We are kicking off this week on Business as Usual by welcoming Matthew Marolda, Executive Vice President of Tulco Holdings (Thomas Tull -- https://tulcoholdings.com). Matthew has a robust career in tech, having served as Chief Analytics Officer of Legendary Entertainment and President of Applied Analytics at Warner Media. His experience in building companies (spun out three companies from Stratbridge) which focus on deep analytics in entertainment and sports franchises will make this a BAU you will not want to miss.
Matthew will talk about how Tulco Holdings enables companies to unlock rapid, sustainable growth through the application of advanced data science. Tulco Holdings identifies industries with static business models and takes material stakes in companies ready to scale with the adoption of leading-edge AI and proprietary technologies.
So good afternoon, everyone. This is Audrey Russo, President and CEO, the Pittsburgh Technology Council kicking off a Monday. I know that today is jhumka port, and I wish good young TIFF to all those that celebrate this holiday. Me included. But I'm here because I wanted to make sure that I got a chance to spend some time with our guests who I'm very excited about. And I want to thank Huntington bank, Huntington bank has been with us right from the onset of this interesting journey of having daily conversations with people from Pittsburgh and from around the world. And today is no different. So I'm excited about that. And thanking Huntington, Jonathan kersting is joining us today. And we want to make this interactive. We want to make this so that you can have an opportunity to talk with our guests, but we have a lot to pack in. So I'll warn you, we have a lot to pack in. So we've muted your microphones and there is a chat. So use the chat. We will work with you on that. Jonathan will monitor the questions. So I'm thrilled to introduce Matthew, He goes by Matt Marolda he is the chief analytics officer. He's the VP here. I would say that titles probably don't matter that much. But what really matters is what you're going to hear is all that he's been involved in. But he is a VP at total holdings. And they've had some noteworthy investments. They've had some noteworthy work. And they have a very, very interesting model. So I want to bring on Matt, I think, Matt, you unmuted yourself if you could, could unmute sometimes it gets wonky. Yeah, there you go. Okay. So Matt, welcome. Thank you for joining us. You're joining us from Boston. Is that correct?
That's correct. I'm in Boston.
Yep. Yes. So thank you, Matt. And you know, listen, you have a very, very impressive career. And it's sort of interesting to figure out like your entire journey. But I know from talking with you, there's been, it's really been fascinating. I've yet to meet someone who's had this kind of spread, particularly with the data analytics background. So it seems like maybe the company strap bridge is where you want to start, or how do you want to start to talk about who is Matt, the man?
Sure. I'm always an awkward talk topic for me, but I'll do the best I can. Um, so strap is probably is a decent place to start. That's a company I started many years ago, and I was strapping sprung three different businesses that I eventually sold all of and they led me to kind of the next stages of my career. They seem sort of disparate, unrelated, but there is a commonality which you identified, which is data and time, nor the type of data science, but data, data analytics, and so on. The three businesses that sprung out of that company, one was one that did predictions for publicly traded companies around the world for that they were going to commit fraud or fail based on publicly available data. So kind of a cool really Prediction Engine, which now would probably run on my iPhone, but used to run on many servers in a room. And then from there, and these are all random walks, we can maybe do the dive into or not. We found our way over to dynamic pricing of tickets for professional sports. And so did that for much of the NBA, MLB NHL. And then from there that led to what I guess people colloquially call Moneyball, so working with professional teams across the mostly NFL and NBA, using data and analytics to be smart about player evaluation, coaching and so on. That's how in that world, and again, all three of those businesses I sold now, maybe more than 10 years ago, but at different times, but last time at Thomas Hall, who is obviously an ardent Pittsburgh person. And he I met him through his partial ownership of the Steelers, and we get to know each other that way. That's because my sports world and he basically after a few years are going to know him or couple years pitched me and said, Would you like to come to Hollywood and do my BA in Hollywood? So I said, Sure, because that sounds like sounds like a the next cool thing to do. And so we we took legend entertainment, which is a company founded and really infused data analytics throughout its entire process, including both the project selection, everything from titles to casting and so on. And none of it was ever weirdly robotic. I mean, it was it was all interlaced with human perception and whatnot, but intuition, but it was an important component. And then probably even more aggressively we we use data analytics to market our our products right? To market our movies and TV shows and so on, that led to our sale of legendary to Wanda large Chinese conglomerate back in 2016. And then Thomas left about a year or so later. And then I was able to take my division sell it from there to Warner media, which is Warner Brothers, HBO Ultron property. So that's where like the arc.
Yeah, that's a big arc. And so what did any commonalities in terms of the sports franchise? And what was happening at legendary at the time? Any any kind of
Yeah, no, they're, they're quite a few. I think. The first thing is, these are human driven things, right? Whether it's a athletic sort of endeavor, like game or whatnot, or even a creative process, like the production of a movie or TV show, there's a real human element to it. And so that part, you have to accept and acknowledge and kind of incorporate or integrate the other pieces, they're both very ambiguous meaning you can't look at if you're doing designs in a way that you prefer, you'd like to be able to have two different worlds, right? One world where you did something, and then I'll read it the opposite thing, you can sort of run a horse race and see which one did better, and then make a choice? Well, you can't really do that. You can't sort of run those those kinds of tests. And so you have to operate in a way that data has to both feather into these more human aspects of either creativity, or athletics or human judgment, alongside the fact that you can't really do the same kind of testing you'd like to do in a more pure data environment, those that's somewhere between both entertainment and sports.
But on the on the entertainment side, did you get involved in deciding what? Because these films at a legendary are huge, they're massive budgets. So did you get involved at the onset? Yeah, post after it was in the distributed? Sure,
I would, I would describe it as if you were to some data visualization kind of person. So I would think of it if you think of a choice, like a bathtub high, then low than high. So high at the beginning, meaning, these aren't major investments in a certain way, you're investing like you would in any other investment, you want to be informed and thoughtful, and incorporate as much information as you can. And so we'd be very involved in those early stages, you know, I mean, I know that it's long enough now that some of the ones that I can think of roof top my head, like a Jurassic World, or straight Compton, those are ones that, in hindsight, looked like huge wins that were no brainers. But at the time, not only were they significant investments, but there was uncertainty around those movies and the properties. And so we were very involved in evaluating audience audience opportunity scale, and try and match that to budget and what would the investment would basically be to fund it and support it, we would also get very involved in some very broad brushstroke stuff is an input to the creative process. So I think of a movie like kong skull island, which we did a few my four years ago now. And how we sort of learned from a movie like Godzilla and brought those learnings from a data perspective to a calm and we you actually compare and contrast those two movies should be happy to do you can sort of see some of the changes that occurred because of that. And so that's like the very beginning, that's that sort of the spike, it's one of the bathtub, then we go quiet, like, so we're not involved in the script writing, or we're never we're involved in that part really, at all, we weren't involved in the production, like I'd go to a movie set, cuz it's a cool thing to do. But I did nothing other than just kind of hang around. And then it would be quiet, and then the movie start getting ready to go into the market. And we'd really crank back up again. At that point, we'd say, Okay, now how do we take this movie and deliver it to the, you know, to these very large populations? Around the world, right? And what kind of techniques and analytics can we use to position movie in a way that will make it stand out in what is not just a competitive landscape? for entertainment, but just you know, people's time, right? Anything with a zero sum of time people have? How do you get out of that fray? So that's where the bathtub can kick back up again, was when it came to the actual propagation and bursting of the property out into the world.
And so would you say that that's prevalent now in Hollywood? I would my research on all this is that it wasn't that prevalent back then.
Oh, definitely wasn't prevalent. This is where Thomas said, so I'd never like you heard with the randomness of my career. I was fortunate that each juncture someone kind of came to me and said, Hey, could you do this? That's a, you know, first fortunate lucky thing. And so he was that person. He's the one who kind of saw in this case around the corner and said, Hey, we're really trying I can, I'll sort of paraphrase him but one thing that really caught him was one of it was the second hangover movie. He got this bill basically for media. It had like all these advertisements on like, lifetime network. And there's always newspaper ads. It's like, why is that happening? Why would you ever do that for this hangover movie? And that's what got him thinking about it. And so that's when we started talking about. So yes, it was very unusual there. In fact, I think some people looked at us like, we have two heads, because it was a very creatively driven place, not only is the actual product creative, but the people who rise up in the ranks across organizations tend to have come from creative backgrounds. And so data and data analytics, any approach like that was very for them, just like it wasn't sports, you know, in my prior life to that. And so, it was very uncommon that I think we, we really sit among those and you know, if you're gonna be grandiose about it, we were maybe a catalyst for thinking about things in that way. But the world was changing around us, like Thomas was present, but it wasn't like he was not going to happen. Right. So I think we were early in it. So the more sophisticated things, but even with digital marketing, when I started in, in Hollywood, which would have been maybe like, eight or nine years ago, 90% of our try media budgets were on TV. And by time, and on one of our first movies that we really shook up things we did it, we thought was crazy. At the time, we I think we did, like 60% on TV, and people thought we were nuts. And the remainder was like on digital. And now things are shifting so much that like everything is like very digitally driven. So the world has changed. I think the part that hasn't changed yet, is some of the cultural aspects. I think some of these large organizations, or media organizations have not quite got their head fully around how to take advantage of they don't have the agility, in some cases, and they have other sort of infrastructural things that make it hard. But they've definitely come a long way. Since say, you know, eight or nine years ago,
so which of the movies was the one that really made this validity testing, you know, sealed? Which was there one movie where it was? Yeah, well,
so I've watched
over my course, my query pile, you know, we, we launched on a 60 or 70 movies. That, yeah, support you. And that's largely driven by more than Warner Brothers, because there's so many, they're over three years, we did like 60, I think, oh, maybe like 6050 something. Um, but the really the ones that will stick out or, and this is, this is a indictment on my sort of the way I look at the world, but the summons stick out where the very early ones and the really bad ones. The really big successes are almost easier to kind of brush aside. The early ones, though, the one that really sort of hit the mark, if you will, and I think caught some attention was Godzilla. That was 2014. So we had like a year or two to really ramp up and build for that movie, we did a lot of things there that were unique in the way we approached it. And when things if you go back and look at it, you sort of see this. And it's kind of funny, and I hate to say it, but I would do it again, we looked at that movie and said, Hey, I need to make this big, right? When you make a prod. And we we found opportunities with women actually who were between the ages of like, almost like late 20s to like 40 ish, which would have been surprised and you wouldn't have necessarily anticipated that for Godzilla movie. But what we found once you start peeling back the onion, there was it wasn't just the demographic, there were certain aspects that they were appealing to them. There's conspiracy theory kind of baked into the, into the movie, there was a bit of I mean, ended up not really playing out this way, there's a bit of sort of a dynamic between husband and wife, and a young kid. And then Bryan Cranston had just come off of Breaking Bad and so he was like this huge star. And so those three things is elements, or ones that we identifies in which people go through data that I don't think people would have anticipated that we really want to lead into. And so we did, we found a market segment we went after and we took the creative materials and crafted them toward those those things, the, you know, the the conspiracy, the sort of dynamics of family and Bryan Cranston. And it worked when we opened up like almost 100 million dollars and so on. If you watch the movie, plus things not super common. Like, I wouldn't, I wouldn't ever use it, determine bait and switch because it wasn't that at all. But it was something where we took elements and amplified them. And we knew we wanted an open bag. And we knew that especially that time, the way the math works, it kind of cascades. And if you can open big then you set a long tail and a lot of money. And so that was a strategy for them. And it worked really well the one right behind it actually the immediate movie after this tiny little horror movie that I'm sure probably no one has caused her to have called As above, so below. So this movie was kind of curse because it has a mouthful of a title. I can barely even say it. It was like super small budget or as Godzilla was like, a 200 100 $80 million movie. This is like a $5 million movie, much lower spend, which is very small. But we went radical on that one did all kinds of really innovative things in the market especially it really kind of worked it became a very profitable movie made actually a bunch of money. And it broke a lot of paradigms and that's the one of the people in Hollywood, so calling us and said hey, well, what are you guys doing? Like what is actually happening there because the Godzilla one it's like it was like oh, it's a big property and He kind of you know, tout your your analytics on it but still Godzilla. This is this tiny little movie How did it do anything? So those two are literally back to back separate about four months and those are the two that really kind of like shone a light on it and actually frankly convinced me that there was actually something there
and then you were involved in dark night.
No, that was right before me the last movie I was I touched but it was very we these are the movies come right after dark night.
I can't it's all blurring to me since kosher.
Yeah, these are the media successive movies.
Right? So what do you how do you feel right now, when you're watching what's happening in Hollywood?
Well, I feel like a dinosaur and I feel out of touch. So like, I already feel like the world has changed. I, I left Warner media and joined telco in March, right before the pandemic, really, you know, the things really went crazy. And so since that time, I've stayed in touch with my friends there. Obviously, the world change show radically. I mean, Warner Brothers has released one movie, since then, which was aggressive as we call Tennant, which is a Christopher Nolan movie, which is struggled to do anything in the box office just because people aren't going to movies. Meanwhile, I left Warner media, we also were launching HBO Max, which is the Netflix competitor. Now, it's really challenging thing to do, and a very hard task. And so those those things are all like, you know, sea changes, right, you've got the economy changing radically, you've got distribution and how properties move around, even as we were leaving. Like there's a movie called scoop, which is this all public SUV was going to be released in theaters, it's based on Scooby Doo. And it was very clear that Scooby Doo is a beloved property, but you know, has a very specific kind of audience. And especially given the pandemic, that was the kind of thing that made a lot of sense to switch over. So watching, they went from planned to release it in theaters to actually release it digitally and put it right on HBO max. And it's really clever thing to see. I mean, other other studios have done similar things. And so that these shifts are happening so fast. And the vanch from this is the only part that I would say regret leaving behind. But as a data person, you don't get a lot of data from a theatrical release, or even a television show, right? So there's very little you can actually learn other than secondary signals like social media, or other conversation, you might go pick up or you know, sort of digital, sort of ephemeral things. Whereas when you have a platform like HBO Max, and you can actually get significant first party data off of, say, a movie like scoop, that's a hugely game changing thing. So that's why it's like a dinosaur that's happened just as
fast it's moved. And how, at the same reason, I mean, I was particularly right, but let's just we'll back up a little bit in terms of the work that you've done in data analytics, and sports and coaching costs, the franchises because that's how you got involved with thumb, Thomas, I believe the steel.
That's right. Yep. That's right. Yeah, um, so very similar conditions. I think the movie Moneyball had a scene which I could relate to, because I've actually experienced it. There's a scene where like, the old scouts were all talking and talking about the way the guy walked across the field, or even his girlfriend they would talk about and things like that. I've been in rooms where the scout there's a scout who literally fell asleep on his cane. So these things are like they were real like that that world was real. And it was it was an interesting uphill battle in the sense of bringing this perspective to that world. Meaning, could you take things like data and other sort of quantitative measures that folks were maybe not comfortable with or hadn't even experienced before, and employ them in the decision making processes, whether it was, again, on a player evaluation basis, or even a coaching basis. And that was, that was an interesting path. One things that was sort of a second order thing I learned, I was effectively a vendor united company that licensed that technology and software to the teams. And when things I learned, which I appreciated when I switched over and jumped into Hollywood with Thomas was if you can only affect so much as the as the party who's providing the tools to actually be have a true seat at the table from a decision making perspective can actually amplify the impact kind of dramatically. I think one of things that's happened in sports since which makes a lot of sense. The, the the tools like the ones that are even still stemming off the ones that my team and I had built, they're still in the market to this day, for the acquirer. They've taken a direction that kind of shifts more of the sort of decision making power back to the team, which is great because it's timely, a lot of them would rely on us to sort of help even interpret it and open up even more kind of raw data and the teams now have such deep skill sets on staff to be able to take advantage of the data that they actually can do more of it in house like we were able to do legendary so I think that's a pretty stark but probably pretty typical transition for an industry is to see that early kind of outside the organization, development of tools and capabilities being licensed in and then eventually brought fully in house. So that transition seems that happened. We thoroughly
expect skill set lie inside the franchise is where is it in marketing? Are they hiring?
Ah, so I think it's, I think it's a, I will get a little out of touch. I've said, I've stayed in touch with friends, but not in a professional way. And since I'm professionally kind of dug in, but my observation is that so I'm tight with like the Red Sox guys, for example, they've built up a really impressive analytics team within the organization. That's in what they would call it front office, right? So working with like, the general manager, or the manager, and so on. Other organizations have more centralized data functions that spread across business as well. So things like marketing, sponsorship, and so on. So I've seen a mix, I think they tend to tend to be those specialized REITs, you tend to have people specialize in the player side of it, or the business side of it. But they they've definitely cultivated I've seen an organization's cultivate both for sure.
Good, and it's right at the front office side. It's no longer back office.
Yeah, that's, that's a little did you get involved in security? related things are not?
Not particularly. We say security, you mean, like digital security or? Yeah, so we were we were we were very conscious of that in the sense that another thing that we did that was new was we were a multi tenant infrastructure, which is sort of a mouthful, but what it means is, is that it's kind of weird. But all the teams were basically the same database. So you think about the hyper competitiveness of those teams. You know, we had to convince them that this was a better infrastructure for them. So we had to be really tight on security. And I took a lot precaution.
Like, in my old days, they were on a single instance. Is that kind of Yeah,
yeah. I mean, there was a lot of precautions within there like it was Salesforce has been at the time, right. So a lot of companies are doing and it wasn't unusual in that sense, but it was unusual to them. And again, so it put a heightened attention on things like security, we never had one issue because I always said if we have one issue, that's that's a good business issue. Like you're done. Like, never was a problem. And it worked out just fine. But it was something we had to spend a lot of time to get
your there. It's totally partition. That's really interesting. I've thought about that.
Yeah. How to be for scale efficiency.
good opportunity for data centers to Yes. Great, huh. So let's so now let's jump into this role that you have tolko. Let's just talk about telco because there's a couple of companies in there that are, you know, have done or doing quite well. Oh, yeah. I have an interesting model, if you could sort of talk about that, because I think people in Pittsburgh would be interested to hear about this. Sure.
Yeah. I mean, the model again, this is work. Again, Thomas sometimes sees around the corner, oftentimes, we'll see around the corner. I think what he had that he identified in Hollywood was a very big example. This is there these industries that are maybe I don't call them sleepy, necessarily, but ones that have sort of older point of view or older approach, or a more staid approach, that they are often right for some disruption, simply by incorporating data and analytics, right. So there's a very simplifying kind of elegance, that hypothesis, right, which is if you take something that's traditionally been an older business and infuse it with this new perspective and approach and capability, you can actually immediately manifest two benefits. I always think about it simply as increasing, like EBITDA, or profit. And then increasing EBITDA, multiple, which is how people sometimes shorthand value something, right? So you make $100 and you have a multiple of five, you're worth $500. If you can make the EBITDA go up to 200 and make the multiple go up to 10. Suddenly, you're at 2000. And so taking these approaches and saying what can we do to affect both the actual core business and its sort of trajectory, which is the representation of profit and value is, again, sort of elegant solution. And so there are a handful of companies in the portfolio, the strategy has been to take a very controlling, if not controlling gray material stake in those businesses, and to then collaborate with them and work with them. And so one of them that you may be thinking of is figs, which is a medical apparel company, total rocketship, and also very interesting. Thomas introduced me to the women who founded that company four or five years ago, maybe even more than that, and they were usually it's one of those things where they walk in the room like these, these two people have it, like whatever it is that they have,
and exists if
a fig started it from again, like a lot of things from a place that have sort of not necessarily driven by like how do I make a ton of money. It was a woman whose friend was a nurse who and this woman was in fashion In her friend who was a nurse was wearing these uncomfortable scrubs, like scratchy, poorly cut uncomfortable scrubs. And this woman who was now the CO CEO, figs, said yourself, I can make you something better than that. And she did. And then suddenly, everyone wanted them. And they turn that concept into what is now many hundred million dollar business. million dollar revenue business. And so it's very impressive that they started from that place. And they were also very early on this mission driven side, every pair of scrubs, there's a matching pair that goes to a medical worker in need somewhere in the world. So they've been doing that since day one, which is really impressive. And so what they've done is they've said, you know, what, we're gonna be direct to consumer, right, which is very different than how the industry is. And so what we're telcos involvement came in was, first of all, corresponding right giving them the capital to drive the business, but also to give them capabilities to be more data centric, or if you're going to be a direct to consumer scrubs company, basically, you need to really understand the people who are buying your scrubs. And you need to be able to get them to buy them again, the frequency, it's like, say, once a year or more, you need to be able to get them to buy more things like so if you go from scrubs to outerwear, even or you might imagine masks now are very popular. How do you how do you basically increase their shopping cart? And then how do you grow that that core and of itself? Or how do you find more people? And so there's a lot of ways that we've been able to think about data analytics that help them, push those arm blocks further, again, increase both the actual profit of the company, but the value as well,
telco holdings, actually, we'll we'll get to the scientists and then and then place them inside the company. Is that right? Yeah.
Yeah, so my role is to sort of provide all the support, you would think that we would need to provide them right, it's how do you actually embed these capabilities in your organization? How do you build a culture around data, to incorporate it into your everyday thing, it's one thing to say, hey, let's look at all these great dashboards, I don't think they actually have data flow into every conversation and be a meaningful seat at the table. So it's helping them to, again, I think it's really important thing that these are capabilities that are built in reside within the company, right, that have to be something that is, you know, a strength of the company. And suddenly, we've done a really, and I and this same predates MCs, I was at Warner media for a time before coming to telco and telco is still up and running. You know, the people have been there, you know, since the beginning of in a good amazing job of building skill sets of people who can then parachute in these companies and then land permanently, and build these capabilities. So yeah, that's been the model. And it's, it is pretty unique. I'm not aware of a lot of other places doing that. And then you're also in invested in an insurance company? Yes. Just Yeah. Another classic. Yeah. Yeah, another classic one, where it's an industry that's huge, obviously, scrubs is huge, believe or not, but your insurance is obviously cuter. And they also have a lot of data, right? They've used date, some form of what you might call it data science for decades, actuarial data is a version of that. But you know, there are aspects of it, that could be reinvigorated, and so telco incubated to companies within it, one being a, like a modern marketing engine for insurance and the other being a modern risk engine for insurance, took those two companies and was able to strike a pretty significant partnership with a company called a Crusher, which is I think, the country's largest brokerage, one of the largest brokerages in the country. That gave us a significant material stick in that business, but also enable us to do the same thing, which is to embed capabilities into an organization and help again, she both profit and value growth.
So are you are you still investing in companies? Are you still looking to invest?
So as of now the focus is on taking the Tigers we have by the tail and making sure that they continue to
be successful. So what's your predictions for the next year? What do you think? I mean, let's your your data scientist, is there any I mean, you know, can we, I think someone Dirk wrote something in here, what can you tell us about data analytics applied to politics, but I mean, I'm interested in what trends Do you see?
I would feel a lot more confident answering that question prior to prior to the COVID than I am now, just because things are so so dynamically changing? I mean, I think so politics is fasting in of itself. We, we've I personally dipped into some of that in the past, data is clearly used extensively, sometimes scarily sometimes inappropriately by all sides, like it's not you know, once or there's it's just a fact of modern politics. In terms of trends, I think the things that are gonna be really fascinating to watch. Again, I'm gonna bias this wildly towards my worlds is not meant to be grand projections or predictions winning but just like how we are At least why it touched every day, or have touched sports and media like those things are going to change radically. I mean, media, sports will come back once people can, you know, sports is back in a lot of ways, for sure. But it'll feel more real. Again, once crowds are back, that's probably a vaccine, right? Before we can really do that. But on the media side, is the like we're talking earlier, the whatever calls over the top, like the over the top aspects of that business, where you can suddenly start taking digital platforms and deploying media out through them is huge. And that's a game changing thing. So I think that that world is going to change radically towards a more home oriented world, the different kinds of movies that actually come into the theaters that are bigger, maybe more of a theatrical experience, where other things might go on different platforms. So that's disrupting dramatically. When it comes to the businesses that telcos in today, I think we're seeing a lot of trends that are exciting. I think insurance is something that is a product that's going to be very important to people, and being able to deliver that to them in a way that's efficient, and gives them information to be informed purchaser of those products, is, you know, it's part of the mission. When it comes to medical apparel again, I mean, obviously, those are frontline workers that everyone feels very strongly towards, especially now. So being able to serve them really well. And know those people really well. You know, a scale that figures out you need data analytics able to do that. And so these things I think, will continue just, you know, mushroom work was from there. I don't know, I think it's, it's hard to imagine.
It's hard to imagine six months ago when you joined telco that
we believe it.
So before we end, what is what's your favorite movie?
Favorite movie? I've worked on a favorite movie of my life.
How about both answer both
of my life, I, I am too data center to not have a curated list that has many variables at
any given moment. And
I will say movies I think of is ones that popping up. You know, of course, there's all the cliches, right? So you can just like, jot down all the typical like Godfather, Goodfellas type movies, but even something like some of these were from when I was a kid, you know, some like a Young Frankenstein, or midnight run. Those kinds of movies are ones that stick out for me, of once I've worked on, certainly, there's been some great ones that were really fun. And, you know, Joker was really interesting, crazy movie. You know, stars born was a really fun one to work on, of course, Godzilla Kong. But weirdly, and this is just partly out of a selfish motivation to get people to watch it. There's a movie we did called game night at Warner Brothers, which is fun kind of movie, it's probably good for this time where people are looking for some some escapism. But that was a movie that we didn't really have much hope for. We're able to flip around. It's been cool with another movie that was like that was the mag, which came out a couple years ago, which is basically Jason Statham punch in a shark. And so that was a fun movie that we thought wouldn't really go anywhere and became quite successful. And so the movies that were kind of the ones that I'll always remember, were the ones that were fun that we were able to take and create x. So outcomes beyond the expectation.
Right, right, which is exciting. Okay, so I guess you stay connected to sports. I'm not going to ask you favorite sports team because you're in Boston.
I'm actually I'm a depressed sports fan today because my favorite team lost last night
in the playoffs, the Celtics, so that's right. Okay, yeah, we have everything but professional basketball here. So right, and get to that. But I want to shout out to people on a more about Toko, they go to Toko holdings.us. And I want to thank Matt merola, who's a VP with Toko holdings. And as you heard, what what a great background that you've had. So the next thing that I want to follow up with you on to see what you're doing in music. I feel like
I am involved in a company that's doing some things music, we can talk about some other time.
So I can't thank you enough for taking the time with us. Stay safe, stay connected, and really appreciate the work that you did.
I think you appreciate the opportunity. Really fun to chat with you. Same here.
Take care everyone. And tomorrow we have who do we have tomorrow? Jonathan? We have Maven machines.
avi Yes. Very cool guy. And of course on Wednesday, the founder and CEO of Aurora stopping by for crying out loud. Come on. It's gonna be awesome.
For Matt, you can join in. There's some really great companies that are right here in Pittsburgh. Probably don't know. Awesome. Yeah, we will send you a link. Anyway. Thanks, everyone. Have a great day. See you tomorrow.
Transcribed by https://otter.ai