what prediction becomes reality, you get a lot more credibility in the marketplace as well for how you're showing trajectories of the business.
Dan Rodriguez 23:19
Yeah, that's the there's so much knowledge in there. And for those of you who are either leading data practices, or are working for executives who aren't data driven, go back and re listen to what Scott just walked through, because as a CEO, what he's talking about and the importance of data, and running his business. That's the that's the summit. That's where we're trying to get all of our customers and all the executive teams because without that, without understanding the value proposition of what data can truly mean to the business. All data journeys become riddled with difficulty. And so I really appreciate your view on data in your business and how it can be leveraged. And, you know, in a personal note, in my journey, it almost felt they hit the initial focus on the data around bookings and driving revenue, the way you just talked about, almost felt disingenuous to what we were and what we were trying to do and growing a really powerful brand that comm employees love to work for. And this focus on revenue seem to have this kind of disingenuous feel to it. And it wasn't until I matured, more to realize that that's how I could truly service the employee base by having that comfortability and lack of anxiety around where's the next quarters money going to come from? How are we going to grow so that I can create more opportunities for the employees to grow, to have more leadership opportunities to bring more of their peers into the business. Without that line of sight. It's really hard to do.
You can't think about a new office in the new Geo, if you're looking paycheck to paycheck from a revenue forecasting standpoint. And so as we got more sophisticated in the same way that you're talking about, we were really able to get more comfortable to unlock growth in the business, and really invest in our people, and invest in bringing in more new hires and not always be reacting to bookings, oh, we just have a bunch of bookings. Now we need to go hire a bunch of people, right. So the more you can get prescriptive, there, it really does unlock the business. And it removes a lot of that stress and anxiety out of the at least out of the talent acquisition and retention standpoint at a minimum. So that's great stuff. There's there's one last topic that I found fascinating, when we were talking earlier, and you said that there was this desire for fortune tellers, as we're predicting revenue, and and finish out that thought, what is required for having good fortune tellers?
Scott Price 26:01
Yeah, I think just as you were talking about the maybe the, the feeling around be able to predict revenue, the same thing may be thought of or viewed about how fortune tellers are versus historians, historians, Chronicle what actually happened, and the fortune tellers are trying to predict the future. And, and we spoke about the fact of, unless the history is well captured, we're not going to be able to use the history to predict the future in the same way. And so as we talked about Predictable Revenue, if we don't have a capture around what occurred, and why it occurred, financing can predict the future, it's you know, being a CPA, you think about this whole accounting and accounting, focus on history, and everyone wants to, you know, use data that you all teach them about, and be able to harness the data for the future.
But if we don't take a good snapshot, and have a good recording of the history, you won't be able to help your clients predict the future. And so I think this fortune teller needs the historian to be able to do their job properly, the historian may not need the fortune teller, but I can tell you, the fortune teller needs that historian so they can predict the future based upon what the past has occurred. I know as a teenager growing up, my mother always told me prior behaviors an indication of future behavior. You know, she was trying to find predict the future with me. So I think that's a something that the the data discipline around it, and the history has to be well chronicled, to the point that fortune teller do their job.
Dan Rodriguez 27:30
Yeah, it's, it's a great I think it's a great way of associating that point, you know, we said garbage in garbage out in the past. And we've talked about looking in the rearview mirror versus looking through the windshield, and that the windshield is so much bigger, because you really want to be looking forward and forecasting, and that the rearview mirror is smaller on purpose. But this is almost saying it in somewhat of an adverse way. Because if we don't have a good view in the rearview mirror, if that's flawed, we know for a fact that all machine learning and all the stuff we're trying to do with AI, if you're running that on bad data, it's going to give you bad predictions, there's no way around that. So you have to feed and train data on good data. And if you don't have that in, like you said, if you haven't had a historian like mindset, and the way that you're capturing information, then yes, forecasting is going to be very difficult. And those Tarot cards or whatever the fortune teller is using, they're gonna be suspect, at the minimum.
So I love those key points. And I think, you know, for the listeners out there, I really want you to take away a couple things that Scott said, one, I'll reiterate, if you're a C suite, whatever, whatever department, I want you to really appreciate where data can play a part in your business, and how important it can be to drive it because there's no way a line would be able to leverage data and go through the challenges and the opportunities and the evolution that Scott's talking about if Scott wasn't involved, and didn't see the value in doing that, because I'm sure Scott at times wanted to give up and say, let's just go back to doing it the old way. This sounds like a total pain in the ass. Every time we started talking about data, there's a new project and a new thing we have to do. But recognizing that value on the unlocks it brings to the business is so critical and so important in adapting and creating that culture.
And then for the folks that are leading data teams who are working with C suite, understanding how to paint that picture and how to relate it to the executive team so that they can buy in and that they can start changing their own behaviors. Because I'm sure Scott, you would agree with this. If you want to change behavior, have a tough department have the leadership of that. department start measuring performance with data. Because once that happens, and everyone goes, wait, what data are you looking at? And how are you measuring my commission and what I'm doing? Everyone starts getting on board with the data and the data validity and becoming data centric, because now they're being held accountable. If leaders aren't doing that, it's very hard to move a business in the direction of being data driven. Why would I adapt something if my leader is not holding me accountable or not measuring the business based on data?
So there's, there's a lot of really critical and important things that I think when we're talking about addressing the culture, talking about the data discipline aspect, and really understanding your story and your data and how it's being managed in that historian mindset will enable us to be to empower fortune tellers, and to predict and forecast things like revenue and pipeline and those other aspects that are so critical to our business. Any last words got incredible advice, I really enjoyed the conversation. But before we let you go, do you have any advice for the audience, kind of as they're on their journey to become data driven?
Scott Price 31:09
I think, no. And thank you, Dan, again, for including me, I think one of the things at every time you start talking to a future investor, or we start looking at acquisitions, the first thing that comes over the wall is a data request. And you want to make sure your data is pristine. And the data that you're reporting on that other people can create the same reports from the raw data themselves, because they'll ask for that data.
So I can't underscore how important it is and how much I learned going through our our first private equity investment, as we now are in the seat enlarger, to look at other investments that we can make as a business as well. So the first thing that gets thrown over is the data request and a data dump from your system. And if you aren't able to have the data recreated by a third party, that's the same data that you have, and you're making decisions on, you're in trouble. And so that's why that data discipline is so important.
Dan Rodriguez 32:02
I couldn't agree more. And we know from companies that have brought us in, that their valuation numbers are higher when they're very good with data, because like you said, if you're very comfortable in predicting and forecasting the future, then they're more confident in that acquisition, and your valuation will show it, especially in areas where you're capturing customer behavioral data.
We're seeing a lot of companies get some pretty ridiculous numbers because of the data that they have internally if it's managed, and curated appropriately. Definitely. Well, Scott, thank you so much, man, I appreciate you taking time on St. Patty's Day, I hope you get to enjoy a green beer or glass of bourbon or something, maybe some Irish Whiskey to cap off the end of the day. always enjoy our conversations. And thanks again and look forward to bringing you back in another time and getting some more knowledge. Put on us.
Scott Price 32:54
Thanks, Dan, I appreciate you including me on the podcast.
Dan Rodriguez 32:57
Alright. And thank you everyone for listening. Make sure you come back and check out our podcasts.