Hebert on Air
0:00 We got Mac a bear I was going to ask if if this was because he's from the north if it was going to be a hebert or an a bear I go with either but I kind of split the difference and say he bear so he
0:14 bear like he man but a bear. Yes and when I call and people don't know they say leave a message mark H E dash B E R which is not his but my name call I'll be honest I thought it was Herbert for quite
0:30 a while I just assumed it was Herbert there's no R before the B I know are yeah I also get the mark E like just the letter E and then the bear at the end. So,
0:42 if you're from the Houston area or obviously Louisiana area that that name is a bear there is no there is no interpretation you don't need to say anything so you come out with a he bear you're going
0:54 to get raised eyebrow down here Yes, and anytime you're anywhere in a French-speaking area. Everyone instantly goes to French and I took it in school, but I do not speak French. We're hosting a
1:08 crawfish boil in April. And our chef is Abair. So we're convinced it's completely authentic. We got an Abair doing the cooking. Please send me the details. April 17th, Saturday of Easter, April
1:24 16th. Okay, all right, April 17th is my daughter's 10th birthday.
1:30 Mark, I've gotten to know you. I really, I like you. I feel like it's been fun aligning funk futures and Dakota analytics are doing some work together. We'll definitely get into the business
1:40 stuff. But there's things you've sort of just been tangentially a word that I like to use lately around me for a number of different things. And we have sort of these strange connections, which I
1:53 definitely want to highlight. One, I want to understand about you and growing up And then let's talk Rutgers, because. My Dad went to Rutgers has two brothers went to rutgers that grew up in New
2:04 Brunswick New Jersey My Grandfather worked at Rutgers for Thirty nine years so rutgers is a place that I'm very familiar with if I didn't go to Brandeis I probably would have considered going to
2:13 rutgers but I want to know about you like where you grew up up to the point why did you go to rutgers then let's dig into your career from their
2:22 shirt so I started the Ruckus Piece I was going to school and from Calgary Canada grew up here it's not unusual for people in school in Canada to take a year either go abroad or go work or do
2:35 something Else I said you know what me to switch majors cause I want to get into like computer science and do comp SCI Stuff and I wasn't doing that at the time so said going to go to the East Coast
2:45 and won't to be close to New York City collecting of somewhere different I'd grown up in Calgary My whole Life so applied to a bunch of schools out on the east coast on a mall one of the ones got into
2:56 his records and was like this is Amazing So I still remember calling the registrar before I went. And my dad was on the line with me. He's like, I can't understand anything she's saying.
3:10 She's the accent, right? So great, went there for a couple of years. And then after Rutgers got recruited to go work in the Boston area. So that's the connection that, Funk and I have to Boston
3:23 stay there for 10 years, basically working for the Goran's Fisherman. You guys know the
3:30 Goran's Fisherman? Probably fish sticks all the time, free plug, I guess. Yeah, I've got the
3:34 jingle going in my head. Yeah, trust the Goran's Fisherman. Yeah, yeah. I worked there for 10 years. And then from there, a couple of my really good friends from Calgary were doing this Dakota
3:47 analytics thing. So the joke is, do you want to come for high pay and low hours? That's what I heard. And we always joke that it's like, no, no, you're dyslexic mark, it's actually low pay and
3:58 high
3:60 They were starting to get into the Microsoft Analytics data platform space, and we had been doing all that at Gordon. So at that time, it kind of made sense to move out to Calgary, and brought my
4:11 wife, who Funk Now knows, is from New Hampshire, grew up in Exeter, yeah. And she moved to Calgary site unseen. Well, I mean, okay, it's more defensible if you grow up and epic New Hampshire
4:27 or Exeter New Hampshire to move to a place like Calgary, because the cold's just, eh, it's just a simple transition, right? It's just slightly different. You're used to four seasons. You're
4:37 used to long and gray winters. How did she deal with that? She agreed to move because we said, let's go for a year,
4:49 and that was 11 years ago. Nice. So yeah, it's just sort of evolved. I mean, kind of, I mean, Calgary's a great place to live. It's very similar to Denver. like sister cities in Denver, like
4:59 just the kind of people, quality, all that stuff is almost exactly the same. My cousin used to live in Denver up until recently, we've been there a bunch of times and yeah, it's really, really
5:10 similar. So at some point we could see ourselves moving back to the States and moving to like live in Denver, climate, everything's kind of the same. Yeah, when Jeremy and I worked for Energy
5:19 Navigator, that was one of the things we always talked about was how Denver, from a lot of aspects, the downtown culture, that whole bit is so similar to Calgary. And it's an easy, same time
5:33 zone, easy flight back and forth. So it made a lot of sense for us to put some of our folks in the Denver area, just for the communications. Yeah, I think, I mean, I love Denver. Yes, it's a
5:45 little bias, maybe. It's great here. So did you meet your wife in college? And she kind of dragged you up to the Boston area? What did you guys meet once you were working for Gordon's? No, I
5:56 was working for Gordon's. She's a social worker. So that's my wife. Yeah, so we met up. I was living in kind of northern Massachusetts and she was living in sort of southern New Hampshire. So we
6:11 met up and kind of hit it off. And so the funny part of the story is that the group had in Calgary had asked me if I wanted to move to Calgary about three months into Audrey and I starting the day.
6:24 My wife's name is Audrey. And so I went to Audrey of course and was like, Hey, I mean we just met like a minute ago. You want to move to Calgary? And she's like, No, you feel like it's very old
6:36 killer. I don't know you. So we held off for a year and then a year later got kind of came up again and said, Okay, would you want to move? And Audrey's brave or stupid, I can't tell which one.
6:50 She's like, Okay, let's go. So probably a pretty good communication she liked me. got married and had a kid shortly after, so. So in your stint in Boston area, it looks like judging by your hat
7:04 that you have been indoctrinated. And in fact, maybe the Red Sox are your team. They absolutely are my team. Of all of the sports teams in Boston, and I say it was all the time, like Boston is
7:16 the greatest sports city in the world. I know that will offend people in other parts of the country, but I believe that and having been a bunch of places, like I cannot believe how rampant the fan
7:28 ship is. I'm like listening to the radio and talk radio and the Red Sox. The joke is I was like, if they lose the first opening night, or opening day, season's over. And if they win, World
7:42 Series, Mark it down, go to Vegas better. This is our year. Yeah. So yeah, big Red Sox fan, a little lukewarm on the Bruins because I grew up in Calgary i mean that's fair so i actually that's
7:55 hockey right Yes. Yeah, it's hockey. So I am curious, like who people root for outside? Obviously everyone has to take a strong stand in Calgary on who they root for. You get a lot of Oilers
8:06 fans, I think probably from their dominance, like with the Wayne Gretzky days and people just can't really let that go. You get flames fans, you get some random like maple leafs, fans and things
8:17 like that. Even some
8:20 Canadian's, which is a Habs is a four letter word as we know But so like who do people grow up rooting for? What's on TV for the other sports in Calgary? Did you get to watch games at Fenway Park
8:33 when you were growing up up there? No. Yeah. No, you get, so I was a big Michigan, 'cause we get Michigan Wolverines game, so I was a big Michigan fan. You get some of the northern states and
8:43 stuff like that, but growing up you didn't get, they didn't have sports packaging, cable TV and all that. Like you can get any game you want now, right? So you get a variety of fans from
8:54 everywhere. the original six teams, so Boston, Chicago, Toronto. You get lots of fans out for those, if you go to a Calgary, lots of Transparent fans. So when did the flames show up in Calgary?
9:09 They moved in '79, 'cause they used to be in Atlanta. Right. Yeah, I think they moved - Okay, so it's been there long enough. So you basically, I guess from a sports perspective, it's
9:18 Stampederes and flames growing up. Oh my gosh, Stampederes, yeah. I'm not a big CFL fan I'm more of an NFL guy, but yes, the Stampederes are in Calgary. Yeah. I'm just showing my knowledge of
9:31 the - Yeah, yeah. And Stampederes is the option on Tim, like this is amazing. We're gonna get you citizenship. No, Tim was like, when I first went to Calgary, I was with Tim and Tim showed me
9:42 around like he really knew the place. It's really something, he had friends out there. Yeah, Tim likes it, Tim likes the cold, deep down.
9:51 I do love getting up there and visiting the cold weather I don't think I'd like, you know, a whole winter of it, but. Um, I, I really enjoy Calgary, just, you get into downtown, stay in your
10:01 hotel and there's stuff going on all around it. I mean, when you're in Houston, you think, Oh, you're downtown, stay in a hotel, you know, five 30 at night. If there's not a game going on,
10:10 you're going to something happening. Yeah. Yeah. You're going to three forks and you're going to bed or something Like., yeah, the Calgary Denver downtown areas for sure are, are more lively.
10:21 Houston's like, like LA. It's like five or six different cities in one that, that are all 10, 15 minutes, 10, 15 miles apart. I want to go back to Boston. Literally, I'd like to go back to
10:31 Boston and hang out for a weekend sometime with you, Mark, but that's a different, different conversation. I want to go back to your time in Boston. So our original connection, Tim,
10:39 interestingly, is a guy named Abe Winograd, who I went to Brandeis with. Both of us were first team, all Brandeis, intramural football players, at least in my first team, Brandeis intramural.
10:56 football player. Okay. Okay. I probably wouldn't have had much of a career anyway, but a Winograd, the softest, most gentle computer science nicest guy, you put him on the intramural football
11:08 field, you've got a six foot nine, 285 pound beast who won't smile or pick you up. So depending on where you get him, it's like, what's wrong with that guy versus like, Oh, he's the nicest guy
11:21 we've ever met. He's a gentle giant. So Mark and Abe, one of grad work together at Gordon's. And I think you guys actually became reasonably good friends. I texted a day of the other day. He
11:31 said that he celebrates candidate day because of you. So you hooked him onto something. We did this. So the old joke at Gordon's was that obviously everyone at Gordon's knew I was Canadian. Is
11:42 they would like do celebrations of candidate? And I think Abe really latched on to that thought it was pretty comical to do that. Yeah, Abe and I worked together for, I don't know, probably a
11:51 year, year and a half. Abe was working for a consulting company. that came in to help us migrate into the Microsoft platform. So we were kind of learning and it was a good experience 'cause that's
12:02 what we do what I do today with a lot of energy companies, right? Is help them learn that Microsoft platform or just analytics in general and help transition it. So we spent a year together and
12:12 sort of, you know, kept in touch and stuff. I really like Abe. He's doing crazy cool stuff now with the craft analytics and that sports space which is so much fun to talk about and hear about So I
12:24 really like it. Yeah, he's carved out a really nice career but it was just super random to see the two of you guys connected, but then the dots that I connected were yeah, these are both, I mean,
12:34 he was a computer science guy, BI analytics guys. So you knew you wanted to get any kind of this BI space. Tim, this is fun because we just had Jose Rodriguez on yesterday who kind of dove into
12:45 his frustration being a 23 year old reservoir engineer when he started and seeing that everybody in his group uses Excel. He's like, no, I just got a master's in data science. Like, I know all
12:56 the tools that we can use, they're not even that expensive. Like, can we get this and that and how challenging it's kind of been. Talk to me about, I guess, your history. You grew up in Calgary.
13:06 So I'm assuming you had some familiarity with oil and gas. Well, that was my whole thing. When this started, I was like, well, he's from Calgary. So his path to oil and gas was already rich.
13:16 It should be direct, right? No, but he's like, he's been all over. But the detour through Gordon's fisherman, that's a little bit of a different path into the oil and gas base. So, all right,
13:25 if you can tell us about that a little bit. Yeah, so my dad, one of his careers in life was being a geologist worked for Dome Petroleum. If you remember, Dome, which got bought out and worked
13:37 for a bunch of other places, Amaco and other places, was a geologist. He used to take me out when I was a kid, he used to take me out to the well site. 'Cause remember, he used to actually log
13:47 samples and wash them. So I spent a summer washing samples, I'm sorry, in the middle of nowhere, right? Anyways, he did a bunch of well-sized geology and did a bunch of that stuff. So I learned
13:58 a little bit. I wouldn't say I got a PhD in oil and gas from my father, but he was certainly very helpful. And then, yeah, sort of went into school and then coming back from school and the whole
14:11 Boston thing of doing analytics, you know, like it's interesting to me 'cause you talk about free cash flow versus EBITDA, you know, like free cash flow is kind of an oil and gas term Big time.
14:21 EBITDA is more of a, they're the same things. They're still the same profit. You're still trying to accomplish the same thing, which is, you know, talking with Jose and stuff. You're still
14:29 trying to drive value, right? Like that's the whole game around analytics. And our philosophy at Dakota is kind of that value gets driven from driving like new technology with business expertise.
14:43 And if you do either or, you're not gonna get there. And you see a lot of conversations like with toze Rodriguez last week. It was like, hey, we can use these tools and we can do stuff better.
14:54 And so he's trying to leverage the technology space 'cause he's got some business expertise. And that's kind of where we live and where we've lived at Dakota for the past 10 years is where I've lived
15:04 at Dakota past 10 years is doing those kinds of things. Is Dakota a provider of software or a consulting group or how do you guys, what is that? So we're a services company, Tim. We just provide
15:18 analytics services, so expertise So help you either, we build a lot of solutions. So we'll, we have a list of probably 40 different analytics solutions that we build and then deploy. And usually
15:32 we'll build something at a company and get some expertise and it drives them to IO and then we'll take that knowledge and exploit it, go to the next company and say, Hey, would you like to do this
15:42 too? So we've not quite productized it into like a software offering 'cause everyone's just a little bit different
15:51 but the end result is usually quite similar. So our claim to fame or what we think we do well is taking the same solutions that we have at other places and plugging them into, you know, new or
16:04 different oil and gas companies to go do stuff. And you're scratching pretty close to where I kind of - Absolutely. Came out of school, residential engineer, all that great. And then eventually
16:17 found my way and I was the first oil and gas guy at Spotfire for however many years. So the term analytics was not really being used in 2000 year. We were trying to kind of corner that phrase,
16:32 business analytics at, you know, when we were at Spotfire, we were just a little bit too soon to get that associated with us. And of course, no one in oil and gas had ever gotten into it. So
16:43 anyway, a little early took a while to get started But anyway, so you're real close to. one of my old stomping grounds. And so it's kind of fun to get into that. So
16:59 what are your tools of choice? What platforms do you lay out top of for your clients? So we're really trying to be tool agnostic because the introduction of tools introduces bias. But we leverage a
17:13 lot of the Microsoft data platform and I don't want to get in trouble, but I think all the tools in Microsoft are good None of them are great, as a good place to live. And from a cost of ownership
17:24 standpoint, at least, and this is my opinion, from a cost of ownership standpoint, that Microsoft tool set spans the whole spectrum of everything you're going to do in algorithms, right? So you
17:34 can do everything, you can do it reasonably and expansively. And I think that's important, probably not today in oil and gas 'cause you're probably not crunching the numbers and managing those
17:45 costs as tightly as you would be, you know, two years ago but, you know, tighter commodity climate where oil prices aren't quite as high. You can kind of drive the value, right? So we look at a
17:57 project and say, Okay, what's it gonna cost to implement and what's the anticipated value you're gonna get out of it? So if I can get software for all the data tools or whatever I need to do for,
18:06 you know, 100 versus100, 000, the value proposition's much higher. So a little bit easier that way. But pretty tool like NOSIT 10, we get into AWS, we get into TIBCO a little bit too We get
18:20 into some of the other tools to do stuff as well. You know, there's the debate we'll rage on for which one's the best tool and what we should use. And you guys kind of pick and choose your spots,
18:30 probably depending on the client needs. That was actually one of the weirdest things, coming out of school back in the early '90s, one of the first realizations I thought was strange was how loyal,
18:46 you know, engineers were to a particular product line. I remember my first internship listening to two engineers debate, this will really throw you back, the value of Lotus versus Excel. Lotus
19:02 one, two, three, to Excel, and they were all - You were older than 29 years old, I can tell that. That is in fact true, that is in fact true. But you know, it was just amusing to me as like,
19:16 guys, you know, for a 22 year old, I was a little younger than that, listening to them argue over the benefits of one versus the other, and how can you use Excel? It's just a copy of Lotus and
19:29 all of this other, and you know, it's just kind of, it was just an amusing thing, but it's never stopped. You know, you've got the guys that are spot fire, which, you know, partially my fault,
19:42 they're spot fire loyalists and others that are power BI loyalists, and, you know, and for a lot of different reasons, it's just kind of interesting how emotional. to a software package someone
19:55 will get. Well, it's a lot like, we have this debate at clients that's all the time. It's a lot like the Ford versus Chevy, right? Like, I'm like, in my opinion, like, well, they're both
20:03 cars and they both run and you know how to drive well, they work great. But we have that debate quite a bit. The Ford's much better.
20:11 Is that your opinion too? Well, I'm a Ford truck guy over a Chevy truck guy, I guess. I don't know. Yeah. But what we're, you know, we're in County a lot now, this might be interesting So the
20:22 Microsoft data platform in our experience is a little bit cheaper than going to TIPCO, especially by my last minute. But the engineering crews at the oil and gas companies typically lean towards
20:34 TIPCO, right? And there's reasons the flatter data, it's easier to manipulate stuff, it's got a client tool.
20:40 So they want to keep using that. And in the CIO IT manager, director of IT, whoever leadership in IT is like, how do we get people on to Power BI? Because the tools cheaper, like on a per
20:51 license basis, whatever they've negotiated. It's cheaper and part of our strategy engagements are around like okay What's the cost to convert an engineer like a good spot fire? Builder of things
21:06 into power of yeah, cuz that's part of the cost That you'd have to factor in right and and part of that's like even attrition. It's people some people will just like
21:18 I'm out The line in the sand. Yeah, you make me use that. No, I'm out. Yeah, I buy it though It I mean Yeah, the job market in oil and gas is pretty good right now at least from what people
21:29 told me so yeah, we've had people that we've had some clients that we worked with So people that have moved to like four different companies or five different companies and then asked to go to come
21:42 and help Build out some of the analytics platform and some of the tools to do stuff Like, again, you talk about being loyal, like, that's really our secret sauce. I guess is that we built some
21:55 really good relationships with some clients and been able to leverage that into work over time. So hopefully we can do that. Which is
22:05 fantastic and brings me back to something I told Mark probably about a month or two ago. The time period was 2013, 2014. And I was at seven lakes and at that point seven lakes had a lot of custom
22:19 kind of integrated data aggregated at HTML5 dashboards, some well profitability. But the ability to visualize not just the profitability of a well to look at what did you forecast, what was your
22:32 downtime, what were the reasons, right? All of your sort of estimates and all of your actuals in one place. And at that time seven lakes was one of the few people who had created a nice seamless
22:42 visualization with drill down to invoices in kind of that well profitability world And I had a meeting with Air Plus. And I went into Air Plus and I was all geeky. up to show them this thing. And
22:53 they literally pulled up their tableau dashboard. That was the same thing. The quadrants are mapped out. They're like, here, take a look at this and you click here and you get to the invoice
23:01 image. And you guys have built that for them. So I was like, shit, man, I hope these guys don't come down here. You know what I mean? Cause if you can start telling these people, this can be
23:09 done within spa fire or tableau or tools they already have, they don't need to buy the front end from me, right? Which is where like that's the sexy part where the executives get sold on the thing.
23:20 So I was like, man, I hope these guys don't don't come down here. But you've you've had success now down here as well. We've had success using the strategy of like, we're not going to build you a
23:31 dashboard and productize it. We're going to teach you how to build it, lower cost of ownership. You can make changes easier. Like it's your you own all the intellectual property versus like buying
23:42 a license from someone for something. Because I very much feel like in the past 10 years, everyone's been moving from a like. print me out the PDF of the report or whatever I wanted to like, no,
23:54 I really want to interact with the data. I want to ask the what if questions. I want to be able to build my own reports and drive my own stuff and do that, right? So for us, a lot of the
24:03 engagements are really more like strategic, like how do we get more business people up to speed to use the tools and answer their questions and help them transition? So they get their data knowledge
24:15 up, right? And then, hopefully, you can get into building your own stuff and you don't have to buy off the shelf for some of the questions you're trying to answer it. Buy off the shelf is still
24:25 great for a whole bunch of things because you can never build it cheaper than you buy it, so I'm not advocating that you build everything. But just so that you can get to that place where you can
24:33 make that decision, right, as a company, whether you're an energy company or not, to say, yeah, we should go build this and, like, I can show Tim how to use the bot fire in an afternoon and he
24:42 can go do some crazy, cool stuff It would probably show you though, I mean, you know, maybe. I was in charge of showing people for a long time. We'll sign up for that, Tim. Send me the, where
24:55 do we register?
24:58 So Tim, I know you got to jump in here, but Mark, I want to ask you this. So you guys work with something like 75 of the top 50 clients in terms of production in Canada. You work with some large
25:13 operators down here in the States as well. But I think also 30 of your business is outside of oil and gas. Can you talk to me a little bit about how this is all played out with you guys having?
25:24 Obviously a lot of oil and gas knowledge, but then going cross border and cross industry as well. What's sort of the makeup of your organization? What does the growth look like moving forward? So
25:35 the makeup is, we kind of separate the world into like engineering and analysts. So engineering be a little more technical in nature, building out ETL, the data movement piece. the infrastructure,
25:48 the setup, all that kind of stuff, and then a little bit more of the analyst side. We would live more in tools like Spotify or Power BI, Tableau, helping, working with business. Having some
25:57 business knowledge, not a lot of professional reservoir engineering knowledge, but enough to be able to know what frackspacing is on a completion sort of thing. So that's kind of the makeups for
26:09 half and half. About 30 of our business is outside oil and gas, and that's through word of mouth or different solutions we built out, we do a lot of planning solutions, so putting a financial face
26:24 on things like free cash flow or e-bittair, that stuff. So we understand that space quite well, so we get pulled into some of those opportunities. And then just kind of mostly through word of
26:33 mouth, or through we do an innovation event twice a year and just talk about kind of new stuff that we're doing at different places. But yeah, about two thirds of our business Jeremy's is still in
26:44 that oil and gas space. Go build something cool at one place and then be able to leverage that knowledge to build something cool somewhere else. Like, you know, oil and gas companies are doing the
26:56 same thing. They have the same business. So with new people we talk about how we're just, they're just making widgets, make it simple, right? I know it's not simple, but for the new people
27:06 working at Dakota, I'd understand, you're just making widgets. And everyone's making the same widgets in kind of the same way. I mean, we can argue subsurface how different it is That's true,
27:16 but in terms of like everyone, you look at the MDA for every energy company and they're gonna be pretty similar. Yeah, they may not believe they're doing it the same as everyone else though. So
27:27 sometimes just like, no, we've got this KPI that we monitor, it's such and such, whatever. And then you kind of have to, I've had to do this a few times. Nah, it's not, you're not the only
27:38 ones looking at that. We'd like to hear that. Nobody likes hearing that.
27:44 You're doing it very similar. I remember going to a large oil and gas company who I won't name
27:52 and they were doing a very interesting, very technical engineering application. They developed it in
27:60 MATLAB and they're wanting us to come in and do some things with it to implement their calculation and it was interesting but they wanted to protect the IP and they had to write down all these things.
28:16 We had to sign contracts that we wouldn't share the calculation with people and all that and the whole time I'm trying to tell the research guys, you know that I saw this exact layout
28:29 over in Europe with a couple of big oil and gas companies are doing pretty much the exact same thing you are. And they just, you know, again, Mike said, Jeremy, they didn't like hearing that,
28:39 but yeah, you're not as unique as you think you are, Happy to sign this, we won't share it with anybody, but I've already seen it once. Yeah, I probably hear two or three times a year.
28:50 Someone's like, Hey, come here, I wanna show you something really cool we're doing.
28:56 And I'm like, Oh, like I'm always perked up. I'm like, Oh, 'cause sometimes it is something really cool. Like I've seen some of our clients have done some really cool stuff, okay? And you get
29:06 in there and they're like, Look at this, man, I'm predicting my declines on this well And I'm like, Uh-huh. Like, do you think other clients would wanna use this? And I'm like, I think of,
29:19 you know, it's probably a few that are already using it.
29:23 Yeah. You know? It's already, you know. Yeah, but as I was like, everyone's sort of, again, certainly people newer in their careers, you don't have that experience right where you've seen
29:33 those things happening. So pretty excited about being able to do things like declines or simple stuff that, you know, We would joke about now and be like, Yeah, I think everyone's doing that.
29:44 You're definitely not alone. Talk to me a little bit about the buyer and the differences in terms of what they want from an analytics perspective in a down market versus an up market. Is it
30:00 generally the same thing that you're seeing right now or is it there's more scrutiny on things like LOE and cost and AFE in a down market and now people are more interested in things like production,
30:12 like what do you generally see in the sort of ups versus downs in the analytics world?
30:19 Yeah, good question. So in a down market, you would see more requests for things like shrink and yields. So like, what's my yield? What's my butane pentane yields? And am I getting paid from
30:32 the facility, the amount? So I think I should be doing all those kind of analytics. We've had clients that have gotten a bunch analytics tools around like just yields and. you know, compressor
30:42 yields, all that stuff, that have saved half a million dollars. It's like, hey, I think we haven't been getting paid on this well for the past 15 months. Vendor spend analysis, things like that.
30:51 Well, not vendor spend, exactly. More like facility throughput, but yeah. And then we'd also get into things like vendor spends and like, why is, you know, why is well A paying2 a liter for
31:03 methanol and, you know, well B's paying 260 a liter? Sure. You can get into the weeds on that stuff And I think that in down times, there's a little more scrutiny around just cost and cost
31:14 structure and driving that out. But I think, in my opinion, we've seen a lot of that get eliminated. Like, I think companies are probably running 10, 20, 30 leaner than they were before. In
31:27 good times, you're gonna see a lot more people wanting to do more forward looking stuff. So we build a lot of planning solutions which integrates all of your, like economics from Bounab and those
31:40 kinds of systems, but then we layer on top things like, you know, your hedges marketing contracts, your taker pays throughputs to really get you to that cash flow number and be able to plug in
31:51 like an acquisition. Again, every acquisition seems to be a bit different in terms of how it gets structured. So the flexibility to layer that into the planning analysis that you're doing and be
32:01 able to roll and iterate through that like five, 10, 20 times a day, like put in 10 price decks and see how that impacts your interest rate over time, right? 'Cause you're gonna go into different
32:13 bands of interest rates, the more money you borrow and all that stuff. So getting to that place, which again, everyone does it. Lots of places do it manually. We've automated a bunch of those
32:23 processes for people. And if you're like a planning analyst in this world right now, phone, you're CEO or CFOs coming to you and saying, Hey, man, we might do these four acquisitions. Yeah
32:35 Usually it's a really unreasonable request. in like no time, that's been our experience. We're going into the data room tomorrow. I need this information now. Yeah, yeah, we might go spend3
32:45 billion tomorrow. What do you think, right? Can you plug it in? And by the way, if you're wrong, like you're fired, like we don't, you gotta be right. And you're like, oh my gosh. So just
32:55 helping people get through that to be able to do that forecast and stuff. That's more stuff you would see when times are good. And then you'd see more innovation when times are good So see people,
33:06 be core clients, be more willing to invest and let's see if this works. 'Cause a lot of data discovery, Tim, you know this too, a lot of data discovery is like, I can't quantify my ROI tomorrow
33:19 for you. Like we think we're gonna do better and save better and be better, but I can't guarantee it. And you know, as we move towards more implementations of machine learning and AI, You know,
33:33 I've seen a lot of.
33:35 I don't want to make this sound bad, but a lot of science fair projects where they're spending money on AI and machine learning because they think there's going to be value at the end. And sometimes
33:48 they have a very clear definition of, well, I've got my opinion on how to design one of these projects so that it does bring value and having seen a bunch that have failed.
34:01 The ones that do approach it as a science fair project, we know we want to get into machine learning because we know there's value there, we just don't know what it's going to be yet.
34:09 We see a little bit more of that in some of the
34:14 better times, if they're not in the middle of an acquisition or absorbing another company or something like that, you'll see a few more of these types
34:24 of, well, I call them science fair projects, but these kinds of projects. I don't know if you've got any opinions on that, but it is interesting to see how when And they're willing to take on.
34:34 some new knowledge without necessarily knowing exactly what the payoff is going to be and when they're not. And surprisingly, during the downturn from 15 to 19 or whatever, there was a little bit
34:46 more of that playing going on. What can we do with these new tools maybe to make up for what we're not getting? Yeah, I think when you can get the right group of people, this becomes a people
34:59 thing, right, to be able to go do these AIML kind of projects, and you've got some really strong data people that also have a really good engineering background, and companies like to go to
35:08 support them with like here's the data or here's easy access to data, so you don't have to like pull it in and manipulate it too well. What I see the biggest hiccup or kind of things people overlook
35:18 is just data quality. So everyone's going to data conferences, everyone's saying AI is a buzzword, we should do AI. Above the surface, I haven't seen a ton of AI in the oil and gas space, just
35:30 because data doesn't, long story. Well, that's what Jose said that yesterday, Tim. If you recall, he said data science, he doesn't believe that data science is actually a big thing in oil and
35:40 gas, but that's a completely separate conversation, which we never actually got back to, but it's sort of, you sort of just said that. So I don't want to let this go completely away. How so Mark,
35:51 how's like, like, let's dive into this a little bit. Yeah. When you're getting into those spaces, so are we going to say above the surface because below the surface of the ground for oil and gas,
36:01 it's quite prominent, okay? But above the surface, you see a lot of, you don't have enough data, so you have enough data points statistically to make it meaningful. And then the outcome, like
36:12 machine learning is math, right? So it's basically spitting out probabilities of stuff. So if I was to say you're 5 more likely to do something different, if we go spend this million dollars on
36:25 this project, would you do it, right? everything comes back to value and the value proposition of what you're trying to do.
36:33 and you're gonna spend a lot of money and do a lot of data cleansing to get to maybe a 5 change in how you run your business. And that's a tough sell, even at100 WZI.
36:47 That's a tough sell. We get asked twice a year, can you guys go do this project? Which are like, we wanna understand the value, right? 'Cause like, you have to code analytics, screws this up.
36:57 It's a small world, right? Right. If I'm free to tell everyone we mess this up Oh, I love doing that, I love. Yeah, well, I mean, that's actually going back to being from Calgary. Calgary is
37:09 a very word of mouth town. So you do somebody right, especially in the only gas space. Your name will spread out in a good way, but I guess, obviously there's a downside to that.
37:23 Yeah, and you just don't see a lot of places that have a lot of experience in doing a bunch of machine learning stuff.
37:32 And again, reach out after I can share with you guys who those pockets are of people doing some really cool stuff. But you've got to marry together this like pretty strong data science background
37:42 with a pretty strong technical background sort of business technical background. To be able to produce something meaningful. So it's just, it's a great place to play Tim, like you said, but
37:56 sometimes you're, it's a little bit more of a like proof of concept or a kind of innovation kind of thing. So I'm going to take this down a lighter side. So this is going to be a big pivot here,
38:07 but you've been in a lot of client meetings, sounds like, you know, certainly a lot of client offices, and we were talking beforehand when we were getting our tool set up, making sure everything
38:20 was working. You know, there's always that moment when is the projector synced with my laptop and how do I cast to your TV and all that stuff going on. There's always this little. things that
38:31 happen when you get into those boardrooms. So, are there, you're slightly different being a services company, but have you ever had just a complete total failure in the boardroom of getting, you
38:46 know, hey, we're gonna have to come back in an hour while I get this figured out type of thing? Did you question how many times? How many, let's just go with maybe the funniest and most
38:54 entertaining for our listeners
38:58 Yeah, sure, so we were doing a demo, I won't say the name of the company, for a company, it took us about six months to get the demo lined up, you know, like merging all the calendars, finally
39:09 get everybody in the room, go to hit like the power button on our demo environment, and like, it's not working. Oh, go. And it would turn on. It was all, it was all like on premise servers we
39:21 had. They had turned off like the power in the server room, this is a while ago, they turned off the power in the server room We just couldn't even connect. So we still had like the printouts,
39:33 right, of some of the presentation material. So at that moment, I mean, your stress could not be higher, right, 'cause you're like, I will show you nothing interactive. I'm gonna pull up a
39:42 piece of paper. Oh, yes, we're a technology company. I'm gonna send you a piece of paper, like a, you know, bind it together and try to walk through it. And you could just see every, like,
39:54 C-suite executive in the room, just their heart just sunk, right? 'Cause they're like, now I don't wanna be here. Yep, yep. But, and you know in Canada, we're really polite. So, like,
40:05 people don't just get up and leave for meetings. Sure. So, like they're, like, now I gotta spend 30 minutes to listen to these guys, show me some pictures on a piece of paper. And then at the
40:16 end, they're gonna be like, Hey, do you wanna do a project? And you know, I have to say no.
40:23 So, yeah, it happens, it happens, you know, every demo seems like something goes wrong.
40:28 Most people are pretty forgiving, 'cause if you've ever worked in the space, which you guys both have, like we all have those four stories. Yeah, that was a moment. Well, of course, you know,
40:36 and now I've already dated myself. Back in the mid '90s, when I was with slumber Jay, and we had geophysics software, which was on a sun spark station, and I had, you know, our production
40:47 engineering software, which was on laptops and all that, and getting those things hooked together was a major feat. We used to come in with dollies of monitors and sun spark stations and cross-link
41:01 cables. You can't just get an ethernet cable when you want to hook up a sun box with a laptop. You actually have to revert, one of them has to be reversed, and you have to know which one goes in
41:11 which box. It was absolutely crazy. But to go in there, there were so many moving parts. One of them was always not gonna work. Disc won't mount or whatever else. So it was so many of those
41:24 times. Of course, I think everyone's a little understanding when you're bringing all this equipment. Nowadays, we used to have to carry our own projectors because nobody had a projector in the
41:34 room. Oh, yeah. I remember that. Yeah, we used to have a laptop, like an enormous laptop. Like it probably weighed 18, 20 pounds. Like, and we used to just run the demo off of that because
41:47 of these things that would kick out. And it was like so funny because some of you have like walked like four or five blocks. Right. And you get in the meeting room and you're like, hold your
41:57 shoulders You're like, just love this weight all the way across the parking lot. Well, in the early days of spot fire, when they came out with their server side technology, we used to have to
42:07 carry a swappable hard drive for our laptops. So you had your, this is what I'm using for business. But then I went for demos, I'd have to swap it out to be able to do a demo and show the
42:18 connections with that in the course. And that's just always a risk. Any time you're pulling these disks out and popping another one in, you never know if it's ever gonna work. So real quick, a
42:29 couple more questions, Mark, before we let you get back to whatever it is you do in Calgary before the weekend.
42:37 From a Bitcoin mining perspective, this is something that's gaining a lot of momentum down here. I think this podcast will be released when we'll be at the Empower Digital Wildcatters Bitcoin plus
42:38 energy conference. There's a lot of buzz
42:42 down here now I mean,
42:54 in Colorado, certainly in Texas and Oklahoma, you're hearing about people getting these, you know, these ASIC, you know, boxes and miners, and it's happening here. Is it also happening in
43:07 Canada? Is there the same type of buzz up there around taking your stranded gas and producing Bitcoin with it? Yeah, yeah, if you have stranded gas, people are looking at doing that. I think
43:20 it's a little bit, I think I've seen less of it lately, or at least conversationally, I've heard less of it as gas prices have gone up. but we have a pretty captive market here for gas. We don't
43:32 send a ton of gas overseas. So when the price goes up to three, four, five bucks, you don't hear much about it. Price goes down to two dollars, say, or nine maxes down to two dollars. Then I
43:43 think you see a lot more events. You're like, what are we gonna do with this gas? Let's go mine some stuff, right? The margins are not amazing from what people have told me, but it's a way of
43:52 doing something with that gas. So you're still leveraging it to do stuff So yeah, you're seeing some of the players in Canada do the same thing as in the States. You got, you know, well, you
44:03 don't just flare all the gas off. So what do you do? Yeah, we had Laura Palmer on the show a few weeks ago, and she was actually talking about, you know, you bring in the economics of Bitcoin
44:13 and actually start weighing, selling the gas, even if you have gas takeaway, selling the gas versus mining for Bitcoin. And sometimes it's still worth it to mine the Bitcoin over actually selling
44:25 the gas Obviously depends on the price of. gas you're getting. But you also have to look at the price of the Bitcoin as well. Yeah. But I think at most of the, at least a bunch of our bigger
44:35 clients, they've, they've got an actual group of people or a team that's now pretty dedicated to like, okay, how do we make this, how do we make this mining thing go? What's what's economic?
44:47 And again, this is part of that innovation that now that oil is at a hundred bucks, you'll see a lot of people or gas support. You'll see a lot of people spending some money to figure out, you
44:56 know, how do we create a different stream of revenue, really, right? Yes. Energy is energy. You see, I think you're going to see over the next five or 10 years, a lot of energy diversification.
45:07 Oh, yeah. So I think you're going to see, you know, the introduction of ESG and public companies and the, the rigor or the demand from a lot of investors to diversify and be responsible around
45:19 your energy production stuff. You're going to see a lot of people diversify that energy into a whole bunch of different streams. I think you're also going to see a ton of innovation. My cousin's
45:28 wife works for one of the big, one of the big EMP companies in the world. And she works for basically doing innovation, figuring out like how we're gonna transition and do all that stuff. So it's
45:40 the right group of people because they understand how energy works, where it comes from. Like, you know, there's no magic to this. So it's gonna be difficult to convert to solar and wind in the
45:53 next two years Like it's, you know, most of us would say that's impossible. And just like energy safety, right? Like, you know, crazy stuff happening in Texas over the winter and stuff. Like,
46:04 how do you make sure that those kinds of things don't happen in the future? And there'll be profit there. So energy companies will invest in it. Are you getting, sorry, are you getting some of
46:14 those requests for more like ESG centric, emiss, emative related dashboards and BI projects? Yeah. Coming up now.
46:25 We're doing a project at a client right now where we're doing like emissions forecasting.
46:31 So, you've got kind of your, I'm only gonna emit so much methane into the world. And so you kind of keep track of that and you really forecast it out. There's some rules going into place in
46:42 Saskatchewan.
46:45 Oh, oh no. Did? Saskatchewan. Where they're changing some of the rules around, what you can emit and how you emit it and all that stuff. And that will impact whether you can produce the well So
47:02 that's how real it's becoming, right? And I think energy companies are really good at being really reactive and to new things and being able to innovate and come up with a solution really quickly.
47:05 I think that's one of the really big differences that I see and why I like the energy industry a lot. It's kind of that grow or die, right? So everyone's like, let's go do some cool stuff and
47:14 we'll be around in 10 years. So I really like that part of that industry and
47:20 that innovation piece. 'Cause that's where we like to live, right? like what's new and cool and fun and interesting to go do from a. from a data perspective. Love it. Mark, where can people
47:29 find you, find Dakota analytics, all that good stuff?
47:36 Dakotaanalyticscom, we're on LinkedIn. They can reach out to phone futures 'cause Jeremy will always respond to that. Yeah, within five minutes. Yeah,
47:46 and if you're looking for Mark on LinkedIn, it's Mark with a C Mark with a C, a bear with a bear. True, true. I will never do that now. Appreciate it Mark. Yeah, that's where you can find us.
48:03 We got a website, you can reach out to us anyway. So yeah, it'd be great to chat with people. We do lots of, lots of just strategy engagements around how do I change my data culture and what are
48:14 you seeing at other clients just to get perspective and lots of the bigger places. We just, we have a footprint like we just want to leverage you guys as expertise right once in a while for some
48:24 stuff. You just can't replicate having been in 40 or 50 different companies and helping them with their reporting and BI. Cause you start to just see the same things over and over and over and over
48:35 again, right? Thousands of projects and you guys have done it, man. You know what you're doing. Yeah.
48:43 We have. Thanks Mark. Thanks a lot, Mark. Okay. Appreciate the time guys.
